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How To Write A Research Summary

It’s a common perception that writing a research summary is a quick and easy task. After all, how hard can jotting down 300 words be? But when you consider the weight those 300 words carry, writing a research summary as a part of your dissertation, essay or compelling draft for your paper instantly becomes daunting task.

A research summary requires you to synthesize a complex research paper into an informative, self-explanatory snapshot. It needs to portray what your article contains. Thus, writing it often comes at the end of the task list.

Regardless of when you’re planning to write, it is no less of a challenge, particularly if you’re doing it for the first time. This blog will take you through everything you need to know about research summary so that you have an easier time with it.

What is a Research Summary?

A research summary is the part of your research paper that describes its findings to the audience in a brief yet concise manner. A well-curated research summary represents you and your knowledge about the information written in the research paper.

While writing a quality research summary, you need to discover and identify the significant points in the research and condense it in a more straightforward form. A research summary is like a doorway that provides access to the structure of a research paper's sections.

Since the purpose of a summary is to give an overview of the topic, methodology, and conclusions employed in a paper, it requires an objective approach. No analysis or criticism.

Research summary or Abstract. What’s the Difference?

They’re both brief, concise, and give an overview of an aspect of the research paper. So, it’s easy to understand why many new researchers get the two confused. However, a research summary and abstract are two very different things with individual purpose. To start with, a research summary is written at the end while the abstract comes at the beginning of a research paper.

A research summary captures the essence of the paper at the end of your document. It focuses on your topic, methods, and findings. More like a TL;DR, if you will. An abstract, on the other hand, is a description of what your research paper is about. It tells your reader what your topic or hypothesis is, and sets a context around why you have embarked on your research.

Getting Started with a Research Summary

Before you start writing, you need to get insights into your research’s content, style, and organization. There are three fundamental areas of a research summary that you should focus on.

• While deciding the contents of your research summary, you must include a section on its importance as a whole, the techniques, and the tools that were used to formulate the conclusion. Additionally, there needs to be a short but thorough explanation of how the findings of the research paper have a significance.
• To keep the summary well-organized, try to cover the various sections of the research paper in separate paragraphs. Besides, how the idea of particular factual research came up first must be explained in a separate paragraph.
• As a general practice worldwide, research summaries are restricted to 300-400 words. However, if you have chosen a lengthy research paper, try not to exceed the word limit of 10% of the entire research paper.

How to Structure Your Research Summary

The research summary is nothing but a concise form of the entire research paper. Therefore, the structure of a summary stays the same as the paper. So, include all the section titles and write a little about them. The structural elements that a research summary must consist of are:

It represents the topic of the research. Try to phrase it so that it includes the key findings or conclusion of the task.

The abstract gives a context of the research paper. Unlike the abstract at the beginning of a paper, the abstract here, should be very short since you’ll be working with a limited word count.

Introduction

This is the most crucial section of a research summary as it helps readers get familiarized with the topic. You should include the definition of your topic, the current state of the investigation, and practical relevance in this part. Additionally, you should present the problem statement, investigative measures, and any hypothesis in this section.

Methodology

This section provides details about the methodology and the methods adopted to conduct the study. You should write a brief description of the surveys, sampling, type of experiments, statistical analysis, and the rationality behind choosing those particular methods.

Create a list of evidence obtained from the various experiments with a primary analysis, conclusions, and interpretations made upon that. In the paper research paper, you will find the results section as the most detailed and lengthy part. Therefore, you must pick up the key elements and wisely decide which elements are worth including and which are worth skipping.

This is where you present the interpretation of results in the context of their application. Discussion usually covers results, inferences, and theoretical models explaining the obtained values, key strengths, and limitations. All of these are vital elements that you must include in the summary.

Most research papers merge conclusion with discussions. However, depending upon the instructions, you may have to prepare this as a separate section in your research summary. Usually, conclusion revisits the hypothesis and provides the details about the validation or denial about the arguments made in the research paper, based upon how convincing the results were obtained.

The structure of a research summary closely resembles the anatomy of a scholarly article . Additionally, you should keep your research and references limited to authentic and  scholarly sources only.

Tips for Writing a Research Summary

The core concept behind undertaking a research summary is to present a simple and clear understanding of your research paper to the reader. The biggest hurdle while doing that is the number of words you have at your disposal. So, follow the steps below to write a research summary that sticks.

1. Read the parent paper thoroughly

You should go through the research paper thoroughly multiple times to ensure that you have a complete understanding of its contents. A 3-stage reading process helps.

a. Scan: In the first read, go through it to get an understanding of its basic concept and methodologies.

b. Read: For the second step, read the article attentively by going through each section, highlighting the key elements, and subsequently listing the topics that you will include in your research summary.

c. Skim: Flip through the article a few more times to study the interpretation of various experimental results, statistical analysis, and application in different contexts.

Sincerely go through different headings and subheadings as it will allow you to understand the underlying concept of each section. You can try reading the introduction and conclusion simultaneously to understand the motive of the task and how obtained results stay fit to the expected outcome.

2. Identify the key elements in different sections

While exploring different sections of an article, you can try finding answers to simple what, why, and how. Below are a few pointers to give you an idea:

• What is the research question and how is it addressed?
• Is there a hypothesis in the introductory part?
• What type of methods are being adopted?
• What is the sample size for data collection and how is it being analyzed?
• What are the most vital findings?
• Do the results support the hypothesis?

Discussion/Conclusion

• What is the final solution to the problem statement?
• What is the explanation for the obtained results?
• What is the drawn inference?
• What are the various limitations of the study?

3. Prepare the first draft

Now that you’ve listed the key points that the paper tries to demonstrate, you can start writing the summary following the standard structure of a research summary. Just make sure you’re not writing statements from the parent research paper verbatim.

Instead, try writing down each section in your own words. This will not only help in avoiding plagiarism but will also show your complete understanding of the subject. Alternatively, you can use a summarizing tool (AI-based summary generators) to shorten the content or summarize the content without disrupting the actual meaning of the article.

SciSpace Copilot is one such helpful feature! You can easily upload your research paper and ask Copilot to summarize it. You will get an AI-generated, condensed research summary. SciSpace Copilot also enables you to highlight text, clip math and tables, and ask any question relevant to the research paper; it will give you instant answers with deeper context of the article..

4. Include visuals

One of the best ways to summarize and consolidate a research paper is to provide visuals like graphs, charts, pie diagrams, etc.. Visuals make getting across the facts, the past trends, and the probabilistic figures around a concept much more engaging.

5. Double check for plagiarism

It can be very tempting to copy-paste a few statements or the entire paragraphs depending upon the clarity of those sections. But it’s best to stay away from the practice. Even paraphrasing should be done with utmost care and attention.

Also: QuillBot vs SciSpace: Choose the best AI-paraphrasing tool

6. Religiously follow the word count limit

You need to have strict control while writing different sections of a research summary. In many cases, it has been observed that the research summary and the parent research paper become the same length. If that happens, it can lead to discrediting of your efforts and research summary itself. Whatever the standard word limit has been imposed, you must observe that carefully.

7. Proofread your research summary multiple times

The process of writing the research summary can be exhausting and tiring. However, you shouldn’t allow this to become a reason to skip checking your academic writing several times for mistakes like misspellings, grammar, wordiness, and formatting issues. Proofread and edit until you think your research summary can stand out from the others, provided it is drafted perfectly on both technicality and comprehension parameters. You can also seek assistance from editing and proofreading services , and other free tools that help you keep these annoying grammatical errors at bay.

8. Watch while you write

Keep a keen observation of your writing style. You should use the words very precisely, and in any situation, it should not represent your personal opinions on the topic. You should write the entire research summary in utmost impersonal, precise, factually correct, and evidence-based writing.

9. Ask a friend/colleague to help

Once you are done with the final copy of your research summary, you must ask a friend or colleague to read it. You must test whether your friend or colleague could grasp everything without referring to the parent paper. This will help you in ensuring the clarity of the article.

Once you become familiar with the research paper summary concept and understand how to apply the tips discussed above in your current task, summarizing a research summary won’t be that challenging. While traversing the different stages of your academic career, you will face different scenarios where you may have to create several research summaries.

In such cases, you just need to look for answers to simple questions like “Why this study is necessary,” “what were the methods,” “who were the participants,” “what conclusions were drawn from the research,” and “how it is relevant to the wider world.” Once you find out the answers to these questions, you can easily create a good research summary following the standard structure and a precise writing style.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

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A Complete Guide to Writing a Research Summary

A summary is a key part of any research. So, how should you go about writing one?

You will find many guides on the Internet about writing research. But, any article seldom covers the prospect of writing a research summary. While many things are shortened versions of the original article, there’s much more to research summaries.

From descriptive statistics to writing scientific research, a summary plays a vital role in describing the key ideas within. So, it begs a few questions, such as:

• What exactly is a research summary?
• How do you write one?
• What are some of the tips for writing a good research summary ?

In this guide, we’ll answer all of these questions and explore a few essential factors about research writing. So, let’s jump right into it.

What is a Research Summary?

A research summary is a short, concise summary of an academic research paper. It is often used to summarize the results of an experiment, summarize the major findings and conclusions, and provide a brief overview of the methods and procedures used in the study.

The purpose of a research summary is to provide readers with enough information about an article to decide whether they want to read it in its entirety. It should be no more than two paragraphs long and should include:

• A brief introduction summarizing why the article was written
• The main idea of the article
• The major findings and conclusions
• An overview of how the study was conducted

In order to write effective research summaries, it is important that you can capture the essential points of the research and provide a concise overview. The key step in writing a good summary is to read through the article and make notes of the key points.

This can be done by underlining or highlighting key phrases in the article. One essential thing is to organize these points into an outline format, which includes an introduction and conclusion paragraph.

Another best and quick way to generate a precise summary of your research paper is to take assistance from the online text summarizer, like Summarizer.org .

The online summarizing tool gets the research paper and creates a precise summary of it by taking the important points.

Finally, you must edit your work for grammar and spelling errors before submitting it for grading.

The purpose of the research summary is to provide a comprehensive sum of everything that’s in the research. This includes a summarization of scientific/literal research, as well as of the writer’s aim and personal thoughts.

As for the summary length, it shouldn’t be more than 10% of the entire content. So, if your research is around 1000-words or so, then your summary should be 100-words. But, considering how most research papers are around 3000-4000 words, it should be 300-400 words.

Key pillars of a Research Summary

The summary of any research doesn’t just include the summarized text of the entire research paper. It includes a few other key things, which we’ll explore later on in this article. But, the purpose of a summary is to give proper insights to the reader, such as:

• The writer’s intention
• sources and bases of research
• the purpose & result.

That’s why it’s important to understand that the summary should tell your reader all these elements. So, the fundamentals of any summary include:

• Write a section and state the importance of the research paper from your perspective. In this section, you will have to describe the techniques, tools, and sources you employed to get the conclusion.
• Besides that, it’s also meant to provide a brief and descriptive explanation of the actionable aspect of your research. In other words, how it can be implemented in real life.
• Treat your research summary like a smaller article or blog. So, each important section of your research should be written within a subheading. However, this is highly optional to keep things organized.
• As mentioned before, the research summary shouldn’t exceed 300-400 words. But, some research summaries are known to surpass 10000-words. So, try to employ the 10% formula and write one-tenth of the entire length of your research paper.

These four main points allow you to understand how a research summary is different from the research itself. So, it’s like a documentary where research and other key factors are left to the science (research paper), while the narration explains the key points (research summary)

How do you write a Research Summary?

Writing a research summary is a straightforward affair. Yet, it requires some understanding, as it’s not a lengthy process but rather a tricky and technical one. In a research summary, a few boxes must be checked. To help you do just that, here are 6 things you should tend to separately:

A summary’s title can be the same as the title of your primary research. However, putting separate titles in both has a few benefits. Such as:

• A separate title shifts attention towards the conclusion.
• A different title can focus on the main point of your research.
• Using two different titles can provide a better abstract.

Speaking of an abstract, a summary is the abstract of your research. Therefore, a title representing that very thought is going to do a lot of good too. That’s why it’s better if the title of your summary differs from the title of your research paper.

2. Abstract

The abstract is the summarization of scientific or research methods used in your primary paper. This allows the reader to understand the pillars of the study conducted. For instance, there has been an array of astrological research since James Webb Space Telescope started sending images and data.

So, many research papers explain this Telescope’s technological evolution in their abstracts. This allows the reader to differentiate from the astrological research made by previous space crafts, such as Hubble or Chandra .

The point of providing this abstract is to ensure that the reader grasps the standards or boundaries within which the research was held.

3. Introduction

This is the part where you introduce your topic. In your main research, you’d dive right into the technicalities in this part. However, you’ll try to keep things mild in a research summary. Simply because it needs to summarize the key points in your main introduction.

So, a lot of introductions you’ll find as an example will be extensive in length. But, a research summary needs to be as concise as possible. Usually, in this part, a writer includes the basics and standards of investigation.

For instance, if your research is about James Webb’s latest findings , then you’ll identify how the studies conducted by this Telescope’s infrared and other technology made this study possible. That’s when your introduction will hook the reader into the main premise of your research.

4. Methodology / Study

This section needs to describe the methodology used by you in your research. Or the methodology you relied on when conducting this particular research or study. This allows the reader to grasp the fundamentals of your research, and it’s extremely important.

Because if the reader doesn’t understand your methods, then they will have no response to your studies. How should you tend to this? Include things such as:

• The surveys or reviews you used;
• include the samplings and experiment types you researched;
• provide a brief statistical analysis;
• give a primary reason to pick these particular methods.

Once again, leave the scientific intricacies for your primary research. But, describe the key methods that you employed. So, when the reader is perusing your final research, they’ll have your methods and study techniques in mind.

5. Results / Discussion

This section of your research needs to describe the results that you’ve achieved. Granted, some researchers will rely on results achieved by others. So, this part needs to explain how that happened – but not in detail.

The other section in this part will be a discussion. This is your interpretation of the results you’ve found. Thus, in the context of the results’ application, this section needs to dive into the theoretical understanding of your research. What will this section entail exactly? Here’s what:

• Things that you covered, including results;
• inferences you provided, given the context of your research;
• the theory archetype that you’ve tried to explain in the light of the methodology you employed;
• essential points or any limitations of the research.

These factors will help the reader grasp the final idea of your research. But, it’s not full circle yet, as the pulp will still be left for the actual research.

6. Conclusion

The final section of your summary is the conclusion. The key thing about the conclusion in your research summary, compared to your actual research, is that they could be different. For instance, the actual conclusion in your research should bring around the study.

However, the research in this summary should bring your own ideas and affirmations to full circle. Thus, this conclusion could and should be different from the ending of your research.

5 Tips for writing a Research Summary

Writing a research summary is easy once you tend to the technicalities. But, there are some tips and tricks that could make it easier. Remember, a research summary is the sum of your entire research. So, it doesn’t need to be as technical or in-depth as your primary work.

Thus, to make it easier for you, here are four tips you can follow:

1. Read & read again

Reading your own work repeatedly has many benefits. First, it’ll help you understand any mistakes or problems your research might have. After that, you’ll find a few key points that stand out from the others – that’s what you need to use in your summary.

So, the best advice anyone can give you is to read your research again and again. This will etch the idea in your mind and allow you to summarize it better.

2. Focus on key essentials in each section

As we discussed earlier, each section of your research has a key part. To write a thoroughly encapsulating summary, you need to focus on and find each such element in your research.

Doing so will give you enough leverage to write a summary that thoroughly condenses your research idea and gives you enough to write a summary out of it.

3. Write the research using a summarizing tool

The best advice you can get is to write a summary using a tool. Condensing each section might be a troublesome experience for some – as it can be time-consuming.

To avoid all that, you can simply take help from an online summarizer. It gets the lengthy content and creates a precise summary of it by using advanced AI technology.

As you can see, the tool condenses this particular section perfectly while the details are light.

Bringing that down to 10% or 20% will help you write each section accordingly. Thus, saving precious time and effort.

4. Word count limit

As mentioned earlier, word count is something you need to follow thoroughly. So, if your section is around 200-word, then read it again. And describe it to yourself in 20-words or so. Doing this to every section will help you write exactly a 10% summary of your research.

5. Get a second opinion

If you’re unsure about quality or quantity, get a second opinion. At times, ideas are in our minds, but we cannot find words to explain them. In research or any sort of creative process, getting a second opinion can save a lot of trouble.

There’s your guide to writing a research summary, folks. While it’s not different from condensing the entire premise of your research, writing it in simpler words will do wonders. So, try to follow the tips, tools, and ideas provided in this article, and write outstanding summaries for your research.

Module 2: Sociological Research

Summary of research methods, learning outcomes.

• Differentiate between the four kinds of research methods: surveys, field research, experiments, and secondary data analysis

Sociological research is a fairly complex process. As you can see, a lot goes into even a simple research design. There are many steps and much to consider when collecting data on human behavior, as well as in interpreting and analyzing data in order to form conclusive results. Sociologists use scientific methods for good reason. The scientific method provides a system of organization that helps researchers plan and conduct the study while ensuring that data and results are reliable, valid, and objective.

The many methods available to researchers—including experiments, surveys, field studies, and secondary data analysis—all come with advantages and disadvantages. The strength of a study can depend on the choice and implementation of the appropriate method of gathering research. Depending on the topic, a study might use a single method or a combination of methods. It is important to plan a research design before undertaking a study. The information gathered may in itself be surprising, and the study design should provide a solid framework in which to analyze predicted and unpredicted data.

Making Connections: When is Sharing Not Such a Good Idea?

Figure 1. Crack cocaine users in downtown Vancouver. (Photo courtesy of Wikimedia commons)

Choosing a research methodology depends on a number of factors, including the purpose of the research and the audience for whom the research is intended. If we consider the type of research that might go into producing a government policy document on the effectiveness of safe injection sites for reducing the public health risks of intravenous drug use, we would expect public administrators to want “hard” (i.e., quantitative) evidence of high reliability to help them make a policy decision. The most reliable data would come from an experimental or quasi-experimental research model in which a control group can be compared with an experimental group using quantitative measures.

This approach has been used by researchers studying InSite in Vancouver (Marshall et al. 2011; Wood et al. 2006). InSite is a supervised safe-injection site where heroin addicts and other intravenous drug users can go to inject drugs in a safe, clean environment. Clean needles are provided and health care professionals are on hand to intervene in the case of overdose or other medical emergency. It is a controversial program both because heroin use is against the law (the facility operates through a federal ministerial exemption) and because the heroin users are not obliged to quit using or seek therapy. To assess the effectiveness of the program, researchers compared the risky usage of drugs in populations before and after the opening of the facility and geographically near and distant to the facility. The results from the studies have shown that InSite has reduced both deaths from overdose and risky behaviours, such as the sharing of needles, without increasing the levels of crime associated with drug use and addiction.

On the other hand, if the research question is more exploratory (for example, trying to discern the reasons why individuals in the crack smoking subculture engage in the risky activity of sharing pipes), the more nuanced approach of fieldwork is more appropriate. The research would need to focus on the subcultural context, rituals, and meaning of sharing pipes, and why these phenomena override known health concerns. Graduate student Andrew Ivsins at the University of Victoria studied the practice of sharing pipes among 13 habitual users of crack cocaine in Victoria, B.C. (Ivsins 2010). He met crack smokers in their typical setting downtown and used an unstructured interview method to try to draw out the informal norms that lead to sharing pipes. One factor he discovered was the bond that formed between friends or intimate partners when they shared a pipe. He also discovered that there was an elaborate subcultural etiquette of pipe use that revolved around the benefit of getting the crack resin smokers left behind. Both of these motives tended to outweigh the recognized health risks of sharing pipes (such as hepatitis) in the decision making of the users. This type of research was valuable in illuminating the unknown subcultural norms of crack use that could still come into play in a harm reduction strategy such as distributing safe crack kits to addicts.

Watch this video to review some of the key methods used in conducting sociological research.

• Research Methods. Authored by : OpenStax CNX. Located at : . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]
• Making Connections. Authored by : William Little. Provided by : BC Open Textbooks. Located at : https://opentextbc.ca/introductiontosociology/ . License : CC BY: Attribution
• Sociological Research Methods. Provided by : CrashCourse. Located at : https://www.youtube.com/watch?v=QwhK-iEyXYA&list=PL8dPuuaLjXtMJ-AfB_7J1538YKWkZAnGA&index=5 . License : Other . License Terms : Standard YouTube License

Research Methods In Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.

Hypotheses are statements about the prediction of the results, that can be verified or disproved by some investigation.

There are four types of hypotheses :

• Null Hypotheses (H0 ) – these predict that no difference will be found in the results between the conditions. Typically these are written ‘There will be no difference…’
• Alternative Hypotheses (Ha or H1) – these predict that there will be a significant difference in the results between the two conditions. This is also known as the experimental hypothesis.
• One-tailed (directional) hypotheses – these state the specific direction the researcher expects the results to move in, e.g. higher, lower, more, less. In a correlation study, the predicted direction of the correlation can be either positive or negative.
• Two-tailed (non-directional) hypotheses – these state that a difference will be found between the conditions of the independent variable but does not state the direction of a difference or relationship. Typically these are always written ‘There will be a difference ….’

All research has an alternative hypothesis (either a one-tailed or two-tailed) and a corresponding null hypothesis.

Once the research is conducted and results are found, psychologists must accept one hypothesis and reject the other. 

So, if a difference is found, the Psychologist would accept the alternative hypothesis and reject the null.  The opposite applies if no difference is found.

Sampling techniques

Sampling is the process of selecting a representative group from the population under study.

A sample is the participants you select from a target population (the group you are interested in) to make generalizations about.

Representative means the extent to which a sample mirrors a researcher’s target population and reflects its characteristics.

Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.

• Volunteer sample : where participants pick themselves through newspaper adverts, noticeboards or online.
• Opportunity sampling : also known as convenience sampling , uses people who are available at the time the study is carried out and willing to take part. It is based on convenience.
• Random sampling : when every person in the target population has an equal chance of being selected. An example of random sampling would be picking names out of a hat.
• Systematic sampling : when a system is used to select participants. Picking every Nth person from all possible participants. N = the number of people in the research population / the number of people needed for the sample.
• Stratified sampling : when you identify the subgroups and select participants in proportion to their occurrences.
• Snowball sampling : when researchers find a few participants, and then ask them to find participants themselves and so on.
• Quota sampling : when researchers will be told to ensure the sample fits certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed.

Experiments always have an independent and dependent variable .

• The independent variable is the one the experimenter manipulates (the thing that changes between the conditions the participants are placed into). It is assumed to have a direct effect on the dependent variable.
• The dependent variable is the thing being measured, or the results of the experiment.

Operationalization of variables means making them measurable/quantifiable. We must use operationalization to ensure that variables are in a form that can be easily tested.

For instance, we can’t really measure ‘happiness’, but we can measure how many times a person smiles within a two-hour period. 

By operationalizing variables, we make it easy for someone else to replicate our research. Remember, this is important because we can check if our findings are reliable.

Extraneous variables are all variables which are not independent variable but could affect the results of the experiment.

It can be a natural characteristic of the participant, such as intelligence levels, gender, or age for example, or it could be a situational feature of the environment such as lighting or noise.

Demand characteristics are a type of extraneous variable that occurs if the participants work out the aims of the research study, they may begin to behave in a certain way.

For example, in Milgram’s research , critics argued that participants worked out that the shocks were not real and they administered them as they thought this was what was required of them. 

Extraneous variables must be controlled so that they do not affect (confound) the results.

Randomly allocating participants to their conditions or using a matched pairs experimental design can help to reduce participant variables. 

Situational variables are controlled by using standardized procedures, ensuring every participant in a given condition is treated in the same way

Experimental Design

Experimental design refers to how participants are allocated to each condition of the independent variable, such as a control or experimental group.

• Independent design ( between-groups design ): each participant is selected for only one group. With the independent design, the most common way of deciding which participants go into which group is by means of randomization. 
• Matched participants design : each participant is selected for only one group, but the participants in the two groups are matched for some relevant factor or factors (e.g. ability; sex; age).
• Repeated measures design ( within groups) : each participant appears in both groups, so that there are exactly the same participants in each group.
• The main problem with the repeated measures design is that there may well be order effects. Their experiences during the experiment may change the participants in various ways.
• They may perform better when they appear in the second group because they have gained useful information about the experiment or about the task. On the other hand, they may perform less well on the second occasion because of tiredness or boredom.
• Counterbalancing is the best way of preventing order effects from disrupting the findings of an experiment, and involves ensuring that each condition is equally likely to be used first and second by the participants.

If we wish to compare two groups with respect to a given independent variable, it is essential to make sure that the two groups do not differ in any other important way. 

Experimental Methods

All experimental methods involve an iv (independent variable) and dv (dependent variable)..

• Field experiments are conducted in the everyday (natural) environment of the participants. The experimenter still manipulates the IV, but in a real-life setting. It may be possible to control extraneous variables, though such control is more difficult than in a lab experiment.
• Natural experiments are when a naturally occurring IV is investigated that isn’t deliberately manipulated, it exists anyway. Participants are not randomly allocated, and the natural event may only occur rarely.

Case studies are in-depth investigations of a person, group, event, or community. It uses information from a range of sources, such as from the person concerned and also from their family and friends.

Many techniques may be used such as interviews, psychological tests, observations and experiments. Case studies are generally longitudinal: in other words, they follow the individual or group over an extended period of time. 

Case studies are widely used in psychology and among the best-known ones carried out were by Sigmund Freud . He conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

Case studies provide rich qualitative data and have high levels of ecological validity. However, it is difficult to generalize from individual cases as each one has unique characteristics.

Correlational Studies

Correlation means association; it is a measure of the extent to which two variables are related. One of the variables can be regarded as the predictor variable with the other one as the outcome variable.

Correlational studies typically involve obtaining two different measures from a group of participants, and then assessing the degree of association between the measures. 

The predictor variable can be seen as occurring before the outcome variable in some sense. It is called the predictor variable, because it forms the basis for predicting the value of the outcome variable.

Relationships between variables can be displayed on a graph or as a numerical score called a correlation coefficient.

• If an increase in one variable tends to be associated with an increase in the other, then this is known as a positive correlation .
• If an increase in one variable tends to be associated with a decrease in the other, then this is known as a negative correlation .
• A zero correlation occurs when there is no relationship between variables.

After looking at the scattergraph, if we want to be sure that a significant relationship does exist between the two variables, a statistical test of correlation can be conducted, such as Spearman’s rho.

The test will give us a score, called a correlation coefficient . This is a value between 0 and 1, and the closer to 1 the score is, the stronger the relationship between the variables. This value can be both positive e.g. 0.63, or negative -0.63.

A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. A correlation only shows if there is a relationship between variables.

Correlation does not always prove causation, as a third variable may be involved. 

Interview Methods

Interviews are commonly divided into two types: structured and unstructured.

A fixed, predetermined set of questions is put to every participant in the same order and in the same way. 

Responses are recorded on a questionnaire, and the researcher presets the order and wording of questions, and sometimes the range of alternative answers.

The interviewer stays within their role and maintains social distance from the interviewee.

There are no set questions, and the participant can raise whatever topics he/she feels are relevant and ask them in their own way. Questions are posed about participants’ answers to the subject

Unstructured interviews are most useful in qualitative research to analyze attitudes and values.

Though they rarely provide a valid basis for generalization, their main advantage is that they enable the researcher to probe social actors’ subjective point of view. 

Questionnaire Method

Questionnaires can be thought of as a kind of written interview. They can be carried out face to face, by telephone, or post.

The choice of questions is important because of the need to avoid bias or ambiguity in the questions, ‘leading’ the respondent or causing offense.

• Open questions are designed to encourage a full, meaningful answer using the subject’s own knowledge and feelings. They provide insights into feelings, opinions, and understanding. Example: “How do you feel about that situation?”
• Closed questions can be answered with a simple “yes” or “no” or specific information, limiting the depth of response. They are useful for gathering specific facts or confirming details. Example: “Do you feel anxious in crowds?”

Its other practical advantages are that it is cheaper than face-to-face interviews and can be used to contact many respondents scattered over a wide area relatively quickly.

Observations

There are different types of observation methods :

• Covert observation is where the researcher doesn’t tell the participants they are being observed until after the study is complete. There could be ethical problems or deception and consent with this particular observation method.
• Overt observation is where a researcher tells the participants they are being observed and what they are being observed for.
• Controlled : behavior is observed under controlled laboratory conditions (e.g., Bandura’s Bobo doll study).
• Natural : Here, spontaneous behavior is recorded in a natural setting.
• Participant : Here, the observer has direct contact with the group of people they are observing. The researcher becomes a member of the group they are researching.  
• Non-participant (aka “fly on the wall): The researcher does not have direct contact with the people being observed. The observation of participants’ behavior is from a distance

Pilot Study

A pilot  study is a small scale preliminary study conducted in order to evaluate the feasibility of the key s teps in a future, full-scale project.

A pilot study is an initial run-through of the procedures to be used in an investigation; it involves selecting a few people and trying out the study on them. It is possible to save time, and in some cases, money, by identifying any flaws in the procedures designed by the researcher.

A pilot study can help the researcher spot any ambiguities (i.e. unusual things) or confusion in the information given to participants or problems with the task devised.

Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all or can complete the task – all performances are low.

The opposite effect is a ceiling effect, when the task is so easy that all achieve virtually full marks or top performances and are “hitting the ceiling”.

Research Design

In cross-sectional research , a researcher compares multiple segments of the population at the same time

Sometimes, we want to see how people change over time, as in studies of human development and lifespan. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.

In cohort studies , the participants must share a common factor or characteristic such as age, demographic, or occupation. A cohort study is a type of longitudinal study in which researchers monitor and observe a chosen population over an extended period.

Triangulation means using more than one research method to improve the study’s validity.

Reliability

Reliability is a measure of consistency, if a particular measurement is repeated and the same result is obtained then it is described as being reliable.

• Test-retest reliability :  assessing the same person on two different occasions which shows the extent to which the test produces the same answers.
• Inter-observer reliability : the extent to which there is an agreement between two or more observers.

Meta-Analysis

A meta-analysis is a systematic review that involves identifying an aim and then searching for research studies that have addressed similar aims/hypotheses.

This is done by looking through various databases, and then decisions are made about what studies are to be included/excluded.

Strengths: Increases the conclusions’ validity as they’re based on a wider range.

Weaknesses: Research designs in studies can vary, so they are not truly comparable.

Peer Review

A researcher submits an article to a journal. The choice of the journal may be determined by the journal’s audience or prestige.

The journal selects two or more appropriate experts (psychologists working in a similar field) to peer review the article without payment. The peer reviewers assess: the methods and designs used, originality of the findings, the validity of the original research findings and its content, structure and language.

Feedback from the reviewer determines whether the article is accepted. The article may be: Accepted as it is, accepted with revisions, sent back to the author to revise and re-submit or rejected without the possibility of submission.

The editor makes the final decision whether to accept or reject the research report based on the reviewers comments/ recommendations.

Peer review is important because it prevent faulty data from entering the public domain, it provides a way of checking the validity of findings and the quality of the methodology and is used to assess the research rating of university departments.

Peer reviews may be an ideal, whereas in practice there are lots of problems. For example, it slows publication down and may prevent unusual, new work being published. Some reviewers might use it as an opportunity to prevent competing researchers from publishing work.

Some people doubt whether peer review can really prevent the publication of fraudulent research.

The advent of the internet means that a lot of research and academic comment is being published without official peer reviews than before, though systems are evolving on the internet where everyone really has a chance to offer their opinions and police the quality of research.

Types of Data

• Quantitative data is numerical data e.g. reaction time or number of mistakes. It represents how much or how long, how many there are of something. A tally of behavioral categories and closed questions in a questionnaire collect quantitative data.
• Qualitative data is virtually any type of information that can be observed and recorded that is not numerical in nature and can be in the form of written or verbal communication. Open questions in questionnaires and accounts from observational studies collect qualitative data.
• Primary data is first-hand data collected for the purpose of the investigation.
• Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.

Validity means how well a piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent.

Validity is whether the observed effect is genuine and represents what is actually out there in the world.

• Concurrent validity is the extent to which a psychological measure relates to an existing similar measure and obtains close results. For example, a new intelligence test compared to an established test.
• Face validity : does the test measure what it’s supposed to measure ‘on the face of it’. This is done by ‘eyeballing’ the measuring or by passing it to an expert to check.
• Ecological validit y is the extent to which findings from a research study can be generalized to other settings / real life.
• Temporal validity is the extent to which findings from a research study can be generalized to other historical times.

Features of Science

• Paradigm – A set of shared assumptions and agreed methods within a scientific discipline.
• Paradigm shift – The result of the scientific revolution: a significant change in the dominant unifying theory within a scientific discipline.
• Objectivity – When all sources of personal bias are minimised so not to distort or influence the research process.
• Empirical method – Scientific approaches that are based on the gathering of evidence through direct observation and experience.
• Replicability – The extent to which scientific procedures and findings can be repeated by other researchers.
• Falsifiability – The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue.

Statistical Testing

A significant result is one where there is a low probability that chance factors were responsible for any observed difference, correlation, or association in the variables tested.

If our test is significant, we can reject our null hypothesis and accept our alternative hypothesis.

If our test is not significant, we can accept our null hypothesis and reject our alternative hypothesis. A null hypothesis is a statement of no effect.

In Psychology, we use p < 0.05 (as it strikes a balance between making a type I and II error) but p < 0.01 is used in tests that could cause harm like introducing a new drug.

A type I error is when the null hypothesis is rejected when it should have been accepted (happens when a lenient significance level is used, an error of optimism).

A type II error is when the null hypothesis is accepted when it should have been rejected (happens when a stringent significance level is used, an error of pessimism).

Ethical Issues

• Informed consent is when participants are able to make an informed judgment about whether to take part. It causes them to guess the aims of the study and change their behavior.
• To deal with it, we can gain presumptive consent or ask them to formally indicate their agreement to participate but it may invalidate the purpose of the study and it is not guaranteed that the participants would understand.
• Deception should only be used when it is approved by an ethics committee, as it involves deliberately misleading or withholding information. Participants should be fully debriefed after the study but debriefing can’t turn the clock back.
• All participants should be informed at the beginning that they have the right to withdraw if they ever feel distressed or uncomfortable.
• It causes bias as the ones that stayed are obedient and some may not withdraw as they may have been given incentives or feel like they’re spoiling the study. Researchers can offer the right to withdraw data after participation.
• Participants should all have protection from harm . The researcher should avoid risks greater than those experienced in everyday life and they should stop the study if any harm is suspected. However, the harm may not be apparent at the time of the study.
• Confidentiality concerns the communication of personal information. The researchers should not record any names but use numbers or false names though it may not be possible as it is sometimes possible to work out who the researchers were.

Advanced research methods: Overview

• Reading scholarly research

This guide is a  general introduction  to scholarly inquiry and the use of advanced research methods, scroll down for definitions, examples and helpful resources.

Understanding Formal Research

Research is defined as the systematic investigation of a subject in order to find something new.

There are many different Advanced Research Methods which are used to conduct research . These methods include:

• Originating with a question or problem
• Starting with a clear articulation of a goal
• Creating a specific plan for proceeding
• Dividing the problem into smaller more manageable sub-problems
• Leading with the specific research problem, question, or hypothesis
• Explaining the assumptions the researcher is starting with
• The collection & interpretation of data
• Results in further questions and new tangents for further research

[Adapted from: Leedy, Paul D, Jeanne E. Ormrod, and Laura R. Johnson.  Practical Research: Planning and Design . Ninth edition, Pearson, 2010. ]

Qualitative versus Quantitative

Quantitative studies are best suited for answering questions that require 'count-able' data, quantities that are often easy to translate into a graph.

For example: "How many times an hour do 22 to 32 year olds check their cell-phone?"

Quantitative: think "describe" ... precise measurements - specific data variables - large sample size - randomly selected - Objective - generalisable to larger populations - Confirmatory : the researcher expects to prove or disprove a hypothesis - Output = Statistical report with clear categories of data

Quantitative Methods: surveys, questionnaires, experiments, analyzing existing data

Qualitative studies are best suited for investigating qualities of a specific issue, often human behaviours or motivations which cannot be easily transformed in to a graph. 

For example: "Why do 22 to 32 year olds prefer social media app A over social media app B." or “what motivates 22 to 32 year olds to stop using a social media platform or app?”

Qualitative: think "discover" ...open-ended responses - non-specific data - small sample size - not randomly selected - Subjective - situational or highly specific information - Exploratory : the researcher is looking for connections, patterns or themes  Output = narrative and contextual reporting or summaries of responses. 

Qualitative Methods: Interviews, case studies, action research, historical research, participant observer, phenomenology and philosophical / intellectual analysis

Mixed Method studies are best suited for highly complex questions: for example the number of times a specific  behaviour is observed, under what conditions.

The research question for a mixed methods study could be " Are people who check their phone more than average also more likely to discard social media apps?”

Sampling and Sample types

You must choose a sample that is likely to help answer your research question!

Sample types: the many diverse possible sources of data that researchers choose from.

Sampling: the process of choosing which source of data to focus on.

Example: Choosing between an online survey , or interviewing 22 to 32 year olds , to discover which social media apps they have used and then discarded, or used and kept, and what they think motivated those decisions? The researcher could also contact the App creators for any demographic or usage statistics that they are willing to provide.

Validity and Reliability

Validity means that your methods measure what you actually set out to measure and that the results you gain from your methods can be trusted.

Reliability means that a different researcher could reproduce your methods - using similar conditions/ same variables - and see the same results as you did or draw similar conclusions.

If you chose to use a  question with   Likert scale  responses on your survey about social media apps:

“How likely are you to Keep Social media app 'A3' on your mobile device?”

Answer options: 1. “very likely” 2. “somewhat likely” 3. Neutral    4. “somewhat unlikely” 5. “very unlikely”

How can you guarantee that the people taking the survey will interpret those categories in the way you meant them?  Perhaps you could change the question to something more concrete and less open to interpretation.

"How long did you use social media app 'A3' on your Mobile device before deleting it?"

A. 5 days or less.      B. 1 -2 weeks      C.   1 - 2 months        D. 3 to 6 months      E. 7 months or longer.

Definition of Likert Scale: "A method of ascribing quantitative value to qualitative data, to make it amenable to statistical analysis. A numerical value is assigned to each potential choice and a mean figure for all the responses is computed at the end of the evaluation or survey."   <Definition from: Business Dictionary >

VIDEO Adv Research Methods

Advanced Research Methods

Before you get started ⇒ think about the questions below, and keep them in mind as you work on your project.

• What type of new knowledge are you seeking?
• Will your research answer a clearly defined question or fill a specific information gap?
• Have you considered how each method might impact your results?
• Are you certain that the methods you have chosen are valid and reliable?

Remember: 

• Your method should be directly related to the nature of the answers you are seeking.
• Each research method requires unique measures of validity
• Tutorial: How to Read Scholarly Materials (2019 update)
• Video: How to Read Scholarly Materials
• Reading Scholarly Research - Camosun
• Conducting a Literature Review - UToronto
• Research methods and statistics in psychology
• Essentials of business research methods
• A concise introduction to mixed methods research

Examples & more resources

• RADAR Framework - Loyola Marymount University Rationale - Authority - Date - Accuracy - Relevance
• Writing a Research Proposal - UCLA
• "Mixed Methods" Chap 7 of Leedy & Ormond's Practical Research
• Sample Qualitative Study (UBC ~ Health Research)
• Sample Mixed Methods study (Undergrad UBC)

Evaluating sources

• Evaluating the Evidence:Evidence-Based Practice for Nursing (East Carolina University)
• Evidence Based Medicine 'Evidence Pyramid' (UToronto)

Resources from other colleges

• Research Questions - the good and the not so good. (Prezi)
• Key Elements of the Research Proposal
• Tips for Reading scholarly research (AET Guide)
• UCLA Guide to Advanced Research Methods
• The Four Types of Data
• NCRM Podcasts Podcasts from the National Centre for Research Methods (UK)
• Duke University Qualitative Methods Guide
• Duke University Research Data Management

BC Campus Open Textbooks

Find more Open Access Textbooks at:

• BC Open Campus
• Principles of Sociological Inquiry: Qualitative and Quantitative Methods
• Research Methods in Psychology
• Communication Theory

Ask a librarian

Need help with your research? Use AskAway, a chat-based library help service.

• Next: Reading scholarly research >>
• Last Updated: May 9, 2022 11:07 AM
• URL: https://camosun.libguides.com/advanced_research

Unit 3: Summarizing and Responding to Writing

13 Techniques for Identifying Main Ideas in a Summary

In order to write an effective summary, you need to be able to identify the main ideas. Below are three methods you might use when reading a text to identify the most important information.

  Technique 1: Underlining main ideas

• Read the article several times to get a good understanding of the information.
• Use a highlighting tool to identify ideas you think are important.
• Go back to the beginning of the article and read the highlighted ideas again. Make sure you understand what they mean.
• Paraphrase these highlighted ideas. Use these paraphrased ideas when you write your summary.

Technique 2: Grouping ideas

• Read the entire article. Pay attention to where the topic in the article seems to shift. Notice how groups of paragraphs seem to be about a similar topic.
• Insert a horizontal line between these different sections of the article.
• Divide a longer article into sections, or groups of paragraphs, to help you identify the various topics discussed in the article.
• Look at these large sections and write a short phrase that explains the topic of each section.
• The topics of these sections are usually the author’s main supporting points. This will help you determine which information is most important and should be included in the summary.
• Use your list of phrases you wrote to describe each section to write your summary.

Technique 3: Summary chart

• Read the entire article. Take notes in a grid for each paragraph or section of the article. Dividing the article into sections will allow you to summarize ideas from more than one paragraph together.
• Write main ideas in one column and supporting ideas in another column.
• Use your notes to write your summary. You might not use all the supporting ideas in your summary.
• NOTE: For a selective summary, summarize ONLY the information that is relevant to the topic of the assignment. Information that is not directly relevant to the topic can be omitted.

Partial example from Megan Gambino’s “How Technology Makes Us Better Social Beings”

Access Gambino’s full article

Adapted from: Dollahite, N.E. & Huan, J. (2012). SourceWork: Academic Writing for Success.

Technique 4: Use AI to Summarize a text

Use this technique for reading and understanding texts as a study technique.

• Read the entire text yourself. If needed, use a translator, but always make sure you read the text in English.
• Try to pick out the important points by yourself. Identify the author’s thesis.
• Then use an AI tool to summarize the text (e.g. QuillBot Summarize , WordTune ,  ChatGPT , etc.). Determine how long you want the summary to be (one paragraph? one page? A double-spaced page is about 250 words).
• Compare the summary with your own notes.

If you are asked to summarize a text for homework, you should try to write the first draft on your own. Your instructor will let you know how and if you can use AI to generate a summary to compare to your own version. Remember, an AI-generated summary might not include correct attribution and the format might not meet the assignment’s expectations (e.g. the first sentence might not include the elements outlined in the assignment).

Academic Writing I Copyright © by UW-Madison ESL Program is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License , except where otherwise noted.

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5.11: Summary of Research Methods

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Learning Outcomes

• Differentiate between the four kinds of research methods: surveys, field research, experiments, and secondary data analysis

Sociological research is a fairly complex process. As you can see, a lot goes into even a simple research design. There are many steps and much to consider when collecting data on human behavior, as well as in interpreting and analyzing data in order to form conclusive results. Sociologists use scientific methods for good reason. The scientific method provides a system of organization that helps researchers plan and conduct the study while ensuring that data and results are reliable, valid, and objective.

The many methods available to researchers—including experiments, surveys, field studies, and secondary data analysis—all come with advantages and disadvantages. The strength of a study can depend on the choice and implementation of the appropriate method of gathering research. Depending on the topic, a study might use a single method or a combination of methods. It is important to plan a research design before undertaking a study. The information gathered may in itself be surprising, and the study design should provide a solid framework in which to analyze predicted and unpredicted data.

Making Connections: When is Sharing Not Such a Good Idea?

Choosing a research methodology depends on a number of factors, including the purpose of the research and the audience for whom the research is intended. If we consider the type of research that might go into producing a government policy document on the effectiveness of safe injection sites for reducing the public health risks of intravenous drug use, we would expect public administrators to want “hard” (i.e., quantitative) evidence of high reliability to help them make a policy decision. The most reliable data would come from an experimental or quasi-experimental research model in which a control group can be compared with an experimental group using quantitative measures.

This approach has been used by researchers studying InSite in Vancouver (Marshall et al. 2011; Wood et al. 2006). InSite is a supervised safe-injection site where heroin addicts and other intravenous drug users can go to inject drugs in a safe, clean environment. Clean needles are provided and health care professionals are on hand to intervene in the case of overdose or other medical emergency. It is a controversial program both because heroin use is against the law (the facility operates through a federal ministerial exemption) and because the heroin users are not obliged to quit using or seek therapy. To assess the effectiveness of the program, researchers compared the risky usage of drugs in populations before and after the opening of the facility and geographically near and distant to the facility. The results from the studies have shown that InSite has reduced both deaths from overdose and risky behaviours, such as the sharing of needles, without increasing the levels of crime associated with drug use and addiction.

On the other hand, if the research question is more exploratory (for example, trying to discern the reasons why individuals in the crack smoking subculture engage in the risky activity of sharing pipes), the more nuanced approach of fieldwork is more appropriate. The research would need to focus on the subcultural context, rituals, and meaning of sharing pipes, and why these phenomena override known health concerns. Graduate student Andrew Ivsins at the University of Victoria studied the practice of sharing pipes among 13 habitual users of crack cocaine in Victoria, B.C. (Ivsins 2010). He met crack smokers in their typical setting downtown and used an unstructured interview method to try to draw out the informal norms that lead to sharing pipes. One factor he discovered was the bond that formed between friends or intimate partners when they shared a pipe. He also discovered that there was an elaborate subcultural etiquette of pipe use that revolved around the benefit of getting the crack resin smokers left behind. Both of these motives tended to outweigh the recognized health risks of sharing pipes (such as hepatitis) in the decision making of the users. This type of research was valuable in illuminating the unknown subcultural norms of crack use that could still come into play in a harm reduction strategy such as distributing safe crack kits to addicts.

Watch this video to review some of the key methods used in conducting sociological research.

An interactive or media element has been excluded from this version of the text. You can view it online here: http://pb.libretexts.org/its/?p=104

https://assessments.lumenlearning.co...essments/13278

• Research Methods. Authored by : OpenStax CNX. Located at : http://cnx.org/contents/02040312-72c8-441e-a685-20e9333f3e1d/Introduction_to_Sociology_2e . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]
• Making Connections. Authored by : William Little. Provided by : BC Open Textbooks. Located at : https://opentextbc.ca/introductiontosociology/ . License : CC BY: Attribution
• Sociological Research Methods. Provided by : CrashCourse. Located at : https://www.youtube.com/watch?v=QwhK-iEyXYA&list=PL8dPuuaLjXtMJ-AfB_7J1538YKWkZAnGA&index=5 . License : Other . License Terms : Standard YouTube License

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Home » Research Methods – Types, Examples and Guide

Research Methods – Types, Examples and Guide

Table of Contents

Research Methods

Definition:

Research Methods refer to the techniques, procedures, and processes used by researchers to collect , analyze, and interpret data in order to answer research questions or test hypotheses. The methods used in research can vary depending on the research questions, the type of data that is being collected, and the research design.

Types of Research Methods

Types of Research Methods are as follows:

Qualitative research Method

Qualitative research methods are used to collect and analyze non-numerical data. This type of research is useful when the objective is to explore the meaning of phenomena, understand the experiences of individuals, or gain insights into complex social processes. Qualitative research methods include interviews, focus groups, ethnography, and content analysis.

Quantitative Research Method

Quantitative research methods are used to collect and analyze numerical data. This type of research is useful when the objective is to test a hypothesis, determine cause-and-effect relationships, and measure the prevalence of certain phenomena. Quantitative research methods include surveys, experiments, and secondary data analysis.

Mixed Method Research

Mixed Method Research refers to the combination of both qualitative and quantitative research methods in a single study. This approach aims to overcome the limitations of each individual method and to provide a more comprehensive understanding of the research topic. This approach allows researchers to gather both quantitative data, which is often used to test hypotheses and make generalizations about a population, and qualitative data, which provides a more in-depth understanding of the experiences and perspectives of individuals.

Key Differences Between Research Methods

The following Table shows the key differences between Quantitative, Qualitative and Mixed Research Methods

Examples of Research Methods

Examples of Research Methods are as follows:

Qualitative Research Example:

A researcher wants to study the experience of cancer patients during their treatment. They conduct in-depth interviews with patients to gather data on their emotional state, coping mechanisms, and support systems.

Quantitative Research Example:

A company wants to determine the effectiveness of a new advertisement campaign. They survey a large group of people, asking them to rate their awareness of the product and their likelihood of purchasing it.

Mixed Research Example:

A university wants to evaluate the effectiveness of a new teaching method in improving student performance. They collect both quantitative data (such as test scores) and qualitative data (such as feedback from students and teachers) to get a complete picture of the impact of the new method.

Applications of Research Methods

Research methods are used in various fields to investigate, analyze, and answer research questions. Here are some examples of how research methods are applied in different fields:

• Psychology : Research methods are widely used in psychology to study human behavior, emotions, and mental processes. For example, researchers may use experiments, surveys, and observational studies to understand how people behave in different situations, how they respond to different stimuli, and how their brains process information.
• Sociology : Sociologists use research methods to study social phenomena, such as social inequality, social change, and social relationships. Researchers may use surveys, interviews, and observational studies to collect data on social attitudes, beliefs, and behaviors.
• Medicine : Research methods are essential in medical research to study diseases, test new treatments, and evaluate their effectiveness. Researchers may use clinical trials, case studies, and laboratory experiments to collect data on the efficacy and safety of different medical treatments.
• Education : Research methods are used in education to understand how students learn, how teachers teach, and how educational policies affect student outcomes. Researchers may use surveys, experiments, and observational studies to collect data on student performance, teacher effectiveness, and educational programs.
• Business : Research methods are used in business to understand consumer behavior, market trends, and business strategies. Researchers may use surveys, focus groups, and observational studies to collect data on consumer preferences, market trends, and industry competition.
• Environmental science : Research methods are used in environmental science to study the natural world and its ecosystems. Researchers may use field studies, laboratory experiments, and observational studies to collect data on environmental factors, such as air and water quality, and the impact of human activities on the environment.
• Political science : Research methods are used in political science to study political systems, institutions, and behavior. Researchers may use surveys, experiments, and observational studies to collect data on political attitudes, voting behavior, and the impact of policies on society.

Purpose of Research Methods

Research methods serve several purposes, including:

• Identify research problems: Research methods are used to identify research problems or questions that need to be addressed through empirical investigation.
• Develop hypotheses: Research methods help researchers develop hypotheses, which are tentative explanations for the observed phenomenon or relationship.
• Collect data: Research methods enable researchers to collect data in a systematic and objective way, which is necessary to test hypotheses and draw meaningful conclusions.
• Analyze data: Research methods provide tools and techniques for analyzing data, such as statistical analysis, content analysis, and discourse analysis.
• Test hypotheses: Research methods allow researchers to test hypotheses by examining the relationships between variables in a systematic and controlled manner.
• Draw conclusions : Research methods facilitate the drawing of conclusions based on empirical evidence and help researchers make generalizations about a population based on their sample data.
• Enhance understanding: Research methods contribute to the development of knowledge and enhance our understanding of various phenomena and relationships, which can inform policy, practice, and theory.

When to Use Research Methods

Research methods are used when you need to gather information or data to answer a question or to gain insights into a particular phenomenon.

Here are some situations when research methods may be appropriate:

• To investigate a problem : Research methods can be used to investigate a problem or a research question in a particular field. This can help in identifying the root cause of the problem and developing solutions.
• To gather data: Research methods can be used to collect data on a particular subject. This can be done through surveys, interviews, observations, experiments, and more.
• To evaluate programs : Research methods can be used to evaluate the effectiveness of a program, intervention, or policy. This can help in determining whether the program is meeting its goals and objectives.
• To explore new areas : Research methods can be used to explore new areas of inquiry or to test new hypotheses. This can help in advancing knowledge in a particular field.
• To make informed decisions : Research methods can be used to gather information and data to support informed decision-making. This can be useful in various fields such as healthcare, business, and education.

Advantages of Research Methods

Research methods provide several advantages, including:

• Objectivity : Research methods enable researchers to gather data in a systematic and objective manner, minimizing personal biases and subjectivity. This leads to more reliable and valid results.
• Replicability : A key advantage of research methods is that they allow for replication of studies by other researchers. This helps to confirm the validity of the findings and ensures that the results are not specific to the particular research team.
• Generalizability : Research methods enable researchers to gather data from a representative sample of the population, allowing for generalizability of the findings to a larger population. This increases the external validity of the research.
• Precision : Research methods enable researchers to gather data using standardized procedures, ensuring that the data is accurate and precise. This allows researchers to make accurate predictions and draw meaningful conclusions.
• Efficiency : Research methods enable researchers to gather data efficiently, saving time and resources. This is especially important when studying large populations or complex phenomena.
• Innovation : Research methods enable researchers to develop new techniques and tools for data collection and analysis, leading to innovation and advancement in the field.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Funding Principles and Priorities

Research funding principles.

• We prioritize research that advances the Society’s strategic plan, with a focus on stopping the disease in its tracks, restoring what has been lost, and ending MS forever through a cure for all forms of MS.
• We maintain a diverse research portfolio that includes short- and long-term investments, balances risks and rewards, and funds research globally.
• We balance investments in research initiated by individual investigators with investments in Society-directed research, all focused on bridging knowledge gaps, seizing opportunities and addressing research priorities.
• We promote synergies between researchers in diverse disciplines, and develop strategic partnerships to accelerate progress.
• We invest in all types of research including: laboratory models, human studies, population-based approaches, and data-intensive investigations that leverage both researcher and patient reported outcomes.
• We support the full spectrum of basic, translational, and clinical research. We also strive to break down barriers to commercial development to ensure that new treatments and wellness approaches are available as quickly as possible.
• We use independent experts to ensure that each research proposal receives a fair, competent and objective assessment of its scientific merit, relevance to MS, relevance to the MS community, and alignment with the Society’s research priorities.
• We attract and support new investigators to foster a robust future workforce focused on finding solutions for MS.
• We expect Society-funded researchers to adhere to rigorous experimental methods and reporting practices.
• We believe that sharing data and resources enhances research and speeds scientific discovery. Data and resources developed through Society-sponsored research will be made available to other researchers after publication in an expeditious manner.

Research Priorities: Pathways to Multiple Sclerosis Cures

• Biomarkers/Screening tools that identify MS in its earliest stages with enough confidence to initiate interventions
• Biological processes driving early MS compared to later stages of disease
• Understanding the heterogeneity of pre-symptom phases of MS in diverse populations
• Biomarkers of prognosis and therapeutic response in individuals
• Pathways driving non-lesional pathology/neurodegeneration involved in progressive stages of disease
• New molecular targets and therapeutic approaches for neuroprotection
• Interventions that target the earliest disease-causing pathways
• Understanding the roles of aging, sex, ethnicity, race, and genetics in MS pathology and response to therapies
• Physiological mechanisms, molecular targets and therapeutic approaches to promote myelin and neural repair
• Clear understanding of the functional heterogeneity of cells involved in repair
• Better physiologic, fluid biomarkers, imaging, and functional measures for earlier readouts of remyelination, reversal of tissue damage, and functional recovery
• Understanding of the roles of aging, sex, ethnicity, race, and genetics in tissue restoration
• Better animal models to study repair
• Understanding how rehabilitation and exercise impact the central nervous system and the extent that they can facilitate CNS repair processes
• Sensitive, valid, and clinically meaningful measures of disability and tools that establish measurable relationships between physiologic findings and meaningful recovery of function
• Sufficiently powered intervention studies that incorporate endpoints focused on type and dose parameters, targeting (including, but not limited to) cognitive or motor rehabilitation, resilience, diet, exercise, electrical stimulation, pain, fatigue, depression, anxiety, and bladder impairment
• Outcome measures, biologic, behavioral or technology driven that can be used to individually tailor interventions
• Innovative approaches that translate research findings to clinical practice and daily disease management
• Identify all relevant risk factors for MS, windows of risk, and determine whether any risk factor is necessary and sufficient to cause disease
• Understanding the contributions of genetic/epigenetic factors and environmental interactions to MS risk
• Understanding the roles of sex, ethnicity, and race with MS risk
• Understanding the early pathological pathways/events that lead to the initiation of MS
• Screening tools that identify MS in its earliest stages with enough confidence to trigger intervention
• Discovery of biomarkers that detect early MS before symptoms appear
• Interventions that target the earliest disease-causing pathways and the ability to determine which treatment will work for which person