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Research Methodologies: Research Instruments

• Research Methodology Basics
• Research Instruments
• Types of Research Methodologies

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Types of Research Instruments

A research instrument is a tool you will use to help you collect, measure and analyze the data you use as part of your research.  The choice of research instrument will usually be yours to make as the researcher and will be whichever best suits your methodology. 

There are many different research instruments you can use in collecting data for your research:

• Interviews  (either as a group or one-on-one). You can carry out interviews in many different ways. For example, your interview can be structured, semi-structured, or unstructured. The difference between them is how formal the set of questions is that is asked of the interviewee. In a group interview, you may choose to ask the interviewees to give you their opinions or perceptions on certain topics.
• Surveys  (online or in-person). In survey research, you are posing questions in which you ask for a response from the person taking the survey. You may wish to have either free-answer questions such as essay style questions, or you may wish to use closed questions such as multiple choice. You may even wish to make the survey a mixture of both.
• Focus Groups.  Similar to the group interview above, you may wish to ask a focus group to discuss a particular topic or opinion while you make a note of the answers given.
• Observations.  This is a good research instrument to use if you are looking into human behaviors. Different ways of researching this include studying the spontaneous behavior of participants in their everyday life, or something more structured. A structured observation is research conducted at a set time and place where researchers observe behavior as planned and agreed upon with participants.

These are the most common ways of carrying out research, but it is really dependent on your needs as a researcher and what approach you think is best to take. It is also possible to combine a number of research instruments if this is necessary and appropriate in answering your research problem.

Data Collection

How to Collect Data for Your Research   This article covers different ways of collecting data in preparation for writing a thesis.

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• Last Updated: Sep 27, 2022 12:28 PM
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Research Instruments

• Resources for Identifying Instruments
• Assessing Instruments
• Obtaining the Full Instrument
• Getting Help

What are Research Instruments?

A research instrument is a tool used to collect, measure, and analyze data related to  your subject.

Research instruments can  be tests , surveys , scales ,  questionnaires , or even checklists .

To assure the strength of your study, it is important to use previously validated instruments!

Getting Started

Already know the full name of the instrument you're looking for? 

• Start here!

Finding a research instrument can be very time-consuming!

This process involves three concrete steps:

It is common that sources will not provide the full instrument, but they will provide a citation with the publisher. In some cases, you may have to contact the publisher to obtain the full text.

Research Tip :  Talk to your departmental faculty. Many of them have expertise in working with research instruments and can help you with this process.

• Next: Identifying a Research Instrument >>
• Last Updated: Aug 27, 2023 9:34 AM
• URL: https://guides.library.duq.edu/researchinstruments

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What is a Research Instrument?

• By DiscoverPhDs
• October 9, 2020

The term research instrument refers to any tool that you may use to collect or obtain data, measure data and analyse data that is relevant to the subject of your research.

Research instruments are often used in the fields of social sciences and health sciences. These tools can also be found within education that relates to patients, staff, teachers and students.

The format of a research instrument may consist of questionnaires, surveys, interviews, checklists or simple tests. The choice of which specific research instrument tool to use will be decided on the by the researcher. It will also be strongly related to the actual methods that will be used in the specific study.

What Makes a Good Research Instrument?

A good research instrument is one that has been validated and has proven reliability. It should be one that can collect data in a way that’s appropriate to the research question being asked.

The research instrument must be able to assist in answering the research aims , objectives and research questions, as well as prove or disprove the hypothesis of the study.

It should not have any bias in the way that data is collect and it should be clear as to how the research instrument should be used appropriately.

What are the Different Types of Interview Research Instruments?

The general format of an interview is where the interviewer asks the interviewee to answer a set of questions which are normally asked and answered verbally. There are several different types of interview research instruments that may exist.

• A structural interview may be used in which there are a specific number of questions that are formally asked of the interviewee and their responses recorded using a systematic and standard methodology.
• An unstructured interview on the other hand may still be based on the same general theme of questions but here the person asking the questions (the interviewer) may change the order the questions are asked in and the specific way in which they’re asked.
• A focus interview is one in which the interviewer will adapt their line or content of questioning based on the responses from the interviewee.
• A focus group interview is one in which a group of volunteers or interviewees are asked questions to understand their opinion or thoughts on a specific subject.
• A non-directive interview is one in which there are no specific questions agreed upon but instead the format is open-ended and more reactionary in the discussion between interviewer and interviewee.

What are the Different Types of Observation Research Instruments?

An observation research instrument is one in which a researcher makes observations and records of the behaviour of individuals. There are several different types.

Structured observations occur when the study is performed at a predetermined location and time, in which the volunteers or study participants are observed used standardised methods.

Naturalistic observations are focused on volunteers or participants being in more natural environments in which their reactions and behaviour are also more natural or spontaneous.

A participant observation occurs when the person conducting the research actively becomes part of the group of volunteers or participants that he or she is researching.

Final Comments

The types of research instruments will depend on the format of the research study being performed: qualitative, quantitative or a mixed methodology. You may for example utilise questionnaires when a study is more qualitative or use a scoring scale in more quantitative studies.

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Research Instruments (Tests & Measures)

How to use this guide, what are research instruments.

• Locating Research Instruments
• CINAHL (Nursing & Allied Health)
• PsycInfo (Psychology)
• ERIC (Education)

Research Librarian

For more help on this topic, please contact our Research Help Desk: [email protected] or 781-768-7303. Stay up-to-date on our current hours . Note: all hours are EST.

This Guide was created by Carolyn Swidrak (retired).

This guide will help you discover resources related to research instruments. This includes information about various measurement tools, including reviews, how to obtain a copy, articles about studies that use various instruments, and more.

If you are a doctoral student you may need to find a research instrument for your own use. Other students may need to find information about the use of research instruments. A good way to discover research instruments that may be relevant to your own research is by reading the methods section in research articles.

This guide provides information on how to find information about research instruments

• using credible websites, or

Note: While the Regis Library can help you find information about tests and measures, we cannot obtain research instruments for you.

Research instruments are devices used to measure or collect data on various variables being studied. Examples include measurement tools such as:

• questionnaires
• observation schedules
• interview schedules
• Next: Locating Research Instruments >>
• Last Updated: Feb 29, 2024 3:35 PM
• URL: https://libguides.regiscollege.edu/research_instruments

Penn State University Libraries

Educational and psychological instruments.

• Welcome and Finding a Few Questions Fast
• Identifying More Instruments for Your Research Project
• Reliability, Validity, and Ethics
• Getting Copies of Instruments
• Penn State Instrument Collections
• Instrument Design and Assistance

Contact the librarian at your campus for more help!

University Park / World Campus: Ellysa Cahoy ([email protected] or 814-865-9696)

Harrisburg / University Park / World Campus: Bernadette Lear ([email protected] or 717-948-6360)

Librarians at additional locations

Introduction

There is a difference between finding a few questions quickly for a class assignment, versus identifying the BEST instruments for your thesis, dissertation, or research project. If you are doing deep research to make an impact on your profession, or you are hoping to publish your results, it's important to know which instruments are widely used and have been peer-reviewed by other researchers. Below are some resources.

Exploring Tests That Are Commonly Used and Peer Reviewed

• Mental Measurements Yearbook with Tests in Print This link opens in a new window Provides critical reviews on the construction, use, and validity of commercially available tests published in English. more... less... Mental Measurements Yearbook provides access to full-text reviews of over 3000 testing instruments for psychology, education, business, and leadership. Also included in this database is Tests in Print, a bibliography providing information on accessing known commercially available English-language tests currently in print.

Identifying Additional Instruments (if needed)

• PsycTESTS (formerly listed as APA PsycTests®) This link opens in a new window The library's best database for Psychology tests/measures. Includes some Education items as well. more... less... PsycTESTS is a research database that provides access to psychological tests, measures, scales, surveys, and other assessments as well as descriptive information about the test and its development and administration.
• Database of Psychological Tests, Instruments, Rating Scales, and Measures A database of tests published within books, compiled by Mark Stover at California State University, Northridge.
• ETS Test Link ETS, the same company that developed the SAT and the GRE, has one of the largest libraries of testing instruments in the world. Its catalog, TestLink, lists more than 25,000 tests that you can purchase from ETS or obtain elsewhere.
• Health & Psychosocial Instruments - HAPI (PSU access will expire on June 30, 2024.) This link opens in a new window Identifies health-related instruments in journal articles. Though focused on medicine and nursing, some psychological tests are included. more... less... Health and Psychosocial Instruments features material on unpublished information-gathering tools for clinicians that are discussed in journal articles, such as questionnaires, interview schedules, tests, checklists, rating and other scales, coding schemes, and projective techniques. The majority of tools are in medical and nursing areas such pain measurement, quality of life assessment, and drug efficacy evaluation. However, HaPI also includes tests used in medically related disciplines such as psychology, social work, occupational therapy, physical therapy, and speech & hearing therapy. For more information on the HaPI database, please click here.
• ERIC (ProQuest) This link opens in a new window Contains Education-related articles, dissertations, and other research. To focus on items that may contain instruments, use the "Advanced Search." Under "Document Type," choose "160: Tests/Questionnaires." more... less... ERIC (Educational Resources Information Center) is the major database for education literature, sponsored by the U.S. Department. of Education. The same database content is available on many platforms.
• Catalog (Penn State University Libraries catalog) This link opens in a new window To find books on testing, add words such as "assessment," "instruments," "measurement," "research," "scaling," or "testing" to your search. more... less... This is the online catalog of materials owned by Penn State Libraries. All formats (books, journals, audiovisuals, maps, recordings, etc.) are included. Circulation status for individual items is also provided. Coverage: Presently contains about 7 million records. Updates: Continuous up-to-the-minute as new records are added.
• Google Book Search Searches the full-text of millions of books.

Search Tips

Finding the best instruments for your project can be challenging. Here are some general tips:

• For instance, assess* will find books and articles that have “assessment” or “assessing” in the title
• For instance, if you’d like to measure problem-solving ability in 16 to 21-year olds, try both "adolescents," "high school," and related words. Also, you can try "intelligence" (a broader term) instead of “problem-solving ability”
• Abbreviations, popular names, and “official” or spelled-out names of instruments
• Names of all authors who were involved in the development of the instruments
• Corporations that published the instruments, or universities where the instruments' authors work(ed)
• Alternative versions and new editions of the instruments
• On the internet, many free versions of tests are edited or shortened -- they are not the complete, original instruments that you would expected to use professionally. 
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• Last Updated: Jan 5, 2024 5:10 PM
• URL: https://guides.libraries.psu.edu/edpsychinstruments

Tests, Instruments & Measurement Tools

Researching a tool, accessing a tool, permissions for a tool.

What are Tests or Instruments? How are they used for research? And how can you find them in order to use them for your own research?

Test and Instruments are types of Measurement tools, and they are used by researchers and practitioners to aid in the assessment or evaluation of research participants, clients, or patients. The tools are used to measure or collect data on a variety of variables, depending on the research questions. Measurement tools include scales, indexes, surveys, interviews, observations, and more.

Below are steps to get you started with finding, obtaining, and using measurement tools in your own research. This list is by no means exhaustive, and should you have more specific questions, you will want to reach out to your liaison librarian. Not sure who that is? Use the link below to find out which librarian works with your program.

• Who's my Librarian?

*This guide has reused material, with permission, from the University of Washington, Health Sciences Library Measurements Tools/Research Instruments guide: https://guides.lib.uw.edu/hsl/measure, maintained by Ann Madhavan.

Researching and Selecting Measurement Tools

• Databases: Lavery Library has a number of databases that specialize in measurement tools. In the Databases section of this guide, you will be introduced to these resources and see example searches.
• Books: Lavery Library has books in our Collection where you can find reviews of measurement tools, and also full versions of measurement tools. In the Books section of this guide, you will see a list of these titles, and examples of what types of tools are available from these resources.
• K-12 Resource Center: The K-12 Resource Center has a selection of Formal Assessments available, these can be checked out for one week. In the K-12 Resource Center section you will learn how to search for these educational test kits.
• Learn more about where you can search for measurement tools.

Obtaining and Accessing Measurement Tools

There's no one way to retrieve a measurement tool, sometimes the Library will have full versions available in our collection (in-print or online); sometimes you might need to request a copy through Interlibrary Loan, and sometimes using Google (gasp) is the best method.

• Online: Sometimes tools will be available as an appendix to an article or dissertation, printed in a book with other tools, or even available freely online. Having the creator and title of a measurement tool in hand before searching for full versions will always make it easier.
• Interlibrary Loan: You can always submit an ILL request for a measurement tool, and we will do our best to try and find a copy for you. Sometimes we need extra information from you to complete these requests, so make sure you respond promptly to emails asking for additional information.
• K-12 Resource Center: Look for Formal Assessment kits in the K-12 Resource Center's collection.
• Learn how to find full versions of measurement tools.

Permissions for Measurement Tools

Similar to how you would cite someone when referring to their research in your own, there are typically permissions that need to be given before using any measurement tool for your own purposes.

• Copyright and obtaining permissions
• Learn about how to use a measurement tool ethically.
• Next: Researching a tool >>
• Last Updated: Jan 4, 2024 3:43 PM
• URL: https://libguides.sjf.edu/tests

• UVM Libraries
• UVM Libraries Research Guides
• Dana Health Sciences Library

Research Instruments: Surveys, Questionnaires, and other Measurement Tools

• Descriptions and Search Tips
• Last Updated: Apr 4, 2024 1:48 PM
• URL: https://researchguides.uvm.edu/researchinstruments

Biokinesiology & Physical Therapy

• Books & Websites
• Journal Literature

About Research Instruments

Databases for finding research instruments, find research instruments in instrument databases, find research instruments in literature databases.

• Mobile Resources: Drug Info
• Mobile Resources: Consumer Health
• Mobile Resources: Books & Articles
• AMA Style (11th ed): Citing Your Sources
• Dissertations/Theses/Archives
• Transformative Agreements / Read and Publish
• Health Statistics and Data
• Professional Associations/Resources
• Library Instruction and Tutorials
• Research instruments are measurement tools, such as questionnaires, scales, and surveys, that researchers use to measure variables in research studies.  
• In most cases, it is better to use a previously validated instrument rather than create one from scratch.
• Always evaluate instruments for relevancy, validity, and reliability. 
• Many older yet relevant, valid and reliable instruments are still popular today. It is time consuming and costly to validate instruments, so re-using instruments is common and helpful for connecting your study with an existing body of research.
• Although you can conduct an internet search to find research instruments on publisher and organization websites, library databases are usually the best resources for identifying relevant, validated and reliable research instruments. 
• Locating instruments takes time and requires you to follow multiple references until you reach the source. 
• Databases provide information about instruments, but they do not provide access to the instruments themselves. 
• In most cases, to access and use the actual instruments, you must contact the author or purchase the instrument from the publisher. 
• In many cases, you will have to pay a fee to use the instrument.
• Even if the full instrument is freely available, you should contact the owner for permission to use and for any instructions and training necessary to use the instrument properly. 
• CINAHL Complete This link opens in a new window Most comprehensive database of full-text for nursing & allied health journals from 1937 to present. Includes access to scholarly journal articles, dissertations, magazines, pamphlets, evidence-based care sheets, books, and research instruments.
• Health and Psychosocial Instruments (HAPI) This link opens in a new window Locate measurement instruments such as surveys, questionnaires, tests, surveys, coding schemes, checklists, rating scales, vignettes, etc. Scope includes medicine, nursing, public health , psychology, social work, communication, sociology, etc.
• Mental Measurements Yearbook (MMY) This link opens in a new window Use MMY to find REVIEWS of testing instruments. Actual test instruments are NOT provided. Most reviews discuss validity and reliability of tool. To purchase or obtain the actual test materials, you will need to contact the test publisher(s).
• PsycINFO This link opens in a new window Abstract and citation database of scholarly literature in psychological, social, behavioral, and health sciences. Includes journal articles, books, reports, theses, and dissertations from 1806 to present.
• PsycTESTS This link opens in a new window PsycTESTS is a research database that provides access to psychological tests, measures, scales, surveys, and other assessments as well as descriptive information about the test and its development. Records also discuss reliability and validity of the tool. Some records include full-text of the test.

• Rehabilitation Measures Database Database of instruments to screen patients and monitor their progress. Developed by Rehabilitation Institute of Chicago, Center for Rehabilitation Outcomes Research, Northwestern University Feinberg School of Medicine Department of Medical Social Sciences Informatics group.

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• Last Updated: Apr 2, 2024 4:20 PM
• URL: https://libguides.usc.edu/healthsciences/pt

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What, what for and how? Developing measurement instruments in epidemiology

Michael reichenheim.

I Universidade do Estado do Rio de Janeiro, Instituto de Medicina Social Hésio Cordeiro, Departamento de Epidemiologia, Rio de Janeiro RJ , Brasil, Universidade do Estado do Rio de Janeiro. Instituto de Medicina Social Hésio Cordeiro. Departamento de Epidemiologia. Rio de Janeiro, RJ, Brasil

João Luiz Bastos

II Universidade Federal de Santa Catarina, Departamento de Saúde Pública, Florianópolis SC , Brasil, Universidade Federal de Santa Catarina. Departamento de Saúde Pública. Florianópolis, SC, Brasil

Authors’ Contribution: Conception and planning of the study: MER, JLB. Writing of the manuscript: MER, JLB. Final approval: MER, JLB.

The development and cross-cultural adaptation of measurement instruments have received less attention in methodological discussions, even though it is essential for epidemiological research. At the same time, the quality of epidemiological measurements is often below ideal standards for the construction of solid knowledge on the health-disease process. The scarcity of systematizations in the field about what, what for, and how to adequately measure intangible constructs contributes to this scenario. In this review, we propose a procedural model divided into phases and stages aimed at measuring constructs at acceptable levels of validity, reliability, and comparability. Underlying our proposal is the idea that not only some but several connected studies should be conducted to obtain appropriate measurement instruments. Implementing the model may contribute to broadening the interest in measurement instruments and, especially, addressing key epidemiological problems.

INTRODUCTION

Considered one of the pillars of public health, epidemiology is chiefly concerned with the frequency, distribution, and determinants or causes of health events in human populations 1 . By emphasizing these aspects, the measurement of related events — either dimensions of the health-disease process or factors that are causally related to it — is key in the development of research in the field. Epidemiologists employ considerable efforts to measure specific health-disease conditions, assess characteristics (of person, place, and time) that allow establishing comparisons and assessing variability, as well as address the processes underlying their occurrence in a given population domain 2 . Although there are exceptions, the epidemiological measurement of these processes and factors is predominantly quantitative, which allows the subsequent statistical analysis of their patterns of association in order to assess the health event and intervene upon it.

The measurement process is not a trivial activity. Rather, it is of considerable complexity and imposes important challenges. This process implies expressive conceptual rigor, in addition to the other issues discussed in greater detail further on in this article 6 , 7 . It is impossible to measure —within acceptable levels of validity and reliability— a phenomenon of epidemiological interest predicated on an ambiguous definition, be it among researchers or even in the population whose health-disease conditions are the object of study. The use of instruments with good psychometric properties is equally important to measure aspects of interest in a given population 6 . In their absence, not only validity and reliability of the measurements become questionable, but it is also more challenging to compare data across studies on the same health event 8 , limiting the proper construction of scientific knowledge on the research object. Knowledge is often established by the systematic accumulation and contrasting of research results that, by assumption, must be amenable to confrontation.

Albeit essential to any epidemiological research, measurement has received less emphasis in the methodological discussions pervading the field. While issues related to study design, potential biases, and statistical techniques often guide epidemiology courses and debates, relatively less space has been allocated to rigors and processes related to measurement. In this scenario, the need for a comprehensive assessment is clear, which includes the stages of theoretical construction and formal psychometric tests employed in the development or adaptation processes of measurement instruments. The authors of this paper were unable to find a discussion about the differences between what, what for, and how a measurement instrument should be developed—including the evaluation of its internal and external structures. The aim of this review is, therefore, to offer a set of guiding principles on possible paths to be followed for the development or cross-cultural adaptation of measurement instruments used in epidemiological studies. By proposing a procedural model comprised of sequential phases and stages, our expectation is that this study will contribute to improve the quality of knowledge production in the health field. We also hope that it will improve academic training in epidemiology. Encouraging the acquisition of information from the specific area of measurement can help students and researchers develop skills and competencies necessary to adhere to the proposal.

Our stance is eminently indicative, though, as the literature on the subject matter is complex and vast. We chose to focus on only a few points with immediate relevance and applicability to epidemiological practice. We used only widely recommended bibliographic references; some specific publications are also cited as suggestions to guide particular processes or decisions. We hope that this introduction will encourage broader readings on the covered topics.

RESEARCH SCENARIOS AND INSTRUMENT DEVELOPMENT OR ADAPTATION

Epidemiological studies require well-defined and socially relevant research questions, which, in turn, demand reliable and accurate measurements of the phenomena and concepts needed to answer them 8 . Berry et al. 9 discuss three perspectives that are particularly relevant for the issues at hand.

From the absolutist perspective, sociocultural nuances are disregarded in the interpretation of health-related events, thus assuming the possibility of unrestricted comparisons between quantitative measurements carried out across populations. In this case, a single measurement instrument could be widely employed in different populations, and results could be directly compared to consolidate scientific knowledge about the object of interest.

The relativist approach lies in a diametrically opposite position. Accordingly, sociocultural specificities are placed at the forefront, so that a different measurement instrument should be used for each population. This approach denies the possibility of quantitatively comparing measurements taken in socioculturally differentiated populations, since instruments would not be equivalent to each other, and the only way to contrast them would be through qualitative analyses.

The universalist perspective assumes an intermediate position, implying both the quantitative measurement of investigated phenomena and the possibility of comparisons between populations. This stance recognizes sociocultural nuances and the need to acknowledge them. If there is similarity in the way events are interpreted among different populations, it would be possible to pursue a so-called “universal” instrument, albeit adapted to each particular situation. According to this view, cross-cultural adaptation would ensure equivalence across different versions of the same instrument 10 . Its application would allow socio-culturally distinct populations to be quantitatively compared, based on equivalent measures of the same problem of interest.

The universalist approach 3 , 6 , 11 , 12 implies three possible scenarios, which must be evaluated and identified by the investigator when selecting the research instrument to be used in the study:

• there is an established and adapted instrument for use in different populations, including the population of interest (Scenario 1);
• an instrument is available, but it requires additional refinement, given its limited applicability to the population of interest, either because it requires complementary psychometric assessments, or because it still needs to be cross-culturally adapted (Scenario 2); or
• no instrument is available and it is necessary to develop an entirely new one (Scenario 3).

In Scenario 2, cross-cultural adaptation studies are often needed, in which the concept of equivalence is a guiding principle 10 . Equivalence is usually unfolded in conceptual, item, semantic, operational, and measurement equivalence: all need to be assessed to consider an instrument as fully adapted. In Scenario 3, the researcher should adjourn the original research initiative and develop completely original instruments 13 . In this case, undertaking a parallel research program to develop an instrument capable of measuring the parameters of interest is necessary. This is crucial, since conducting the research without good measurement instruments puts the whole project at risk; it decreases the chances of contributing to the advancement of knowledge or of attending to a particular health need, becoming, thus, ethically reprehensible. Most of the time, epidemiological studies are conducted within the limits of Scenarios 2 and 3, the first being the most common in the Brazilian research context.

An important implication of working within these scenarios is the need to know, in detail, the state of the art of the available instruments. Such knowledge is essential for adapting, refining, or developing measurement tools.

PHASES OF DEVELOPMENT OR ADAPTATION OF INSTRUMENTS

Different procedural stages need to be followed whether the objective is to develop a new instrument or cross-culturally adapt an existing one. The Figure shows one proposed procedural model. The first phase elaborates and details the construct to be measured, which involves several steps: specifying, preparing, and refining the items regarding their empirical and semantic contents; detailing operational aspects, inter alia, the scenarios under which the instrument will be administered; and implementing several pre-tests to refine some aspects, such as item wording and their understanding by the target population. Provisionally called “prototypical” because it involves assembling one or more sketches of the instrument (i.e., prototypes or preliminary versions) to be subsequently tested, this first phase of the process is essential for achieving good results. This step is as essential in the development of a new instrument as in cross-cultural adaptations, in which the notion of equivalence (referred to in the previous section) requires thorough examination. This must be emphasized, since the efforts dedicated to this stage are often scarce in adaptation processes—if not completely ignored.

Besides its importance in achieving a functional instrument, this first phase is not only essential from a substantive point of view—in the search for correspondence between the construct to be measured and the tool for doing so—but it also makes the next phase, testing of prototypes, more efficient. Enough time allocated for this stage and procedural rigor decrease the possibility of finding problems in subsequent validation studies, which are generally large and, therefore, more expensive. The worstcase scenario is to find pronounced deficiencies at the end of a long and intricate process, involving multiple interconnected studies, and having to go back to the field to test an almost new prototype.

The prototype specified in the previous phase is then examined in an extensive second phase, which we would call “psychometric.” Unlike the first one, in which qualitative approaches are more prominent, this second phase, as already suggested, comprises a sequence of larger quantitative studies. Expanding the upper right part of the Figure , the lower portion shows the various psychometric aspects of this phase. Two distinct segments should be noted: one concerns the internal structure of the instrument, covering its configural, metric, and scalar structures; and the other addresses its external validity, assessing whether patterns of association between estimates derived from the instrument and measures of other constructs agree with what is theoretically expected, for example.

Before detailing the proposed procedural model, it is worth mentioning the types of instruments to which the Figure refers. As should be clear throughout the text, the model we propose involves constructs (dimensions) in which the object of study intensifies or recedes according to a particular gradient. Although these types of constructs are common—e.g., diseases and injuries, depression, psychosocial events (violence), perceptions of health or quality of life—in some cases this increasing or decreasing severity or intensity is not applicable or does not matter much. A good example is what we might call “inventories”: a questionnaire to investigate whether an individual was ever exposed to a given chemical agent. Here, the instrument should contain a wide range of questions about potential contact situations over a period, with just one endorsement (hit) required to confirm the respondent’s exposure. Although one can think of a second instrument to capture the degree of exposure to this chemical agent—measuring the increasing intensity of this exposure—such an inventory would not focus on an underlying gradient. Another situation in which the model in the Figure would not be applicable refers to pragmatic instruments based on a set of risk predictors that are not theoretically linked to an underlying construct. An example would be a tool to predict the risk of dying from Covid-19 at the first contact of a patient with the health service, composed of variables covering several aspects, such as sociodemographic characteristics, health-related behaviors, pre-existing conditions, recent contacts with Covid-19 cases, or even admission exams. Though extremely important, this set of items would still not constitute a construct to be mapped.

In many other situations, the items of an instrument do not connect with a construct and/or form an explicit gradient of intensity. It is, therefore, up to the researcher to assess them and to evaluate whether a procedural model—such as the one proposed here—applies to the problem at hand. The following three sections provide some details about the two phases. It is worth pointing out that there are numerous paths to be followed and that our choice is only one of many. To the interested reader, we suggest checking the related bibliography; in the following section, we discuss some of it.

PROPOSING AN INSTRUMENT

The details of the first phase of the procedural model illustrated in the Figure can be found in Box 1 . Adapted from Wilson’s 13 proposal, the process contains five distinct stages. In the first, the theory supporting the construct is evaluated as to the extent to which it represents what one wants to measure. This representation is technically called the “construct map,” which outlines the ideas the developers (or adapters) of the instrument have about what is to be captured, including its gradient of intensity 13 . The construct map guides the process of developing items that will reflect the construct in question. The aim is to arrive at an efficient and effective set of items with good measurement properties. The goal is, at the end of the process, to identify those items that—in the most discriminating and orderly way possible—can map the metric space of the construct. Consisting of items positioned in the expected increasing gradient of intensity 13 . The empirical expression of the construct map is sometimes called the Wright map, which consists of the selected items positioned in the expected increasing gradient of intensity.

Note: References: Streiner et al. 7 , Beatty et al. 42 , Moser and Kalton 43 , Bastos et al. 3 , Reichenheim and Moraes 6 , Johnson and Morgan 44 , DeVellis 45 ; Gorenstein et al. 46 Some of these references are occasionally marked, when necessary, along with other specific ones.

Moving from the theoretical-conceptual dimension of the construct map to the empirical dimension of the items requires contextualization and, thus, a good grasp of the population to which the instrument will be administered. On the one hand, the construct (and what it represents within the underlying theory) should be pertinent to the population in question. On the other hand, eligible items must be potentially endorsed in the desired context. It is always necessary to ask whether an item has some potential to be endorsed or whether negative answers to it do not stem from an intrinsic impossibility. As an example, we can mention an item on explicit discrimination experienced in the workplace asked to schoolchildren who still have not reached working age. Although somewhat obvious when pointed out, this is a common problem that requires careful consideration.

Once the construct map is specified, it is used to identify and develop the items that will be part of the instrument. At this stage, researchers should identify the various ways in which the construct manifests, including its different levels of intensity 13 . Box 1 distinguishes the process of identifying items from how these will be conveyed to respondents. These are, indeed, different tasks. The process of identifying potential items derives directly from the construct map, having to do with recognizing the empirical manifestations representing the outlined gradient of intensity. It concerns the content (meaning) of an item and not its form (wording). Syntactic and semantic questions come in later (third step), when the number of candidate items have been further restricted through sequential qualitative studies 3 , 6 .

The fourth stage of the first phase concerns operational issues, starting with the specification of the outcome space of each item. Identifying the type and number of response categories that items should contain is an important task. Like other eminently operative issues—instrument format, administration scenario etc.—debating and specifying the types of answers should be done early on, as soon as the target population of the instrument is identified. The third stage is then resumed with this focus: writing the qualifications of the response categories that were previously outlined/defined.

At this point, it is worth emphasizing that the validity of an instrument—its adequacy and performance—is dependent upon a close connection with the background content, attention to respondents’ cognitive and emotional capacity, and a productive environment in which answers can be provided with ethics, spontaneity, and safety. One should keep in mind that even a validated instrument can still underperform if administered to a population for which it was not originally developed or in an adverse operative context.

Item design and outcome specification require a first visit to the target population so that the first batches of prototypes (i.e., alternative and preliminary versions of the instrument) are assessed regarding acceptability, understanding, and emotional impact. A good strategy is to pre-test the instrument (fifth stage). Based on evidence from the pre-test, the most promising prototypes are then put to test in the next phase. Box 1 provides additional information and suggests several references for consultation.

ASSESSING INTERNAL STRUCTURE ADEQUACY

As already shown in the Figure , Box 2 expands the second phase of the development or adaptation of instruments: the structures to assess (configural, metric, and scalar); the properties under evaluation and the main questions to be answered; the models and analytical techniques used; as well as comments on what is expected of each property and how to evaluate it, including the demarcations guiding decisions.

a Legend: ACP - principal component analysis; CFA - confirmatory factor analysis; AFE - exploratory factor analysis; ESEM - exploratory structural equation modeling; IRT - item response theory; CFV - convergent factorial validity; DFV - discriminating factorial validity; AVE - average variance extracted.

b References: Gorsuch 67 , Rummel 68 , Brown 17 , Kline 19 , Marsh et al. 48 , Embretson and Reise 62 , Bond and Fox 27 , De Boeck and Wilson 69 , Van der Linden 21 , Davidov et al. 30 Some of these references are occasionally marked, when necessary, along with other specific ones.

Box 2 highlights how many properties need to be scrutinized before judging the internal structure as adequate, thus endorsing this validity component of the instrument 15 , 16 . This is at odds with the general literature on the topic, in which the validity of an instrument tends to be accepted by somewhat sparse and weak evidence. Quite often, decisions on the acceptability of the instrument rely on a few factor analyses, using only model fit indices, demarcated by generic cut-off points (e.g., Root Mean Square Error of Approximation/RMSEA, Comparative Fit Index/CFI, Tucker-Lewis Index/TLI 17 ). These analyses usually fall short in further examining items and the scale(s) as a whole. Strictly speaking, the range of properties listed in Box 2 does not fit in single products (e.g., scientific articles), and serial studies are often necessary to visit one or more properties at a time. The methodological intricacies relating to each property certainly require detailing and greater editorial space.

A previously addressed point illustrates this fundamental rigor: the need for explicit demarcations to decide whether an item or scale meets the property under scrutiny. All estimators used in the evaluations require specific cut-off points, so that choices can be replicated or, when appropriate, criticized, rejected, or modified during the development or adaptation of an instrument. Box 2 offers some landmarks indicated in the literature. Beyond prescriptive benchmarks, these should serve as a stimulus to the empirical examination of an instrument. The main point is that the many decisions related to the psychometric suitability of an instrument need clear anchors, previously agreed upon by peers of the scientific community. The literature would certainly be enriched if these details extended to scientific articles.

One point to make regarding the procedural context in question is that multivariate analyses are used as diagnostic devices. As process tools, they must answer the central questions posited a priori . In this sense, it is necessary to distinguish eminently qualitative from quantitative issues related to a technical and methodological sphere. The third configural property presented in Box 2 serves as an example. Rather than simply verifying whether an exploratory factor analysis identifies cross-loadings, it is important to answer if a violation of factorial specificity effectively occurs, which would be antithetical to what was projected in the first phase of instrument development. A cross-loading suggests ambiguity in the item, and therefore that its clear-cut function as an “empirical representative” of the dimensional construct map was not fulfilled. Here, quantitative evidence meets qualitative findings, signaling a problem and the need for action, either by modifying the item semantics, or by replacing it with an item with better properties. The other properties demand the same approach.

In addition to the internal properties of items and scales summarized in Box 2 , two other related questions deserve mentioning. The first concerns the presumption of measurement invariance (configural, metric, and scalar) 17 . The assumption that the instrument performs similarly in different population subgroups is almost a rule. Often, it is tacitly assumed that the instrument functions equally well across groups (e.g., genders, age groups, strata with different levels of education or residing in different parts of the country), so that any differences observed between them are considered factual and not due to measurement problems. However, without further evidence, this is a difficult argument to sustain since inconsistent functioning of an instrument among subgroups of the population can lead to incorrect inferences and inefficient or even harmful health decisions and actions 20 . This demands stepping up research programs on measurement instruments. Beyond scrutinizing their properties, evaluating them in various population segments is also needed. To ensure invariance of the instrument in different population subgroups is to allow reliable comparisons.

Along with invariance is the issue of equalization and linking of instruments 22 . These concern the search for common metrics across instruments that supposedly capture the same construct, but hold different items and/or varied response options 25 , 26 . In both cases, one must be careful when summarizing and comparing studies. Study results may not be comparable—even if focused on the same construct—when they are conducted in different populations and with different instruments. Without equalization, measurement instruments may lack metric and scalar tuning.

An issue related to the scalar properties of an instrument concerns the appropriateness of grouping individuals when applying cut-off points to scores (whether crude scores, formed by the sum of item scores, or model-based scores, such as factor-based or Rasch scores 27 , 28 ). This point deserves attention, especially regarding the approaches frequently used in epidemiology. It is common to categorize a score into a few groups, by taking the mean, median, or some other “statistically interesting” parameter as a cut-off point. This procedure has downsides, however, since the study population is not necessarily partitioned into internally homogeneous and externally heterogeneous groups. Substantive knowledge on the subject matter is undoubtedly crucial in the process of grouping respondents appropriately, but the search for internally similar yet comparatively distinct groups may gain from using model-based approaches, such as latent class analyses or finite mixture models 29 .

ASSESSING CONNECTIONS BETWEEN CONSTRUCTS AND THEORIES

Box 3 proposes a typology that is in line with validity based on hypothesis testing presented in the early 2010s by the COSMIN initiative (COnsensus-based Standards for the selection of health Measurement INstruments) 15 , 16 , 33 . Contrary to the apparent conciseness of the suggested typology, this stage of the second phase of instrument evaluation implies a long process—perhaps as long as the study of the construct itself in all its relationships of causes and effects. Evoking other texts 7 , 11 , it is important to point out that the validity of an instrument ultimately corresponds to establishing validity of the theoretical construct that the instrument aims to measure. Somewhat circular and dismaying due to the long road it projects, this reasoning alerts us to how risky and reckless it is to support an instrument that has been assessed by only a few studies. Consolidating and eventually endorsing the suitability of an instrument requires many tests, both regarding its internal structure and its external connections.

a References: Streiner et al. 7 , Bastos et al. 3 , Reichenheim and Moraes 6 , Lissitz 70 , Armitage et al. 71 , Corder and Foreman 72 , Kline 19 , Little 61 , Hernán and Robins 5 , VanderWeele 35 .

As suggested in Box 3 , external validation of an instrument ranges from simple tests of association between component subscales to intricate hypotheses tests about the construct—what scholars often take as the nomological network of interconnected concepts of a theory 5 , 7 , 34 , 35 . Whatever the level of complexity of the study, a question that arises—often in the context of scientific publications—is when an external validity study should be performed, given all the necessary prior steps to better know the intricacies of the instrument. Would it be worth conducting studies along the lines that Box 3 indicates, without first having some evidence about the sustainability of the instrument’s configural, metric and scalar structures? One should recognize that correlations between scales (e.g., the instrument in question and others that cover the same construct) may well occur even in the face of multiple psychometric insufficiencies at the internal level. What would these correlations mean, knowing, for example, that the set of items does not satisfactorily meet the requirements of factorial specificity, convergent factorial validity, and scalability? The answer based on the mere correlation would indicate external validity, but one could ask “of what?” if the ability to represent the underlying construct is flawed and uninformative. These questions cannot be answered clearly, but it is necessary to pose them before “blindly” carrying out external validity studies. The timing of these stages is a decision to be taken within each research program, but the saying “haste makes waste” serves as a reminder: little time and effort (and resources!) invested in one step can be double time and effort (and resources!) needed in a following step.

CONCLUDING REMARKS

This article clarifies that the development of a measurement instrument involves an extensive process, comprising multiple connected studies. This trajectory can be even longer and tortuous considering the need for replication studies or when certain psychometric studies raise fundamental questions that only returning to the prototypic phase of development may provide answers. This panorama contrasts sharply with the way epidemiologists often approach measurement instruments. Contrary to common practice, evidence on the adequacy of a measurement tool demands more than one or two studies on its dimensional structure, or the magnitude of factor loadings. This warning also extends to critical analyses of external validity that, as mentioned in the former section, require attention to the inner workings of the instrument.

The development and refining of different versions of the instrument are also vital, so that research carried out in distinct populations retains comparability and can be compared with each other. The cross-cultural adaptation process is as intricate as the development of a new instrument. All phases and stages apply equally to adaptation processes. In fact, a researcher performing a cross-cultural adaptation often finds a variety of gaps in the original research program giving rise to the instrument. Sometimes, they are problems related to the execution of previous studies; other (many) times, several properties have not even been assessed. In this case, the focus shifts from equivalence (see section on Research Scenarios) to the core of the structure of the instrument. This is not trivial, since the origin of the problem is always dubious: an intrinsic problem of the instrument or a problem in the process of cross-cultural adaptation. Be that as it may, examining an instrument in another sociocultural context requires even more time and effort. That is why many consider cross-adaptation as an additional construct validation step 33 .

A recurring question is whether all phases and stages need to be completed to deem an instrument suitable for research or for use within health services. This question is difficult to answer, but some milestones may guide us. One suggestion has already been offered in the section on the process stages: a well-planned and developed prototypic phase helps greatly to obtain favorable results in the second major phase of the process. Rigor in the first phase contributes to better psychometric properties; it also adds efficiency, as several problems tend to be solved or even avoided early on. Epidemiological studies in the psychometric phase are usually large and, therefore, rarely susceptible to replications to solve emerging issues.

Another guide is resorting to the fundamentals: always remembering the essence of each property and what its violation means. For example, would we firmly declare an instrument as valid and ready for use in light of a few exploratory factor analyses—preliminary stating a configural structure—and/or some studies correlating the score(s) of the (sub)scale(s) with certain sociodemographic variables as evidence on theoretical pertinence? Given the range of the substantive and procedural possibilities, would this be sufficient, or should we postpone the use of the instrument and obtain additional evidence to support its validity? We reiterate that a quick and prompt response does not exist, but that, perhaps, a rule can be useful for decision-making: even if we are not prepared to let the great mess the good—or even let the good get in the way of the reasonable—it may be worth letting the reasonable get in the way of the bad. Although this is a subjective perspective, always negotiable among peers, if put into practice it will possibly lead us to better instruments and, as we have already pointed out, to better results and comparisons between studies or health interventions.

The continuous development, refinement and adaptation of measurement instruments should be an integral part of epidemiologic research. Knowledge construction requires instruments with acceptable levels of validity and reliability, up to par with the level of rigor commonly required in the elaboration of study designs and their complex analyses. Meticulousness and rigor in these spheres are pointless if the dialogue between publications and appreciation of consistent scientific evidence fail due to precariousness of measurement instruments. As products focused on collective use, measurement instruments require development processes that resemble those found for medicines or other health technologies. And as such, they deserve care and dedication.

Funding Statement

Funding: MER was funded in part by the Conselho Nacional de Desenvolvimento Científico e Tecnológico do Brasil (CNPq - Process 301381/2017-8). JLB was funded in part by the Conselho Nacional de Desenvolvimento Científico e Tecnológico do Brasil (CNPq - Process 304503/2018-5).

• Rev Saude Publica. 2021; 55: 40.

O quê, para quê e como? Desenvolvendo instrumentos de aferição em epidemiologia

I Brasil, Universidade do Estado do Rio de Janeiro. Instituto de Medicina Social Hésio Cordeiro. Departamento de Epidemiologia. Rio de Janeiro, RJ, Brasil

II Brasil, Universidade Federal de Santa Catarina. Departamento de Saúde Pública. Florianópolis, SC, Brasil

Contribuição dos Autores: Concepção e planejamento do estudo: MER, JLB. Preparação e redação do manuscrito: MER, JLB. Aprovação final: MER, JLB.

Embora fundamental para a pesquisa epidemiológica, o desenvolvimento e a adaptação transcultural de instrumentos de aferição têm recebido menos destaque nas discussões metodológicas que permeiam o campo. Em paralelo, a qualidade das mensurações realizadas em muitos estudos epidemiológicos está frequentemente aquém do desejado para a construção de conhecimento sólido sobre o processo saúde-doença. A escassez de sistematizações sobre o que, para que e como aferir na área provavelmente contribui para esse cenário. Nesta revisão, propomos um modelo processual composto por uma sequência de etapas voltadas à mensuração de construtos em níveis aceitáveis de validade, confiabilidade e, por extensão, comparabilidade. Subjaz à proposta a ideia de que não apenas alguns, mas diversos estudos concatenados entre si e sucessivamente mais aprofundados devem ser conduzidos para obter aferições adequadas. A implementação do modelo poderá contribuir para alargar o interesse sobre instrumentos de aferição e, especialmente, para enfrentar os problemas investigados em epidemiologia.

INTRODUÇÃO

Considerada um dos pilares da saúde pública, a epidemiologia se preocupa fundamentalmente com a frequência, a distribuição e os determinantes ou as causas de eventos de saúde em populações humanas 1 . Ao enfatizar esses aspectos, a atividade relacionada à mensuração dos fenômenos de interesse – sejam eles dimensões do processo saúde-doença ou questões que o condicionam – assume centralidade nas pesquisas desenvolvidas na área. O epidemiologista emprega parte considerável de seus esforços na mensuração de condições específicas de saúde-doença, de características (de pessoa, lugar e tempo) que permitam observar sua variabilidade e de processos subjacentes à sua ocorrência em um determinado domínio populacional 2 . Embora haja exceções, a mensuração epidemiológica dos aspectos mencionados é predominantemente quantitativa, o que permite a subsequente análise estatística de seus padrões de associação com vistas a apreciar o evento de saúde e intervir sobre ele 3 .

Ainda que central à epidemiologia, o processo de mensuração não consiste em uma atividade trivial. Pelo contrário, é de considerável complexidade, impondo importantes desafios a serem enfrentados. Tal processo implica expressivo rigor conceitual, além das outras questões discutidas em maior detalhe neste artigo 6 , 7 . Não é possível mensurar com níveis aceitáveis de validade e confiabilidade um fenômeno cuja definição é ambígua entre os pesquisadores ou a própria população cujas condições de saúde-doença são objeto de apreciação. Igualmente importante é o uso de instrumentos com boas propriedades psicométricas para mensurar os aspectos de interesse na população 6 . Na ausência destes, não somente a validade e a confiabilidade das mensurações são potencialmente postas em xeque, como também fica mais difícil comparar os dados com os de outras pesquisas acerca do mesmo evento de saúde 8 , limitando, por sua vez, a construção própria do conhecimento científico delimitado no objeto de investigação. Tal conhecimento frequentemente se estabelece pelo acúmulo e contraste sistemático de resultados de pesquisas que, por pressuposto, requerem ser passíveis de confrontação.

Embora fundamental para a pesquisa epidemiológica, há que se reconhecer que a atividade de mensuração tem recebido menos destaque nas discussões metodológicas que permeiam o campo. Enquanto questões ligadas aos desenhos de estudo, aos possíveis vieses e às técnicas estatísticas frequentemente pautam os cursos de epidemiologia e os debates travados entre pesquisadores da área, relativamente menos espaço tem sido destinado aos rigores e aos processos atinentes à mensuração. Neste cenário, observa-se a necessidade de uma apreciação abrangente, que inclua desde as etapas de construção teórica até testes psicométricos formais, empregados no processo de desenvolvimento ou de adaptação dos instrumentos de aferição. Os autores deste estudo não localizaram na literatura uma discussão sobre as diferenças entre o que, para que e como no âmbito do desenvolvimento de um instrumento de aferição, incluindo a avaliação de suas estruturas interna e externa. O objetivo desta revisão é, portanto, oferecer um conjunto de sugestões sobre possíveis percursos a serem seguidos no desenvolvimento ou na adaptação transcultural (ATC) de instrumentos de aferição utilizados em estudos epidemiológicos. Ao propormos um modelo processual composto por uma sequência de etapas, nossa expectativa é que o texto contribua para melhorar a qualidade da produção do conhecimento sobre saúde. Esperamos, também, que o artigo sirva para aprimorar a formação acadêmica em epidemiologia. O incentivo à aquisição de informações na área específica da medição pode estimular estudantes e vindouros pesquisadores a dotar-se das habilidades e competências necessárias para aderir à proposta.

Nossa postura é eminentemente indicativa, uma vez que a literatura sobre o tema é complexa e vasta. Optamos por aprofundar apenas alguns pontos que entendemos de recorte aplicado e de relevância imediata à prática epidemiológica. Nesse movimento, procuramos nos ater a referências bibliográficas amplamente recomendadas, adicionadas de algumas publicações pontuais, como sugestões para demarcar alguma conduta ou decisão específica. Ainda assim, esperamos que esta introdução incentive leituras mais amplas em sequência.

CENÁRIOS DE PESQUISA E DESENVOLVIMENTO OU ADAPTAÇÃO DE INSTRUMENTOS

Estudos epidemiológicos exigem perguntas suficientemente delimitadas e socialmente relevantes, as quais requerem mensurações confiáveis e acuradas dos fenômenos e conceitos necessários para respondê-las 8 . Berry et al. 9 discutem três perspectivas a serem adotadas nesta direção.

Na perspectiva absolutista, desconsideram-se nuances socioculturais na interpretação dos eventos de interesse e assume-se, portanto, que há possibilidade de comparação irrestrita de aferições quantitativas levadas a cabo em diferentes populações. Neste caso, salvo a necessidade de tradução literal para os idiomas pertinentes, um único instrumento de aferição poderia ser amplamente utilizado nas mais variadas populações, podendo-se comparar diretamente os seus resultados com vistas à consolidação do conhecimento científico sobre o objeto de interesse.

Em situação diametralmente oposta encontra-se a abordagem relativista, a qual eleva as especificidades socioculturais à sua máxima importância, pressupondo que um instrumento de aferição diferente seja utilizado para cada nova população investigada. Essa abordagem nega a possibilidade de comparação quantitativa de medidas realizadas em populações socioculturalmente diferenciadas, visto que os instrumentos não seriam equivalentes entre si, e a única forma de contrastá-las seria por meio de análises qualitativas.

Assumindo uma posição intermediária está a perspectiva universalista, que implica tanto a aferição quantitativa de fenômenos em investigação quanto a possibilidade (mas, não garantia) de comparação entre populações distintas por meio dessa medida. Essa posição reconhece as nuances socioculturais e apregoa que devem ser levadas em consideração. Havendo semelhança na forma como os eventos são interpretados em diferentes populações, seria possível prosseguir com a utilização de um instrumento dito “universal”, mas adaptado para cada situação particular. Nessa visão, a ATC garantiria a equivalência entre as suas diversas versões 10 . Sua aplicação permitiria que populações socioculturalmente distintas fossem comparadas quantitativamente a partir de medidas equivalentes do mesmo problema de interesse.

A abordagem universalista 3 , 6 , 11 , 12 implica três possíveis cenários, que devem ser avaliados e identificados pelo pesquisador para escolher o instrumental de pesquisa, respondendo se:

• existe um instrumento consagrado e adaptado para uso em distintas populações, incluindo a de interesse (Cenário 1);
• há instrumento disponível, mas seu uso requer cautela ou refinamento adicional, dada sua ainda limitada aplicabilidade à população em tela, seja por necessitar de avaliações psicométricas complementares ou porque ainda precisa ser submetido a um processo de ATC (Cenário 2); ou
• inexiste instrumento, sendo necessário propor o desenvolvimento de um inteiramente novo (Cenário 3).

No Cenário 2, frequentemente há necessidade de desenvolver estudos de ATC, nos quais o conceito de equivalência deve ser tomado como norte 10 . A equivalência é usualmente desdobrada em conceitual, de itens, semântica, operacional e de mensuração, as quais requerem uma avaliação meticulosa para que se considere um instrumento plenamente adaptado. No Cenário 3, por sua vez, o pesquisador deve suspender a iniciativa original de pesquisa e propor o desenvolvimento de instrumental completamente original 13 . Aqui, é preciso empreender um programa de investigação paralelo que vise gerar um instrumento capaz de produzir as medidas de interesse. Isso é crucial, uma vez que seguir com a pesquisa sem bons instrumentos de aferição põe todo o projeto a perder, diminuindo suas chances de contribuir com o avanço do conhecimento ou de atender a uma necessidade de saúde, tornando-se, assim, eticamente condenável. Na maioria das vezes, os estudos epidemiológicos são conduzidos nos limites dos Cenários 2 e 3, o primeiro sendo o mais comum e afeito ao contexto brasileiro de pesquisa.

Uma implicação importante de trabalhar em meio a esses cenários é a necessidade de conhecer detalhadamente o estado da arte do desenvolvimento dos instrumentos disponíveis. Tal conhecimento é imprescindível para proceder tanto a uma ATC e/ou ao refinamento de instrumentos de aferição pré-existentes quanto para o desenvolvimento de novo instrumental e a subsequente condução da pesquisa epidemiológica de fundo.

FASES A PERCORRER NO PROCESSO DE DESENVOLVIMENTO OU ADAPTAÇÃO DE INSTRUMENTOS DE AFERIÇÃO

Seja no caso da proposição de um novo instrumento ou de uma ATC, vislumbram-se etapas processuais distintas, ainda que complementares e interativas. A Figura esquematiza um modelo processual a ser adotado.

A primeira fase visa a elaboração e o detalhamento conceitual do construto a ser medido; a especificação, a confecção e o refinamento dos itens quanto aos seus conteúdos empíricos e semânticos; a pormenorização dos aspectos operacionais, incluindo os cenários de aplicação admissíveis para o instrumento; e várias jornadas de pré-testes para alcançar sintonia fina, como melhorias na redação e na compreensão da população-alvo quanto aos itens. Provisoriamente denominada “prototípica” por encerrar as etapas de construção de um ou vários esboços do instrumento (i.e., protótipos ou versões preliminares) a serem subsequentemente testados, esta primeira fase do processo é essencial para os bons frutos finais. Se, na perspectiva do desenvolvimento de um novo instrumento, esse passo é claramente imperativo, ele não é menos importante em ATC, em que a noção de equivalência (referida na seção anterior) exige um exame minucioso. Este ponto requer ênfase, uma vez que os esforços dedicados às suas fases constituintes são frequentemente parcos nos processos de ATC, quando não totalmente ignorados.

Além de sua central relevância para o alcance de um instrumento funcional, apuro nesta primeira fase não é somente importante do ponto de vista substantivo – na busca de correspondência entre o construto a ser aferido e a ferramenta para sua mensuração –, mas também torna mais eficiente a fase seguinte, de teste dos protótipos. Tempo empenhado e rigor procedimental nesta fase diminuem a possibilidade de se encontrar impropriedades nos estudos de validação subsequentes, que são geralmente de grande porte e, portanto, bastante dispendiosos. O pior cenário é encontrar deficiências marcantes no final de um longo e intrincado processo envolvendo múltiplos estudos encadeados ( cf . próxima seção), ter de voltar a fases anteriores de desenvolvimento e retornar ao campo para testar um protótipo praticamente novo.

O protótipo especificado na fase anterior é, então, examinado em uma segunda grande fase, que, também provisoriamente, poderia ser cunhada de “psicométrica”. Diferentemente da primeira, em que preponderam abordagens qualitativas, esta segunda fase, como já aventado, encerra uma sequência de estudos quantitativos de maior porte. Expandindo a parte superior direita da Figura , a porção inferior mostra os diversos aspectos psicométricos que compõem essa fase. Há dois segmentos distintos: um concerne à validade da estrutura interna do instrumento, cobrindo o exame de suas estruturas configural, métricas e escalares; outro aborda sua validade externa, permitindo verificar se o seu comportamento – relativo a medidas de outros construtos, por exemplo, – está de acordo com o que teoricamente se espera.

Antes de passar para o detalhamento do modelo processual proposto, vale uma ressalva sobre os tipos de instrumentos aos quais a Figura se refere. Como deverá ficar claro ao longo do texto, o modelo que propomos envolve, principalmente, construtos (dimensões) em que o objeto em tela, por pressuposto, se intensifica ou remite em gradiente. Ainda que estes tipos de construtos sejam muito frequentes – e.g., doenças e agravos (e.g., depressão), eventos psicossociais (e.g., violências), percepções de saúde ou de qualidade de vida –, há situações em que este (de)crescente de gravidade ou intensidade não se aplica ou não importa tanto.

Um bom exemplo está no que poderíamos chamar de “inventários”, como seria um questionário para investigar se um indivíduo já se expôs a algum agente químico. Aqui, o instrumento deveria conter uma gama de perguntas sobre situações de contato potencial ao longo de um determinado período, sendo o endosso a ao menos uma destas situações a própria positivação do respondente. Ainda que se possa pensar em um segundo instrumento para captar o grau de exposição a este agente químico – e que, portanto, estaria aferindo a intensidade crescente dessa exposição –, para os fins propostos o questionário em tela prescindiria dessa qualidade. Outra situação à qual o modelo na Figura não se aplicaria se refere a instrumentos pragmáticos, baseados em um conjunto de variáveis preditoras de risco que, no entanto, não estariam vinculadas teoricamente a um construto. Um exemplo seria uma ferramenta de predição de risco de letalidade da covid-19 a ser usada ao primeiro contato de um paciente com o serviço de saúde, composta por variáveis que cobrissem diferentes ângulos, como o sociodemográfico, hábitos de vida, condição patológica pregressa, prática preventiva, trajetória e contatos recentes ou, ainda, exames de entrada. Mesmo que claramente de extrema valia, não haveria um construto definido a ser mapeado por esse conjunto.

Há, por certo, muitas outras situações em que itens componentes de um instrumento não se conectam teoricamente e/ou formam um explícito gradiente de intensidade. Compete, pois, ao pesquisador discerni-las e avaliar se um modelo processual como o proposto aqui é pertinente. Alguns pormenores sobre suas duas fases são oferecidos nas três seções seguintes. Vale apontar, no entanto, que as possibilidades são amplas e que, assim sendo, nossa escolha é forçosamente uma de muitas. Ao leitor interessado sugerimos recorrer à bibliografia conexa, da qual oferecemos alguns artigos e livros de interesse no texto que segue.

ASPECTOS A AVALIAR NA PROPOSIÇÃO DE UM INSTRUMENTO

Os detalhes da primeira fase do modelo processual ilustrada na Figura estão no Quadro 1 . Adaptado da proposta de Wilson 13 , o processo encerra cinco etapas distintas. Na primeira, avalia-se a teoria que embasa o construto com vistas à representação do que se quer medir. Essa representação é denominada tecnicamente de “mapa do construto”, a qual delineia as ideias que os desenvolvedores (ou, dependendo, os adaptadores) do instrumento têm sobre o que está por ser captado, incluindo seu gradiente de intensidade 13 . É a partir do mapa do construto que se alicerça a busca dos itens para representá-lo. De muitos possíveis, a proposta é se chegar a um conjunto eficiente e efetivo de itens que contenham boas propriedades de mensuração. A meta é, ao fim do processo, identificar aqueles que, de forma mais discriminante e escalonada possível, consigam mapear o espaço métrico do construto. Constituído de itens posicionados no esperado gradiente crescente de intensidade, o mapa de Wright 13 é a expressão empírica do mapa do construto.

* Referências de fundamentação: Streiner et al. 7 , Beatty et al. 42 , Moser e Kalton 43 , Bastos et al. 3 , Reichenheim e Moraes 6 , Johnson e Morgan 44 , DeVellis 45 ; Gorenstein et al. 46 Algumas destas referências são também assinaladas ocasionalmente, quando necessário, juntamente com outras específicas.

É preciso entender que o processo de translado do plano teórico-conceitual ao empírico requer contextualização e, assim, uma boa compreensão sobre a população-alvo na qual se intenciona empregar o instrumento em desenvolvimento ou ATC. Por um lado, o construto (e o que este representa no âmbito da teoria subjacente) pressupõe pertinência ao domínio populacional em tela. Por outro, é necessário que os itens elegíveis tenham potencialidade de endosso no contexto previsto. Cabe sempre perguntar se a resposta a um item tem como se realizar e se uma potencial negativação não advém de uma impossibilidade intrínseca. Como exemplo podemos citar um item sobre discriminação explícita vivenciada no domínio laboral perguntado a escolares que ainda não alcançaram o mercado de trabalho. Ainda que um tanto óbvio quando destacado, trata-se de um problema bastante comum e que requer atenção constante.

Uma vez especificado o mapa do construto, passa-se para a identificação e confecção dos itens que comporão o instrumento. É nessa etapa que os pesquisadores deverão identificar as variadas formas pelas quais o construto se manifesta, incluindo suas diferentes intensidades 13 . De fato, o Quadro 1 distingue o processo de identificação de itens da elaboração de como estes serão transmitidos aos respondentes. São, efetivamente, afazeres distintos. O processo de identificação de potenciais itens deriva diretamente do mapa do construto, tendo a ver com o reconhecimento das manifestações empíricas que representam o gradiente de intensidade esboçado. Diz respeito ao conteúdo (significado) de cada item e não à sua forma (redação). Questões sintáticas e semânticas vêm depois (terceira etapa), quando já se tem um número mais restrito de itens candidatos, selecionados por meio de estudos qualitativos sequenciais 3 , 6 .

A quarta etapa da primeira fase concerne às questões operacionais, a começar pela especificação do espaço de desfecho de cada item. Identificar o tipo e número de categorias de resposta que cada item deve conter não é algo secundário. Como outras questões eminentemente operativas – formato do instrumento, mídia de veiculação, cenário de aplicação etc. –, debater e especificar o espaço de desfecho dos itens é algo a ser visto precocemente, tão logo seja identificado o público-alvo para o qual o instrumento será direcionado. É com esse foco que, subsequentemente, é preciso retomar a terceira etapa, redigindo-se as qualificações das categorias de resposta antes acordadas no âmbito do conteúdo.

Nesse ponto, vale a pena sublinhar que a validade de um instrumento – sua adequação e seu desempenho – não ocorre em um vazio, mas depende de estreita sintonia com o conteúdo de fundo, da atenção à capacidade cognitiva e emocional dos respondentes e de um ambiente profícuo no qual respostas podem ser oferecidas com ética, espontaneidade e segurança. É preciso lembrar que um instrumento já muitas vezes validado pode ter um desempenho aquém do esperado se for aplicado a uma população para o qual não foi originalmente confeccionado ou em um contexto operativo adverso.

As etapas de desenho de itens e de especificação do espaço do desfecho contemplam uma primeira visita à população-alvo para que os primeiros lotes de protótipos (i.e., versões alternativas e preliminares do instrumento) sejam submetidos a uma avaliação de aceitabilidade, compreensão e impacto emocional. Uma estratégia atraente é pré-testar o instrumento (quinta etapa). A partir das evidências encontradas no pré-teste são escolhidos os protótipos mais promissores, que deverão ser testados formalmente na fase seguinte. O Quadro 1 oferece algumas informações adicionais, bem como sugere diversas referências para consulta.

AVALIAÇÃO DE ADEQUAÇÃO DE ESTRUTURA INTERNA

Já anunciada na Figura , esta etapa da segunda fase de desenvolvimento ou ATC de instrumentos é aprofundada no Quadro 2 , no qual são apresentados: as estruturas a serem avaliadas (configural, métrica e escalar); as respectivas propriedades em avaliação e as principais questões que demandam resposta; os modelos e as técnicas de análise envolvidos; além de comentários sobre o que se espera de cada propriedade visitada e como avaliá-la, inclusive quanto às demarcações que norteiam decisões.

a Legenda: ACP – análise de componentes principais; AFC – análise fatorial confirmatória; AFE – análise fatorial exploratória; MEEE – modelos de equação estrutural exploratória; TRI – modelos de teoria de resposta ao item; VFC – validade fatorial convergente; VFD – validade fatorial discriminante; VME – variância média extraída.

b Referências de fundamentação: Gorsuch 67 Rummel 68 , Brown 17 , Kline 19 , Marsh et al. 48 , Embretson e Reise 62 , Bond e Fox 27 , De Boeck e Wilson 69 , Van der Linden 21 , Davidov et al. 30 Algumas destas referências são também assinaladas ocasionalmente, quando necessário, juntamente com outras específicas.

O Quadro 2 evidencia quantas propriedades necessitam ser escrutinadas antes que se possa julgar a estrutura interna como adequada e, assim, endossar este componente de validade do instrumento 15 , 16 . É um panorama que em muito contrasta com o que a literatura habitualmente oferece, em que a validade de um instrumento tende a ser satisfeita por evidências um tanto quanto escassas e frágeis. Com efeito, não raramente decisões sobre a aceitabilidade de uma escala se escoram em algumas poucas análises fatoriais usando apenas índices de ajuste de modelo, demarcados por pontos de cortes genéricos (e.g., Root Mean Square Error of Approximation/ RMSEA, Comparative Fit Index/ CFI, Tucker-Lewis Index/ TLI 17 ) e carecendo de exames mais aprofundados sobre os itens e a(s) escala(s) como um todo. A rigor, a gama de propriedades arroladas no Quadro 2 não cabe em produtos únicos (e.g., artigos científicos), sendo necessários, para tal, estudos seriais visitando um ou mais aspectos por vez. Os meandros metodológicos relativos a cada propriedade a ser coberta certamente exigem detalhamento e maior espaço editorial.

Um ponto já abordado ilustra esse rigor fundamental: a necessidade de demarcações explícitas para se decidir se um item ou escala atende à propriedade em escrutínio. Todos os estimadores utilizados nas avaliações requerem delimitação de pontos de corte, de tal sorte que escolhas possam ser replicadas ou, se for o caso, criticadas, rejeitadas ou alteradas no decurso do desenvolvimento ou da ATC de um instrumento. O Quadro 2 procura oferecer alguns marcos indicados na literatura afim. Mais do que parâmetros de referência prescritivos, estes devem nos servir de estímulo ao exame empírico do instrumento. O ponto principal é que as muitas decisões a tomar rumo à adequabilidade psicométrica de um instrumento precisam de âncoras claras e previamente acordadas com os pares da comunidade científica. A literatura, por certo, se enriqueceria se estes pormenores se estendessem aos artigos de divulgação científica.

Uma questão a salientar é que, no contexto processual em tela, as análises multivariadas têm utilidade primordial como dispositivos diagnósticos. Sendo ferramentas de processo, devem atender às perguntas centrais postuladas a priori . Nesse sentido, é preciso distinguir as questões eminentemente qualitativas das quantitativas que envolvem estritamente a esfera técnico-metodológica. A terceira propriedade configural apresentada no Quadro 2 serve de exemplo. Mais do que simplesmente verificar se uma análise fatorial exploratória mostra uma carga cruzada, importa responder se efetivamente há violação de especificidade fatorial, o que seria antitético ao projetado na primeira fase, quando da elaboração do protótipo. A presença de uma carga cruzada de larga monta sugere ambiguidade no item em tela, que não seria exclusivo ao fator pressuposto e que, portanto, sua função como um “representante empírico” do mapa do construto não seria satisfeita. Aqui, a evidência quantitativa atende à qualitativa, sinalizando que há problema e necessidade de ação, seja modificando a semântica do item, seja substituindo-o por outro de melhor propriedade. Em nada diferentes, as demais propriedades demandam o mesmo olhar.

Para além das propriedades internas de itens e escalas sintetizadas no Quadro 2 , duas outras questões relacionadas merecem alusão por sua recorrência. A primeira diz respeito à presunção de invariância de medida (configural, métrica e escalar) 17 . A suposição de que o desempenho de um instrumento não varia em domínios populacionais diferentes é quase uma regra. No mais das vezes, assume-se tacitamente que o funcionamento do instrumento é consistente entre os diversos grupos populacionais investigados (e.g., gêneros, faixas etárias, escolaridades, estratos geográficos), de modo que as diferenças encontradas entre eles são tomadas como factuais e não decorrentes de problemas de mensuração. No entanto, esta é uma posição difícil de sustentar sem maiores evidências, uma vez que o funcionamento inconsistente de um instrumento em subgrupos populacionais pode conduzir a inferências espúrias e, no limite, a decisões e ações sanitárias ineficientes ou até mesmo danosas 20 . Há de se ter cuidado nessa direção, levando os programas de investigação sobre instrumentos de aferição um passo adiante. Não cabe apenas escrutinar suas propriedades, mas avaliá-las em diversos segmentos populacionais. Garantir invariância do instrumento em diferentes grupos populacionais é permitir comparações fidedignas.

Adjacente à invariância está a questão da equalização e ligação ( linking ) de instrumentos 22 . Trata-se da busca de métricas comuns a instrumentos que supostamente captam o mesmo construto, mas que possuem itens distintos e/ou com opções de resposta variadas 25 , 26 . Em ambas as situações há de se ter cuidado ao oferecer sínteses. Resultados de estudos podem não ser comparáveis se, mesmo focados em um mesmo construto, são realizados em domínios populacionais diferentes e com instrumentos distintos. Sem equalização, ferramentas de aferição podem carecer de sintonia métrica e escalar.

Também ligada às propriedades escalares de um instrumento está a adequação de agrupamentos quando se aplicam pontos de corte a um escore (seja bruto, formado pelo somatório dos escores dos itens componentes, seja baseado em modelos, como o são os escores fatoriais ou Rasch 27 , 28 ). Esse ponto merece atenção, especialmente no que diz respeito às abordagens frequentemente utilizadas em epidemiologia. Não é incomum categorizar um escore em um ou poucos grupos, muitas vezes o inflexionando na média, na mediana ou em algum outro ponto “estatisticamente interessante”. Esse procedimento, no entanto, não é desprovido de riscos, uma vez que a população de estudo não necessariamente é particionada em grupos homogêneos internamente e heterogêneos entre si. O conhecimento de especialistas sobre o objeto é certamente fundamental no processo de se especificar agrupamentos adequados, mas a busca da semelhança interna de grupos com distinção comparativa pode ser mais bem servida utilizando-se adicionalmente abordagens baseadas em modelos, tais como análises de classes latentes ou modelos de mistura finita 29 .

AVALIAÇÃO DA CONEXÃO CONSTRUTO-TEORIA

O Quadro 3 propõe uma tipologia, na linha do que seria a validade por teste de hipótese apresentada no início da década de 2010 pela iniciativa COSMIN ( COnsensus-based Standards for the selection of health Measurement INstruments ) 15 , 16 , 33 . Ao contrário da concisão aparente da tipologia, esta etapa da segunda fase de avaliação de um instrumento implica, de fato, um longo processo, talvez tão longo quanto caberia estudar o próprio construto em tela, em todas as suas relações de causas e efeitos. Revisitando outros textos 7 , 11 , valeria lembrar que determinar a validade de um instrumento corresponde, em última instância, ao estabelecimento da própria validade da teoria da qual faz parte o construto que o instrumento se propõe a medir. Um tanto circular e algo desalentador devido ao longo caminho que projeta, este raciocínio, por sua vez, nos alerta para o quão arriscado e imprudente é restringir o endosso e a aprovação de um instrumento a algumas poucas investidas de pesquisa. A solidificação e, por fim, o aval de adequabilidade de um instrumento requerem muitas testagens, seja no âmbito interno ao instrumento, seja de suas conexões externas.

a Referências de fundamentação: Streiner et al. 7 , Bastos et al. 3 , Reichenheim e Moraes 6 , Lissitz 70 , Armitage et al. 71 , Corder e Foreman 72 , Kline 19 , Little 61 , Hernán e Robins 5 , VanderWeele 35 .

Nessa direção, conforme sugere o Quadro 3 , validar externamente um instrumento vai de simples testes de associação entre as subescalas componentes até testes de intrincadas hipóteses sobre o construto e que a literatura entende como a rede nomológica das predições interligadas de uma teoria 5 , 7 , 34 , 35 . Seja qual for o nível de complexidade da investida externa, uma pergunta que se impõe – e que frequentemente surge no âmbito das publicações científicas – é quando um estudo de validade externa de um instrumento deve ser executado, dadas as etapas a serem antes superadas para melhor conhecer seus meandros. Vale investir em projetos de pesquisa na linha do que o Quadro 3 indica sem antes ter uma mínima evidência sobre a sustentabilidade das estruturas configural, métricas e escalares do instrumento? É preciso reconhecer que correlações entre escalas (e.g., do instrumento em tela e de outras que cubram o mesmo construto) podem perfeitamente se materializar, mesmo diante de múltiplas insuficiências psicométricas de âmbito interno. O que significariam estas correlações, sabendo-se, por exemplo, que o conjunto de itens não atende satisfatoriamente aos requisitos de especificidade fatorial, validade fatorial convergente e escalabilidade? A resposta baseada na mera correlação indicaria validade externa, mas restaria perguntar “de quê?”, se a capacidade de representação do construto é falha e pouco informativa. Não há resposta clara a essas questões, mas é preciso levantá-las antes de se proceder “cegamente” a estudos de validade externa. O timing dessas etapas é evidentemente da alçada de cada programa de investigação, mas o ditado “quem tem pressa, come cru” serve de lembrete: pouco tempo e esforço (e recursos!) investidos em uma etapa pode ser tempo e esforço (e recursos!) dobrados em outra posterior.

CONSIDERAÇÕES FINAIS

Com a leitura do presente artigo, deve ficar claro que o desenvolvimento de um instrumento de aferição envolve um processo extenso, compreendendo múltiplos estudos concatenados. Há de se notar que a trajetória pode ser ainda mais longa e tortuosa em se considerando os estudos de replicação ou quando certos estudos psicométricos suscitam questões que requerem respostas fundamentais que só a retomada da fase prototípica do desenvolvimento pode oferecer. Esse panorama contrasta sobremaneira com a forma como os investigadores em epidemiologia costumam abordar seus instrumentos de aferição. Como visto, ao contrário do que muitos supõem, evidências sobre a adequação de uma ferramenta de medida não se esgotam em um ou dois estudos sobre sua constituição dimensional, acompanhados, quiçá, da magnitude das cargas fatoriais encontradas. Esse alerta se estende também a acríticas análises de validade externa que, conforme mencionado na seção antecedente, requerem que a constituição interna do instrumento esteja minimamente cuidada.

E há também o desenvolvimento e o refino de versões para que as pesquisas realizadas em populações socioculturalmente distintas guardem comparabilidade e possam dialogar entre si. O processo de ATC não é menos intrincado do que o de um instrumento novo. Todas as fases e etapas se aplicam igualmente aqui. Aliás, um(a) pesquisador(a) realizando uma ATC frequentemente se depara com variadas lacunas no próprio programa de investigação original do instrumento. Por vezes, há problemas na execução dos estudos disponíveis; outras (muitas) vezes, diversas propriedades sequer foram estudadas. Nesse momento, o foco passa das equivalências ( cf. seção sobre Cenários de Pesquisa) para o cerne da própria estrutura do instrumento. Isso não é trivial, pois haverá sempre a ambivalência entre se tratar de um problema intrínseco da ferramenta e ser um problema no processo de ATC 6 , 11 . Seja como for, examinar um instrumento em outro contexto sociocultural demanda ainda mais tempo e esforços. Não é para menos que muitos entendem as instâncias de ATC como mais uma etapa de validação de construto 33 .

Uma questão que se coloca frequentemente é se todas as etapas precisam ser cumpridas para tornar o instrumento apto à utilização em pesquisa ou aplicação nos serviços de saúde. Esta é uma pergunta difícil de responder, mas alguns marcos podem nos guiar. Um já foi aventado na seção sobre as fases do processo: ter uma fase prototípica bem planejada e desenvolvida ajuda sobremaneira a obter resultados favoráveis na segunda grande fase do processo. Profundidade na primeira fase não somente contribui para se chegar a melhores propriedades psicométricas, mas também agrega eficiência, na medida em que vários problemas tendem a ser mitigados ou mesmo evitados precocemente. Cumpre lembrar que os estudos epidemiológicos na fase psicométrica, a rigor, costumam ser de grande porte e, logo, são raramente passíveis de replicações com vistas à resolução de anomalias emergentes.

Outro norte é recorrer aos fundamentos, lembrando sempre a essência de cada propriedade e o que significa sua violação. Por exemplo, sentiríamos firmeza em declarar um instrumento como válido e pronto para uso à luz de umas poucas análises fatoriais exploratórias – afirmando preliminarmente uma estrutura configural – e/ou alguns estudos correlacionando o(s) escore(s) da(s) (sub)escala(s) em teste com certas variáveis sociodemográficas – que ofereçam uma primeira evidência sobre a pertinência teórica? Dada a gama de possibilidades substantivas e processuais que visitamos, seria isto suficiente ou deveríamos adiar a utilização do instrumento e obter adicionais e diversas provas para apoiar sua validade? Reiteramos que não há resposta rápida e pronta, mas que, talvez, uma máxima possa nos ser útil à tomada de decisão: ainda que não estejamos preparados a deixar o ótimo atrapalhar o bom, ou mesmo deixar o bom atrapalhar o razoável, pode ser que valha a pena deixar o razoável atrapalhar o ruim. Embora seja uma perspectiva subjetiva – sempre a ser negociada entre pares –, se colocada em prática, possivelmente nos conduzirá a melhores instrumentos e, conforme já apontamos, a melhores resultados e comparações entre estudos ou ações de saúde.

O contínuo desenvolvimento, refinamento e adaptação de instrumentos de aferição deve ser visto como parte fundamental e integrada à pesquisa epidemiológica. A construção do conhecimento requer instrumental em patamares aceitáveis de validade e confiabilidade, à altura dos rigores comumente exigidos, por exemplo, na elaboração de desenhos de estudos e suas complexas análises. De nada adiantam meticulosidades e aprimoramentos nessas esferas se o diálogo entre as publicações e a apreciação de consistência das evidências científicas acabam falhando por conta da precariedade dos instrumentos utilizados. Sendo também produtos voltados ao uso coletivo, instrumentos de aferição demandam processos de desenvolvimento que pouco diferem dos encontrados para medicamentos ou outras tecnologias de saúde. E, como tal, merecem zelo e dedicação.

Financiamento: MER foi parcialmente apoiado pelo Conselho Nacional de Desenvolvimento Científico e Tecnológico do Brasil (CNPq - Processo 301381/2017-8). JLB foi parcialmente financiado pelo Conselho Nacional de Desenvolvimento Científico e Tecnológico do Brasil (CNPq - Processo 304503/2018-5).

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Research Instruments 

Educational research results in evidence based practices, put into action by the educational community.

Instruments allow programs to collect relevant data  related to a research problem, designed for  measuring their intended outcomes.  Various types of instruments may include surveys, tests, questionnaires, achievement / aptitude tests, observation forms, tally sheets, etc…

Use these following pages to guide you in locating

• Instrument(s) by name or acronym
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Finding Research Instruments: ERIC

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What is ERIC?

ERIC is an excellent database for searching the education literature.

• ERIC (EBSCO) This link opens in a new window This database, sponsored by the Institute of Education Sciences of the U.S. Department of Education, includes citations, abstracts, and full-text of scholarly journal articles, reports, and more related to all facets of education.

Important Definitions

• searchable research tool that includes records about a wide range of sources, primarily articles
• collection of information about a single item, usually an article, within a database; includes several fields
• section of a record that provides a specific piece of information about the item described (the title, the author, the abstract, etc.)

Truncation (*)

• the star or asterisk key tells the database to look for any ending of a word; one example: searching for measure* in a database would find the words measure, measures, and measurement

Searching By Topic

To find instruments about your research topic, use keywords about it in one or more of the search boxes. In the final box, try using this string of words: test* OR measure* OR survey* OR questionnaire* OR scale* OR batter* OR inventor* OR checklist* OR instrument* OR pretest* OR posttest* OR interview* . It's generally unwise to limit to any particular field here, since the name of a test may show up in the abstract or the identifier, so to be comprehensive you need to search both.

To narrow your results, if they're too broad, consider using the ERIC Thesaurus to find the appropriate descriptor for your topic.

Alternately, you can use additional keywords to reduce irrelevant results.

ERIC does have a Publication Type limit for Tests/Questionnaires , but it significantly narrows your search results. That may make it difficult to find test name options that you could try in another database, even if they don't show up in ERIC.

Searching By Title

As mentioned in the Searching By Topic box above, limiting to a specific field isn't your best option here, so try putting the name of your instrument (if you know it exactly) in quotation marks. You can use the acronym instead, if you know it.

Searching For Evaluations

Follow the instructions for either Searching By Topic or Searching By Name , depending on what you're trying to do. In the final box, put this string of words: "Test Reviews" OR "Test Reliability" OR "Test Validity" OR "Construct Validity" OR "Content Validity" and use the drop-down menu next to the box to select SU Descriptors . This tells ERIC to search the descriptor field for terms relating to evaluation of tests.

If you're searching by topic, this will give you considerably more results than a more specific search. As an alternative, if you want only test reviews, just use "Test Reviews" instead, still using the drop-down to choose SU Descriptors .

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Climate change research.

Science in Space: April 2024

Everyone on Earth is touched by the effects of climate change, such as hotter temperatures, shifts in rain patterns, and sea level rise. Collecting climate data helps communities better plan for these changes and build more resilience to them.

The International Space Station, one of dozens of NASA missions contributing to this effort, has multiple instruments collecting various types of climate-related data. Because the station’s orbit passes over 90 percent of Earth’s population and circles the planet 16 times each day, these instruments have views of multiple locations at different times of day and night. The data inform climate decisions and help scientists understand and solve the challenges created by climate change.

While crew members have little involvement in the ongoing operation of these instruments, they do play a critical role in unpacking hardware when it arrives at the space station and in assembling and installing the instruments via spacewalks or using the station’s robotic arm.

One investigation on the orbiting lab that contributes to efforts to monitor and address climate change is ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station ( ECOSTRESS ). It provides thermal infrared measurements of Earth’s surface that help answer questions about water stress in plants and how specific regions respond to climate change. Research confirmed the accuracy of ECOSTRESS surface estimates 1 and found that the process of photosynthesis in plants begins to fail at 46.7 degrees C (114 degrees F). 2 Average temperatures have increased 0.5 degrees C per decade in some tropical regions, and temperature extremes are becoming more pronounced. Rainforests are a primary producer of oxygen and, without sufficient mitigation of the effects of climate change, leaf temperatures in these tropical forests soon could approach this failure threshold.

The Total and Spectral Solar Irradiance Sensor ( TSIS ) measures total solar irradiance (TSI) and solar spectral irradiance (SSI). TSI is the total solar energy input to Earth and SSI measures the Sun’s energy in individual wavelengths. Energy from the Sun drives atmospheric and oceanic circulations on Earth, and knowing its magnitude and variability is essential to understanding Earth’s climate. Researchers verified the instrument’s performance and showed that it made more accurate measurements than previous instruments. 3,4 TSIS maintains a continuity of nearly 40 years of data on solar irradiance from space-based observations.

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The Global Ecosystem Dynamics Investigation ( GEDI ) observes global forests and topography using light detection and ranging (lidar). These observations could provide insight into important carbon and water cycling processes, biodiversity, and habitat. One study used GEDI data to estimate pan-tropical and temperate biomass densities at the national level for every country observed and the sub-national level for the United States. 5

Earth Surface Mineral Dust Source Investigation ( EMIT ) determines the type and distribution of minerals in the dust of Earth’s arid regions using an imaging spectrometer. Mineral dust affects local warming and cooling, air quality, rate of snow melt, and ocean plankton growth. Researchers demonstrated that data from EMIT also can be used to identify and monitor specific sources of methane and carbon dioxide emissions. Carbon dioxide and methane are the primary human-caused drivers of climate change. Increasing emissions in areas with poor reporting requirements create significant uncertainty in the global carbon budget. 6 The high spatial resolution of EMIT data could allow precise monitoring even of sources that are close together.

The station’s Orbiting Carbon Observatory-3 ( OCO-3 ) collects data on global carbon dioxide during sunlit hours, mapping emissions of targeted local hotspots. This type of satellite-based remote sensing helps assess and verify emission reductions included in national and global plans and agreements. Monitoring by OCO-3 and the Italian Space Agency’s PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite of 30 coal-fired power plants between 2021 and 2022 showed agreement with on-site observations. 7 This result suggests that under the right conditions, satellites can provide reliable estimates of emissions from discreet sources. Combustion for power and other industrial uses account for an estimated 59% of global human-caused carbon dioxide emissions.

The Stratospheric Aerosol and Gas Experiment III-ISS ( SAGE III-ISS ) measures ozone and other gases and tiny particles in the atmosphere, called aerosols, that together act as Earth’s sunscreen. The instrument can distinguish between clouds and aerosols in the atmosphere. A study showed that aerosols dominate Earth’s tropical upper troposphere and lower stratosphere, a transition region between the two atmospheric levels. Continuous monitoring and identification of these layers of the atmosphere helps quantify their effect on Earth’s climate. 8

An early remote sensing system, ISS SERVIR Environmental Research and Visualization System ( ISERV ), automatically took images of Earth to help scientists assess and monitor disasters and other significant events. Researchers reported that this type of Earth observation is critical for applications such as mapping land use and assessing carbon biomass and ocean health. 9

John Love, ISS Research Planning Integration Scientist Expedition 71

Search this database of scientific experiments to learn more about those mentioned above.

1 Weidberg N, Lopez Chiquillo L, Roman S, Roman M, Vazquez E, et al. Assessing high resolution thermal monitoring of complex intertidal environments from space: The case of ECOSTRESS at Rias Baixas, NW Iberia. Remote Sensing Applications: Society and Environment. 2023 November; 32101055. DOI: 10.1016/j.rsase.2023.101055.

2 Doughty CE, Keany JM, Wiebe BC, Rey-Sanchez C, Carter KR, et al. Tropical forests are approaching critical temperature thresholds. Nature. 2023 August 23; 621105-111. DOI: 10.1038/s41586-023-06391-z.

3 Richard EC, Harber D, Coddington OM, Drake G, Rutkowski J, et al. SI-traceable spectral irradiance radiometric characterization and absolute calibration of the TSIS-1 Spectral Irradiance Monitor (SIM). Remote Sensing. 2020 January; 12(11): 1818. DOI:  10.3390/rs12111818.

4 Coddington OM, Richard EC, Harber D, Pilewskie P, Chance K, et al. The TSIS-1 hybrid solar reference spectrum. Geophysical Research Letters. 2021 April 26; 48(12): e2020GL091709. DOI:  10.1029/2020GL091709

5 Dubayah R, Armston J, Healey S, Bruening JM, Patterson PL, et al. GEDI launches a new era of biomass inference from space. Environmental Research Letters. 2022 August; 17(9): 095001. DOI: 10.1088/1748-9326/ac8694.

6 Thorpe A, Green RD, Thompson DR, Brodrick PG, Chapman DK, et al. Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space. Science Advances. 2023 November 17; 9(46): eadh2391. DOI: 10.1126/sciadv.adh2391.

7 Cusworth DH, Thorpe A, Miller CE, Ayasse AK, Jiorle R, et al. Two years of satellite-based carbon dioxide emission quantification at the world’s largest coal-fired power plants. Atmospheric Chemistry and Physics. 2023 November 24; 23(22): 14577-14591. DOI: 10.5194/acp-23-14577-2023.

8 Bhatta S, Pandit AK, Loughman R, Vernier J. Three-wavelength approach for aerosol-cloud discrimination in the SAGE III/ISS aerosol extinction dataset. Applied Optics. 2023 May; 62(13): 3454-3466. DOI: 10.1364/AO.485466 .

9 Kansakar P, Hossain F. A review of applications of satellite earth observation data for global societal benefit and stewardship of planet earth. Space Policy. 2016 May; 3646-54.

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Educational and Psychological Instruments

• Finding tests and test info
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Education Librarian

Researchers use a variety of terms to describe the tools used to study human behavior, attitudes, ect. These terms include: survey, instrument, scale, questionnaire, test, measure, measurement, assessment, inventory, etc.

• There's no one-stop shop that contains all tests/measures for free.
• There may be hundreds of tests available for your research topic area. Tests may be free or commercialized.
• Choose an appropriate test for your research and use it ethically.

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If you just need to find a test quickly for a simple class assignment where nearly any professional test will do, try:

• APA PsycTests Limit to Full Text to see the results with tests included. more... less... APA PsycTests is a database of psychological tests and measures designed for use with social and behavioral science research.
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AU invests $500K in scientific instruments to enhance research & teaching

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ASHLAND — Ashland University has entered into a formal partnership with Shimadzu, a multinational leader in the manufacturing of precision scientific equipment, that will transform AU’s capability for research and teaching within the College of Arts and Sciences.

AU has acquired four new Shimadzu scientific instruments, valued at more than $500,000, that have been installed in the Kettering Science Center.

In addition, AU is now a SPARQ partner, which stands for Shimadzu Program for Academics, Research and Quality of Life, an exclusive, invitation-only opportunity of which few schools in the United States are granted access.

“I am delighted to work with Shimadzu Scientific Instruments to enhance the Kettering Labs because the SPARQ program represents a true partnership,” stated Katie Brown, Ph.D., dean of AU’s College of Arts and Sciences.

“Shimadzu has worked closely with our faculty and staff to ensure that the selection of instruments is catered to our student learning outcomes. Shimadzu also ensures that our faculty will have the support they need to make the most effective use of the new equipment in both teaching and research.

“These new instruments will significantly expand the topics and methods that our faculty and students can explore in their research projects.”

“We at Shimadzu are very excited for this SPARQ partnership with Ashland University and to see how the faculty and students expand their research experience. Ashland now has a state-of-the-art lab that ensures any testing needs are within their capabilities,” remarked Matthew Chaidez, regional manger of Shimadzu Scientific Instruments.

“I am personally most excited for the students. Having this level of instrumentation and experience as an undergraduate will be an invaluable tool to prepare them for their futures in the science field and ensure they are set apart from their peers at other universities.

“Hopefully in the near future, we have a few AU graduates come join the Shimadzu team and help lead the way for our future as well.”

The new lab equipment will benefit all students and faculty who use the Kettering Science Center, especially those in the biology, chemistry, environmental science, geology, physics and toxicology academic programs.

Specifically, the four new instruments are:

• Liquid Chromatography Mass Spectrometer, a modern mass spectrometer offering fast and accurate detection of trace chemical compounds in pharmaceutical samples, environmental pollutants and other mixtures
• Nexera Ion Chromatography System, which can process water samples, a key component for environmental science, analytical chemistry and geochemistry courses and research
• Nexera Gel Permeation Chromatography System, which possesses polymer-specific analysis tools that will elevate research in a variety of applications and complies with American Chemical Society-approved programs
• Inductively Coupled Plasma Atomic Emission Spectrometer, a device that measures concentrations of many metals and solutions at once, which will enhance current research efforts in toxic metals found in consumer products, environmental water and social studies and geochemical measurements

Jeff Weidenhamer, the Trustees’ Distinguished Professor of Chemistry, is thrilled to start working with the new instruments, which will make his  groundbreaking research  more efficient and AU even more appealing to aspiring scientists.

“One of the things we pride ourselves on is to give students hands-on experience with state-of-the-art equipment. Students come here because of the instrumentation we have in lab that they know they are going to get trained on,” said Weidenhamer. “This will help us to continue to attract excellent students.”

As for the SPARQ partnership, it will serve as a bridge between academic research and applications development. AU faculty and students will consult and work with Shimadzu’s scientists and industry experts on various projects. This unique educational opportunity will be mutually beneficial.

“It is an honor to be part of the Shimadzu SPARQ program,” said Rebecca Corbin, Ph.D., chair of the department of chemistry, geology and physics at AU. “Not only will the new equipment help to sustain and to expand our chemical instrumentation laboratory, but this initiative is a great step forward in our deep-rooted efforts to provide hands-on opportunities for scientific study,”

“We are excited about this truly transformative partnership.”

Shimadzu selected AU as an award recipient because of its proven track record of outstanding science student preparation and its potential for tremendous growth.

“Shimadzu is delighted to establish this partnership with Ashland University. Through this collaboration, we aim to elevate their already outstanding chemistry program by providing cutting-edge instrumentation,” said Dave Jorissen, sales director at Shimadzu.

“Our commitment extends beyond technology; we look forward to fostering continued collaboration with Ashland’s incredibly talented students and faculty. We view this as the beginning of a long and mutually beneficial relationship.”

This partnership and the new equipment were made possible by a lead gift from Dawn Swit ’92, who labeled it an “easy decision” to be a part of.

“Being in a science-based field, I understand the company or academic institution … is only as good as the level of the equipment that they have,” explained Swift, who recently retired from a highly successful career in the information technology and insurance business.

“If a (student’s) resume doesn’t show that they’ve worked with the equipment their industry wants them to have, they are at a disadvantage.

“So, this will not only help (Ashland) attract students, but it will help the graduates get better jobs. And, Shimadzu seems like a great partner. Meeting with the rep and the engineer, I’m even more excited what this will mean.”

During an April 13 ribbon-cutting ceremony and visit to AU, Swit was excited to see how “the campus has really continued to grow” and looks “even more amazing than when (she) was here.”

And, she is very much looking forward to seeing the impact of the Shimadzu partnership.

“I love it. I’m so excited. It gives me goosebumps to think that there are going to be students in here grinding away at 11 o’clock at night on a Tuesday trying to work on their samples and finish a project to be able to turn in. It’s fantastic,” she said.

Also making significant donations to the Shimadzu partnership were Jeff Gorman, Sherrill Hudson, Richard Metz and Donald Senz, as well as the dean’s office of the College of Arts and Sciences and the department of chemistry, geology and physics.

Shimadzu Scientific Instruments

Shimadzu Scientific Instruments (SSI) is the American subsidiary of Shimadzu Corporation, headquartered in Kyoto, Japan.

Founded in 1875, Shimadzu is a $3.5 billion multinational corporation with three major divisions: Medical Diagnostics, Aerospace/Industrial and Analytical Instruments. In the United States, SSI has a network of more than 50 locations providing local and regional sales, service and technical support.

Visit  ssi.shimadzu.com  for more information.

Source Media Properties used an experimental artificial intelligence tool to locate the source data and develop the first draft of this article. A professional editor reviewed the accuracy and writing before publishing.

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NASA Mission Excels at Spotting Greenhouse Gas Emission Sources

Flaring, in which excess natural gas is intentionally burned into the air, is one way methane is released from oil and gas facilities. NASA’s EMIT mission, in more than a year in operation, has shown a proficiency at spotting emissions of methane and other greenhouse gases from space.

Since launching 16 months ago, the EMIT imaging spectrometer aboard the International Space Station has shown an ability to detect more than just surface minerals.

More than a year after first detecting methane plumes from its perch aboard the International Space Station, data from NASA’s EMIT instrument is now being used to identify point-source emissions of greenhouse gases with a proficiency that has surprised even its designers.

Short for Earth Surface Mineral Dust Source Investigation, EMIT was launched in July 2022 to map 10 key minerals on the surface of the world’s arid regions. Those mineral-related observations, which are already available to researchers and the public, will help improve understanding of how dust that gets lofted into the atmosphere affects climate.

Detecting methane was not part of EMIT’s primary mission, but the instrument’s designers did expect the imaging spectrometer to have the capability. Now, with more than 750 emissions sources identified since August 2022 – some small, others in remote locations, and others persistent in time – the instrument has more than delivered in that regard, according to a new study published in Science Advances .

“We were a little cautious at first about what we could do with the instrument,” said Andrew Thorpe, a research technologist on the EMIT science team at NASA’s Jet Propulsion Laboratory in Southern California and the paper’s lead author. “It has exceeded our expectations.”

EMIT identified a cluster of 12 methane plumes within a 150-square-mile (400-square-kilometer) area of southern Uzbekistan on Sept. 1, 2022. The instrument captured the cluster within a single shot, called a scene by researchers.

By knowing where methane emissions are coming from, operators of landfills, agriculture sites, oil and gas facilities, and other methane producers have an opportunity to address them. Tracking human-caused emissions of methane is key to limiting climate change because it offers a comparatively low-cost, rapid approach to reducing greenhouse gases. Methane lingers in the atmosphere for about a decade, but during this span, it’s up to 80 times more powerful at trapping heat than carbon dioxide, which remains for centuries.

Surprising Results

EMIT has proven effective at spotting emission sources both big (tens of thousands of pounds of methane per hour) and surprisingly small (down to the hundreds of pounds of methane per hour). This is important because it permits identification of a greater number of “super-emitters” – sources that produce disproportionate shares of total emissions.

The new study documents how EMIT, based on its first 30 days of greenhouse gas detection, can observe 60% to 85% of the methane plumes typically seen in airborne campaigns.

In a remote corner of southeastern Libya, EMIT on Sept. 3, 2022, detected a methane plume that was emitting about 979 pounds (444 kilograms) per hour. It’s one of the smallest sources detected so far by the instrument.

From several thousand feet above the ground, methane-detecting instruments on aircraft are more sensitive, but to warrant sending a plane, researchers need prior indication that they’ll detect methane. Many areas are not examined because they are considered too remote, too risky, or too costly. Additionally, the campaigns that do occur cover relatively limited areas for short periods.

On the other hand, from about 250 miles (400 kilometers) altitude on the space station, EMIT collects data over a large swath of the planet – specifically the arid regions that fall between 51.6 degrees north and south latitude. The imaging spectrometer captures 50-mile-by-50-mile (80-kilometer-by-80-kilometer) images of the surface – researchers call them “scenes” – including many regions that have been beyond the reach of airborne instruments.

This time-lapse video shows the Canadarm2 robotic arm of the International Space Station maneuvering NASA’s EMIT mission onto the exterior of the station. Extraction from the SpaceX Dragon spacecraft began around 5:15 p.m. PDT on July 22 and was completed at 10:15 a.m. PDT on July 24. Portions of the installation have been omitted, while others have been speeded up.

“The number and scale of methane plumes measured by EMIT around our planet is stunning,” said Robert O. Green, a JPL senior research scientist and EMIT’s principal investigator.

Scene-by-Scene Detections

To support source identification, the EMIT science team creates maps of methane plumes and releases them on a website , with underlying data available at the joint NASA-United States Geological Survey Land Processes Distributed Active Archive Center ( LP DAAC ). The mission’s data is available for use by the public, scientists, and organizations.

Since EMIT began collecting observations in August 2022, it has documented over 50,000 scenes. The instrument spotted a cluster of emissions sources in a rarely studied region of southern Uzbekistan on Sept. 1, 2022, detecting 12 methane plumes totaling about 49,734 pounds (22,559 kilograms) per hour.

In addition, the instrument has spotted plumes far smaller than expected. Captured in a remote corner of southeastern Libya on Sept. 3, 2022, one of the smallest sources so far was emitting 979 pounds (444 kilograms) per hour, based on estimates of local wind speed.

More About the Mission

EMIT was selected from the Earth Venture Instrument-4 solicitation under the Earth Science Division of NASA’s Science Mission Directorate and was developed at NASA’s Jet Propulsion Laboratory, which is managed for the agency by Caltech in Pasadena, California. The instrument’s data is available at the NASA Land Processes Distributed Active Archive Center for use by other researchers and the public.

To learn more about the mission, visit:

https://earth.jpl.nasa.gov/emit/

News Media Contact

Andrew Wang / Jane J. Lee

Jet Propulsion Laboratory, Pasadena, Calif.

626-379-6874 / 818-354-0307

[email protected] / [email protected]

• Texas Instruments-stock
• News for Texas Instruments

Analysts Conflicted on These Technology Names: Enphase Energy (ENPH), Texas Instruments (TXN) and Super Micro Computer (SMCI)

Companies in the Technology sector have received a lot of coverage today as analysts weigh in on Enphase Energy ( ENPH – Research Report ), Texas Instruments ( TXN – Research Report ) and Super Micro Computer ( SMCI – Research Report ).

Enphase Energy (ENPH)

In a report released today, Sophie Karp from KeyBanc maintained a Hold rating on Enphase Energy. The company’s shares closed last Tuesday at $113.48.

According to TipRanks.com , Karp is a 4-star analyst with an average return of 2.8% and a 52.2% success rate. Karp covers the Utilities sector, focusing on stocks such as Constellation Energy Corporation, Edison International, and Consolidated Edison.

Enphase Energy has an analyst consensus of Moderate Buy, with a price target consensus of $126.96, representing a 15.5% upside. In a report issued on April 17, DZ BANK AG also initiated coverage with a Hold rating on the stock with a $116.00 price target.

See the top stocks recommended by analysts >>

Texas Instruments (TXN)

KeyBanc analyst John Vinh maintained a Buy rating on Texas Instruments today. The company’s shares closed last Tuesday at $165.47.

According to TipRanks.com , Vinh is a 5-star analyst with an average return of 18.8% and a 60.2% success rate. Vinh covers the Technology sector, focusing on stocks such as Advanced Micro Devices, Lattice Semiconductor, and indie Semiconductor.

Currently, the analyst consensus on Texas Instruments is a Hold with an average price target of $167.45, implying a 2.7% upside from current levels. In a report issued on April 15, Evercore ISI also initiated coverage with a Buy rating on the stock with a $213.00 price target.

Super Micro Computer (SMCI)

KeyBanc analyst Thomas Blakey initiated coverage with a Hold rating on Super Micro Computer today. The company’s shares closed last Tuesday at $761.86.

According to TipRanks.com , Blakey is a 4-star analyst with an average return of 5.2% and a 49.1% success rate. Blakey covers the Technology sector, focusing on stocks such as Zoom Video Communications, CommVault Systems, and Juniper Networks.

The word on The Street in general, suggests a Moderate Buy analyst consensus rating for Super Micro Computer with a $1047.45 average price target, implying a 43.5% upside from current levels. In a report issued on April 19, Wells Fargo also maintained a Hold rating on the stock with a $960.00 price target.

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Americans feel favorably about many federal agencies, especially the Park Service, Postal Service and NASA

As President Joe Biden and the new Republican majority in the U.S. House of Representatives face off over the debt ceiling and government spending, more Americans say they have favorable than unfavorable opinions of many agencies and departments of the federal government.

Americans view 14 of 16 federal agencies more favorably than unfavorably, according to a survey of 10,701 adults conducted March 13-19 by Pew Research Center. Of those 14 agencies, 11 have net favorable ratings of 15 points or more.

Topping the list are the National Park Service (81% favorable), the U.S. Postal Service (77%) and NASA (74%). Smaller majorities have favorable impressions of other agencies, including the Social Security Administration (61% favorable) and the Department of Health and Human Services (HHS, 55%).

Americans have mixed views of the Department of Education (45% favorable, 47% unfavorable) and the Federal Reserve (43% favorable, 37% unfavorable, 20% unsure). The least popular federal agency of the 16 asked about is the IRS. About half of Americans (51%) have an unfavorable opinion of this agency, while 42% have a favorable view.

Pew Research Center regularly conducts surveys to gauge the public’s attitudes about the federal government, including government agencies and departments. For this analysis, we surveyed 10,701 adults from March 13-19, 2023. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for the analysis and its methodology .

Agencies viewed favorably in this online survey were also among the most favorably viewed in past Pew Research Center surveys conducted by telephone. However, because of differences in survey mode and question wording, the specific percentages from past telephone surveys and this web survey are not directly comparable. (Refer to the drop-down box below for more details.)

This survey is the first time Pew Research Center has measured the public’s attitudes about federal government agencies on our online American Trends Panel . Previous surveys measuring views of federal agencies were conducted by telephone.

The findings in the current survey are not directly comparable with those past surveys for two reasons:

1. This survey uses different question wording than past telephone surveys. Telephone respondents had to volunteer that they did not have an opinion about an agency, while online survey respondents receive an explicit “not sure” response option. This generally results in a larger share of respondents declining to offer an opinion.

2. Surveys conducted by telephone or online often produce different results because respondents at times answer similar questions differently across modes. This is called a “mode effect.”

These two factors mean that point estimates (for instance, the share of respondents expressing a favorable opinion about a single agency between this survey and a prior phone survey) should not be directly compared to measure change over time, as the differences between the two would conflate mode and question wording differences with change over time. Despite this, some broad comparisons can be made: For example, if a wide partisan gap is evident for one agency that was not apparent in past surveys, whereas the partisan gap is relatively stable for other agencies, that change is likely not only a result of the transition from telephone to online polling.

Republicans have mostly negative views of the CDC, Department of Education

There are wide partisan gaps in Americans’ views of federal agencies. Democrats and those who lean toward the Democratic Party hold consistently favorable views of all 16 agencies asked about, while Republicans and those who lean toward the Republican Party express more unfavorable than favorable views for 10 of the agencies.

The partisan divisions in favorability are deepest for the Centers for Disease Control and Prevention, or CDC (80% favorable among Democrats vs. 31% among Republicans); the Environmental Protection Agency, or EPA (74% vs. 36%); and the Department of Education (62% vs. 29%). Republicans’ and Democrats’ views are also deeply divided over the Department of Transportation, HHS, the FBI, the IRS, the Federal Reserve and other agencies.

In contrast, there is more partisan agreement on the Department of Veterans Affairs (56% favorable among Republicans vs. 57% among Democrats); the National Park Service (81% vs. 84%); the Postal Service (73% vs. 82%); and NASA (71% vs. 79%). Among Democrats, the CDC and EPA receive some of the highest net favorability ratings. Eight-in-ten Democrats give a favorable rating to the CDC compared with 15% who see the agency unfavorably – for a 65 percentage point net advantage. For the EPA, 74% of Democrats see the agency favorably – 62 points more than the share who see it unfavorably. Democrats view the IRS least favorably of the 16 federal agencies: They are only 13 percentage points more likely to view it favorably than unfavorably (53% vs. 40%).

Republicans are much less favorable toward most federal agencies than Democrats. However, the agencies that Republicans feel most favorably toward are the National Park Service (72-point net favorability), NASA (58 points) and the Postal Service (48 points).

While it is not possible to make direct percentage point comparisons to past surveys due to a shift in survey mode, Republicans have substantially more negative than positive views of a majority of the agencies today than in the past.

Republicans’ negative opinions of the CDC, in particular, appear to reflect a shift since the early days of the coronavirus outbreak . Past Pew Research Center surveys have shown that Republicans have been especially critical of the CDC’s handling of the virus. Last September , just 32% of Republicans said that public health officials such as those at the CDC had done an excellent or good job in responding to the COVID-19 outbreak, compared with 73% of Democrats. In March 2020, at the start of the pandemic, large majorities of Republicans (84%) and Democrats (74%) had expressed positive views of the CDC’s performance.

Note: Here are the questions used for the analysis and its methodology .

• Federal Government
• Politics & Policy

J. Baxter Oliphant is a senior researcher focusing on politics at Pew Research Center

Andy Cerda is a research assistant focusing on politics at Pew Research Center

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