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Self-efficacy

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Julie Waddington, Self-efficacy, ELT Journal , Volume 77, Issue 2, April 2023, Pages 237–240, https://doi.org/10.1093/elt/ccac046

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Self-efficacy is a construct that focuses on an individual’s evaluation of their capacity to do something successfully in a given situation. Albert Bandura defined the construct as ‘people’s judgements of their capabilities to organise and execute courses of action required to attain designated types of performances’ ( Bandura 1986 : 391). A crucial point to understand is that the concept relates to beliefs about one’s perceived abilities or inabilities to complete a specific task, and not to one’s actual capabilities or performance ( Mills, Pajares and Herron 2007 ). Initial interest in self-efficacy emerged with the development of social cognitive theories in which individuals are understood to be active agents in control of their own choices and behaviours ( Wyatt 2018a ). Bandura (1977) made a significant contribution to these developments by showing how self-efficacy beliefs can influence our choice of activities, the amount of effort we expend on them, and our persistence in completing them, especially in the face of challenges. To understand how an individual’s self-efficacy beliefs emerge, Bandura (1977 , 1997 ) identified four different sources: (1) mastery experiences; (2) vicarious experiences; (3) verbal persuasion; and (4) physiological and affective states. ‘Mastery experiences’ correspond to a person’s recollection of and reflection on their own past accomplishments in similar tasks, while ‘vicarious experiences’ are gained from seeing or hearing about the accomplishments of others. ‘Verbal persuasion’ relates to the appraisals or feedback provided by others, while ‘physiological and affective states’ concern a person’s interpretation of information derived through their own senses. Being aware of these different sources can help us gain a better understanding of how self-efficacy beliefs are formed, and, importantly, how they may be changed.

Research shows that self-efficacy beliefs can influence academic motivation, learning and achievement ( Schunk 1995 ; Pajares 1996 ; Schunk and Pajares 2002 ). Taking this into account, the most useful efficacy judgements may be those that slightly exceed one’s actual capabilities, ‘as this modest overestimation can actually increase effort and persistence during difficult times’ ( Artino 2012 : 77). The emphasis, nevertheless, is on ‘modest’, as over-estimating one’s abilities may lead to inappropriate behaviour or unrealistic expectations. This is illustrated by Wyatt’s ( 2018a ) focus on language teacher self-efficacy, showing how an inflated sense of ability can lead to effort reduction or complacency. Wyatt’s hypothetical examples of different teacher expectations and behaviours shows how a teacher with low self-efficacy may avoid certain tasks, while, at the other extreme, a teacher with an excessively high sense of efficacy may become complacent, putting less effort into the task than may be required ( Wyatt 2018a : 124). While strong self-efficacy beliefs can help us face challenges and stay committed to our goals, low levels can have the opposite effect, generating avoidance behaviour, and negative feelings that can have a detrimental effect not only on performance, but also on our wellbeing.

Within the specific area of foreign language education, there are two main strands of self-efficacy research: one focusing on learners, and the other focusing on teachers. Work focusing on learner self-efficacy has helped stress the link between student self-efficacy beliefs and motivation or achievement in foreign language learning. Identifying low self-efficacy beliefs can be a first step towards promoting more positive and realistic attitudes to foreign language learning ( Waddington 2019 ) and improving language learners’ abilities to develop their own self-regulating strategies ( Zhang 2020 ). Bandura’s (1977) description of the four different sources of self-efficacy beliefs can be used to identify specific areas where teachers can work to boost learners’ self-awareness. For example, in relation to mastery experiences , understanding how learners interpret and make sense of their successes or failures is considered a basic component of motivational teaching practice ( Dörnyei 2001 ). Interpretations of past successes or failures can reinforce negative self-beliefs (‘I failed because I’m useless at languages’) or identify aspects that can be worked on constructively to improve self-efficacy and performance (‘I’ll have more chance of succeeding if I focus on . . .’). As Ushioda states, ‘the ideal motivational scenario is one in which students attribute positive outcomes to personal ability, and negative outcomes to temporary shortcomings that can be remedied’ ( 1996 : 13). Regarding vicarious experiences , activities involving peer modelling and peer observation can provide opportunities for learners to build their own self-efficacy by watching others perform tasks successfully ( Waddington 2019 ). ‘Near peer role models’ ( Muir 2018 ) can be particularly inspiring by demonstrating that foreign language learning is achievable. Defining ‘near peer role models’ as those who are comparable to us in one or more fundamental ways, Muir ( 2018 ) suggests that they can help their peers establish more attainable and realistic language learning goals, counteracting the tendency to position native speakers as the standard benchmark or most desirable model to follow. Considering verbal persuasion , teachers can play a key role in encouraging positive and realistic self-efficacy beliefs by providing learners with salient and timely feedback that encourages them to identify areas for improvement and to recognise that these improvements are within their reach. Finally, in relation to physiological and affective states , positive and constructive self-efficacy beliefs can be fostered by ensuring that learners’ emotions are duly considered in the language classroom ( Miyahara 2015 ), and that efforts are taken to detect and minimise the discomforts and anxieties that have long been recognised as potential barriers to foreign language learning ( Horwitz, Horwitz, and Cope 1986 ).

Work focusing on language teachers’ self-efficacy has emerged this century ( Wyatt 2018b ), underpinned by the growing awareness that teacher efficacy can significantly influence student achievement levels, teacher attitudes towards innovations, and beliefs in their ability to cope with changes ( Thompson and Woodman 2019 ). Attending to teacher self-efficacy could be implemented as part of a wider focus on self-care and self-development to promote teacher wellbeing, which is a fundamental basis for effective teaching ( Mercer and Gregerson 2020 ). Mercer and Gregerson (2020) present several practical tasks that could be used in teacher training settings, or indeed by individual teachers, to build healthy and realistic self-efficacy beliefs. One task resonates with the mastery experiences discussed above, concerning how learners interpret and make sense of their successes or failures:

As a language teacher, you will have a greater sense of control and efficacy if you can attribute successes and failures to elements over which you can have an impact, rather than elements that are beyond your control – a type of attribution which can ultimately lead to a sense of helplessness. (Mercer and Gregerson 2020: 42)

Exploring attitudes and beliefs to language teaching ideologies and practices can also help identify issues that can impact self-efficacy levels, as demonstrated in a recent study which detected a strong link between low self-efficacy beliefs among preservice preschool teachers and the prevalence of the ‘ideal native speaker teacher’ model ( Waddington 2022 ). The assumption that ‘native must be best’ held by most participants had a negative effect on their self-beliefs, leading to disempowering views about their capacity to be effective early years language teachers, and reinforcing discriminatory attitudes in which they assumed positions of inferiority. Reflecting on these views and assumptions throughout a focused teaching intervention led to a readjustment of beliefs and a significant increase in self-efficacy levels. Interventions like this can have a significant impact on future teachers by raising awareness of debilitating beliefs that affect ‘non-native English-speaking teachers’ ( Selvi 2011 ), challenging ‘imposter syndrome’ ( Bernat 2009 ), or the feeling that they will never be good enough. On the other hand, the self-efficacy beliefs of ‘native-speaker teachers’ may also be affected if their own variety of English use is being dismissed or questioned ( Dörnyei and Ushioda 2011 ), or if they are being positioned negatively as unqualified backpackers ( Wyatt 2018a ). Considering these issues in the context of teacher education, Banegas (2020) shows how teacher development needs to be considered in the widest sense of the term, taking into account personal as well as professional experiences. Working with ELT educators, his work demonstrates how self-efficacy beliefs are influenced by the range of cultural, individual, and professional funds of knowledge that teachers draw on to support their teaching. Recognising and leveraging the diverse funds of knowledge and skills that teachers bring to the classroom can help challenge deficit views and foster more affirmative self-beliefs with clear and realistic future development goals.

Advancing knowledge on psychological issues that affect learners is crucial to inform and enhance foreign language teaching and learning ( Williams, Mercer, and Ryan 2015 ). The self-efficacy of learners and teachers should receive greater attention in all spheres of learning and development in order to positively influence achievement levels and contribute to the wellbeing of both students and teachers.

Julie Waddington Dept. Didàctiques Específiques / Facultat d’Educació i Psicologia, University of Girona, 17004 Girona, Spain.

Email:   [email protected]

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• Research article
• Open access
• Published: 26 July 2019

The influence of general self-efficacy on the interpretation of vicarious experience information within online learning

• Natalie Wilde 1 &
• Anne Hsu 1  

International Journal of Educational Technology in Higher Education volume  16 , Article number:  26 ( 2019 ) Cite this article

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An individual’s general self-efficacy affects their cognitive behaviours in a number of ways. Previous research has found general self-efficacy to influence how people interpret persuasive messages designed to encourage behavioural change. No previous work has looked into how general self-efficacy affects the interpretation of vicarious experience information and how this affects self-efficacy in being able to complete a set task within a career skills online learning environment. The study presented considers this gap in knowledge, analysing the effect of six different types of vicarious experience information on the self-efficacy of online workshop participants to complete a set task. In analysing the results, each participant’s general self-efficacy was considered.

Results showed individuals with low general self-efficacy to find vicarious experience information significantly less beneficial for their self-efficacy in completing a set task when compared to others with high general self-efficacy. Those with low general self-efficacy were more likely to make negative self-comparisons to the vicarious experience information, restricting its potential to increase their self-efficacy. In contrast, participants with high general self-efficacy found many of the vicarious experience information presented to be beneficial to their self-efficacy to complete the set task as they were more likely to dismiss any information they interpreted to be negative. Results from this study highlight the importance of more research into how vicarious experience information can be designed and presented in a way that ensures benefit to the task-specific self-efficacy of all individuals, regardless of their general self-efficacy beliefs at the time.

Introduction

Self-efficacy (SE) refers to an individual’s belief that they are able to succeed given any task that they encounter (Bandura, 1977 ). SE can be general or task specific, allowing individuals to have a range of SE beliefs about themselves at any one time. An individual’s beliefs surrounding their own levels of SE can have an impact on how they feel, think and motivate themselves. This can lead to significant contrasts in behaviour between individuals with differing levels of SE. Those with a strong or high sense of SE believe in their own capability deeply, seeing challenges as tasks to be mastered rather than threats to be avoided (Bandura, 1977 ). They also engross themselves into tasks and exert strong commitment. Any setbacks they encounter are easily recovered and learned from. These factors can all lead to enhanced personal well being by reducing stress, resulting in the individual being less likely to experience depression. Others with a weak or low sense of SE have major doubts over their own capabilities (Bandura, 1977 ). This can lead to a total avoidance of challenges as they see them as threatening situations. These individuals can spend a lot of time focussing on their previous failings and this can lead to setbacks being difficult to recover from. For this reason, these individuals can be more vulnerable to depression and stress (Bandura, 1977 ).

Levels of SE are not static and have the ability to be increased through exposure to influential information sources, one of which is vicarious experience information (VEI). VEI is argued by Gist and Mitchell ( 1992 ) to have the most instant and direct effect on an individual’s SE. If we read information about someone which implies that they have succeeded at a certain task, it raises our own belief that we too can succeed at the same task. This belief is further increased if we observe an individual that we consider to be similar to ourselves (Schunk, 1987 ). Previous studies have not considered how an individual’s level of general SE affects how they interpret VEI and the benefit to their task-specific SE that they get from this information.

Bandura ( 1994 ) explains how an individual’s current general SE can shape their behaviours and this may influence how they interpret and perceive information (Gist & Mitchell, 1992 ), which could include VEI. Due to individuals with low general SE being more likely to be brought down by information and to dwell upon previous negative experiences, they may not interpret VEI or pay it as much attention when compared to others with higher levels of general SE (Bandura, 1994 ). This puts them at a disadvantage, as this may lead to low general SE individuals not finding the VEI as beneficial on their SE. The study presented in this paper considers how an individual’s general SE influences how they interpret VEI and the effect this information has on their task-specific SE. This effect is considered within the context of a career skills online learning environment (OLE). In this study an OLE is defined as ‘a virtual environment that allows individuals to access learning material’ (Ally, 2004 ).

The study works with two types of SE beliefs, general and task-specific SE, with distinct differences between the two. General SE beliefs mirror the definition provided by Bandura ( 1977 ), ‘the belief in one’s capabilities to organize and execute the courses of action required to manage prospective situations’. General SE concerns an individual’s self-belief that they are able to complete any set task at any time and are not specific. Task-specific SE beliefs, in the study presented in this paper, will refer to an individual’s self-belief that they are able to complete a specific set task presented online. Results of this study will provide knowledge on whether an individual’s general SE should be considered in the design of VEI to use within future online learning processes.

General SE and its effect on VEI interpretation

When considering the influence of VEI on an individual’s SE, previous researchers have suggested the consideration of an individual’s general SE levels (Bandura, 1994 ; Bandura & Wood, 1989 ). Bandura ( 1994 ) outlines how behaviours of those with low general SE, when compared to others with higher levels of SE, differ in four major psychological processes: c ognition, selection, motivation and affect .

With regards to cognitive processes , those with higher levels of general SE find it easier to visualise success scenarios (Bandura, 1994 ). In contrast, those with lower levels of general SE are more likely to visualise scenarios in which they fail to successfully complete the required task. Selection processes also vary between those with high and low general SE. Those with high general SE have selection processes that allow them to feel more open to trying new tasks (Bandura, 1994 ). Others with low general SE are more likely to have narrower selection processes which causes them to shy away from any new ventures that they haven’t completed successfully in the past. Higher levels of general SE are also linked to higher motivation in goals, allowing greater effort and persistence in the face of difficulties (Bandura, 1994 ; Bandura & Wood, 1989 ). Finally, affective processes differ, with individuals who have higher levels of general SE being able to deal with threats easier than others with low general SE (Bandura, 1994 ). When faced with a threat, those with low general SE dwell on their coping deficiencies and this can lead to anxiety. This anxiety can lead to them fearing their environment and worrying about the worst outcomes from situations (Bandura & Wood, 1989 ).

Considering the behaviours described above, people with varying levels of general SE may be affected differently when presented with VEI. Firstly, due to their inability to visualise success and their susceptibility to be brought down by both negative or positive social comparisons, VEI may be less effective in helping individuals with low general SE. Also, the hesitance and shying away from new ventures that those with low general SE demonstrate could limit how open they are to the positive influence of certain types of VEI. Past experiences could also influence how an individual interprets VEI. If an individual has low general SE because they have experienced failures in related tasks that have been set before, it could be difficult for VEI to increase their SE in being able to attempt completing the task again. This could be due to the prevailing negative memories that gave rise to the individual’s current low level of general SE. Finally, individuals with low general SE may be more cautious towards potential threats and less likely to be able to deal with the stress caused by these effectively.

Previous work

During a literature search, we were unable to find any previous work conducted which examined how the effects of VEI for promoting task-specific SE in OLE’s were moderated by general SE. However, we did find previous studies that considered the moderating effect of different types of SE (both general and task-specific) on an individual’s interpretation of other types of persuasive messages designed to encourage behavioural changes. The work presented is based upon these types of previous work.

A series of previous studies have supported the key role that SE can play in shaping recipients behavioural responses to health messages with a particular focus on ‘framed messages’ (Riet, Ruiter, Werrij, & De Vries, 2008 ; Riet, Ruiter, Werrij, & De Vries, 2010 a; Riet, Ruiter, Smerecnik, & De Vries, 2010 b; Yang, Chen, & Wang, 2016 ). Two equivalent pieces of information can be framed in either a positive or negative way (Block & Keller, 1995 ), named ‘gain-framed ‘or ‘loss framed’ respectively (Yang et al., 2016 ). Gain-framing presents the positive outcomes of adherence to the message communicated, for example ‘If you reduce your daily sugar intake, you reduce your risk of developing tooth decay’. Loss-framing communicates the negative consequences of non-adherence to the message communicated, for example ‘If you don’t reduce your daily sugar intake, you increase your risk of developing tooth decay ‘.

Riet et al. ( 2008 , 2010 a, 2010 b) conducted a series of studies looking into the influence that an individual’s SE has on how they interpret loss and gain framed health messages. In Riet et al. ( 2008 ), researchers studied the effect of message framing on helping individuals to quit smoking. They found that when an individual had high SE in being able to quit, loss-framed messages were more beneficial in encouraging them to take the behavioural steps to stop smoking. For others with lower levels of SE in being able to quit, they found neither loss or gain framed messages to be of any benefit on their behavioural intention to stop smoking. The researchers suggest that individuals with high SE are able to avert the threats presented in loss framed messages more effectively than others with lower SE. This was one of the earliest studies to present the moderating effect that an individual’s SE can have regarding the effect of message framing on persuading behavioural change.

Following on from this, Riet et al. ( 2010 a) conducted another study looking into the effect of skin cancer detection messages among university students. The SE described in this study was that of being able to perform a skin cancer self-examination. Once again, this study supported the benefit of using loss framed over gain framed messages for students with higher levels of SE, as these messages were found to increase their intention to perform skin examinations. Also, similar to the earlier study, neither type of framing was found to be of benefit to those with lower SE and their intentions to perform future skin examinations. The researchers suggest that for those with lower SE, the loss framed message presents a great sense of threat. For some this may lead to lower levels of message acceptance, as they are likely to engage in defensive avoidance (e.g. ‘That won’t happen to me’ ) or message derogation processes (e.g. ‘This doesn’t apply to me’ ) (Witte, 1992 ).

In a third study Riet et al. ( 2010 b) explored whether an individual’s SE in being able to decrease their salt intake had any influence on the effect of gain and loss framed messages that promoted a low salt diet. The results of this study supported the earlier two studies. As a result, the researchers suggested that loss framed messages may be more effective than gain framed messages in decreasing salt intake, but this is only for individuals that already had a high SE to do so.

Yang et al. ( 2016 ) conducted a study investigating the effect of message framing on individuals decisions about undergoing treatment in the form of therapeutic exercise. All of the participants in this study suffered with some form of chronic pain and during the study were shown either loss or gain framed messages about therapeutic exercise. The mediating effect of an individuals SE in being able to complete therapeutic exercise was considered, with the effect on individuals with low and high SE being analysed. Results of this study differed slightly to the earlier studies outlined by Riet et al. ( 2008 , 2010 a, 2010 b) as they found both low and high SE individuals to be positively influenced by the loss framed message. The researchers put this new result regarding low SE individuals down to self-affirmation. If a low SE individual felt good about themselves generally, this may have reduced the perceived threat of the information and may have lead to them acting in less of a defensive way towards it (Sherman, Nelson, & Steele, 2000 ).

Previous literature has highlighted the differences between the behaviour of those with low and high SE when interpreting certain types of persuasive message. However, there has not been any previous work regarding the interpretation of VEI. Due to the difference in behaviour between those with low and high general SE (Bandura, 1977 ), it could be assumed that VEI being presented within an OLE may also be interpreted in different ways dependant on the general SE of the individual at the time.

Research purpose and hypotheses

The effect of an individual’s general SE and how it influences the benefit of VEI on task-specific SE within an OLE is an area where little previous work has been conducted. This study will focus on the effects that different forms of VEI have on the task-specific SE beliefs of individuals within an online learning process. Analysis will compare these effects between individuals with low and high levels of general SE. For this study, the following three hypotheses are proposed:

Hypothesis 1: Individuals with low general SE will find VEI less beneficial for increasing their task-specific SE compared to those with high general SE.

Hypothesis 2: Individuals will find VEI demonstrating high levels of success to be more beneficial on their task-specific SE when compared to VEI demonstrating lower levels of success, regardless of their general SE.

Hypothesis 3: Individuals with high general SE will not experience any negative effect on their task-specific SE when exposed to any type of VEI whereas individuals with low general SE will experience negative effects on their task-specific SE as a result of some VEI types.

The results of previous studies have shown individuals with low general SE to find persuasive messages less effective in encouraging behavioural changes (Riet et al., 2008 , 2010 a, 2010 b). Hypothesis 1 predicts, based upon these previous studies, that individuals with low general SE will not find VEI as beneficial on their task-specific SE when compared to others with high general SE.

Hypothesis 2 expects VEI types demonstrating a high level of success to be more beneficial to an individuals task-specific SE than VEI demonstrating lower levels of success. Bandura ( 1977 ) suggests that VEI that conveys a clear level of success is more likely to improve an individual’s SE more so than information where the success level is unclear or low. Considering this previous literature, this study will investigate the effect of using VEI demonstrating a clear success and whether this is more beneficial on an individuals task-specific SE within a career skills OLE.

Bandura ( 1994 ) also outlines characteristics of individuals with high general SE. Hypothesis 3 is based upon these characteristics predicting those with high levels of general SE to be more resilient and therefore less likely to be faulted by negative information, such as VEI demonstrating low levels of success. Because of this, it is expected that no VEI types will have a negative effect on the task-specific SE of individuals with high general SE. In contrast this hypothesis suggests that the task-specific SE of individuals with low general SE may be affected in a negative way by some types of the VEI presented in this study. This is based on characteristics of individuals with low general SE outlined by Bandura ( 1994 ) and Bandura and Wood ( 1989 ). Those with low general SE may experience anxiety or threat when presented with VEI portraying low levels of success, which could have a negative impact on their task-specific SE.

Methodology

Participants.

Participants were recruited using Amazon mechanical turk. They received a small monetary reward for completing the study. All participants were native english speakers and actively looking for a job at the time of the workshop. One hundred and thirty-six participants took part in the study. Of those that provided demographic information, the sample was 50% male and 50% female. Participant age ranged from 20 to 67 ( M  = 36, SD  = 11.4). Most participants were in some form of employment: full time (38%), part-time (12%) or self-employed (8%) at the time of completing the study. The full demographic information of the study participants is shown in Table  1 .

Before starting the analysis, we grouped participants based upon their general SE beliefs. The data population was split into two halves: low and high general SE groups. Participants were grouped, depending on their general SE score provided in the pre-workshop questionnaire. Those in the low SE group had a general SE scale score lower than the total population mean of 31 ( N =  68). Participants in the high SE group had a general SE scale score of 31 or above ( N =  68).

Research design

We used a between-groups experimental design, with each participant only being shown one type of VEI. In this study, the independent variable was the VEI type that the participant had read. Other variables included in the study include participant general SE, VEI type and benefit of the VEI on participants task-specific SE.

In order to analyse the data with reference to Hypothesis 1, significance testing looked for a main effect between a participants level of general SE and the benefit found to their task-specific SE from the information they had read, regardless of what VEI type it was. For Hypothesis 2 analysis, significance testing looked for a main effect between the level of success demonstrated in the VEI (low or high) and the benefit found to a participants task-specific SE after reading the VEI. But further to this, analysis also observed to see if there was an interaction effect between the level of success demonstrated in the VEI and an individuals general SE on how beneficial the VEI is for their task-specific SE. In this case, it is assumed that no significant interaction effect would be present.

Analysis for Hypothesis 3 was conducted in two halves. Firstly, the mean effect of each of the VEI types on the task-specific SE of participants with low and high general SE was calculated. A one sample two-tailed t-test was then conducted to find differences from the mean rating of 3, ‘no effect’. Once these significant differences were found, they were sorted into either significantly positive effects or significantly negative effects on task-specific SE. These significant effects on participants with low and high general SE were then considered when analysing for Hypothesis 3.

There were three types of VEI; a percentage completion statement, a previous answer and a testimonial. For each of these VEI types there were versions demonstrating low and high levels of success, resulting in six different types of VEI altogether. The different types of VEI represented different ways of conveying information about more or less successful completion of tasks by previous participants. All of the VEI forms created were fictitious and were created for the purpose of the study.

The first VEI type conveyed completion directly through a statistic, via a percentage completion statement (See Fig.  1 ). This statement described the percentage of individuals that had completed the task before them and the percentage that had failed to complete it. The first version of this VEI type stated that a low percentage of participants had completed the workshop successfully (45%) and the second version stated a high percentage of previous workshop participants (95%) had been successful in completing the set task. This type of VEI was chosen because it was considered the most direct way of communicating levels of success to the reader.

Percentage completion statement (High level of success version)

The second type of VEI demonstrated more or less successful completion of the task indirectly via an example of a previous participant’s answer (See Fig.  2 ). This type of information had been used in a previous study but was not found to lead to increases in SE beliefs (Newman & Tuckman, 1997 ). The first version was an answer that would have scored low according to a mark scheme that was provided earlier on in the workshop. The second version was an answer that would be scored highly according to the markscheme. This type of VEI conveyed not only success in completing the task but gave information about how to complete the task well through the good and bad examples.

Previous participants answer (Low level of success version)

The last type of VEI conveyed success of completion through a testimonial from a previous workshop participant (See Fig.  3 ), a type of VEI that has also been used in previous studies (Kelly, 2017 ). The first version was a testimonial in which an individual described how they were unsuccessful in completing the set task. In contrast, the writer of the second testimonial describes how they were able to successfully complete the task set. This type of VEI included the subjective opinions from previous participants about the experience of doing the task.

Participant testimonials (High level of success version)

Data was collected using questionnaires at two points during the study: the pre-workshop questionnaire and the VEI response questionnaire .

The pre-workshop questionnaire obtained participants demographic data including their age, gender and current employment status. Participants initial levels of general SE were assessed in this questionnaire using the ten item general SE scale (Schwarzer & Jerusalem, 1995 ). Evidence of this scales validity has been found in a variety of domains (Grammatopoulou et al., 2014 ; Mystakidou, Parpa, Tsilika, Galanos, & Vlahos, 2008 ). In this scale, participants were presented with ten statements and asked to state how true of themselves they feel each statement is. They indicated their answer on a four-point likert scale, ranging from 1 ( Not at all true ) to 4 ( Exactly True ). One to four points were awarded for each item based on their scale response, with exactly true having the highest four points awarded and not at all true having the lowest one point awarded. All 10 item points are totalled up to create an overall general SE score, out of a possible 40. During analysis it was assumed that the higher the score, the higher the participants general SE beliefs were at the time.

During the VEI response questionnaire , participants were asked what effect they felt reading the VEI had on their task-specific SE. Participants provided answers on a five-point likert scale, ranging from 1 ( Strongly decreased ) to 5 ( Strongly Increased ). An open ended question followed directly after this question which asked participants to explain why they felt the VEI had the effect on their task-specific SE that it did. This question would provide qualitative data which would help offer insight into participants reasoning for their earlier answer.

During the study, participants were guided through an online workshop entitled The Career Skills Workshop . The workshop focussed on career skills, providing information on the STAR principle. The STAR principle outlines a structure commonly used to answer competency based questions in job interviews. Competency based questions are where an interviewer asks the interviewee to provide evidence of a particular skill they are looking for in an employee. The workshop was created using the Google forms platform.

Before beginning the workshop, participants were asked to fill in the pre-workshop questionnaire which collected their demographic data and starting general SE levels. The workshop started initially by presenting the participant with a number of pages to navigate through. These pages included information about the STAR principle, including an explanation of what it is and how to use it correctly. After reading the workshop material, participants were presented with a small quiz. The quiz contained three multiple choice questions, asking them to recall what they had just read. Anyone who scored 33% or less in the quiz was discounted from the dataset, as it was concluded that they had not effectively read the information presented to them up to this point.

After completing the quiz, participants were shown a task to complete, the exact task set is outlined in Fig.  4 . This task drew upon the skills learnt in the first section of the workshop, asking them to answer an example job interview question using the STAR principle. Participants were shown a mark scheme (see Fig.  5 ) which outlined the aspects that would make up a high scoring answer. At this point, participants were randomly exposed to one of the six VEI types created. After exposure to the VEI, participants completed the VEI response questionnaire to gauge their reactions to the single VEI they were presented with and the effect it had on their task-specific SE. After this, participants were left to complete the task if they wished. In this study, actual performance on the task was not considered as it was not relevant to the hypotheses posed.

The set task that participants were asked to complete in the online workshop

Mark scheme shown to participants

Effect of participants general SE

The results outlined in this section address Hypothesis 1 directly, considering the effect an individual’s general SE has on how much of a boost they experience to their task-specific SE from reading the VEI presented. Figure  6 presents a comparison of the main effect of participant general SE level on the benefit to their task-specific SE when considering all VEI types combined. Testing found that overall, participants with high general SE found the VEI presented to have a more positive effect on their task-specific SE ( M  = 3.7, SD  = 0.80) when compared to the low general SE group ( M  = 3.2, SD  = 0.81), F (1, 124) = 15.8, p  < .001.

A comparison of the mean effect of VEI on task-specific SE between participants with low and high levels of general SE

VEI level of success

The results in this section address Hypothesis 2, considering the benefit on task-specific SE of VEI demonstrating low and high levels of success. There was a main effect found of the level of success demonstrated in the VEI presented on the benefit of the information to an individuals task-specific SE. Figure  7 presents a comparison of the effect on task-specific SE between VEI showing low and high levels of success. VEI showing a high level of success was found to have a more positive effect on an individuals task-specific SE ( M  = 3.6, SD  = 0.68) when compared to VEI showing a lower level of success ( M  = 3.3, SD  = 0.95), F (1, 124) = 6.7, p  = .01. No interaction effect was found between the level of success communicated in the VEI and participants general SE on how beneficial they found the VEI for their task-specific SE, F (1, 124) = 0.49, p  = .48.

Comparison of the mean effect on task-specific SE of VEI showing low and high levels of success

A three-way ANOVA found a significant two-way interaction between VEI type (percentage statement, previous answer or testimonial) and level of success (low or high) on participants’ task-specific SE (Decreased, increased or no effect), F (2, 124) = 9.02, p  < .001.

Figure  8 shows a comparison of the interaction effect on benefit to an individuals task-specific SE of VEI type and level of success demonstrated. Significant differences were found when comparing the effect of low success and high success versions of each of the VEI types. The percentage statement demonstrating the high level of success was found to have a significantly more positive effect on participants’ task-specific SE ( M  = 3.7, SD  = 0.68) when compared to the percentage statement demonstrating the low level of success ( M  = 3.1, SD  = 1.12), t (41) = 2.18, p  = .03, d  = 0.64. The positive testimonial demonstrating a high level of success was also found to be more beneficial for task-specific SE ( M  = 3.7, SD  = 0.56) when compared to a negative testimonial demonstrating a low level of success ( M  = 2.9, SD  = 0.64), t (45) = 4.75, p  < .001, d  = 1.32. However, in the case of the previous answer, the version showing low levels of success was found to have a significantly better effect on task-specific SE ( M  = 4.0, SD  = 0.79) when compared to the good previous answer demonstrating high levels of success ( M  = 3.5, SD  = 0.72), t (41) = 2.26, p  = .03, d  = 0.66. This is in contrast to the relationship between levels of success communicated for the other two VEI types presented in the study.

Comparison of means - VEI type vs Level of success communicated

When considering the effect in the other direction, a one-way ANOVA considered the benefit of each of the low success VEI types against each other and there was a significant difference found, F (2,64) = 10.9, p  < .001. Post hoc testing found significant differences between the effect on task-specific SE of the low percentage statement and the poor answer. Two sample t-testing showed the bad answer to have a significantly more beneficial effect on task-specific SE ( M  = 4.0, SD  = 0.72) when compared to the low percentage statement ( M  = 3.1, SD  = 1.12), t (33) = 3.01, p  = .004, d  = 0.96. The bad answer was also found to be significantly more beneficial on an individuals task-specific SE when compared to the unsuccessful testimonial ( M  = 2.9, SD  = 0.64), t (38) = 5.45, p  < .001, d  = 1.61. No differences were found between the effects of the unsuccessful testimonial and the low percentage statement on individuals task-specific SE, t (28) = 0.76, p  = .45. The ANOVA found no significant differences when comparing the benefit of the three successful VEI types against each other, F (2,66) = 0.9, p  = .4.

Potential negative effect of VEI on participants with low vs. high general SE

To address Hypothesis 3, the presence of significant negative effects on the task-specific SE of each of the separate VEI types was calculated for those with low and high general SE. A one sample two-tailed t-test was conducted for differences from the mean rating of 3, ‘no effect ‘.

Figure  9 shows the mean effect of each VEI type on the task-specific SE of individuals with low general SE, with an asterisk highlighting the effects to task-specific SE (both negative and positive) that were found to be significantly different to the known mean of 3 (‘no effect ‘). In Fig.  9 , there is a horizontal dotted line through the Y axis at ‘No effect ‘, representing the boundary between negative and positive effect on task-specific SE. Significant differences to the known mean were found for four of the six VEI types: the high percentage statement, the poor answer, the unsuccessful testimonial and the successful testimonial.

Mean effect of each VEI type on the task-specific SE of individuals with low general SE. An asterisk (*) indicates a mean significantly different from 3 (‘No effect ‘)

The effect of the high percentage statement ( M  = 3.3, SD  = 0.5) was found to be significantly different from the known mean, indicating that this type of VEI was significantly beneficial on the task-specific SE of those with low general SE, t (10) = 2.3, p  = .04, d  = 0.6. The poor answer ( M  = 3.5, SD  = 0.72) was found to be significantly beneficial on task-specific SE of this group also, t (8) = 2.29, p  = .05, d  = 0.69. Finally, the successful testimonial ( M  = 3.6, SD  = 0.52) was found to have a significantly positive effect on the task-specific SE of individuals with low general SE, t (7) = 3.42, p  = .01, d  = 1.18. In contrast, the unsuccessful testimonial ( M  = 2.7, SD  = 0.47) was found to have a significantly negative effect on the task-specific SE of individuals with low general SE, t (13) = 2.28, p  = .04, d  = 0.64.

Figure  10 shows the mean effect of each VEI type on the task-specific SE of individuals with high general SE, with an asterisk highlighting the effects to task-specific SE (both negative and positive) that were found to be significantly different to the known mean of 3 (‘no effect ‘). There is a horizontal dotted line through the Y axis at ‘No effect ‘, representing the boundary between negative and positive effect on task-specific SE. One-sample t-tests found significant differences to the known mean for four of the six VEI types (the high percentage information, the poor answer, the good answer and the successful testimonial), with all of them being significantly more beneficial than the known mean.

Mean effect of each VEI type on the task-specific SE of individuals with high general SE. An asterisk (*) indicates a mean significantly different from 3 (‘No effect ‘)

The effect on task-specific SE from the high percentage information ( M  = 4, SD  = 0.68) was found to be significantly higher than the known mean t (13) = 5.5, p  < .001, d  = 1.5. This was also the case when considering the poor answers ( M  = 4,4, SD  = 0.5) effect on participants task-specific SE, t (10) = 8.9, p  < .001, d  = 2.8. The good answer ( M  = 3.6, SD  = 0.81) was found to significantly benefit the task-specific SE when compared to the known mean, t (10) = 2.6, p  = .03, d  = 0.74. Finally, the last type of VEI found to have a significantly positive effect on task-specific SE when compared to the known mean was the successful testimonial ( M  = 3.8, SD  = 0.60), t (12) = 4.62, p  < .001, d  = 1.33.

Qualitative analysis on influence of VEI types

Further to the quantitative data outlined above, we collected qualitative data during the study which outlining participants thoughts on how the type of VEI they were presented with affected their task-specific SE beliefs. The aim of this analysis was to get a more in depth understanding of possible reasons why each of the VEI types presented affected participants task-specific SE either positively, negatively or not at all. We analysed the qualitative data from the open ended question asked during the study using thematic analysis (Braun & Clarke, 2006 ). Common themes mentioned within responses to each VEI type were identified and are outlined below. Themes were sorted by the effect they had on participants task-specific SE (positive, negative or no effect) as well as by whether the participant had low vs. high general SE.

Reasons for positive effect on task-specific SE

With regards to the positive effects on task-specific SE stated, four main themes were identified which are explained for each VEI form below: self-comparisons, reassurance, reducing task difficulty and gaining of knowledge.

With regards to the high completion statement, participants in both groups made positive self-comparisons after reading the information. They believed if 95% had been successful in completing the task then they could also be successful. These beliefs had a positive effect on individual ‘s task-specific SE, ‘I feel I’m with the 95%. If so many can do it, I certainly can’. The fact that so many others had completed it also lead to some participants perceiving the task to be less difficult. This in turn had a positive effect on their task-specific SE, ‘ Knowing that a very high percentage of participants were able to complete the task lets me know that completing the task must not be that difficult to do’.

Some participants also conducted positive self-comparisons to the bad answer and felt that they could do better, ‘ The information was not that great and I believe my abilities are beyond what was shown to me’. The bad answer also appeared to reinforce participants awareness in their own ability which had a positive effect on their task-specific SE, ‘ My awareness of my own ability was reinforced and therefore increased my confidence and motivation to be able to perform effectively and therefore increased my self-belief’. Participants also felt they gained knowledge as the bad answer taught them about what not to do in their answers and this had a positive effect on their task-specific SE, ‘ It increased my self-belief as I could clearly identify what was lacking in the answer’.

Participants also felt that they gained knowledge from reading the good previous answer, as it provided an example which helped understanding, ‘I feel better about how I will handle the task at hand because I now have a better understanding of what is required of me and what form of answer is acceptable’. Some participants made positive comparisons between themselves and the testimonial writer. They felt that because the testimonial writer. Had been successful, they could be too, ‘ Seeing someone else accomplish this goal has made me think that I too can be successful’.

Positive self-comparisons were also made when participants read the unsuccessful testimonial and this was done by both the low and high general SE groups. Participants described how they felt they were more capable than the individual in the testimonial presented, ‘ My capability is not the same as this persons. What they feel they are capable of doing has no bearing on me’.

When reading the positive testimonial, participants in the high general SE group felt it increased their task-specific SE because they gained knowledge from it which included tips and examples, ‘ It gave me a good idea on what to do to solve the task’. Participants in both groups made positive self-comparisons which had a positive effect on their task-specific SE. They felt that if the testimonial writer could do it, then so could they, ‘ If someone else that was unsure was able to do it that I could too’. Participants in both groups stated that reading the testimonial decreased the perceived task difficulty which had a positive effect on their SE. Overall, participants appeared to find the positive testimonial reassuring and it had a beneficial effect on their task-specific SE, ‘ I feel like this person boosted my thoughts and ability to do the task at hand’.

Reasons for negative effect on task-specific SE

Two main themes were found within the negative effects the VEI had on participants task-specific SE, worry and negative self-comparisons. With regards to worry, the low percentage statement left many participants in the low general SE group questioning their own beliefs, leading to feelings of uncertainty and worry, ‘ I feel a little more worried about my ability to complete the task’.

S ome participants in the low general SE group made negative self-comparisons to the good answer presented. They felt that they wouldn’t be able to write something as good and this lead to a decrease in their perceived task-specific SE, ‘ A good answer puts me down because I realise that I wouldn’t be able to come up with something this easy’. For participants in both the low and high general SE groups, reading the negative testimonial also lead to negative self-comparisons. This resulted in some participants realising they shared the same views as the testimonial writer and this had a negative effect on their task-specific SE, ‘ Because we share same views and beliefs about the task, I believe I will underperform for the question’.

Reasons for no effect on task-specific SE

One key theme was highlighted in the comments of those participants of which the VEI had no effect and that was dismissal of the information. This theme was mentioned in participants responses regarding all of the VEI forms presented apart from the good answer. Much of the dismissal was down to participants already having established strong self beliefs, ‘ I am a very self-confident person, and being shown a percentage of those who complete a task or not does not change my self-confidence’. Others stated that they are never influenced by external information in cases like this, ‘ I believe in the talents that I have. I would never let outside forces influence my confidence to such a degree’.

Discussion and conclusion

Overall, the results of this study have highlighted the mediating effect that an individual’s general SE can have on the interpretation and effect of VEI when presented within an OLE. The first hypothesis suggested that based upon previous studies looking into the moderating effect of an individual’s general SE on their interpretation of persuasive messages (Riet et al., 2008 , 2010 a, 2010 b), individuals with low general SE beliefs would not find VEI to boost their task-specific SE as much as others with high general SE. Results of the study supported this hypothesis. A main effect was found of an individual’s general SE level on the boost felt to their task-specific SE from reading the VEI presented. Those with high levels of general SE found reading the VEI to increase their task-specific SE significantly more than participants with low levels of general SE. Results support this hypothesis and show participants with low levels of general SE to find VEI less beneficial for increasing task-specific SE compared to those with high general SE.

The qualitative results highlighted how those with low general SE were less likely to make positive self-comparisons to the VEI they were presented with when compared to the high general SE group. Those in the low general SE group were more likely to make negative self-comparisons to VEI presented, even if it communicated a high level of success. In the case of the good previous answer, some low general SE individuals made negative self-comparisons, feeling that they were not able to create an answer as good as the one they had just read. Results of this study support the mediating role of an individual’s general SE in the interpretation of persuasive messages, as suggested in previous studies (Riet et al., 2008 , 2010 a, 2010 b). But this study considered this previous work within the interpretation of persuasive messages in the form of VEI, an information type that had not been considered previously.

The results also supported Hypothesis 2, as a main effect was found of the level of success demonstrated in the VEI on its benefit to an individual’s level of task-specific SE. Results describe how study participants perceived the VEI demonstrating a high level of success to be significantly more beneficial to their task-specific SE when compared to VEI communicating low levels of success. Qualitative analysis offered some insight into why participants found VEI demonstrating high levels of success to be beneficial. For some individuals, successful types of VEI provided them with extra information which they felt increased their SE in being able to complete the task. For example, the good answer provided the participants with a guide of how to structure their task answers. Other participants felt successful VEI types encouraged positive self-comparisons. In this process, the participant would compare themselves to the information, which would lead to increases in task-specific SE. In reference to the positive testimonial, some participants felt that if the testimonial writer was able to complete the task successfully, then so could they. VEI demonstrating high levels of success lead to some participants perceiving the task to be less difficult, increasing their task-specific SE. Finally, some participants felt reassured in their own abilities by reading information regarding others successes, this was especially the case for the successful testimonial information.

The qualitative data collected also gave an indication as to why some individuals found VEI types demonstrating low levels of success to decrease their task-specific SE. When reading these VEI types, some individuals would conduct negative self-comparisons. This process would result in participants feeling that they were not similar at all to the individuals in the VEI presented. Because of this, some participants felt that they would not be able to complete the task. These comparisons would lead to worry, which was found to have a negative effect on individuals task-specific SE.

Where there was a main effect of VEI demonstrating a high level of success to be more beneficial to an individuals task-specific SE than low success VEI types, this was caveated by an interaction effect where the bad example answer VEI type was perceived as more beneficial by participants to their task-specific SE than the good example answer. Qualitative data provided by the participants that were presented with the poor answer was useful in understanding why it had a positive effect on some individuals task-specific SE. Some people made positive social comparisons to the poor answer, they felt that they were able to do a lot better and this increased their task-specific SE. For others it was reassuring seeing other people not do that well on the task, and reinforced their beliefs about their own skills and abilities. The characteristics of individuals with high general SE outlined by Bandura ( 1994 ) were considered in this hypothesis. As those with high levels of general SE are more resilient and less likely to be faulted by negative information, it was suggested that VEI demonstrating a low level of success would not have a negative impact on their task-specific SE.

Finally, the results presented support Hypothesis 3, as none of the VEI presented in this test had a significantly negative effect on the task-specific SE for individuals with high general SE, not even the VEI demonstrating low levels of success. Qualitative results offered some insight into the thought process of individuals with high general SE when presented with VEI communicating a low level of success. Many individuals in the high general SE group ‘dismissed ‘any low success VEI they were shown. Some individuals in the high general SE group stated that they already had strong self-beliefs that would not be affected by such information. Others explained how they were never influenced by external information. Overall these results support the resilience that Bandura ( 1994 ) suggests those with high general SE have when confronted with negative types of information within an OLE.

The second half of Hypothesis 3 was also supported, as not all VEI presented to those with low general SE had a positive effect on their task-specific SE. A one-sample t-test found the unsuccessful testimonial information to have a significantly negative effect on individuals task-specific SE when compared to the known mean (‘No effect ‘). Qualitative data collected helps to understand why this type of VEI might have a negative effect on the task-specific SE of individuals with low general SE. For some individuals, reading the negative testimonial lead to negative self-comparisons. This was a process in which some participants realised they shared the same views as the person they were presented with. This perceived similarity may lead to the individual believing that because they were similar to the testimonial writer, they too wouldn’t be able to complete the set task, leading to the information having a negative effect on their task-specific SE. These results support theory regarding the anxiety and threat an individual with low general SE feels when presented with a VEI demonstrating low levels of success (Bandura, 1994 ).

Overall, the results have supported all three hypotheses posed in the study, building upon previous work regarding the effect of an individual’s general SE on how they interpret persuasive messages. An individual’s level of general SE was found to be a mediating factor in the effect different types of VEI had on their task-specific SE within a career skills OLE. Results have shown VEI to be less effective in increasing the task-specific SE of individuals with low general SE beliefs within the context of an OLE. Results suggest a need for VEI to be designed and presented in a way that considers the behaviours of both individuals with high but in particular, low levels of general SE.

Results support the need for more research to be conducted to find the most effective way of presenting VEI so it increases the task-specific SE of all learners within an OLE, regardless of their general SE. Individuals with low general SE found the unsuccessful testimonial presented in this study to have a negative impact on their task-specific SE, so this type of VEI should be avoided for this group. In contrast, individuals with high general SE didn’t find any of the VEI presented to have a negative impact on their task-specific SE. Results show low general SE individuals to be a more sensitive influenceable group and because of this, care must be taken that their responses to VEI presented are considered differently than those with high SE.

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Abbreviations

Online learning environment

• Self-efficacy
• Vicarious experience information

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Acknowledgements

The authors would like to thank Dr. Antonios Kaniadakis and Claire Revell for their kind help in the dissemination of the workshop.

This work was funded by the Engineering and Physical Sciences Research Council (EPSRC) through the Media and Arts Technology Programme, a Research Councils UK Centre for Doctoral Training (EP/G03723X/1).

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NW led on writing of the paper with AS also contributing to the writing of the paper. All authors worked on the study design. NW carried out the data analysis, with results being discussed with AS. Both authors read and approved the final manuscript.

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Wilde, N., Hsu, A. The influence of general self-efficacy on the interpretation of vicarious experience information within online learning. Int J Educ Technol High Educ 16 , 26 (2019). https://doi.org/10.1186/s41239-019-0158-x

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Received : 04 March 2019

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Original research article, a mixed methods study of self-efficacy, the sources of self-efficacy, and teaching experience.

• 1 Center for Education Integrating Science, Mathematics, and Computing, Georgia Institute of Technology, Atlanta, GA, United States
• 2 Department of Educational Studies, St. Mary’s College of Maryland, St. Mary’s City, MD, United States

Although teaching self-efficacy is associated with many benefits for teachers and students, little is known about how teachers develop a sense of efficacy in the early years of their careers. Drawing on survey ( N = 179) and interview ( N = 10) data, this study investigates the sources of self-efficacy in a national sample of teachers who participated in the Noyce program. All teachers completed an online survey that included both the Teacher Sense of Efficacy Instrument and open-ended items prompting them to reflect on the sources of their self-efficacy. Ten teachers participated in semi-structured follow-up interviews. Enactive mastery experiences were the most common source of self-efficacy identified by teachers, followed by social persuasions and vicarious experiences. Physiological and affective states were identified infrequently and more often related to negative experiences that lowered self-efficacy than to positive experiences. Beginning teachers identified more negative enactive experiences than either Novice (2–3 years experiences) or Career teachers. In interviews, teachers described how the sources combined or interacted to influence their self-efficacy. Findings contribute to better understandings of the sources of self-efficacy with implications for how best to support teachers at different stages of their careers.

Introduction

As researchers have sought to understand factors influencing teacher effectiveness, many have explored teaching self-efficacy, defined as the teachers’ beliefs about their capability to carry out the professional tasks of teaching ( Tschannen-Moran and Hoy, 2001 ). Research conducted over several decades provides a growing body of evidence linking teachers’ self-efficacy beliefs to the quality of instruction, student achievement, and student motivation ( Klassen and Tze, 2014 ; Klassen et al., 2011 ; Zee and Kooman, 2016 ). In their synthesis of 165 studies of teaching self-efficacy, Zee and Kooman (2016) found associations between positive teaching self-efficacy and students’ academic outcomes, patterns of teacher behavior and practices related to classroom quality. Moreover, teaching self-efficacy has been shown to be related to factors underlying teachers’ psychological well-being. Teachers who believe in their capabilities tend to be more satisfied, more committed to the profession and less susceptible to burnout ( Brown, 2012 ; Aloe et al., 2014 ; Chesnut and Burley, 2015 ; Zee and Kooman, 2016 ). Thus, by understanding teaching self-efficacy and how it develops over the course of teachers’ careers, researchers and practitioners gain insight into a powerful influence on outcomes at both the classroom and individual teacher levels.

Given the benefits of a healthy teaching self-efficacy, scholars have called for research exploring the sources of these beliefs ( Klassen et al., 2011 ; Morris et al., 2017 ). What types of information, experiences, and interactions shape teachers’ self-efficacy beliefs? In his social cognitive theory, Bandura (1997) hypothesized that individuals interpret information from four sources when evaluating their self-efficacy: 1) enactive mastery experiences , which involve attainment of goals through direct action; 2) vicarious experiences , which occur through an observation of a model (or oneself) completing a task, 3) social persuasions , which consist of messages from others, and tend to differentially influence self-efficacy based on the contents of the feedback and the perceived standing of the person providing the feedback; and 4) physiological and affective states like mood, stress, and anxiety. It is important to note that sources of information can be combined when making judgments about self-efficacy. For example, individuals draw on both direct and vicarious experiences when they make referential comparisons to a perceived group norm.

Enactive mastery experiences, which involve the attainment of goals through direct action, are typically the most potent source of self-efficacy and are especially powerful when an individual accomplishes a task they view as demanding ( Bandura, 1997 ). When teachers perceive their teaching as successful, they are likely to believe in their instructional capabilities. Likewise, when teachers perceive that they have been unsuccessful, they may doubt their teaching ability. Vicarious experiences involve observing a model perform a task and can be a particularly powerful source of self-efficacy when a task is still novel and when the model being observed is perceived as similar to oneself. Thus, teaching efficacy beliefs may be most influenced by vicarious experiences in the earliest stages of teachers’ careers when many teaching tasks are still novel. Social persuasions in the form of evaluative feedback represent another source of self-efficacy beliefs. The influence of feedback depends, in part, on the degree to which the person offering feedback is considered credible and sincere. Teaching self-efficacy may be unaffected by “empty praise” or feedback from observers for whom teachers have little trust or respect. Bandura (1997) also suggested that self-efficacy beliefs are more easily altered by negative feedback than by positive feedback. Self-efficacy may also be informed by physiological and affective states including mood, anxiety, and stress.

The Sources of Teaching Self Efficacy

Attempts to study the sources of teaching self-efficacy have been somewhat limited in scope ( Klassen et al., 2011 ; Morris et al., 2017 ). In their review of research on the sources of teachers’ self-efficacy, Morris et al. (2017) described a number of limitations in this body of work. Rather than direct measures of the sources of teachers’ self-efficacy, many researchers have used elements of teacher education or professional development experiences as proxies for the four hypothesized sources in quantitative studies. When direct measures have been used, they have often been inconsistent with Bandura (1997) descriptions. For instance, many researchers operationalized mastery experiences as the quantity of teaching experiences (e.g., years teaching, opportunities for teaching) or affective appraisals, such as rating of overall satisfaction with performance. Few scholars have examined how teachers interpret the actual outcomes of their direct actions (e.g., enactive experiences) when evaluating their self-efficacy. Qualitative research typically provides more detailed accounts of the sources of teachers’ self-efficacy, yet relatively few researchers have asked teachers to describe how particular teaching experiences influence their self-efficacy. Morris et al. (2017) also noted that less research has been devoted to sources outside of mastery experiences and that few studies have been designed to assess all four sources. One exception is a recent cross-cultural study by Yada et al. (2019) that explored the sources of self-efficacy among Japanese and Finnish teachers. Consistent with previous research, this study found that in both countries, mastery experiences were the strongest contributor to self-efficacy. Interestingly, Japanese and Finnish teachers differed in how verbal persuasions predicted self-efficacy and other sources were identified as influencing Japanese teachers’ self-efficacy. A final limitation had to do with the samples used in these studies; the studies more often focused on preservice teachers than practicing teachers, and the majority of participants taught at the elementary or early childhood level. This is notable given evidence that teachers’ self-efficacy and levels of stress differ for practicing and secondary teachers ( Geving, 2007 ; Rots et al., 2007 ; Wolters and Daugherty, 2007 ; Klassen and Chiu, 2011 ).

Self-Efficacy and Teacher Experience

The relationship between the teaching experience level and self-efficacy remains unclear. In large-scale studies, bivariate correlations between years of teaching experience and self-efficacy tend to be nonsignificant or weak (e.g., Kim and Burić, 2020 ; Tschannen-Moran and Johnson, 2011 ). However, in a longitudinal study, George et al. (2018) found that teachers’ self-efficacy increased across all dimensions of self-efficacy as they progressed from their first to fifth year of teaching. Similarly, in their large-scale cross-sectional study, Wolters and Daugherty (2007) found that teachers with more experience reported higher self-efficacy. Conversely, teachers with low self-efficacy early in their careers may be more inclined to leave the profession ( Hong, 2012 ). Klassen and Chiu (2010) , on the other hand, identified a curvilinear relationship between teaching experience and self-efficacy across 1,430 practicing teachers. Across all dimensions, teaching self-efficacy peaked at approximately 23 years of experience before declining. They speculated that this decline in the later years – which may explain the overall weak correlations between experience and self-efficacy – may be due to the loss of enthusiasm Huberman (1989) described toward the end of a teaching career.

Few scholars have explored differences in teachers’ self-efficacy at different points in their careers, and the existing research has been undermined by problematic measures. Research from teacher education and professional development programs indicates that learning pedagogical skills and having a chance to apply them in an authentic setting can improve self-efficacy ( Tschannen-Moran and McMaster 2009 ; Bruce et al., 2010 ). Pfitzner-Eden (2016) reported that mastery experiences were strong predictors of changes in self-efficacy for preservice teachers who had completed a teaching practicum but not for those who had only engaged in an observation practicum. However, mastery experiences in the study were assessed as general appraisals of success rather than the accomplishment of instructional goals. Consistent with Morris et al. (2017) description of the development of self-efficacy, these general appraisals mediated the relationship between other sources and teaching self-efficacy. As such, the inclusion of the variable obscured the direct contribution of the other sources to teaching self-efficacy.

Research on preservice teachers’ experiences may offer clues as to how teachers develop a sense of efficacy once employed. In their longitudinal study, Woolfolk Hoy and Burke-Spero (2005) found that teachers’ self-efficacy rose during their teacher education program but declined after their first year of teaching. Individuals may draw on different sources of information in evaluating their instructional capabilities as they leave teacher education and begin working in schools. Such a transition involves a change in context and more opportunities to perform instructional tasks, both of which can alter the relative potency of the sources ( Bandura, 1997 ). This can lead to seemingly contradictory findings when making comparisons across groups. For example, Klassen and Chiu (2011) reported that practicing teachers were more likely than preservice teachers to report that teaching was stressful, but had higher self-efficacy for classroom management.

Little is known about how the sources of teaching self-efficacy differ for practicing teachers at different stages in their careers. In interview studies, mastery experiences and social persuasions have emerged as powerful sources during instructors’ early experiences ( Mulholland and Wallace, 2001 ; Morris and Usher, 2011 ). These were often intertwined; given that there are few objective markers of mastery in teaching, perceptions that instructional goals are achieved were confirmed by the social appraisals of others. Woolfolk Hoy and Burke-Spero (2005) reported that affective appraisals of success (i.e., satisfaction with past performance) and perceived support from others were positively associated with changes in self-efficacy during the first year of teaching. However, teachers’ referential comparisons, in which they evaluated their success against their colleagues’, had no such influence, perhaps due to the lack of opportunities to observe others once hired. Tschannen-Moran and Woolfolk Hoy (2007) compared novice teachers (≤3 years of experience) to career teachers (>4 years of experience) using similar measures of support and satisfaction with instructional performance. In this study, career teachers reported higher self-efficacy for instructional strategies and classroom management. For both groups, satisfaction with performance predicted their teaching self-efficacy. However, overall perceptions of interpersonal support predicted self-efficacy only for career teachers, and the support of colleagues and community negatively predicted novice teachers’ self-efficacy beliefs. Tschannen-Moran and Woolfolk Hoy (2007) suggested that this may reflect the tendency of struggling new teachers to seek out support from others.

Whereas these findings offer a glimpse into the development of teaching self-efficacy, they also lead to more to questions than answers. Namely, what are the actual sources of teachers’ beliefs? The purpose of this study is to begin to develop such understandings about the sources of self-efficacy among a population of teachers participating in the National Science Foundation’s (NSF) Noyce Scholarship program. Two research questions guided the study:

1) What sources of self-efficacy are identified by Noyce teachers?

2) How do self-efficacy and the sources of self-efficacy vary according to Noyce teachers’ experience levels?

This study, which is one strand of a larger research program focused on Noyce teachers, follows an explanatory sequential design ( Creswell and Clark, 2017 ) in which qualitative data were collected to develop a deeper understanding of survey findings. Specifically, interviews were utilized to further describe and explore the sources of self-efficacy and possible interconnections among teacher experience, self-efficacy and the sources of self-efficacy.

Participants

Survey participants were 179 teachers who have participated in the Robert Noyce Teacher Scholarship program (“the Noyce program”). The Noyce program provides grants to university-based teacher education programs seeking to recruit and support STEM majors and professionals as K-12 teachers in high-need school districts. The Noyce program defines high-need districts with schools in which the majority of students are eligible for free and reduced price lunch programs, greater than 34% of teachers do not have a degree in the field in which they teach, and/or there is a teacher attrition rate over 15 percent for the previous three school years. Researchers compiled a database of Noyce programs and sent emails to each program inviting them to forward study information to teachers who had completed their program within the last 5 years. This email recruitment strategy resulted in a sample of teachers representing 47 Noyce programs in 30 states. As the larger study for which survey data were collected focuses on recent Noyce participants, the majority of survey participants ( n = 153) are considered “early career” teachers who have been full-time classroom teachers for 5 years or less. In order to ascertain variations in self-efficacy according to teachers’ experience levels, the current study divides the survey sample into three groups: “Beginning Teachers” in their first year of teaching ( n = 60), “Novice Teachers” with 2–3 years of teaching experience ( n = 50), and “Career Teachers” with at least 4 years of teaching experience ( n = 69). See Table 1 for survey participant demographics.

TABLE 1 . Survey participant demographics ( n = 179).

A purposive sample of interview participants ( n = 10) was recruited from a pool of survey participants indicating willingness to participate in a follow-up interview. Using a maximum variation strategy ( Miles et al., 2019 ), the research team selected interview participants representing a range of experience and self-efficacy levels and, to the extent possible, a sample balanced with regard to subject area (math or science), teaching level (middle or high school), and gender. Note that because interview participants were recruited from the sample of teachers completing the survey the previous year, the interview sample does not include beginning teachers in their first year teaching. To protect participant confidentiality, all interview participants are identified using pseudonyms. See Table 2 for interview participant demographics.

TABLE 2 . Interview participant demographics.

Data Sources

The survey was administered online to Noyce teachers during the second half of the academic school year. As described below, the survey included a self-efficacy scale and open-ended items prompting teachers to reflect on the sources of their self-efficacy. Teachers were also asked to provide demographic data (age, gender, race/ethnicity), information on their teaching experience (years of teaching experience, subject taught, level taught), and educational background (undergraduate major).

The Teachers’ Sense of Efficacy Scale

Tschannen-Moran and Hoy (2001) Teachers’ Sense of Efficacy Scale (TSES) was utilized to measure self-efficacy beliefs. The TSES asks teachers to rate their agreement with self-efficacy items along a 9-point continuum (with anchors at 1 - Nothing, 3- Very Little, 5 - Some Influence, 7 - Quite A Bit, 9 - A Great Deal). It includes three subscales measuring teachers’ self-efficacy for instructional strategies, classroom management, and student engagement. The TSES has been widely utilized and is generally accepted as a valid and reliable measure of teachers’ self-efficacy beliefs ( Klassen et al., 2011 ; Zee and Koomen, 2016 ). Because teachers were completing the TSES as part of a much longer survey, this study used the twelve-item short form of the instrument. Tschannen-Moran and Hoy (2001) reported strong evidence of construct validity and reliability values (alphas) of 0.90 and for each of the subscales ranging from 0.81 to 0.86.

Open-Ended Items

Following the TSES, two open-ended prompts adapted from Morris and Usher (2011) were used to elicit teacher reflections on the sources of their self-efficacy:

1) What experiences in your professional life as a teacher have made you more confident in your teaching ability? Please explain why these experiences made you feel more capable as a teacher.

2) What experiences in your professional life have lowered your confidence in your teaching ability? Please explain why these experiences made you feel less capable as a teacher.

Teachers’ responses to open-ended survey items ranged in length from a few words to several paragraphs, with most responses including three to four sentences in response to each question.

Ten semi-structured interviews lasting approximately 60 min were conducted by one of three members of the research team during the school year following survey administration. Interviews were conducted by telephone during a 1-month period. All interviews were audio-recorded and transcribed for analysis. Interviews utilized a protocol adapted from Morris and Usher (2011) designed to elicit teachers’ accounts of the sources of their self-efficacy (see Table 3 ). The protocol included both prompts designed to tap the hypothesized sources of self-efficacy as well as questions that allowed teachers to reflect more broadly on the sources of their self-efficacy.

TABLE 3 . Interview protocol.

Data Analysis

TSES data were analyzed using guidelines suggested by Tschannen-Moran and Hoy (2001) , with average scores calculated across all items and for items within each sub-scale. One-way ANOVAs and independent samples t -tests were used to compare teachers’ scores on the TSES and TSES sub-scales by gender, subject area, and experience level (Beginning, Novice, Career).

Responses to open-ended items were subjected to sequential qualitative analysis ( Miles et al., 2019 ). The initial codebook consisted of Bandura (1997) definitions of the sources along with specific guidance from the self-efficacy literature concerning the types of responses to be coded to each source. To identify instances related to increases or decreases in self-efficacy, the codebook included both positive and negative codes for each of the sources. Note that, because we coded for both positive and negative examples, we describe results using the term “enactive experiences” rather than “mastery experiences,” which are inherently positive. Additional codes were iteratively added and refined to code for other experiences teachers described as increasing or decreasing their confidence. Using the NVIVO software program, responses were coded by two coders who convened after coding a subset of the data to refine the codebook and establish reliability (>90%). Although the vast majority of responses could be coded to at least one source, twenty-three (6%) did not provide sufficient detail to code. Following coding, we created a database of dichotomous entries (0 = No; 1 = Yes) indicating whether each teacher identified each of the sources of self-efficacy. Chi-square tests of independence were calculated to explore the frequency with which teachers’ identified each of the sources by experience level, gender, subject, and whether teachers teach at a high-need school.

Interviews were coded and analyzed by one researcher using a codebook adapted from the one used to code open-ended survey items. In addition to applying theory-driven codes aligned to the sources, interview coding and analysis sought to identify salient patterns, themes, and stories illustrating how teachers’ experiences shaped their self-efficacy beliefs. Following coding, partially-ordered and case-ordered matrices ( Miles et al., 2019 ) were constructed to describe patterns in the sources of self-efficacy identified by interview participants.

This section first summarizes the self-efficacy and sources of self-efficacy identified by Noyce teachers then describes variations in self-efficacy by teacher experience level.

Self-Efficacy

Overall scores on the TSES ranged from 4.2 to 9.0 with an average of 6.9. Table 4 presents TSES data by experience level (Beginning, Novice, and Career). One-way ANOVAs indicated significant but modest differences in average TSES scores, F (2,176) = 3.69, p < 0.05, instructional strategies, F (2,176) = 4.94, p < 0.01, and classroom management, F (2,176) = 3.61, p < 0.05 by teacher experience level. Tukey’s HSD tests showed that Beginning teachers had lower overall self-efficacy and self-efficacy for instruction and classroom management than Career teachers. Average TSES scores and TSES subscale scores did not differ significantly by subject area (Math, Science, Both Math/Science, or Other), level (elementary, middle, or high school), gender, or whether respondents teach in a high need school.

TABLE 4 . Means, standard deviations, and one-way analyses of variance in teaching self-efficacy by teaching experience.

The Sources of Self-Efficacy

Consistent with Bandura (1997) assertion that enactive mastery experiences typically represent the most potent source of self-efficacy, these types of experiences were the most commonly cited, with 67% of teachers describing positive mastery experiences as a source of increased self-efficacy and 50% describing negative enactive experiences (e.g., failures, mistakes) as a source of decreased self-efficacy (see Table 5 ). Social persuasions were also reported frequently in open-ended survey responses, followed by vicarious experiences and affective and physiological states. Teachers were more likely to identify mastery experiences, social persuasions, and vicarious experiences when reflecting on increases in their self-efficacy than they were when describing experiences that decreased their self-efficacy. Notably, this was not the case for affective/physiological states, which only occurred in 5 (3%) teachers’ reflections on experiences increasing their self-efficacy but 31 (17%) teachers’ descriptions of experiences that decreased their self-efficacy. See Table 6 for illustrative quotations for each of the sources of self-efficacy.

TABLE 5 . Frequency of sources identified in open-ended survey responses as increasing or decreasing teaching self-efficacy.

TABLE 6 . Illustrative examples of open-ended survey responses by self-efficacy source.

Chi-square tests of independence were calculated to determine whether the frequency with which teachers identified each of the sources in open-ended survey responses (coded with binary 0–1 values) varied by teacher experience level (Beginning, Novice, Career), gender, subject area, and whether teachers currently teach at a high need school. Beginning teachers were more likely to report negative enactive experiences (e.g., failures, mistakes; 67%) that lowered their self-efficacy than Novice (42%) or Career teachers (41%), χ 2 ( 2 ,   N = 179 ) =   10.39 , p < 0.01; see Table 7 ). Women were more likely (28%) than men (2%) to identify negative affective experiences decreasing their self-efficacy, χ 2 ( 1 ) =   6.83 , p < 0.01). Science teachers were more likely (57%) to discuss negative mastery experiences decreasing their self-efficacy than mathematics teachers (36%), χ 2 ( 3 ,   N = 179 ) =   8.61 , p < 0.05. Teachers in high-need schools were less likely (11%) to report vicarious experiences increasing their confidence than teachers not teaching in high-need schools (29%), χ 2 ( 1 ,   N = 179 ) =   4.71 , p < 0.05). All other comparisons were not significant.

TABLE 7 . Frequency and percentage of teachers identifying sources of self-efficacy by experience level.

Consistent with Bandura’s assertion that people integrate multiple sources of efficacy-relevant information in forming their self-efficacy beliefs, many teachers shared experiences reflective of multiple sources. Of the 179 teachers in the sample, 49 (27%) described multiple sources when discussing experiences that increased their confidence and 26 (16)% described multiple sources when discussing experiences that decreased their confidence. These instances included both examples in which teachers listed various sources as well as examples in which teachers described experiences that integrated more than one source. In light of the frequency with which teachers cited and integrated multiple sources, the following summary presents qualitative findings related to each source while also including examples illustrating combinations of the sources of self-efficacy.

Enactive Experiences

Teachers’ reflections on enactive experiences often focused on successes and failures related to student learning and performance. As in the following survey response from Chris, teachers commonly discussed how students’ earning good grades or performing well on assessments affirmed their beliefs in their teaching ability:

The success that my students had on the end of year State Regents exams made me confident in my teaching ability. You are always a little unsure in your first year whether you are missing something, or spending too much time on certain topics or not enough on others, so to get good results reaffirms your teaching methods.

Conversely, many teachers described how students’ poor performance lowered their teaching self-efficacy. In the following survey response, a teacher described how looking at her students’ poor grades made her “feel incapable of teaching”:

I feel incapable of teaching when I look at my students’ grades and see that many of them are struggling. I provide multiple chances for my students to make up work and they still choose to let their grades slip. Even though I know I have done everything I can to assist them in passing and understanding content, I still struggle with watching them fail.

In addition to measures such as grades and test scores, teachers shared more subjective observations related to student learning. One theme that emerged from both open-ended survey responses and interview data was the occurrence of “light-bulb moments” in which teachers observed a student suddenly come to understand a new concept. In the following survey response, a high school mathematics teacher drew a direct connection between her confidence in her teaching ability and one of these “light-bulb moments”:

I feel more confident in my teaching abilities when I see a student have that light bulb moment. For example, if a student did not understand a concept the previous year or the even the first time I taught it, I feel it is encouraging when they say “Oh, now I get it!”

Other teachers highlighted observations related to student engagement and classroom management as either increasing or decreasing their self-efficacy. For example, in her survey response, one middle school science teacher wrote:

When a lesson goes really well and all students are very engaged and are using appropriate language to talk to each other about the content, this makes me feel really good and like I am doing something right. I know that I provided them enough information and support for them to understand the topic and that I chose something interesting enough to get their attention.

Teachers tended to discuss classroom management as a challenge that decreased their self-efficacy more often than they described classroom management successes increasing their self-efficacy. Several anecdotes about classroom management challenges coupled mastery experiences and affective states, often with teachers describing how frustrated or exhausted they felt when they “lost control” of their classroom.

Consistent with findings in Morris and Usher (2011) study, there were many examples of teachers framing negative teaching experiences in adaptive ways that did not seem to lower their self-efficacy. Joe described how positive experiences were fortifying, stating that on days when his lessons go well “it kind of gives you a reason to keep working through the tougher days.” He went on to discuss how he draws on these positive experiences he has “in the bank” to cope with challenging days:

There are days where you’re like, ‘Wow. That really didn’t work at all. I really need to revisit that’, but you have in the bank those days that worked really well, so you’re more motivated, I guess, to try and improve and compare the things that went well in that lesson, to maybe some of the things that didn’t go so well, and try and change the lesson for the next time that you teach it.

The tendency to reflect on negative teaching experiences opportunities for problem-solving rather than deficits in teaching ability is apparent in Alicia’s inclination to take lackluster student performance as a “cue” to reflect on “mis-instruction”:

I would know that a lesson has not gone as well as I thought it had when on the exit ticket I see that my high flyers did not do as well. That’s my cue to look for patterns of mis-instruction, write them down, think about how to reteach it or how to further explain something.

Although this type of adaptive framing was most common among experienced teachers with relatively high self-efficacy, Katy and Nicole, both second year teachers with lower than average self-efficacy, also framed negative teaching episodes as learning experiences. Katy described her reaction to lessons that do not go well, saying, “I mean, I kind of like those, because then I learn from them, you know?” Similarly, Nicole explained how “being humble enough to admit when the lesson sucks actually increases my confidence probably more than having a lesson that is successful because it gives me more information about trying different things.”

In discussing how negative enactive experiences lowered their self-efficacy, teachers primarily identified patterns of persistent failure, such as consistent low student performance over time or high proportions of students performing poorly, rather than isolated episodes. For example, in her survey response, one high school mathematics teacher shared that “students in my class consistently score low on their summative assessments. This makes me lose confidence over whether or not I am effectively communicating the information in the chapters.” Another high school mathematics teacher who struggled with student engagement shared in her survey response that she doubted her teaching ability when “multiple students in a single class were failing and none of my tactics to get them to complete work was working.”

As evident in this teacher’s reference to none of her tactics working, teachers described instances when students failed in spite of their exerting great effort as particularly detrimental to their self-efficacy. Brian explained how his confidence in his teaching ability decreased when no matter what he tried, some students “just don’t get it”:

When the kids don’t get it and when I can tell that the wheels aren’t spinning. I’m going to be honest, I can try 50 different things and there are a few kids that no matter what I try, no matter how much I do, they just don’t get it.

Similarly, several teachers described how not being able to explain students’ poor performance lowered their self-efficacy. For instance, one high school science teacher noted in her survey response that “I have had many instances where students unexpectedly fail a test or assignment, and I cannot explain why. This always makes me feel like I have done something to fail them.”

A number of science teachers described how expectations to teach outside their area of expertise, teach multiple science disciplines, or switch between disciplines precipitated negative enactive experiences that lowered their self-efficacy. For example, Steve, who majored in chemistry, noted that “my first couple years of teaching I was changing subjects pretty quickly,” adding that it was “definitely a setback, after spending a year or two in developing a curriculum, and then just being thrown into a new subject where I hadn’t taught for a while and wasn’t as confident.” This shifting context for science teachers may explain why they were more likely than math teachers to identify negative mastery experiences.

Interview data suggest that our open-ended survey data may not necessarily capture how enactive experiences interacted with other sources of self-efficacy. When asked to elaborate on survey responses that focused on enactive experiences, several teachers added information indicative of other sources. Consider the following survey response provided by Stephanie:

I was able to give a professional development on anchor charts where I was recognized for bridging the gap for ELLs. This made me feel capable because I felt like my actions truly made an impact for my students.

Although Stephanie referenced receiving recognition, this response was coded as a mastery experience because it focuses on the achievement of “bridging the gap for ELLs” and draws an explicit connection between her successful enactive experience (providing professional development) and feeling capable in her teaching. However, when Stephanie elaborated on this response in her interview, social persuasions became a more prominent source:

During those observations, they were really impressed with what I was doing, and they asked me to share it with the whole team, because that was something that the whole staff was not doing….they told me that they were impressed by the anchor charts, by the visuals that I would supply during the lesson plan, during the lesson, the kinesthetic movements that I would do with the kids, and at some point, the principal came up to me and told me that she would like to do a professional development on different teaching styles, and that what she really wanted to do was help the staff learn how to bridge the gap for the ELL learners.…So they were really impressed by it. The staff really enjoyed it and a lot of them have been emailing me and asking me to help them with anchor charts for their classroom, graphic organizer, worksheets for their class, how to translate documents.

Stephanie acknowledged her success working with ELL students but foregrounded social persuasions, noting several times that observers were impressed and referencing validation of her efforts by her principal and others. Thus, in this example, Stephanie’s teaching self-efficacy is bolstered through both her successful deployment of strategies with ELL students (mastery experiences) and, perhaps even more so, through positive feedback from other teachers and administrators (social persuasions). In other interview studies, instructors have similarly described relying on social persuasions to evaluate their achievements ( Phan and Locke, 2015 ; Morris and Usher, 2011 ).

Social Persuasions

The social persuasions teachers described most often took the form of positive or negative feedback from other teachers, administrators, students, or parents. As illustrated in the following survey response from a high school mathematics teacher, participants commonly described how receiving recognition for their teaching boosted their confidence:

Within my first months as a teacher, I was honored to be observed as an effective teacher during instructional rounds. I receive regular coaching observations that consistently show high marks for engagement and classroom culture. My Student Perception surveys report scores higher than my district and school averages. This strong positive feedback is validating, and it has helped me to feel confident that my efforts are noticed, appreciated, and effective.

Similar to Stephanie’s account above, this teacher’s response focuses on social persuasions (being identified as an effective teacher, student perception surveys, positive feedback) while also alluding to mastery experiences (success with student engagement and classroom culture). Indeed, social persuasions and mastery experiences tended to be a powerful combination, occurring in many of the most fervent accounts of positive experiences increasing teachers’ self-efficacy. For example, Andrea described an observation debrief with her principal as a particularly positive social persuasion, stating, “hearing from another adult that they learned something and they enjoyed my lesson made me feel like I could conquer the world.”

Teachers also shared examples of negative feedback or comments lowering their teaching self-efficacy. These instances often occurred in conjunction with observations conducted as part of teacher evaluations. In some cases, teachers described how receiving negative feedback precipitated a strong emotional response. For example, in her survey response, one high school science teacher explained how a walkthrough during her first year of teaching occurred “during a really bad moment in the classroom” and resulted in her feeling “like I was seen and judged at my worst,” adding that “I felt powerless to avoid being put into that situation again.”

Although teachers cited feedback from other teachers and administrators most often, they often mentioned feedback from multiple people and frequently highlighted feedback from students as particularly influential. In the following survey response, a middle school math teacher described how eliciting feedback from students increased his self-efficacy:

Having open and candid discussions with my students about their preferences has helped me gain confidence in my teaching. During those discussions, my students and I reflect on my efforts in teaching and their efforts in learning to find a happy medium where students are able to learn effectively.

In addition to informal student feedback, a number of teachers noted that their self-efficacy is influenced by formal feedback conveyed through student surveys. For example, Katy describes how she was “fairly confident” in her self-efficacy for classroom management based on the results of her school’s quarterly Learner Perceptions Survey. The dataset also includes numerous examples of teachers receiving positive feedback conveyed by former students, with students attributing their successes or the application of knowledge or skills to their experience in a teachers’ class.

Open-ended survey prompts were not designed to elicit reflections on the trustworthiness of social persuasions; however, all ten interview participants described factors that influenced how much they trusted feedback received from various sources. The most common factor teachers cited was the expertise of the person providing feedback, often sharing perceptions of administrators’ or colleagues’ experience in their subject area. For example, Steve explained how his respect for his colleagues and administrators’ influenced how much he trusts feedback stating, “there are teachers, at my school, who I respect as fellow educators. So, hearing them complement something that I’ve done means a lot more than teachers who I have less respect for.” He added that the same is true of administrators, noting that he tends to trust feedback from administrators who have a science background more readily than those who do not. In his reflection on student feedback, Steve shared how he weighs feedback provided by students according to their effort, another tendency that was recurring in the dataset:

There’s students whose feedback matters to me more than others. There is a student who’s doing well and trying really hard in class, probably more trying hard in the class than anything else. Hearing feedback from them telling me I did a good job means a lot more than a student who doesn’t really do much or a student who is sort of naturally skilled.

Vicarious Experiences

Relative to enactive experiences and social persuasions, vicarious experiences were mentioned less often. Teachers who did reference vicarious experiences most often shared observations of colleagues or mentors or strategies modeled in the context of professional development (e.g., conferences, PLCs). In the following reflection, Alicia described how her experience observing in a “random classroom” and co-teaching mathematics vicariously influenced her teaching:

I feel like I’ve been exposed to a lot of teaching styles. With the three years that I’ve been teaching, I’ve taken a lot of time out of one of my free periods to just sit in random classrooms and observe different teaching styles. Within my classroom, there are two teachers that teach two different maths, regular 8th grade math and then algebra, which is me. So when I’m not teaching, the other teacher is teaching, and through her, I’ve learned to be more detailed in my explanations … I’ve learned a lot just through watching a lot of teachers teach.

In another interesting example from the survey data, one middle school math teacher recounted filming and watching her own teaching, an activity Bandura (1997) identified as self-modeling:

Filming my teaching and watching my growth throughout my first year as a teacher, this made me feel more confident because it shows evidence of my improvement. Sometimes it’s hard to feel that I am improving since there is so much to learn as a first year teacher. However, when it is on film, the evidence cannot be denied and this makes me feel proud of my accomplishments although I know I still have room for improvement.

The influence of video self-modeling on self-efficacy has been explored in studies of parents, athletes, and students (e.g., Schunk and Hanson, 1989 ; Marcus and Wilder, 2009 ; Middlemas and Harwood, 2020 ). However, this vicarious experience has remains largely unexamined in the context of teaching, where studies have instead focused on the vicarious influence of watching others teach (e.g., Posnanski, 2002 ; Palmer, 2011 ). Bandura (1997) noted that self-modeling can provide unique information about one’s enactive attainments. As indicated by this participant, watching oneself may be particularly powerful in the early years of teaching when improvements are more obvious.

Vicarious experiences also informed referential comparisons in which teachers compared their performance to that of others. In survey responses, one teacher described feeling less confident when “students have compared my teaching to another teacher who they preferred” and another shared that “there are a lot of really good teachers at my school, and sometimes I feel very intimidated or under a lot of pressure from them.” Teachers also noted that referential comparisons could either increase their confidence or make them question their instruction. Joe explained:

I think you sort of naturally draw comparisons, and when you’re watching them teach, you are also able to watch the students a little bit more in-depth, because you don’t have to worry as much about what you’re presenting, and you can see when something really resonates with the students. So if that’s something that you also do, it reaffirms your beliefs in how you do things. Whereas, on the other hand, if it’s something that falls flat and doesn’t really resonate with the kids, you’re like, “Okay. I know that I need to avoid that in the future.”

Although vicarious experiences were identified less frequently than enactive experiences and social persuasions, there were teachers who described referential comparisons as the most important factor influencing their self-efficacy. For example, Craig admitted that comparing himself to less effective teachers is the “the thing that increases my confidence the most”:

Like I said, I think the thing that increases my confidence the most is comparing myself to other teachers, which I don’t think is necessarily a good thing. But it’s reassuring when I feel down on myself and I’m like, “I’m not a great teacher,” and then I look at the teachers around me and I’m like, “Okay, well relatively speaking, I guess I’m a really good teacher.”

By comparing his own performance (enactive experiences) with those of others he observed (vicarious experiences), Craig obtained what he felt was a more accurate assessment of his capabilities.

Affective or Physiological States

Although affective or physiological states were rarely mentioned as increasing self-efficacy, 17% of teachers referenced affective or physiological states when discussing experiences that decreased self-efficacy. Examples of physiological/affective states cited by teachers included feelings of exhaustion/fatigue, stress, feeling “burned-out,” and negative mental states (e.g., depression, anxiety). Most often, teachers described negative affective or physiological states in connection with attempts to cope with difficult students, colleagues, or administrators. For example, in his survey response, one high school science teacher cites stress arising from administrator expectations as the primary experience lowering her confidence: “At times there is much negativity and uncertainty of support or clear expectations from admin. This has resulted in times of stress, which has led to feeling insecure in my ability to perform to the best of my ability.”

A number of teachers recounted how their early teaching experiences were “exhausting” or “overwhelming,” often connecting these negative states to the feeling that they were failing their students. For example, one high school science teacher discussed his feeling of being overwhelmed by the demands of teaching in a high needs school:

Trying to help everyone can be overwhelming. My time in a high-needs school was exhausting as my natural habit is to help everyone. I still do this. But the problems with my students are so complex or rooted in years of abuse, mobility, etc. When students get expelled or drop out it feels like failure.

This teacher provides another example of how different sources, in this case enactive experiences and physiological and affective states, are often intertwined in efficacy judgments.

Female teachers referenced affective and physiological states more frequently and described more acute examples than male teachers in both surveys and interviews. Four female teachers and one male teacher told stories recounting incidents evoking a strong emotional response. For example, after describing how the lack of support from her previous administration “ruined how I thought of myself as a teacher,” Andrea stated:

It took an emotional toll but also kind of spiritual toll because if you feel like every day when you get to work that you’re not important and that you’re not a beneficial teacher, it makes you not want to do it anymore.

Andrea’s response reflects how physiological states may be both a source and an effect of teachers’ self-beliefs ( Bandura, 1997 ; Kim and Burić, 2020 ).

Teaching Experience

Beginning teachers were more likely to report negative enactive experiences (e.g., failures, mistakes) as decreasing their self-efficacy than novice or career teachers. Many of these negative enactive experiences pertained to early experiences with classroom management. Although teachers at various experience levels reflected on classroom management, teachers in their first 3 years of teaching tended to describe more serious challenges; experienced teachers discussed challenges managing the behavior of individuals or small groups of students or occasional lapses in classroom management rather than more global challenges. In a survey response, one high school science teacher shared this reflection on struggles with classroom management during her first year:

My first year of teaching made me feel helpless about the behaviors of my students and my ability to have a respectful classroom or a place where students can come to peacefully learn. The students were not motivated and they fed off of each other to make a difficult environment for everyone else and I didn’t always know how to handle it or how to correct it.

In contrast, in a survey response, one experienced teacher shared that:

While I am able to build relationships, I still feel like at times I struggle with classroom management and that lowers my confidence in my teaching ability. It tends to be a handful of students that will push the limits.

When career teachers described experiences that lowered their confidence, many referred to challenges in their first years in the classroom rather than recent experiences. For example, one high school science teacher described the consequences of early struggles with classroom management:

My first year teaching I struggled immensely with classroom management. Especially with the two physical science classes that I taught. I had a rough year and was fired as a result. I seriously doubted if I could teach and manage a classroom the way that I had envisioned.

Similar to this retrospective reflection on enactive experiences, regardless of experience level, teachers tended to focus on vicarious experiences occurring early in their careers. This is not surprising given that vicarious experiences are considered especially powerful when a task is still novel ( Bandura, 1997 ). Many beginning teachers referred to preservice teaching experiences, such as one survey respondent who stated simply “student teaching gave me an example and model of effective teaching.” A number of more experienced teachers described early vicarious experiences that involved observing mentors. For example, in his survey response, one high school science teacher shared, “early on, team teaching with more experienced teachers allowed me to observe effective teachers in action and implement strategies that they use.”

Although survey responses describing affective and physiological states were brief and generally did not vary according to teacher experience level, in interviews, teachers described an evolution in their approach to managing affective and physiological states. For example, Rachel provided the following account of how she responded to a “bad day” as a beginning teacher versus her current approach to coping with challenges:

I used to cry on the whole ride home. So, if I had a bad day, I taught an hour away from where I lived. I would cry for the whole hour home. Now, I feel like it’s more of a I can look at it more critically. This went bad. This is why. I need to change X, Y, and Z for next year. So, as opposed to being just kind of depressed and bummed, I feel like I have the tools to make a change so it’s not depressing anymore. It’s kind of more like I take it as feedback as opposed to someone screamed at me saying my lesson sucked. It’s more of something to build from as opposed to just depressing.

Notably, as in Rachel’s account of crying for the entirety of her commute, teachers typically described strong emotional responses or more acute examples of physiological states rather than mild or moderate levels of arousal, which are thought to promote improved performance ( Teigen, 1994 ).

The primary purpose of this study is to investigate the sources of self-efficacy identified by Noyce teachers and interconnections between self-efficacy, the sources of self-efficacy, and teacher experience. Analysis of self-efficacy data coupled with qualitative survey and interview data lends insight into the experiences teachers find most meaningful when reflecting on and evaluating their teaching ability.

Teachers with more experience reported higher self-efficacy for instructional strategies and classroom management, but not for student engagement. This finding is consistent with other studies comparing practicing teachers with different amounts of experience ( Tschannen-Moran and Woolfolk Hoy, 2007 ; Wolters and Daugherty, 2007 ). Once removed from teacher education programs, new teachers must contend with managing a classroom and deploying multiple instructional strategies on their own for the first time. As described by interviewees, teaching during a practicum is a somewhat limited and protected experience that reflects only a fraction of the demands of full-time teaching. This may be why, as Woolfolk Hoy and Burke-Spero (2005) found, teachers’ self-efficacy decreases between the end of teacher education and the first year of teaching. As teachers accumulate more experience managing classrooms of their own, they may feel more capable as instructors. Alternatively, these trends – both in this study and in the wider literature – may reflect attrition of those who do not believe they can teach well. That self-efficacy for student engagement did not change at different levels of experience may indicate that, even with limited previous experiences, teachers entered their career with a relatively stable sense of their ability to motivate students. Thus, these findings lend support to previous research underscoring the importance of providing continuing support for early career teachers as they make the transition from pre-service to full-time teaching positions, particularly when it comes to developing proficiency with classroom management and instructional delivery.

Teachers with less experience were also more likely to identify negative enactive experiences (i.e., instructional failures, mistakes) when reflecting on the sources that decreased their self-efficacy. This seemingly conflicts with findings by Tschannen-Moran and Woolfolk Hoy (2007) , who suggested that other sources are more salient for novice teachers because they have had fewer mastery experiences. However, this finding may instead point to the problems inherent in measuring enactive experiences only as positive affective appraisals (i.e., “satisfaction with your professional performance this year”; Tschannen-Moran and Woolfolk Hoy, 2007 ). Bandura (1997) did indeed note that other sources can be more powerful when a task is novel and individuals have had few opportunities to perform that task. However, the task is no longer novel for teachers who have already had some experience teaching a classroom of their own. Their experiences differ from those of preservice teachers who are just beginning to teach. No longer do they observe teaching models on a regular basis (vicarious experiences) nor receive the abundance of feedback (social persuasions) typical of a teaching practicum. Instead, as documented in our interviews, teaching in a class of one’s own provided the most powerful information that one was, or was not, capable. Scholars have suggested that teachers may begin to feel less capable when struck by the complexity of teaching in an authentic setting ( Rushton, 2000 ; Woolfolk Hoy and Burke-Spero, 2005 ). Our quantitative and qualitative findings provide evidence that feelings of failure during these early instructional experiences can have a particularly profound influence on teachers’ self-efficacy beliefs. Critically, when considering the implications of teachers’ early enactive experiences, it is important to remember that self-efficacy reflects teachers’ perceptions of their ability rather than actual performance. For teachers in our study who shared negative enactive experiences, lower self-efficacy wasn’t necessarily an inevitable result of failures or mistakes made in their early teaching experiences but rather a reflection of how they interpreted efficacy-relevant information related to failures or mistakes. Indeed, consistent with previous research ( Morris and Usher, 2011 ) some teachers framed failures more adaptively as learning experiences that did not threaten their overall teaching self-efficacy. The rather profound, lasting influence that negative enactive experiences had for some teachers suggests that continuing support aimed at guiding early career teachers to reflect on and perhaps even reframe negative teaching experiences may be a promising approach to protecting teachers’ sense of efficacy at the early stages of their careers.

Vicarious experiences were identified less frequently than enactive mastery experiences and social persuasions for teachers at all experience levels. According to Bandura (1997) , vicarious experiences tend to be most influential when a task is still novel, which may explain why vicarious experiences were relatively rare within our dataset and often described as occurring during preservice teaching experiences. In other studies, preservice teachers have similarly described teaching models as powerful sources of self-efficacy during teacher education, in that they model effectiveness and the skills to become effective (e.g., Gunning and Mensah, 2011 ; Siwatu, 2011 ). However, little is known about the influence of vicarious experiences for practicing teachers who no longer benefit from an assigned in-class mentor. Prior to this study, no published research existed in which the vicarious experiences of practicing teachers were quantified. In interviews following professional learning experiences, practicing teachers have described feeling more capable after seeing a colleague teach well, particularly when they gained pedagogical knowledge from the experience ( Bruce et al., 2010 ; Palmer, 2011 ; Chong and Kong, 2012 ). However, consistent with Bandura (1997) descriptions, these experiences could also lead to referential comparisons in which teachers’ self-efficacy improved with favorable comparisons but diminish when they viewed others as more capable ( Bruce and Ross, 2008 ; Locke et al., 2013 ). For some teachers in our study, such comparisons had a profound impact on their pedagogical knowledge and sense of efficacy. Taken together, our findings suggest that for practicing teachers, observations of colleagues are most influential when used to judge one’s relative mastery of instructional skills and knowledge.

That physiological and affective states were described least frequently is consistent with previous studies in which teachers were interviewed ( Palmer, 2011 ; Morris and Usher, 2011 ; Mulholland and Wallace, 2001 ). Morris et al. (2017) suggested that this may be due to the difficulty of recalling something that is ongoing rather than a more salient event. In both surveys and interviews, female teachers in the study were more likely than male teachers to describe physiological and affective states that influenced their sense of efficacy. In previous research, preservice and practicing female teachers have similarly reported provided higher ratings of stress ( Klassen and Chiu, 2010 ; Klassen and Durksen, 2014 ). The differential influence of stress on practicing teachers’ self-efficacy has been unclear, however. Klassen and Chiu (2010) found that female teachers reported higher stress related to student behaviors, which in turn predicted lower teaching self-efficacy across all measured dimensions. Their higher workload stress, however, was paradoxically associated with higher self-efficacy for classroom management. Findings from the present study provide more evidence of the gendered influence of stress on self-efficacy and suggest that relationships with school administration can be an additional source of stress for female teachers. Moreover, the qualitative approach allowed a richer understanding of how enactive experiences can be inextricably tied to teachers’ physiological and affective states. Future research can investigate the causes of differences in reported stress levels by gender. It is likely that the differential pressures, expectations, and even discrimination or harassment faced by female teachers have implications for their physiological and affective states. It is also plausible that, due to traditional notions of masculinity, differences in reporting reflect that men are more reluctant to express or even acknowledge vulnerable feelings ( Levant et al., 2003 ).

Teachers reflections and stories also highlight the complexity of self-efficacy beliefs and the constellation of sources teachers draw upon when making determinations about their teaching ability. We found clear evidence of each of the sources of self-efficacy postulated by Bandura (1997) and the frequency with which teachers identified the various sources conformed to what we might expect based on social cognitive theory and previous research. For instance, given that mastery experiences are thought to be the most potent source of self-efficacy, we would have been surprised if they were not the most commonly cited source by teachers in our study. At the same time, the ways in which teachers referenced and often integrated multiple sources, especially when asked to elaborate in interviews, remind us that there is no simple formula by which teachers’ experiences are translated into self-efficacy beliefs and that self-efficacy beliefs are not cultivated in a vacuum. Indeed, many survey responses and narratives foregrounded contextual factors and the particularities of their teaching circumstances when describing experiences related to the sources of self-efficacy. Future research should further explore the ways in which contextual factors and the level and sources of support teachers receive influence their appraisals of self-efficacy. For instance, our finding that science teachers more frequently report negative mastery experiences than math teachers appeared to be due, at least in part, to the frequency with which science teachers are asked to teach new subjects that may or may not align with their previous education and pedagogical training. This finding points to a particular need to carefully consider the ways in which frequent changes in teaching placements may influence science teachers’ self-efficacy and whether there may be ways to better prepare science teachers for the likelihood of teaching multiple subjects in their first years of teaching.

Although we hope this study will be instructive for a broad audience of teacher educators and researchers, it is not without limitations. We sought to include a diverse sample representing numerous Noyce programs across the country; however, certain characteristics of Noyce programs and the teachers who participate in them, such as their focus on recruiting and supporting STEM majors, along with our relatively small sample mean that the results of this study should be considered within the context of the Noyce program. Additionally, the study’s reliance on cross-sectional data limits the degree to which we can draw conclusions about the differential influence of the sources of self-efficacy over the early years of teachers’ careers. Longitudinal qualitative research that traces how the sources of self-efficacy manifest over the course of teachers’ careers would advance our understanding of the relationship between teaching experience and the sources of self-efficacy. Finally, although open-ended survey items may provide more useful data on the sources of self-efficacy than some of the more simplistic measures used in previous research (e.g., retrospective ratings of mastery, time spent teaching), teachers’ responses did not always draw clear connections between the sources identified and their appraisals of their teaching ability. The second phase of our study in which we conducted in-depth interviews was intended to address limitations in the open-ended survey methodology. Indeed, we found that qualitative interviews generated much richer accounts of the sources of self-efficacy identified by Noyce teachers.

This study offers potential implications for theory, practice, and research relevant to self-efficacy and the preparation of early career teachers. Previous research on the sources of practicing teachers’ self-efficacy has largely been devoted to examining changes following professional development (e.g., Bruce et al., 2010 ; Chong and Kong, 2012 ). Few scholars have examined how the influence of the sources naturally evolves during a teaching career. This study is unique in that it is the first mixed-methods study to explore this evolution across all four sources identified by Bandura (1997) . Thus, this study adds to the field’s current understanding of the sources of teaching self-efficacy and the ways in which the sources may combine or interact to influence teachers’ self-efficacy after they enter the field. Given the relative importance of early enactive experiences and social persuasions, those who educate and supervise teachers can work to develop environments that support, rather than discourage, novice teachers when they fail. Research that further explores the influence of particular experiences on teachers’ self-efficacy at different stages of their career can inform what administrators can do to foster self-efficacy and how induction programs can best support new teachers.

Data Availability Statement

The datasets presented in this article are not readily available because Data sharing is limited by IRB approved participant consent forms. Requests to access the datasets should be directed to [email protected] .

Ethics Statement

The studies involving human participants were reviewed and approved by Georgia Institute of Technology Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

JG, MA, and CC designed the study. JG led the collection and analysis of data and wrote the first draft of the manuscript. MA and CC developed the online survey, assisted with interview data collection and analysis. DM wrote sections of the manuscript and advised on data collection and analysis. MA, CC, and DM reviewed and edited the manuscript. All authors have made a substantial contribution to the work and have agreed to the published final manuscript.

This project is funded by the National Science Foundation, grant #1660597. Any opinions, findings, and conclusions or recommendations expressed in these materials are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We would like to acknowledge CEISMC Research Coordinator, Ms. Emily Frobos for her assistance with this research.

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Keywords: teacher self-efficacy, self-efficacy, teacher beliefs, STEM teacher education, sources of self-efficacy

Citation: Gale J, Alemdar M, Cappelli C and Morris D (2021) A Mixed Methods Study of Self-Efficacy, the Sources of Self-Efficacy, and Teaching Experience. Front. Educ. 6:750599. doi: 10.3389/feduc.2021.750599

Received: 30 July 2021; Accepted: 15 September 2021; Published: 30 September 2021.

Reviewed by:

Copyright © 2021 Gale, Alemdar, Cappelli and Morris. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jessica Gale, [email protected]

Temporal Focus Profiles in the College and the Workplace: Exploration and Relationships with Well-being Constructs in Mexico

• Published: 18 March 2024

Cite this article

• Daniel A. Cernas-Ortiz   ORCID: orcid.org/0000-0001-7325-1968 1  

Subjective time is fundamental to understanding individuals’ experience of happiness and well-being. More specifically, temporal focus is an individual difference that, as separate dimensions, refers to the attention that people pay to their psychological past, present, and future. Taken together, temporal foci form profiles that are likely to influence well-being across a person´s lifespan. In this context, there is a paucity of research about the influence of temporal focus profiles on many cognitive, affective, and trait-like constructs that are relevant to well-being, in different population segments, and alternative (non-Anglo-Saxon) cultures. To address this void in research, we conducted two cross-sectional, survey-based studies in Mexico. We used two-step cluster analysis to uncover initial temporal focus profiles in undergraduate students (Study 1), and highly educated employees (Study 2). We tested the differences across the profiles that we uncovered in five well-being-related constructs that are relevant to each population segment. Comparing and contrasting the results of the two studies, less variety of temporal focus profiles was found in employees than in students. Also, whereas temporal focus profiles in students exhibited larger differences in affective outcomes (e.g., positive and negative affective well-being), the profiles showed larger differences in cognitive constructs in employees (e.g., occupational self-efficacy, core self-evaluations, and life satisfaction). Overall, the results highlight the importance of identifying and characterizing temporal focus profiles in different population segments, and in different cultures, so as to enable the implementation of nuanced strategies to improve well-being.

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Cernas-Ortiz, D.A. Temporal Focus Profiles in the College and the Workplace: Exploration and Relationships with Well-being Constructs in Mexico. Applied Research Quality Life (2024). https://doi.org/10.1007/s11482-024-10298-w

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Development and Evaluation of a Reliable Medication Management Self-Assessment Checklist

Brian Isetts

University of Minnesota College of Pharmacy

Kristine Talley

University of Minnesota School of Nursing

Ann Brearley

University of Minnesota School of Public Health

DOI: https://doi.org/10.24926/iip.v15i1.5802

Keywords: medication, self-management, self-efficacy

     An ability to effectively self-manage medications is the result of several factors influencing a person’s decision to take medications. The need for new approaches to medication self-management are evident in the persistent trends of ineffective and unfortunate medication use consequences, referred to as drug-related morbidity and mortality.  Fortunately, pioneering initiatives have emerged to reshape our approach for developing a rational organizational paradigm so that patients can confidently self-manage medications.

     Favorable outcomes of studies pertaining to the delivery of comprehensive medication therapy management services within the practice of pharmaceutical care prompts the question, ‘Can patients and family members apply the 4-step pharmacotherapy workup process to better organize their decision-making and confidence in medication self-management?’ To answer this question an Effective Medication Self-Management Toolkit based on this 4-step process, and a Medication Management Self-efficacy Checklist, were created and evaluated for feasibility, acceptability, and internal consistency reliability.

     The first evaluation established the preliminary acceptability and feasibility of the toolkit using a convenience sample of 39 residents of independent living facilities in focus group sessions. All participants indicated they perceive that the 4-step process can help individuals successfully self-manage medications. At the conclusion of the focus group sessions, all 39 participants completed the 7-item post-session checklist. This paper presents the second evaluation to establish the internal consistency reliability of the toolkit’s Medication Management Self-efficacy Checklist using Cronbach’s alpha. There was good internal consistency of the self-efficacy checklist with a Cronbach’s alpha value of 0.82.

     This investigation of a novel approach for applying the 4-step pharmacotherapy assessment process by patients suggests that it is feasible and acceptable to use, and that the medication self-efficacy checklist provides a reliable and useful measure of a patient’s confidence in self-managing medications.

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• Congyang Wu 2 , MBA   ; 
• Ge Zhang 2 , BM   ; 
• Jing Zhang 2 , PhD   ; 
• Yanhui Liao 1 , PhD  

1 Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China

2 Johnson & Johnson Pharmaceutical Company, Shanghai, China

Corresponding Author:

Yanhui Liao, PhD

Sir Run Run Shaw Hospital

Zhejiang University School of Medicine

3 East Qingchun Road

Hangzhou, 310016

Phone: 86 18814898844

Email: [email protected]

Background: The overall prevalence of cigarette smokers in China is very high, and China’s total cigarette consumption makes up more than 40% of the world’s consumption. In view of the lack of smoking cessation services and social support in China and the effectiveness of mobile phone apps for quitting smoking in other countries, we carried out a smartphone app–based smoking cessation trial in China.

Objective: This study aimed to evaluate the efficacy of a cognitive behavioral therapy (CBT)–based smoking cessation smartphone app among smokers seeking treatment in China.

Methods: We conducted a randomized controlled, web-based pilot clinical trial in China between February 23 and June 27, 2021. Eligible participants were randomly assigned to the smoking cessation app intervention group or the control group in a ratio of 1:1. The intervention group received the CBT smoking cessation intervention using a smartphone app, and the control group received a “thank you” message. The intervention was 4 weeks long, and the patients were followed up for 4 weeks. The primary outcome was self-reported continuous smoking abstinence at week 4 after the quit date. The secondary outcomes included self-reported 7-day point prevalence of smoking abstinence; reduction of the number of cigarettes smoked per day at weeks 1, 2, 3, and 4; and program acceptability.

Results: A total of 973 people were recruited to quit smoking, of whom 262 completed basic information, 56 were excluded, and 206 were randomized and included in the final analysis. There were 189 (91.7%) men and 17 (8.3%) women, with an average age of 34.46 (SD 7.53) years and an average daily smoking rate of 15.93 (SD 7.10) cigarettes/day. We found 30 (29.7%) of the 101 participants in the intervention group and 7 (6.7%) of the 105 participants in the control group reported continuous smoking cessation after the quit date at week 4 (odds ratio 5.92, 95% CI 3.78-9.26; P <.001). The 7-day point prevalence abstinence rate of the intervention group varied from 42.6% (43/101) to 46.5% (47/101) after 1, 2, 3, and 4 weeks, while the control group varied from 18.1% (19/105) to 26.7% (28/105). Compared to the control group, continued smokers consumed 1.5-3.0 fewer cigarettes per day in the intervention group. The overall program got positive user feedback with a high satisfaction rate (66/87, 76%) and an average Mobile Application Rating Scale user version score of 3.46.

Conclusions: Our pilot study provided preliminary evidence that the CBT-based smoking cessation smartphone app led to improved smoking quit rates versus control in Chinese smokers. The study demonstrated the CBT-based smartphone app may be an effective and feasible digital treatment model to help smokers quit, which may improve smoking cessation service quality and accessibility in China.

Trial Registration: ClinicalTrials.gov NCT04421170; https://clinicaltrials.gov/study/NCT04421170

International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2020-041985

Introduction

Tobacco smoking remains one of the leading causes of preventable death [ 1 ]. More than 8 million smokers worldwide die each year from smoking-related causes, of whom about 7 million die of diseases caused by smoking and about 1.2 million die from diseases caused by secondhand smoke exposure [ 2 ]. More than 1 million people in China lose their lives due to smoking every year. If effective action were not taken to significantly reduce the smoking rate, the number of deaths due to smoking would increase to 2 million per year by 2030 and 3 million per year by 2050 [ 3 ]. Since 1978, cigarette production in China has grown from 20% to over 40% of the world’s cigarette products [ 4 ]. Tobacco has caused a huge economic burden to society and individuals, including the high cost of medical care, more diseases, and premature death [ 5 ]. According to survey results on adult smoking prevalence in China in 2018, the smoking rate of people aged 15 years or older in China was 26.6% [ 6 ], which was still higher than in many other countries.

One of the key reasons for China’s low smoking cessation rate is limited smoking cessation services. The 2018 China Adult Tobacco Survey demonstrated that 90.1% of smokers who tried to quit in the past 12 months did not use any form of cessation aid [ 6 ]. A report in 2019 showed that 366 hospitals and primary health care institutions in China set up smoking cessation clinics, of which only 43% provided smoking cessation medications [ 7 ]. Few smokers were willing to go to the smoking cessation clinic for help [ 5 ], and most self-help cessation attempts failed [ 8 , 9 ]. Most smokers tend to relapse in the first few weeks after trying to quit smoking [ 10 ]. The success rate of quitting smoking after 1 year was 3%-5% for those without support, 7%-16% when smokers received behavioral intervention, and as high as 24% when smokers received drug treatment and behavioral help [ 11 ]. At present, it is necessary and meaningful to find accessible, effective, and scalable smoking cessation intervention methods to improve smoking cessation services in China.

Nowadays, mobile phone–based smoking cessation support provides a new channel for those who cannot get access to or lack the willingness to use face-to-face support [ 12 ]. About 45% of mobile phone subscriptions worldwide were related to smartphones, and this number continues to grow as 75% of new mobile phone sales were smartphones [ 13 ]. Around the world, mobile phones are becoming more and more useful in health information and health care service delivery [ 14 ]. Digital medical service has the advantages of economy, easy access [ 12 ], and easy promotion, which provides an opportunity for developing cost-effective smoking cessation digital interventions [ 15 ]. We previously carried out a study on smoking cessation intervention based on SMS text messaging (Happy Quit) in China, which supported the effectiveness and feasibility of digital medical services [ 16 ]. Smartphone apps for health and health care are increasing rapidly, but there are few in the smoking cessation area [ 17 ]. Smartphone apps can enable diverse functions, including audio and video materials, and can provide additional resources through the network [ 18 ]. Besides, smartphone apps could be more powerful than SMS text messaging programs for digital intervention because they have the potential to increase user engagement through diversified user interfaces and user experiences [ 19 ]. A study has found that under the same intervention content, the effect of a smartphone-based smoking cessation intervention app was stronger than that of a non–mobile device–based web page intervention. Mobile devices have the potential to make it easier for smokers to get smoking cessation support [ 20 ]. However, most of the currently available smartphone smoking cessation apps on the market have the problem of low compliance with standard clinical practice guidelines [ 21 ]. In 2018, a study of smoking cessation apps for the UK mobile phone app market found that most smoking cessation apps had low theoretical adherence, and the overall quality of smoking cessation apps was still unsatisfactory [ 22 ]. A review showed that there was insufficient evidence of the smartphone app’s effectiveness on smoking cessation support; thus, more randomized controlled trials (RCTs) were recommended to validate the smartphone-based digital smoking cessation interventions [ 12 ]. Specifically, as far as we know, there has been no mobile smoking cessation app with sufficient clinical evidence in China.

As an indispensable part of psychotherapy, cognitive behavioral therapy (CBT) plays an important role in the field of psychological and behavioral intervention [ 23 ]. One of the roles of CBT involves challenging behaviors that may trigger or sustain difficulties, such as smoking. CBT has been proven to help reduce cravings and promote smoking cessation by changing participants’ thoughts and behaviors [ 24 ]. The CBT quitting method consists of several parts, generally including preparation before quitting smoking, starting quitting smoking, and maintaining or preventing the recurrence treatment stage [ 25 ]. CBT may be a good choice for people who want to quit smoking, especially for those who want to quit smoking through nondrug methods [ 25 , 26 ]. Our previous study on “Happy Quit” SMS text message smoking cessation in China found that a CBT-based smoking cessation intervention can effectively improve the 24-week continuous smoking cessation rate [ 16 , 27 ]. As far as we know, there is little research to explore the effect of CBT-based mobile apps on smoking cessation intervention. Therefore, we are committed to designing a CBT-based mobile app for Chinese smokers who want to quit smoking, so as to find more effective ways to quit smoking.

Considering the above factors, in order to provide more feasible and effective smoking cessation services, we developed a scientific mobile smoking cessation app based on clinical practice guidelines. Smoking is an unhealthy behavior that can be altered, and CBT can help solve a wide range of smoking cessation problems. Various forms of interventions were developed in the app based on CBT to help smokers learn new skills, resist smoking cravings [ 28 ], and better deal with emotional disorders [ 29 ].

This Mandarin mobile smoking cessation app, based on CBT, integrates smoking cessation support and social skills training and finally achieves the goal of cognitive behavior change. A previous 1-arm study on the feasibility and acceptability of this CBT-based smartphone app was carried out for Chinese smokers who wanted to quit and showed that the smoking cessation app may become a new digital therapy model and have the potential to provide support for smoking cessation services in China [ 30 ]. We hypothesized in this study that the CBT-based smoking cessation app is feasible and acceptable and can significantly increase the quit rate.

In the current trial, the objectives were to evaluate the feasibility and acceptability of this Chinese CBT-based app in a direct-to-participant clinical design and preliminarily evaluate the efficacy of the CBT-based app for smoking cessation in China. Given that CBT [ 23 ] is the current standard in behavioral intervention for smoking cessation, we tested the hypotheses that participation in this intervention will lead to significant improvement in the self-reported continuous smoking cessation rate at 4 weeks; self-reported 7-day point prevalence smoking abstinence and reduction of the number of cigarettes smoked per day at weeks 1, 2, 3, and 4; and that the program would be acceptable to participants.

Study Design

This was a randomized controlled, direct-to-participant clinical trial conducted in China. Researchers conducted preliminary conditional screenings for each participant. In the baseline assessment, all eligible participants were required to fill out a baseline questionnaire that included demographic information, motivation to quit smoking and willingness.

Using a randomization method by electronic data capture system, participants were randomly assigned to a smoking cessation app intervention group or to a control group in a 1:1 ratio after the completion of the screening, consent, and baseline questionnaires. No changes have been made to the trial design since its commencement. Participants in the intervention group received the CBT-based smoking cessation app, while those in the control group were encouraged to quit but were not provided with the CBT-based smoking cessation app. A control group was used since this was an exploratory study designed to assess both the feasibility, acceptability, and initial efficacy of the app intervention. Participants were required to complete the program acceptability assessment, including the App Satisfaction Assessment Scale and the Mobile Application Rating Scale, user version (uMARS; including engagement, functionality, aesthetics, information, and the average score of the uMARS total score), 4 weeks after the quit date. Each item is scored from 1 to 5, with a maximum total score of 5.0. The higher the score, the better the satisfaction [ 31 ]. Follow-up visits were conducted at weeks 1, 2, 3, and 4 after the participants started smoking cessation. The study design is depicted in Figure 1 .

Participants

The eligibility criteria for participants are shown in Textbox 1 .

Inclusion criteria

• Cigarette smokers (smoked more than 100 cigarettes in their lifetime and currently smoke 5 or more cigarettes a day)
• Aged 25 years or older
• Able to read and write in Chinese
• Owning a smartphone (operating system: iOS or Android)
• Having experience in using apps
• Expressing an interest in quitting smoking within the next month
• Willing to provide informed consent to participate in the study
• Able to follow up for at least 1 week

Exclusion criteria

• Nonsmokers or only use electronic cigarettes
• Smokers without previous “serious” attempts to quit smoking (Motivation to Stop Scale score <7)
• Currently experiencing severe mental illness
• Had already started their quit attempt or used any smoking cessation treatment at the time of registration
• Unable to use smartphones and apps
• Did not have sufficient command of Chinese to participate in the trial

Sample Size

A sample size of about 200 participants was calculated to give 80% power and a 2-sided 5% significance for detecting a beneficial difference in the self-reported continuous smoking cessation rates between the CBT app intervention and the control intervention. These assumptions were made based on our previous RCT of CBT-based SMS text messaging interventions for smoking cessation [ 16 ] and other previous RCTs of smartphone app interventions for smoking cessation [ 15 ], as well as the consideration of the better efficacy of the CBT-based app than the non–CBT-based app for smoking cessation [ 32 ]. A total of 200 participants randomized 1:1 to each arm (n=100) would obtain a 95% CI width estimate of ±10% for the CBT-based app for a 4-week self-reported continuous quit rate. The 20%-30% CBT-based app quit rate CI (95% CI) was designed to provide precision in estimating the main study of CBT-based app intervention. There were no planned interim analyses or stopping rules.

Recruitment

From February 23 to June 27, 2021, a total of 206 participants were recruited through advertisements on social media, such as WeChat (Tencent), Weibo, the website, and the principal investigator–affiliated hospital WeChat official account. Potential participants were screened through a mobile phone or WeChat phone contact. Of the 973 screened, 711 did not meet the preliminary inclusion and exclusion criteria. Of the 262 baseline assessments completed, 56 were deemed ineligible to participate. Therefore, a total of 206 participants were randomized and included in the analysis according to the intention-to-treat (ITT) principle.

Recruitment was undertaken through (1) the telephone number for quitting smoking and (2) WeChat, a popular social media in China. For recruitment through the telephone number, research investigators directly contacted these participants about the study by phone call. For recruitment through WeChat, participants were invited to make a WeChat voice or video call to research investigators. A link to informed written consent was sent by email to each eligible participant, and e-consent was obtained from all participants before the study commencement and data collection.

Stratified Block Randomization

Randomization was conducted by an electronic data capture system, a computerized system designed for the collection of clinical data in electronic format for RCTs and other clinical trials. Randomization was at the level of the individual participant with a 1:1 ratio by the method of minimization stratified by balancing for (1) with or without previous quit attempts and (2) 10 cigarettes or more per day. The study investigators were blinded to participants’ treatment allocation until all data were collected. The investigators who analyzed the data were also blinded to participants’ allocated groups until analysis completion.

Interventions

Following randomization, participants set a smoking cessation day. On that day, participants began receiving personalized messages to help quit smoking through either a smartphone app (intervention group) or by simply receiving SMS text messages (control group). The intervention group also logged into the smoking cessation app, started a smoking cessation journey, completed tasks, and sought personalized smoking cessation assistance under the automatic guidance of the app, while the control group received regular SMS text messages.

Control Group

Participants in the control group received information to thank them for their participation and to remind them to complete their smoking status at each point.

Intervention Group

Participants from the intervention group were invited to download the CBT-based app. The app integrates cognitive-behavioral principles and tailored behavior-change skills in Chinese. More descriptive details of this smartphone app were available elsewhere [ 33 ]. Participants who were randomly assigned to the intervention group were instructed on how to access and use the app, including a schedule of intervention activities, tasks during the pre- and postpreparation stages, and expected completion dates. Participants could begin their assigned tasks immediately after completing the pretest assessment. The system limited participants to 3 tasks each day during the preparation stage. To encourage completion, SMS text message reminders were sent each week after the quit date.

Both Groups

All participants earned CNY 20 (US $2.8) phone top-ups for the completion of pre- and posttest questionnaires. Participants from both groups received a reminder by SMS text message to complete questions about their smoking status during weeks 1, 2, 3, and 4 after the quit date by electronic Patient Reported Outcomes (ePRO) software.

Outcome Measures

Participant demographics and smoking behaviors at baseline.

Participant demographic and smoking behaviors at baseline, including gender, age, height, weight, education, cigarettes per day, quit history, motivation, self-efficacy to quit, quitting smoking gradually or abruptly, smoking craving, and severity of nicotine dependence, were evaluated using the Fagerstrom Test for Nicotine Dependence (FTND).

4-Week Continuous Smoking Abstinence

Continuous smoking abstinence for 4 weeks is defined as smoking no more than 5 cigarettes in the past 4 weeks since quitting, measured through response to the following item: (1) “How many cigarettes have you smoked in the last 4 weeks?” Response choices were “0,” “1-5,” or “more than 5”; and (2) “If ‘more than 5,’ recorded the number of smoked cigarettes per week.” Within 4 weeks, participants who smoked more than 5 cigarettes indicated a recurrence [ 34 ]. This was the primary outcome measure.

7-Day Point Prevalence Smoking Abstinence

Self-reported abstinence of at least 7 days before the assessment day was assessed 1, 2, 3, and 4 weeks after each participant’s quit date. It is defined as smoking no more than 5 cigarettes in the past 1, 2, 3, and 4 weeks since quitting.

Reduction of the Number of Cigarettes Smoked Per Day

Daily cigarette consumption among participants who were still smoking after quitting days (participants who smoked more than 5 cigarettes in total but less than 1 cigarette per day were considered to have smoked 1 cigarette per day).

Program Acceptability

A questionnaire of program acceptability was assessed at 4 weeks post quitting, including the App Satisfaction Assessment Scale and the uMARS. Questions are shown in the Results section.

The safety of this program was evaluated by the collection and analysis of spontaneous adverse events reported by participants. No serious adverse events were reported by participants in our trial.

Intervention Effects

The primary outcome was the self-reported continuous smoking abstinence rates at 4 weeks after the quit date. Secondary outcomes included self-reported 7-day point prevalence smoking abstinence at weeks 1, 2, 3, and 4, reduction of the number of cigarettes smoked per day from week 1 to week 4, program acceptability, and the association of outcomes with baseline data. In all analyses, participants who dropped out or were lost to follow-up were considered treatment failures and smokers. Participants using smoking cessation methods not allowed in this study were not included in the efficacy analysis.

Statistical Analysis

Statistical analyses were conducted with R software (R Foundation for Statistical Computing) and SPSS (version 23; IBM Corp). All baseline data comparisons, including participant demographics and smoking behaviors, were conducted using a chi-square test. A total of 206 participants were included in the analysis according to the ITT principle. In both groups, nominal and ordinal demographics were compared using chi-square tests, and continuous variables were compared using independent samples 2-tailed t tests. The number of average cigarettes smoked per day was compared using a 2-sample t test between groups. The mixed-effects model was used to test the self-reported smoking abstinence rates in intervention groups and control groups. Program acceptability (treatment satisfaction ratings) for participants with the app intervention was evaluated by tallying the proportion of users answering each item on the usability measure. If the smoking status was not available after quitting, the participant was considered to have smoked the same number of cigarettes per day as before quitting. The odds ratio was used as a measure of outcomes in the intervention group compared to the control group. Multiple imputations will be used in chained equations. A 2-sided P <.05 was used to determine statistical significance.

Ethical Considerations

The study protocol was approved by the ethics committee of Sir Run Run Shaw Hospital, an affiliate of Zhejiang University School of Medicine (protocol number 20200129-33), and was published [ 33 ]. The trial was performed in accordance with the Declaration of Helsinki. Informed consent was obtained from all participants. The purpose, procedures and measurements, potential risks, and benefits of the trial were explained to each participant before recruitment. The investigators who analyzed the data were also blinded to participants’ allocated groups until analysis completion.

Follow-Up Rate

Figure 1 shows the process of screening, grouping, and follow-up of participants in this study. A total of 206 participants were recruited from February 23 to June 27, 2021. Of the 973 screened, 711 did not meet the preliminary inclusion and exclusion criteria. Overall, 262 completed baseline assessments, but 56 were deemed ineligible to participate. Therefore, a total of 206 participants were included in the analysis according to the ITT principle.

Participant Characteristics

Demographics and smoking characteristics at baseline for all participants are presented in Table 1 . There were no statistically significant differences in the baseline characteristics of the 2 groups of participants ( P >.05). A total of 206 participants were enrolled in the trial. There were 189 (91.7%) men and 17 (8.3%) women, with an average age of 34.46 (SD 7.53) years and an average daily smoking rate of 15.93 (SD 7.10) cigarettes per day.

a FTND: Fagerstrom Test for Nicotine Dependence.

b VAS: Visual Analogue Scale (VAS measures the degree of craving for smoking; 0-10 points, where 0 represents no craving and 10 represents strong craving.

The Outcome of Abstinence Rates

The primary outcome.

Compared with 7/105 (6.7%) participants in the control group, self-reported continuous smoking abstinence at week 4 was higher (30/101, 29.7% participants) in the intervention group (odds ratio 5.92, 95% CI 3.78-9.26; P <.001; Table 2 ).

a OR: odds ratio.

b Bonferroni corrected P values.

The Secondary Outcomes

Table 2 details the results of self-reported 7-day point prevalence of smoking abstinence at weeks 1, 2, 3, and 4. It was shown that the self-reported 7-day point prevalence of smoking abstinence at weeks 1, 2, 3, and 4 of the intervention group were 46.5% (47/101), 42.6% (43/101), 42.6% (43/101), and 44.6% (45/101), respectively, while 7-day point prevalence of smoking abstinence in the control group was 26.7% (28/105), 18.1% (19/105), 20% (21/105), and 19% (20/105), respectively. The differences were statistically significant at all time points. Compared to the control group, continued smokers consumed 1.5-3.0 fewer cigarettes per day in the intervention group ( Table 3 ).

The Acceptability and Feasibility of the CBT-Based Smoking Cessation App Program

Participants were required to complete the program acceptability assessment, including the App Satisfaction Assessment Scale and uMARS, 4 weeks after their quit date. All participants (n=101) in the intervention group were contacted to evaluate the program based on their experience, and we finally obtained responses from 87 people, including 87 on the App Satisfaction Assessment Scale and 84 on the uMARS. The overall program satisfaction was 76% (66/87) and the percentage of dislikes was less than 10% (9/87). The uMARS included the average scores of 5 items scored 1-5, namely, engagement (2.96), functionality (3.73), aesthetics (3.56), information (3.6), and the average score of the uMARS total score (3.46). More details are available in Tables S1 in Multimedia Appendix 1 and Table 4 .

a Average of total score = total score (engagement + functionality + aesthetics + information)/4.

Principal Findings

In this study, our main results indicate that (1) the 4-week continuous smoking cessation rate of the intervention group participants (30/101, 29.7%) was statistically significantly higher than that of control group participants (7/105, 6.7%); (2) the self-reported 7-day point prevalence smoking abstinence rate in the intervention group at the weeks 1, 2, 3, and 4 was higher than that in the control group (43/101, 42.6% to 47/101, 46.5% vs 19/105, 18.1% to 28/105, 26.7%); (3) compared with the control group, those who continued to smoke in the intervention group smoked 1.5-3.0 fewer cigarettes a day; (4) the app had high overall satisfaction rating (66/87, 76%) and average uMARS scores (3.46). These findings suggest that the CBT-based smartphone app is effective for smoking cessation, and it could be an effective, feasible, and easy-to-access quitting app in China. It is hopeful for this app to be introduced to a large-scale Chinese population to intervene in smoking cessation.

The effectiveness of this CBT-based smartphone app intervention on short-term smoking cessation rates was encouraging. About half (47/101, 46.5%) of participants in the intervention group and about a quarter (28/105, 26.7%) in the control group reported 7-day abstinence in the first week after quitting, which was comparable to the preliminary results of other randomized controlled digital intervention studies on smoking cessation [ 35 , 36 ]. Previous research results for smartphone apps and SMS text messaging smoking cessation programs were similar to ours [ 16 , 37 ]. Participants in the intervention group reported point prevalence that was 3 to 4 times higher than that in the control group from 1 to 4 weeks, and self-reported continuous abstinence at 4 weeks in the intervention group was similar to that in previous smartphone smoking cessation app studies [ 37 , 38 ].

The results of this study show that the smoking cessation rate is high, and there have been some similar or inconsistent studies in the past, although there are some differences in smoking cessation standards. A systematic evaluation of smartphone apps for quitting smoking found that the results of 11 RCTs were not consistent. Among these 11 studies, the abstinence rate of the test group was significantly higher than that of the control group in 4 studies, the abstinence rate of the test group was not significantly higher than that of the control group in 5 studies, and there was no difference between the test and control groups in 2 studies [ 1 ]. The social environment in China is still quite tolerant of smokers and appears less supportive of quitting behavior, so potential quitters in China may be more resistant to personal intervention than smokers in other countries [ 16 ]. As far as we know, there are no mobile smoking cessation platforms developed under the theoretical guidance of professional medical institutions in the domestic software development market, and most of the smoking cessation apps in China are developed by individuals or companies that may not have knowledge of clinical smoking cessation practice. Those apps comply less with the recommendations from the China clinical smoking cessation guidelines (2015 edition), and their smoking cessation effect is limited [ 21 ]. Therefore, for most Chinese smokers, using apps to quit smoking is a new way to quit smoking that needs further improvement.

China has introduced some smoking control measures, but the choice of a mobile smoking cessation service is relatively limited. The earliest method of smoking cessation based on mobile phones was mainly SMS text messages [ 39 ]. Our team previously carried out an SMS text message smoking cessation project, and the effect of smoking cessation was relatively significant [ 16 ]. China’s smoking cessation services are inadequate. An authoritative national survey found that in 31 provinces, only 366 hospitals and primary care centers offered smoking cessation clinics [ 7 ]. Among them, smoking cessation clinics are mostly attached to tertiary or secondary hospitals, but population-level interventions rely heavily on primary care settings [ 40 ], where fewer clinics exist. In addition, the limited use of smoking cessation medications in China is also a serious problem [ 7 ]. Additionally, many smokers who want to quit smoking have low awareness of and use of smoking cessation support services [ 41 ].

It is noteworthy that the overall program satisfaction (66/87, 76%) and the average score of the uMARS total score (3.46) were high. About 80% (69/87) of the participants would happily recommend the app to others, which was consistent with the results of a randomized clinical trial of a smartphone app based on acceptance and commitment therapy for quitting smoking [ 37 ]. In this study, except for engagement, the software’s functionality, aesthetics, information, and the average score of the uMARS total score were all around 3.5, indicating that the participant’s overall satisfaction level was relatively high. Similar to our results, a study showed that participants made suggestions, including making features more ramified and integrating with some social media platforms to increase app and user interactivity, although some smartphone smoking cessation apps were widely accepted [ 41 ].

This pilot study provided valuable learning for future research. A review study showed that the certainty of evidence comparing smartphone apps to very low-intensity smoking cessation support was very low, and more RCTs were needed to test these interventions [ 12 ]. Also, the recruitment of participants in the intervention and control groups of RCTs related to smartphone apps for smoking cessation was not easily supported [ 41 ]. It is worth mentioning that we recruited eligible participants in this preliminary study and carried out RCTs in accordance with the norms, obtaining relatively accurate data and also providing a reference and basis for subsequent RCT studies. These preliminary data still provide sufficient and reliable information for our subsequent larger, robust trials.

Limitations and Strengths

There are some limitations to our study. First, this study was a pilot study with a small sample size, and the results may be biased. At present, our large-sample trial has begun, which will help to further confirm our preliminary research results. Second, due to the need to master the basic ability to use the app, the enrolled smokers were relatively younger and had a higher education level, so the smoking cessation effect of the smoking cessation APP is uncertain for older or less educated smokers, and more caution needs to be exercised if the results are generalized to older or less educated smokers. Finally, some important subgroup analyses, such as smoking cessation rates between men and women, tobacco users, and e-cigarette users, were not considered in this study. Although we matched the 2 groups of quitters on factors such as gender and smoking status, these differences could potentially have an impact on smoking cessation outcomes. Despite these limitations, this study’s strengths included its conduct in China, the direct-to-participant design, and the use of an RCT.

Conclusions

This pilot study of a CBT-based smartphone smoking cessation app provided preliminary evidence that the app led to improved smoking cessation rates versus control in Chinese smokers. This study demonstrated that the CBT-based smartphone app may be an effective and feasible digital treatment model to quit smoking, which may improve smoking cessation services in China.

Acknowledgments

We sincerely thank all participants, their families, and all workers for their support. We are grateful to Johnson & Johnson Pharmaceutical Company for providing critical comments and suggestions for the study design and development of the digital intervention app. The source of funding had no impact on the data collection and analysis of the study or the writing and submission of the manuscript.

The research is supported by Johnson & Johnson Pharmaceutical Company (K-20201478). The funder was collaboratively involved in the study design, development of the data collection tool, and app software development, but the company had no involvement in enrollment, providing an informed consent form, contacting participants, addressing safety issues, or monitoring and collecting data.

Data Availability

All data in this study will be available from the corresponding author on reasonable request and upon completion of the data user agreement.

Authors' Contributions

YL and JT developed and designed the study, and SC collected and analyzed the data. SC and YL took the lead in drafting the manuscript protocol, with contributions by JT, who advised on the study design and coordinated study approval. YL and JT read and proposed critical comments, as well as approved the manuscript for publication. All authors read and approved the final manuscript.

Conflicts of Interest

YL received funding from Johnson & Johnson Pharmaceutical Company for the study. SC, JT, CW, GZ, JZ, and YL have no potential conflicts of interest to declare.

Questions for assessing program satisfaction.

CONSORT-eHEALTH checklist (V 1.6.1).

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Abbreviations

Edited by A Mavragani; submitted 10.04.23; peer-reviewed by D Xiao, J Zhu; comments to author 30.07.23; revised version received 27.08.23; accepted 28.09.23; published 18.03.24.

©Shanshan Chen, Jinsong Tang, Congyang Wu, Ge Zhang, Jing Zhang, Yanhui Liao. Originally published in JMIR Formative Research (https://formative.jmir.org), 18.03.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

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• PMC10916921

Association between child behavioural problems and parenting stress in autism spectrum disorders: the role of parenting self-efficacy

Kristin strauss.

1 Association for Treatment and Research in Autism and Related Conditions “Umbrella”, Rome, Italy

Michela Servadio

Giovanni valeri.

2 Child Neuropsychiatry Unit, Department of Neuroscience, I.R.C.C.S. Bambino Gesù Children's Hospital,,  Rome, Italy

Laura Casula

Stefano vicari, leonardo fava, associated data.

The authors have full access to all the data used in this study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Introduction: The present study build on previous research that found a bidirectional relation of parenting stress and negative behavioural outcomes in children with Autism Spectrum Disorders.

Aim: To investigate the mediating role of parenting self-efficacy in the relationship of parenting stress and children’s behavioural and emotional problems.

Materials and methods: The sample included 32 young children and their families. Sociodemographic and clinical data were collected. Hierarchical regression analysis revealed direct and indirect mediating effects.

Results: Parenting self-efficacy mediated the relationship between parenting stress and children’s behavioural and emotional problems in fathers only.

Conclusions: We discuss potential ways targeted parenting self-efficacy intervention can support fathers. Results contribute to gain father-informed knowledge in, a research branch generally focused on mothers.

Introduction

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders characterized by core deficits in two domains: social communication, and restrictive, repetitive and/or sensory behaviours or interests (American Psychiatric Association, 2013 ). These disorders provoke a variable degree of impairment among individuals and impact on psychological well-being of affected families. Specifically, the burden of psychological symptoms (i.e. stress, depression, and anxiety) found in parents of children with ASD is a well-known condition (Bitsika and Sharpley 2004 ). Not surprisingly, over the last decade, interest in developing effective psychological supporting interventions for parents has increased (McConachie and Diggle 2007 , Oono et al. 2013 , Rojas-Torres et al. 2020 ).

Among parents of children with ASD, parenting stress is one of the most reported distress conditions. Indeed, parenting stress is consistently reported on significantly higher levels in parents of children with ASD than those with typical development (Davis and Carter 2008 , Estes et al. 2009 , Giovagnoli et al. 2015 ) or with other neurodevelopmental disorders (Craig et al. 2016 , Estes et al. 2009 , Hou et al. 2018 ). These research findings have been confirmed in a meta-analysis (Hayes and Watson, 2013 ). In ASD, parental stress is reported, as clinical significant, in more than 70% of mothers (Kiami and Goodgold 2017 ).

Although, parenting stress is a well-documented problem in parents with children with ASD, inferring variables are still partially unknown. A research branch investigated the impact of child’s emotional and behavioural problems in children with ASD on poor psychological well-being reported in parents. As such, behavioural problems of children with ASD predicted high parenting stress levels (Argumedes et al. 2018 , Hou et al. 2018 ) and lower quality of life (McStay et al. 2014 ). A meta-analysis performed by Yorke et al. ( 2018 ) highlighted a strong relationship between child’s emotional and behavioural problems and parents’ well-being, including parental stress. However, longitudinal studies results are more controversial, not indicating a linear relationship between these factors. Future studies with longitudinal design and larger samples may shed light on this aspect (Yorke et al. 2018 ). Interestingly, Giovagnoli et al. ( 2015 ) found that child’s emotional and behavioural problems may affect components of parenting stress differently, highlighting the hypothesis that, both, child and parent related variables, may inform parent training.

Thus, specific parent variables have been tested as possible predictors of psychological well-being in parents of children with ASD. Research findings include socioeconomic support and parental cognition demonstrating a higher predictive value on parents’ psychological well-being than child related variables (Falk et al. 2014 ), with child’s behavioural and emotional impairment being associated with overall level of distress, but not directly impacting parenting stress (Firth and Dryer 2013 ). Indeed, it is worthy to address parenting stress and psychological well-being during investigations of the population of interest, due to their value as potential intervention outcomes of parent training and support programs targeting parents of children with ASD (Catalano et al. 2018 ).

Similarely, parenting self-efficay has been identified as a possibile intervention target in such parent training and support programs (Hohlfeld et al. 2018 , Jones and Prinz 2005 , Solish and Perry 2008 ). Self-efficacy is defined as one’s own belief regarding their capability to successfully exercise control in specific situations, or regarding their capability to accomplish specific tasks (Bandura 1977 ). Thus, parenting self-efficacy concerns the ability of parents to face the multiple difficulties, that may appear, while successfully raising one's own children. An association between parenting self-efficacy and parents’ mental health and child’s behavioural problems has been demonstrated (Albanese et al. 2019 ). Insofar, outcome meaures, as the increase in parenting self-efficacy and high quality child-mother interactions, or the decrease in parenting stress, had long been included in stress parent training programs as targets (Gross et al. 1995 ). Nevertheless, similar results failed to emerge in fathers.

Regarding mothers of children with ASD, previous findings indicate the association between mother’s mental health and parenting self-efficacy. A significantly reduced parenting self-efficacy towards their child with ASD rather than their child with Typical Development (TD) has been found (Meirsschaut et al. 2010 ). Furthermore, high levels of parenting self-efficacy were associated with reduced stress and depression in mothers (Kuhn and Carter 2006 , Meirsschaut et al. 2010 ), reduced parental anxiety and child’s behavioural problems (Hastings and Brown 2002 ). In detail, Hastings and Brown ( 2002 ) demonstrated that child behavioural problems may affect maternal anxiety and depression through self-efficacy as mediator. Whilst, in fathers the relationship between child behavioural problems and paternal anxiety may hold in presence of the poor self-efficacy, identified as a moderator. In addition, such differences between mother and fathers have been confirmed in parents of children with TD. Higher levels of self-efficacy may predict lower levels of parenting stress in fathers only, as a similar finding was not detected in mothers (Batool and Khurshid 2015 , Sevigny and Loutzenhiser 2010 ).

Although, parenting self-efficacy has been addressed in studies regarding parent-training programmes, results are controversial. A person-centered approach to parent training and support, aiming to enhance the quality of parent-child relationship in ASD, may benefit from a separeted analysis of variables that may be differntially of impact in father and mothers.

Considering the analysis of previous findings, our study has a threefold aim:

• To confirm and describe the relationship between child’s behavioural and emotional problems and parenting stress in mothers and fathers of children with ASD.
• To investigate potential mediating role of parenting self-efficacy affecting the relationship between child’s behavioural and emotional problems and parenting stress in mothers and fathers of children with ASD.
• To tackle some of the differences found in mothers and fathers, thus, analyses have been performed on subsamples of mothers and fathers, separately.

Materials and methods

Setting and procedures.

Participants in this study were 32 families (32 mothers and 30 fathers) with children with ASD. All children and families were enrolled in early intensive behavioural intervention (EIBI) and were recruited from the treatment providers database. Procedures of recruitment and study conduct were implemented in accordance with the principles of the Declaration of Helsinki. A member of the research team (the second author) made initial telephone and email contact with 54 eligible families and requested their collaboration. After being informed about the objectives, the parents signed the consent forms to participate in the study, and they were fully aware that they could drop out if they so desired. Eligible parents had the following characteristics: (1) were at least 18 years of age; (2) served as primary caregivers for at least one eligible child enrolled in a EIBI program at the Umbrella center; and (3) had not received a diagnosis of dementia or severe cognitive impairment, compromising the self- and proxy-report procedures implemented. A total of 38 families gave their written informed consent to participate in the cross-sectional study (approximately 69%, including a single mother household). Lastly, 32 families (approximately 84%) completed questionnaire survey over a one-month period. All questionnaires were implemented in their validated Italian version and no additional translation was performed by the research team.

Participants

Most of the children were male (27), and ages ranged from 3 to 11, with a mean age of 70.75 months (SD = 28.27). The clinical diagnosis of an autism spectrum disorder has been confirmed in the Child Psychiatry Unit in paediatric hospitals in the Rome area approximately within a recent 3-year period (mean time since diagnosis 2.81 years (SD = 2.28)). Diagnosis was made according the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013 ) utilizing the Autism Diagnostic Observation Schedule-Second Edition ADOS-2 (ADOS-2, Lord et al. 2012 ), and/or the Autistic Diagnostic Interview – Revised (ADI-R, Rutter et al . 2003 ). Generally, the children had a moderate to severe autism severity level (as indicated by the ADOS-2) with extremely low overall, conceptual, social and practical adaptive functioning (as indicated by the Adaptive Behavior Assessment System II; ABAS II, Harrison and Oakland 2003 ). All children attended regular school classes with varying degrees of additional support.

Concerning parents, a total of 62 parents (32 mothers and 30 fathers) were included in the analysis. Mothers’ mean age was 41.28 (5.04) years, fathers’ mean age was 44.53 (5.61) years, with an age range from 32-58 years. The majority of parents had obtained a university degree and was employed, with a lower distribution in the mother sample. See Table 1 for child and parents’ sociodemographic characteristics.

Sociodemographics of parents and children.

SD = standard deviation; N = sample size; Family Economic Status: refer to the text for description of measure and definition of classes; CA = Chronological Age; TSD = Time Since Diagnosis; ADOS-2 = Autism Diagnostic Observation Schedule-Second Edition; ABAS II = The Adaptive Behavior Assessment System-Second Edition.

Family demographic information

Sociodemographic information of parents was collected through questionnaires for: age, gender, educational level, employments status and family economic status. To measure family economic status each family was asked to quantify whether their monthly income covers all expenses (this question was selected and adapted from the Italian survey of the Statistics on Income and Living Conditions project ( https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions )). The answer options were as follow: with very much difficulty, with difficulty, with mild difficulty, easily, or very much easily. Then level of family economic status was inversely recoded as follow: low, middle-low, middle, middle-high and high.

Measurement of stress

Parenting stress was measured using the Parenting Stress Index – Short Form (PSI-SF; Abidin 1995, adapted to Italian by Guarino et al. 2016 ). The instrument consists of 36 items comprising four subscales: defensive responding (DR, an internal integrity check-scale), parental distress (PD, distress due to personal factors, conflicts in partnership, and demands due to their role as parents), parent–child dysfunctional interaction (PCDI, parents feeling and degree of frustration regarding the interactions with their child) and difficult child (DC, parents perception of their child’s self-regulatory abilities), as well as a total parenting stress score (PS) by adding up PD, PCDI and DC scores. According to the scoring manual, raw scores are transformed in percentile scores and values ≥ 85 are considered clinically significant. Cronbach’s alpha internal consistency coefficients in our sample demonstrated satisfactory internal consistency for total PS (.93), and each subscale (PD = .89, PCDI = .80, DC = .85).

Measurement of child behavioural problems and problem-related parenting self-efficacy

The Child Adjustment and Parent Efficacy Scale-Developmental Disability (CAPES-DD) was used to assess emotional and behavioural problems of children, as well as caregivers' self-efficacy in managing these problems (Emser et al. 2016 : adapted to Italian by Benedetto and Calderone, 2018 ). The questionnaire comprised 24 items divided into three subscales: behavioural problems (BP), emotional problems (EP) and prosocial behaviour (PB) and 3 additional items contributing to the Children’s Total Problems measure (CTP). In addition, Parenting Self-Efficacy scale (PSE) is the sum of the parents’ confidence rates in managing EP and BP (from item 1 to item 16). Higher scores indicate greater levels of child’s EP and BP, PSE and PB. Cronbach’s alpha internal consistency coefficients in our sample demonstrated excellent internal consistency for PSE (.93), and this value is line with previous studies (Benedetto and Calderone 2018 , Emser et al. 2016 , Mazzucchelli et al. 2018 ), a good internal consistency for both CTP (.73) and the subscale BP (.66), and a relatively low value for EP (Cronbach’s Alpha = .53). We are aware about the low internal consistency of the EP subscale; however, it is also important to note that very few parent-reported measures of self-efficacy in managing challenging behaviours of children with ASD are available, and none has been adapted to an Italian sample as for the CAPES-DD (Benedetto and Calderone 2018 ), so far.

Data from mothers and fathers was analysed separately. No statistically significant differences among mothers and fathers regarding levels of parenting stress, ratings of child's behavioural problems and perceptions of parenting self-efficacy were found (see supplementary information Table S1 ).

The Statistical Package for the Social Sciences (SPSS) software (version 25; IBM Corp.) was used. Differences between mother and fathers, regarding sociodemographic characteristics, the component measures of the PSI-SF (defensive responding, parental distress, parent–child dysfunctional interaction and difficult child) and the CAPES-DD (behavioural problems, emotional problems, prosocial behaviour and parenting self-efficacy) have been tested using one-way ANOVAs. The internal consistency for the CAPES-DD questionnaire was determined by computing the Cronbach’s alpha coefficient. An acceptable coefficient alpha is set typically at 0.70 (Kline 2005 ). The correlative relations between the components of PSI-SF, CAPES-DD and ADOS severity have been explored via Pearson’s correlations, for fathers and mothers separately. Regression analysis has been performed based on correlation results, maintaining PSI-SF and CAPES-DD components, and excluding ADOS severity measures due to lacking relation. Multiple linear regression analysis was conducted to evaluate the relations between the dependent variable (components of parenting stress) and explanatory variables (sociodemographic variable, child problems, parenting self-efficacy). In mediation models we assume a third variable (mediator; M = parenting self-efficacy) that influence the indirect relationship between the independent variable (X = child's behavioural problems) and the dependent variable (Y = parenting stress). In the current paper we followed the four-step approach (Baron and Kenny 1986 , Holmbeck 2002 ): (1) a linear regression is conducted with X predicting Y. This confirms the presence of a path c, a direct or indirect effect that may be mediated; (2) a linear regression is conducted with X predicting M. This confirms the presence of a path a, checking the relation of the mediator with the causal variable; (3) a linear regression is conducted with M predicting Y. This confirms the presence of a path b, confirming a potentially independent relation with the outcome variable; and (4) a linear regression is conducted with M predicting the X-Y relationship. This confirms a full mediation : the effect X on Y on the path c (should be zero) is indirect in nature and fully controlled by M. In case, the first three steps are met but not the fourth, partial mediation is detected. A Sobel test was then conducted to examine the significance of indirect and direct effect of the mediator (parenting self-efficacy). Additionally, to further explain the mediation, the proportion of the total effect that was mediated was calculated by multiplying the unstandardized regression coefficients of paths a and b and dividing by the unstandardized regression coefficient of path c (Baron and Kenny 1986 ). The statistical significance of the model was set at the 0.05 α level.

Associations among demographic variables, ASD symptoms, child behavioural problems parenting stress and parenting self-efficacy

Associations between demographic factors and the study variables were analysed via ANOVA for dichotomous variables (gender, educational level, family economic status, employment status, child’s current diagnosis) and via Pearson product-moment correlation analysis for continuous variables (age, time since diagnosis). In mothers, a statistically significant association was found between child’s gender and the parent-child dysfunctional interaction subscale, F(29) = 4.712, p = .038; between educational level and parenting stress, F(29) = 7.664, p = .010; and between parenting self-efficacy and time since diagnosis, r(27) = −0.424, p = .027. Follow-up analyses revealed that mothers of girls reported more parent-child dysfunctional interactions ( M  = 31.80) compared to mothers of boys ( M  = 25.81), and that mothers with higher educational levels reported more parenting stress (PS ( M  = 34.05) compared to mothers with lower educational levels ( M  = 25.20).

In fathers, statistically significant associations were found between family economic status and parenting stress, F(22) = 2.843, p = .049; and between the emotional problem subscale and time since diagnosis, r(29) = 0.389, p = .037. Follow-up analyses for parenting stress revealed no statistically significant differences in fathers. Sociodemographic factors that were found to have a significant relationship with dependent variables, were retained as covariate within the analyses described later.

Bivariate correlation between the study variables and parenting stress are shown in table 2 , for fathers and mothers separately. Pearson product-moment correlation analysis confirmed the presence of statistically significant correlations between child total behavioural problems and parenting stress, both in mothers ( p < .008) and fathers ( p < .001), the parenting self-efficacy scale, both in mothers ( p < .008) and fathers ( p < .008), and between parenting stress and the parenting self-efficacy scale, both in mothers ( p < .023) and fathers ( p < .0001). No statistically significant relationships were found between the ADOS-2 severity and parenting stress, in mothers ( p = .368) and fathers ( p = .516), the child total behavioural problems, in mothers ( p = .367) and fathers ( p = .975), and the parenting self-efficacy scale, in mothers ( p = .371) and fathers ( p = .799). Due to the lacking association of ASD symptom severity with any of the study variables, ADOS-2 severity has not been included in subsequent analyses.

Intercorrelation of the primary variables of interest in mothers and fathers.

Data analysis: Pearson correlation statistics *Correlation is significant at the 0.05 level or less ( p ≤ .05) **Correlation is significant at the 0.01 level or less ( p ≤ .01) M-PSI = Mothers’ Parenting Stress Index; F-PSI = Fathers’ Parenting Stress Index; M-CAPES-DD = Mothers’ Child Adjustment and Parent Efficacy Scale-Developmental Disability; F-CAPES-DD = Fathers’ Child Adjustment and Parent Efficacy Scale-Developmental Disability; ADOS = Autism Diagnostic Observation Schedule; PS = Parenting Stress; PSE = Parenting Self-Efficacy; CTP = Children’s Total Problems.

Multiple regression analysis

To proceed with regression analyses, distributions of variables should be checked for skewness. Our data set did not reveal skewed data, thus no squared root transformation has been applied.

Multiple regression analysis was carried out in both, the mother, and the father sample, to evaluate the relationship between the dependent variable of parenting stress and the explanatory variables, namely child behavioural problems and parenting self-efficacy. The results of the regression analysis indicated that each of the explanatory variables are statistically significant predictors ( table 3 ). In mothers, an approximately 18% of variance in parenting stress was explained by child behavioural problems (β = .458, p < .008), parenting self-efficacy (β = −.437, p < .023). In fathers, an approximately 45% of variance in parenting stress was explained by child behavioural problems (β = .600, p < .001) and parenting self-efficacy (β = −.682, p < .0001).

Multiple linear regressions to evaluate the relationship between the dependent variable and the explanatory variables.

Data analysis: Linear regressions; PSE = Parenting Self-Efficacy; CTP = Children’s Total Problems.

Mediation analysis controlling for parenting self-efficacy

Using the steps of mediation outlined by Baron and Kenny ( 1986 ) and Holmbeck ( 2002 ), a series of regression analyses were conducted to assess parenting self-efficacy as potential mediator, to examine the explanatory mechanisms underlying significant relation of child behavioural problems and parenting stress. Three series of regression analyses were conducted.

The first regression analysis examined the relationship between the predictor and the criterion (pathway c); the second regression analysis examined the relationship between the predictor (pathway a) and the potential mediator; the third regression analysis examined the relationship between the potential mediator and the criterion (pathway b); the fourth regression analysis examined the effect of the predictor and the potential mediator on the criterion. Additionally, to further explain the mediation, a sobel z was calculated; and the proportion of the total effect that was mediated was calculated by multiplying the unstandardized regression coefficients of paths a and b and dividing by the unstandardized regression coefficient of path c (Baron and Kenny 1986 ).

Figure 1 shows a simple mediation model in which the parenting self-efficacy mediates the relationship between child behavioural problems and parenting stress, in fathers only. Detailed results of the multiple mediation analysis are available in table 4 . Table 4 shows the results of the separate regression analyses testing the mediation hypothesis. In fathers, a statistically significant effect of the amount of child behavioural problems on paternal parenting stress (b c = 2.82, p = .01) and of child behavioural problems on paternal parenting self-efficacy (b a = −2.48, p = .008) was confirmed. After including the mediator variable (parenting self-efficacy, b c’ = −0.621, p < .001) into the model, the effect of child behavioural problems decreased to b c = 1.51, p = .051. The difference b c – b c’ = 1.31 was significant (Sobel test: z s = 2.831, p < .01). Paternal self-efficacy was thus a significant full mediator of the association of child behavioural problems and paternal parenting stress. The original regression coefficient of the effect decreased by 54% when self-efficacy was included as mediator, hence 54% of the effect of child behavioural problems on paternal stress is mediated by paternal self-efficacy.

Standardized regression coefficients for paths within the mediation model for fathers.

Note: Analyses were controlled for family economic status.

Series of regression analyses for self-efficacy as mediator child’s total problems and total parental stress in fathers and mothers.

Data analysis: Hierarchical regressions; Family economic status, mother’s educational level and time since diagnosis were entered into the equations as control variables based on the ANOVA and correlations results.* Significant at the 0.05 level ( p ≤ .05) ** Significant at the 0.01 level ( p ≤.01) PS = Parenting Stress; PSE = Parenting Self-Efficacy; CTP = Children’s Total Problems.

In mothers, such a mediation effect was not detected. A statistically significant effect of the amount of child behavioural problems on maternal parenting stress (b c = 1.25, p < .05) and of child behavioural problems on maternal parenting self-efficacy (b a = −1.63, p < .05) was confirmed. After including the mediator variable (parenting self-efficacy) into the model, no significant mediation effect of maternal self-efficacy has been detected (b c = −0.20, p = .081).

In order to exclude possible alternative explanations and because of the cross-sectional nature of the study, the mediation analysis was repeated with reversed direction (testing parenting stress as mediator and self-efficacy as the outcome variable). After interchanging dependent and independent variables, a significant but smaller effect was obtained. Approximately a 12% of the original effect of child behavioural problems on paternal parenting self-efficacy was mediated by paternal parenting stress. The difference b c – b c’ = −2.94 was significant (z s = 2.385, p < .05).

The current study was carried out to explore the relational strength of child behavioural problems and parenting stress among parents of children with autism. Results partially supported our hypotheses. We found a consistent relationship of child’s behavioural problems and perceived parenting stress, both in fathers and mothers. Some child-related and sociodemographic variables were differentially associated with parenting stress. Mothers with higher educational levels of female children perceived more parenting stress, whereas in fathers parenting stress was association with rates of lower economic status, with time since diagnosis and, specifically, higher emotional problems in their child. It appeared that child behavioural problems and parenting self-efficacy are salient predictors of stress among both, fathers, and mothers, indicating that increase in severity of challenging behaviour problems is directly related to an increase in parenting stress. Results coincide with previous finding (Bitsika and Sharpley 2017 , Tomeny 2017 ). Furthermore, the lacking association of core symptomatology of ASD and parenting stress has been found in previous work (Ben-Sasson et al. 2013 , Giovagnoli et al. 2015 , Barroso et al. 2018 , Yorke et al. 2018 ).

We found that parenting self-efficacy fully mediated the relationship between child behavioural problems and parenting stress, in fathers only. Mediation analysis showed that 54% of the effect of child behavioural problems on paternal parenting stress was mediated by paternal self-efficacy. In a control test of the reverse direction, self-efficacy mediated only 12% of the effect of child behavioural problems on paternal parenting stress. These results suggest that a high amount of child behavioural problems may lead to a sharp increase in paternal parenting stress, in part, through reduced paternal self-efficacy. Thus, paternal self-efficacy, or the strong belief in one’s own capabilities to be able to control difficult situations, may function as a parameter of resilience when the child’s challenging behaviours surface.

In mothers, as proposed by the mediation model, a statistically significant direct relation between child behavioural problems and parenting stress, and significant positive associations between maternal self-efficacy and child behavioural problems, parenting stress as well as paternal self-efficacy, has been found. Nevertheless, although child’s behavioural and emotional problems contribute to maternal parenting stress, a mediating role of maternal parenting self-efficacy fails to emerge. Thus, self-efficacy in mothers may not exercise such a potentially protective effect, when child’ behavioural problems arise. Similar findings can be found in past research that indicated a reduction of problem-focused coping strategies in mothers of children with higher symptom severity (Miranda et al. 2019 ).

Practical implications

The results of this study highlight the differences of personal belief sets between mothers and fathers, of childredn with ASD, towards the capability to control child-related hazzles and the relative efficacy to alleviate stress. This suggests that specific, parent training and parent support interventions aiming at reducing parenting stress, preserving mental health, and ameliorating well-being need to progress research findings differentially for fathers and for mothers and need to engage strategies specific to mothers and fathers.

We acknowledged that there is a need of tailored interventions for parents, as there is a need of individualized interventions for children with ASD. Collecting information about their experiences as parents may contribute to overcome the lack of such practice.

Strengths, limitations and future directions

To our knowledge the present study is the first one to explore parenting stress and parenting self-efficacy as a potential mediator separately in parents of children with ASD, caracterized by a relatively moderate to severe symptomatology and by an extremely low overall, conceptual, social, and practical adaptive functioning. Thus, a sample of parents of children that demonstrate challenging behaviours and emotional problems with relatively high frequency and intensity.

Another strength of our study is the measurement of task-specific parenting self-efficacy rather than general parenting self-efficacy. Most of previous works that investigated parenting self-efficacy, primarily involved general measures of self-efficacy (Jones and Prinz 2005 , Wittkowski et al. 2017 ). Our decision to specifically address task-specific self-efficacy is consistent with coping research showing that higher levels of problems-focused coping acts as a buffer when autism symptomatology reaches high severity levels (Smith et al. 2008 ).

Nonetheless, the study has several limitations. The small sample size and cross-sectional nature of the study design imply that results need to be considered preliminary and replication studies are needed. Again, the cross-sectional nature and the specific child characteristics who present severe levels of autism symptomatology and an extreme low adaptive functioning, restrict generalizability. Although, the homogeneity of the sample increases specificity, no implication can be drawn for families of children with ASD without developmental disabilities, lower impacting ASD severity and higher adaptive functioning. Accessing a representative data pool is warranted. Additionally, most of the children were male. Although this represents the general population of children with autism, results may poorly represent parents with girls, especially as having a female child was significantly related to increased parenting stress in mothers. Information was obtained through parent self-report. Arguably, this is appropriate as permanent belief sets and personal perceptions are set in the definition of the study variables. However, some parents may either under- or overreport for a variety of cultural or personal reasons.

The limitations of this study provide directions for the future research. As only 45% of variance of the mediation model is accounted for by the study variables in fathers and 18% of variance in mothers, a 55% and 82% of variance, respectively, is unknown. A variety of potential factors, like active and avoidant coping (Hastings et al. 2005 , Smith et al. 2008 ), social community support (Ekas et al. 2010 ), cognitive reframing (Benson, 2010 , Benson, 2014 ) and family functioning (Rao and Beidel, 2009 ) may be included in such a future model. However, the analysis of parenting stress must be considered from a more complex perspective, through the examination of protective and risk factors, that may be involved differentially in fathers and mothers, due to the vast social, personal, and cultural differences. It would be parsimonious in future research to apply a multiple mediation model engaging potential mediators simultaneously and to examine pairwise contrast of indirect effects, rather than applying a single-mediation model, as used in the current study (Preacher and Hayes, 2008 ).

Another potential limitation is the measurement of the child behavioural problems and parenting self-efficacy variables on the same measure. The frequent problem of multicollinearity in regression analysis and mediation analysis may arise. That is when variables are highly correlated to one another, generally indicated by correlation of .75 or higher in correlation coefficient matrix’. Such high correlation coefficients are not present in the current data set, nor there are significant f-values for the equation while t-ratios of the coefficient are not significant. Generally, multicollinearity cannot be fully avoided in mediation analysis. Furthermore, the measurement instrument (CAPES-DD) has been implemented due to its unique characteristic in assessing task-specific parenting self-efficacy, a rating that each parent matches to specific child behavioural problems frequent in children with developmental disabilities. Nevertheless, future studies may be able to assess a bigger sample size and conduct latent variable analysis to reduce effects of such correlated measurement errors.

Our research findings demonstrate distinct differences in mothers and fathers regarding potential variables that may affect mental health and well-being outcomes. Future studies, therefore, warrant the inclusion of samples of fathers and a separated data analysis for mothers and fathers.

The role of paternal self-efficacy, that is significantly affecting the relation between child behavioural problems and paternal parenting stress, is lacking in mothers. For fathers, in this study parenting self-efficacy appears to be differently accessible when needed to navigate challenges in parenting tasks. This may be culturally rooted in distinct involvement within the family, observable in households where most parenting tasks are organized by a manager-helper dynamic. That is when mothers primarily navigate the family life and fathers provide specific assistance through task completion (Daly 2002). Thus, a high perception of task-specific self-efficacy (in other words being a problem solver) may successfully counteract the relation between hazzles and stress in fathers, whereas being an emotionally supported parent is more salient aspect of women’s personal identity. One of the few longitudinal studies in ASD research demonstrated that persistent maternal stress is exacerbated when personal and social resources are insufficient. Active coping strategies acted as a resilience factor over time in mothers (Zaidman-Zait et al. 2016 ). Future research needs to examine the potential buffering effect of social and confidant support, the quality of intimate relations and coparenting that may be more closely related to parenting stress perceived in mothers. Such investigations are needed to untangle the complex mechanisms underlying mental health outcome in parents with children with ASD, thus providing implications for tailored parent training and parent support interventions.

Acknowledgments

The authors would like to thank parents and children for their participation in this cross-sectional analysis.

Disclosure statement

The authors report no conflict of interest.

The authors received no specific funding for this work.

Data availability statement

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