a definition of research instrument

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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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The scope of the study is defined at the start of the study. It is used by researchers to set the boundaries and limitations within which the research study will be performed.

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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

In the field of research, there are endless possibilities for experiments, all involving unique tools to carry out the work involved to answer the questions. The many requirements of a researcher make it hard for everyone to know every tool available, especially as technology advances at such an exponential rate.

Although every scope of science is different from the next, one thing they all have in common is the need for research instruments to help carry out the experiments to search for knowledge expansion. Tools, equipment, software, and intellectual property are crucial components of every scientist’s daily life. Each of these pieces plays an integral role in filling in the missing gaps and puzzle pieces of solving answers, and research instruments have an essential role above all the rest. Understanding what a research instrument is and what’s available to you helps you as a scholar make informed decisions and keep records that track the usage of the tools so other researchers can emulate your work.

What is the Definition of “Research Instrument”?

It might seem like calling one tool a research instrument and another something else wouldn’t be a big deal, but as a scholar, it can mean the difference between obtaining funding and losing it. When you list the instruments you will be using in your experiment, it must look like you know what you’re doing. Putting one tool in the wrong category is a mistake that can be costly.

The term “research instrument” refers to any tool that is used by a scientist to obtain, measure, and analyze data. The data is sourced from subjects included in the research experiment and focused on the topic. 

The instruments used have various roles. There are different tools that help you conduct quantitative, qualitative, and mixed studies. How you choose the instrument depends on what type of study you’re performing. However, whatever you use has to be described in the Methods section of your research paper. The more thoroughly you explain it, especially if you have created your own instrument, as in a survey, the better likelihood that someone else can repeat your study for authenticity.

In some cases, you may have to request permission to use the instrument, and this should be acknowledged in your paper so other scholars know they’ll have to do the same.

Characteristics of Solid Research Instruments

Whatever equipment you choose to use in your work, it must have consistent characteristics that can stand up under intense scrutiny. Should your final outcome end up having significant impactful consequences, you don’t want the choice of instrument you used to send the whole experiment falling down.

Keep these tips in mind as you determine the research instruments that will get you through your experiment:

• They must be valid and reliable (the same results occur repetitively).
• Use instruments that use a conceptual framework to do the job.
• The tools have to be able to gather the data that pertains to the research topic and they should help you to test the hypothesis or answer the research questions being investigated.
• Ensure all tools withstand scrutiny of bias and are appropriate in the context in which you are using them. Try to include tools that reflect the culture and diversity impacted by the research.
• In your methodology section, include clear, concise directions on how to use any uncommon instruments or instruments that are predominantly used in your field of study.

Choosing the right instrument makes the work easier. Choosing the wrong one, though, can be damaging to the whole project.  

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Research Instruments: Definition, Functions, Types, and Examples

Research Instruments – When writing scientific papers, research instruments are a part that cannot be missed. You will not be able to do research without determining the instrument first. For this reason, understanding research instruments is very important in the process of writing scientific papers such as theses, theses, dissertations, or research reports.

Table of Contents

Given the importance of research instruments, you should study them too. The reason is, as a student or researcher you will often write scientific papers. Automatically, you will also do research. Well, when researching something, you have to make instruments. In order for the process of writing scientific papers and determining instruments to run well, you should first pay attention to the following reviews.

Definition of Research Instruments

In general, research instruments are tools used to obtain research data. Without instruments, you will not be able to collect the data needed in research. If the data is not available, the research will not be carried out.

It should not be arbitrary, there is a separate way when determining the research instrument. As is known, research is scientific in nature, so the instrument must be measured and tested scientifically. If not, the research can be questioned and simply broken.

Basically, qualitative and quantitative research instruments are different. However, before discussing the differences between the two, it is better to look at the meaning of the instrument according to the experts below. The definitions below will give you an idea of ​​the research instrument.

1. Suharsimi Arikunto

Research instruments are tools used by researchers when collecting data. The goal is to make research more systematic and easy.

2. Ibn Hajar

The research instrument is a measuring tool used to obtain quantitative information that contains objective and character variables. The data or information in question includes:

• Quantitative data, namely the type of data related to the amount or quantity in the form of numbers, so that the data is counted and symbolized in the form of certain measurements.
• Qualitative data, namely the type of data related to quality values, for example very good, good, moderate, good, sufficient, lacking, and so on.
• Nominal data, ordinal data, and interval or ratio data.
• Primary data or secondary data.

3. Suryabrata

The research instrument is a tool used to record the state or activity of psychological attributes. The term psychological attribute is indeed less familiar to the layman. These attributes are divided into two, namely cognitive attributes and non-cognitive attributes. Cognitive attributes are associated with questions, while non-cognitive attributes are associated with statements.

4. Notoatmodjo

Research instruments are the tools used to obtain or collect data. This can be done by using questionnaires, observation forms, other forms related to data recording, and others.

Instruments in research are tools used by researchers to measure social and natural phenomena as they exist in research variables.

6. Sukmadinata

The instrument in the research is a test that has the characteristics of being able to measure informants through a number of questions in the research.

Instruments in research are tools used in data collection activities and research information. According to him, research activities are measurement activities, so they must use valid and good measuring instruments.

Some of the experts above do have different views. However, from the various definitions according to these experts you can find similarities. The various meanings and definitions are expected to make you able to better understand the meaning and function.

Well, how about you guys? After seeing some of these definitions, you can take the general definition right? In simple terms, instruments in research can be interpreted as tools or methods used in data collection.

As previously mentioned, quantitative research instruments and qualitative research instruments are not the same. In qualitative research, the data collection instrument is the researcher himself. That is, researchers who observe, ask, hear, and retrieve research data.

Researchers are required to obtain valid data, so that the data obtained is not arbitrary or can be accounted for. For this reason, the condition of the information must be clear and in accordance with the needs. This needs to be done so that the data collected can be recognized as true.

Meanwhile, the data obtained in quantitative research is usually by using a questionnaire or questionnaire. The data is quantified so that it can be processed statistically. If the data obtained deviates from statistical provisions, it can be ignored. Broadly speaking, the difference between the two lies in the type of data obtained. Qualitative data is in the nature of statements, while quantitative data is in the form of numbers or symbols that can be processed statistically.

Functions of Research Instruments

Research instruments have a very important function in the research process, which is used as a tool in collecting data needed in a study. With the existence of research instruments, it will know the data resources to be examined and the types of data, data collection techniques, data collection instruments, the steps for preparing the research instruments and knowing the validity, reliability, level of difficulty of differentiating power, and distractors of data in research. .

A good instrument has certain criteria in research, so as to produce good quality research data as well. Vice versa, instruments that do not have good criteria in research will produce poor research data quality as well.

It is often found that research data do not match the expected results. This is caused by a discrepancy between the theory used as a basis and the instruments used to measure variable characteristics. In order for the research instrument to carry out its functions properly, the instrument must be prepared according to the theory used in the research.

The research instrument is derived from the theories raised in the research. Therefore, the selection of the theoretical basis is to really consider the characteristics of the research variable data to be studied. Instruments derived from the theory used will produce data in accordance with the basic concepts outlined in the theory.

Types of Research Instruments

There are several types of research instruments that are usually used by researchers. This instrument can be used for research and writing scientific papers such as theses, theses, dissertations, reports, and so on. Research instruments are also used for qualitative research and quantitative research.

The following are some of the research instruments:

1. Questionnaire

What is a questionnaire? Questionnaire is an instrument that contains a list of questions. Usually used to collect research data from respondents. The questionnaire contains a series of questions that are structured and not. If the questionnaire is wrong, the research results will also be wrong. For this reason, the questionnaire must be formed and designed in a valid, reliable, and not fake. This is done so that the data obtained can be validated.

According to Popoola, a good questionnaire has criteria, namely:

• Questions should not be ambiguous and should have one interpretation.
• Questions should be easy to understand.
• Questions must be able to have a precise answer.
• Questions should not contain words that are not clear in meaning.
• Questions should not require strict calculations.
• The questions do not require the respondent to decide on a classification.
• Questions should not trigger biased answers.
• Questionnaires should not be too long.
• Questions are not too wordy.
• The questionnaire must include the right object.

When compared with other types of instruments, the questionnaire has the advantage of hiding the personal data of the respondent; so the respondent can be anonymous. The data collected can be large in a relatively short time.

It’s just that, kueseiner was not free from weaknesses. Sometimes some of the questions in the questionnaire are confusing and cannot be classified. This is because the researcher is not in place to explain questions that are difficult for the respondent.

2. Interview

Interviews are one of the research instruments that are often used for qualitative research. In interviews, researchers collect information from respondents through verbal interaction. Previously the researcher prepared a list of structured questions related to research. The researcher then met with the resource persons and asked questions.

Tools and equipment that can be used during the interview period are tape recorders, paper, pens, laptops, and others. Interviews can be conducted in person or by telephone or electronic mail system (e-mail).

The main advantage of the interview method is that it produces a high response rate. In addition, the interviews were more representative of the entire study population. In addition, the personal contact between the researcher and the respondent allows the researcher to explain confusing and ambiguous questions in detail.

Just like the questionnaire, the interview was not without its weaknesses. This instrument has a weakness, namely the number of sources reached is not large due to limited time and research staff.

3. Observation

The next type of instrument is observation. This method is used by a researcher to observe individual behavior or situation. So far, there are two types of observation, namely participant observation and non-participant observation. In participant observation, the researcher is a member of the group to be observed.

Accurate and timely results will be obtained by researchers, but sometimes have problems with bias. Whereas in non-participant observation, the researcher is not a member of the group to be observed. So the results are more feasible because they are free from bias but have problems with imprecision and delayed results.

The advantages of the observation method are that it is more flexible and cheaper to run. This method requires less active cooperation than observed and the results can be relied upon for research activities. However, Akinade & Owolabi emphasized that the observation method is a popular tool in research, especially in the behavioral and social sciences.

This method requires specific skills to make and evaluate behavioral observations in research. When observing behavior, the first thing you should do is develop a category of behavior (coding scheme). This method involves identifying specific attributes that will provide clues to the problem at hand.

4. Focus Group Discussion (Focus Group Discussion)

Have you ever had an FGD? Yes, the research instrument in the form of this discussion can also be used to obtain data. This data collection instrument allows the researcher to obtain data from a large group of people at the same time. This method is different from the interview method.

If in the interview method the researcher focuses on one person at a time, then in the focus group discussion method, the researcher obtains data from a large number of people for his research activities. Usually the focus group discussion method is very popular when conducting research related to behavioral (behaviour), library and information science, archival science, records and information technology.

In the FGD, a researcher must identify key informants who can be contacted. The goal is to obtain proper information about the variables studied in the study. This approach is used to produce qualitative research data in explaining a phenomenon that is being researched or investigated.

Another condition, FDG membership may not be more than 10 people. It is like a mini-conference, where group members can gather in a conducive location. Before carrying out the FGD, the researcher must first obtain consent from the participants. In addition, the researcher must design an FGD guide which usually contains an outline to capture the variables of interest.

The main advantage of this method is that it adds credibility and originality to research activities. Meanwhile, the challenges of the FGD method include too much cost to do, too much time to do, and some respondents may not be free to contribute.

5. Experiment or Trial

The next type of data collection is experimentation. This method takes place in both pure and applied science research. So the researchers conducted several experiments in a laboratory setting to test some of the reactions that might occur in the object of study.

The advantage of the experimental method is that it produces direct data, the results are persistent and error-free if it is carried out properly under normal conditions or circumstances. The downside is that it is quite expensive. When in laboratory studies the chemicals used can cause permanent damage if they are handled carelessly.

Tests can be in the form of a series of questions, exercises, worksheets and so on which have the purpose of measuring skills, intelligence, abilities and talents possessed by an individual or group that is the subject of research.

The test can later be in the form of standardized questions that require research subjects to answer them in order to obtain certain results. Examples include personality tests, talent interest tests, academic potential tests, achievement tests, and so on.

7. Multilevel Scale

A multilevel scale is also called a rating, which is an objective measure that is made scalable or multilevel. This instrument makes it easy for researchers to provide an overview of appearance which can then indicate the frequency of appearance of certain traits.

This instrument is also useful for obtaining a quantitative description of certain aspects of an item in the form of an ordinal scale such as very good, good, moderate, not good, and very bad.

8 . Documentation of Research Instruments

Documentation refers to written items. This instrument allows researchers to obtain data through research on written objects, such as books, magazines, diaries, artifacts, videos and so on. This instrument was developed in research with a content analysis approach. Therefore, it is usually used in research such as historical evidence, the legal basis for a regulation, and so on.

Examples of Research Instruments

This example is in the form of an interview method. Before collecting data, researchers must prepare a list of questions as below.

Appendix 1. Interview Draft (Research Instrument)

Researchers have a role as an instrument of data collection. In collecting the data, assistive devices were also used. The tool used is an interview guide (interview guide). In this case, the researcher conducted interviews with Mr. H. Abu Bakar as the manager of the Manba’ul ‘Ulum Islamic Boarding School Cooperative and Nina Zuliani as bookkeeper. The interview draft used is as follows:

Draft Interview for Mr H. Abu Bakar

• Regarding the financing products available at the Manba’ul ‘Ulum Islamic Boarding School Cooperative, which profit-sharing financing can dominate all existing financing?
• What is the process of doing mudharabah financing at the Manba’ul ‘Ulum Islamic Boarding School Cooperative?
• What is the intent and purpose of applying the concept of mudharabah ?
• What is the target market for mudharabah distribution ?
• What type of financing (business) is financed by mudharabah financing ?
• What policies are taken to avoid the risk of mudharabah financing ?
• What is the profit sharing system for mudharabah financing ? Is it different for each type of business, and will the financing period also affect the profit sharing of the business?
• When calculating margin distribution, is it in percentage or nominal form?
• What is the system and procedure for payment and settlement of mudharabah financing ?
• During the implementation of the mudharabah concept , what obstacles were sufficient to impede the implementation process?

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Research Methodologies: Research Instruments

• Research Methodology Basics
• Research Instruments
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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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CINAHL (Cumulative Index to Nursing and Allied Health Literature): Research Instruments

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What are Research Instruments?

In CINAHL, what are Research Instruments? http://support.epnet.com/knowledge_base/detail.php?id=3099 The text below copied from Ebsco.

"Research Instruments are measurement tools (for example, questionnaires or scales) designed to obtain data on a topic of interest from research subjects. Research instrument records are researched and created by CINAHL staff and these provide information about the research instrument, including information such as the purpose of the instrument, the population addressed, the variables measured, and more. CINAHL Plus includes research instrument records, research instrument validation records, and research instrument utilization records. CINAHL includes just research instrument records.

Research Instrument Records - provide details on validation and utilization of research instruments. The records indicate which studies have used a specific research instrument and include the purpose/variable measured, sample population, methodology, other instruments, items and questions, where the original study was mentioned and how to obtain the actual research instrument.

Research Instrument Validation and Utilization Records - provide details on the validation and utilization studies of each instrument. They include the purpose/variable measured, sample population, methodology, other instruments, items and questions and the source for the instrument."

A consise and helpful pdf on this topic is Finding Research Instruments and Questionnaires in CINAHL by Duke University.

Locate a Survey or Instrument in Cinahl

Use the Cinahl Heading  "Research Instrument" to see what is available. If you choose the main subject heading of  "Research Instrument" remember to click "Explode" - this means you want all the narrower aspects of this main subject heading, like Instrument by Name and Instrument by Type, etc.

You can select all available research instruments, or you can click on Research Instruments to see more specific aspects of this topic, like Instrument by Type.

• To find articles about instruments, select Instrument By Name or Instrument By Type
• To find articles about how to develop or validate instruments , select Instrument Construction , Instrument Scaling or Instrument Validation

After you have made your selection, click on "Search Database." 

Cinahl will run a search based on this selection and you will return to the main search screen. In the first search box you can see that our "Research Instruments" search has been added. Now, add your own terms in the next search box to see what instruments are available related to your topic.

Search for a Known Survey Instrument

There are many searchable fields in Cinahl. One field is Instrumentation. If you know the name of your instrument, you can enter that term or phrase and then select "IN Instrumentation" from the drop down menu.

Start With a Topic and Limit to Research Instruments

If you want to limit a subject search to research instruments, click edit from the Search History . This will open a menu of search limits.

The Edit Search menu is quite extensive. Look for the Publication Type on the right side of the screen.

You will want to limit your selection to

• Questionnaire/Scale
• Research Instrument(s)

You can choose more than one option by holding down the control key (PC) or command key (MAC).

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• 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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Understanding and Evaluating Survey Research

A variety of methodologic approaches exist for individuals interested in conducting research. Selection of a research approach depends on a number of factors, including the purpose of the research, the type of research questions to be answered, and the availability of resources. The purpose of this article is to describe survey research as one approach to the conduct of research so that the reader can critically evaluate the appropriateness of the conclusions from studies employing survey research.

SURVEY RESEARCH

Survey research is defined as "the collection of information from a sample of individuals through their responses to questions" ( Check & Schutt, 2012, p. 160 ). This type of research allows for a variety of methods to recruit participants, collect data, and utilize various methods of instrumentation. Survey research can use quantitative research strategies (e.g., using questionnaires with numerically rated items), qualitative research strategies (e.g., using open-ended questions), or both strategies (i.e., mixed methods). As it is often used to describe and explore human behavior, surveys are therefore frequently used in social and psychological research ( Singleton & Straits, 2009 ).

Information has been obtained from individuals and groups through the use of survey research for decades. It can range from asking a few targeted questions of individuals on a street corner to obtain information related to behaviors and preferences, to a more rigorous study using multiple valid and reliable instruments. Common examples of less rigorous surveys include marketing or political surveys of consumer patterns and public opinion polls.

Survey research has historically included large population-based data collection. The primary purpose of this type of survey research was to obtain information describing characteristics of a large sample of individuals of interest relatively quickly. Large census surveys obtaining information reflecting demographic and personal characteristics and consumer feedback surveys are prime examples. These surveys were often provided through the mail and were intended to describe demographic characteristics of individuals or obtain opinions on which to base programs or products for a population or group.

More recently, survey research has developed into a rigorous approach to research, with scientifically tested strategies detailing who to include (representative sample), what and how to distribute (survey method), and when to initiate the survey and follow up with nonresponders (reducing nonresponse error), in order to ensure a high-quality research process and outcome. Currently, the term "survey" can reflect a range of research aims, sampling and recruitment strategies, data collection instruments, and methods of survey administration.

Given this range of options in the conduct of survey research, it is imperative for the consumer/reader of survey research to understand the potential for bias in survey research as well as the tested techniques for reducing bias, in order to draw appropriate conclusions about the information reported in this manner. Common types of error in research, along with the sources of error and strategies for reducing error as described throughout this article, are summarized in the Table .

Sources of Error in Survey Research and Strategies to Reduce Error

The goal of sampling strategies in survey research is to obtain a sufficient sample that is representative of the population of interest. It is often not feasible to collect data from an entire population of interest (e.g., all individuals with lung cancer); therefore, a subset of the population or sample is used to estimate the population responses (e.g., individuals with lung cancer currently receiving treatment). A large random sample increases the likelihood that the responses from the sample will accurately reflect the entire population. In order to accurately draw conclusions about the population, the sample must include individuals with characteristics similar to the population.

It is therefore necessary to correctly identify the population of interest (e.g., individuals with lung cancer currently receiving treatment vs. all individuals with lung cancer). The sample will ideally include individuals who reflect the intended population in terms of all characteristics of the population (e.g., sex, socioeconomic characteristics, symptom experience) and contain a similar distribution of individuals with those characteristics. As discussed by Mady Stovall beginning on page 162, Fujimori et al. ( 2014 ), for example, were interested in the population of oncologists. The authors obtained a sample of oncologists from two hospitals in Japan. These participants may or may not have similar characteristics to all oncologists in Japan.

Participant recruitment strategies can affect the adequacy and representativeness of the sample obtained. Using diverse recruitment strategies can help improve the size of the sample and help ensure adequate coverage of the intended population. For example, if a survey researcher intends to obtain a sample of individuals with breast cancer representative of all individuals with breast cancer in the United States, the researcher would want to use recruitment strategies that would recruit both women and men, individuals from rural and urban settings, individuals receiving and not receiving active treatment, and so on. Because of the difficulty in obtaining samples representative of a large population, researchers may focus the population of interest to a subset of individuals (e.g., women with stage III or IV breast cancer). Large census surveys require extremely large samples to adequately represent the characteristics of the population because they are intended to represent the entire population.

DATA COLLECTION METHODS

Survey research may use a variety of data collection methods with the most common being questionnaires and interviews. Questionnaires may be self-administered or administered by a professional, may be administered individually or in a group, and typically include a series of items reflecting the research aims. Questionnaires may include demographic questions in addition to valid and reliable research instruments ( Costanzo, Stawski, Ryff, Coe, & Almeida, 2012 ; DuBenske et al., 2014 ; Ponto, Ellington, Mellon, & Beck, 2010 ). It is helpful to the reader when authors describe the contents of the survey questionnaire so that the reader can interpret and evaluate the potential for errors of validity (e.g., items or instruments that do not measure what they are intended to measure) and reliability (e.g., items or instruments that do not measure a construct consistently). Helpful examples of articles that describe the survey instruments exist in the literature ( Buerhaus et al., 2012 ).

Questionnaires may be in paper form and mailed to participants, delivered in an electronic format via email or an Internet-based program such as SurveyMonkey, or a combination of both, giving the participant the option to choose which method is preferred ( Ponto et al., 2010 ). Using a combination of methods of survey administration can help to ensure better sample coverage (i.e., all individuals in the population having a chance of inclusion in the sample) therefore reducing coverage error ( Dillman, Smyth, & Christian, 2014 ; Singleton & Straits, 2009 ). For example, if a researcher were to only use an Internet-delivered questionnaire, individuals without access to a computer would be excluded from participation. Self-administered mailed, group, or Internet-based questionnaires are relatively low cost and practical for a large sample ( Check & Schutt, 2012 ).

Dillman et al. ( 2014 ) have described and tested a tailored design method for survey research. Improving the visual appeal and graphics of surveys by using a font size appropriate for the respondents, ordering items logically without creating unintended response bias, and arranging items clearly on each page can increase the response rate to electronic questionnaires. Attending to these and other issues in electronic questionnaires can help reduce measurement error (i.e., lack of validity or reliability) and help ensure a better response rate.

Conducting interviews is another approach to data collection used in survey research. Interviews may be conducted by phone, computer, or in person and have the benefit of visually identifying the nonverbal response(s) of the interviewee and subsequently being able to clarify the intended question. An interviewer can use probing comments to obtain more information about a question or topic and can request clarification of an unclear response ( Singleton & Straits, 2009 ). Interviews can be costly and time intensive, and therefore are relatively impractical for large samples.

Some authors advocate for using mixed methods for survey research when no one method is adequate to address the planned research aims, to reduce the potential for measurement and non-response error, and to better tailor the study methods to the intended sample ( Dillman et al., 2014 ; Singleton & Straits, 2009 ). For example, a mixed methods survey research approach may begin with distributing a questionnaire and following up with telephone interviews to clarify unclear survey responses ( Singleton & Straits, 2009 ). Mixed methods might also be used when visual or auditory deficits preclude an individual from completing a questionnaire or participating in an interview.

FUJIMORI ET AL.: SURVEY RESEARCH

Fujimori et al. ( 2014 ) described the use of survey research in a study of the effect of communication skills training for oncologists on oncologist and patient outcomes (e.g., oncologist’s performance and confidence and patient’s distress, satisfaction, and trust). A sample of 30 oncologists from two hospitals was obtained and though the authors provided a power analysis concluding an adequate number of oncologist participants to detect differences between baseline and follow-up scores, the conclusions of the study may not be generalizable to a broader population of oncologists. Oncologists were randomized to either an intervention group (i.e., communication skills training) or a control group (i.e., no training).

Fujimori et al. ( 2014 ) chose a quantitative approach to collect data from oncologist and patient participants regarding the study outcome variables. Self-report numeric ratings were used to measure oncologist confidence and patient distress, satisfaction, and trust. Oncologist confidence was measured using two instruments each using 10-point Likert rating scales. The Hospital Anxiety and Depression Scale (HADS) was used to measure patient distress and has demonstrated validity and reliability in a number of populations including individuals with cancer ( Bjelland, Dahl, Haug, & Neckelmann, 2002 ). Patient satisfaction and trust were measured using 0 to 10 numeric rating scales. Numeric observer ratings were used to measure oncologist performance of communication skills based on a videotaped interaction with a standardized patient. Participants completed the same questionnaires at baseline and follow-up.

The authors clearly describe what data were collected from all participants. Providing additional information about the manner in which questionnaires were distributed (i.e., electronic, mail), the setting in which data were collected (e.g., home, clinic), and the design of the survey instruments (e.g., visual appeal, format, content, arrangement of items) would assist the reader in drawing conclusions about the potential for measurement and nonresponse error. The authors describe conducting a follow-up phone call or mail inquiry for nonresponders, using the Dillman et al. ( 2014 ) tailored design for survey research follow-up may have reduced nonresponse error.

CONCLUSIONS

Survey research is a useful and legitimate approach to research that has clear benefits in helping to describe and explore variables and constructs of interest. Survey research, like all research, has the potential for a variety of sources of error, but several strategies exist to reduce the potential for error. Advanced practitioners aware of the potential sources of error and strategies to improve survey research can better determine how and whether the conclusions from a survey research study apply to practice.

The author has no potential conflicts of interest to disclose.

Advanced Research Instrumentation and Facilities (2006)

Chapter: 2 introduction to instrumentation, 2 introduction to instrumentation.

T his chapter introduces the subject of instrumentation in general; defines the particular instrumentation that is the subject of this report, advanced research instrumentation and facilities (ARIF); and gives examples of ARIF used in various fields.

WHAT IS INSTRUMENTATION, AND WHY IS IT IMPORTANT?

Instruments have revolutionized how we look at the world and refined and extended the range of our senses. From the beginnings of the development of the modern scientific method, its emphasis on testable hypotheses required the ability to make quantitative and ever more accurate measurements—for example, of temperature with the thermometer (1593), of cellular structure with the microscope (1595), of the universe with the telescope (1609), and of time itself (to discern longitude at sea) with the marine chronometer (1759). Instruments have been an integral part of our nation’s growth since explorers first set out to map the continent. The establishment of the US Geological Survey had its roots in the exploration of the western United States, and its activities depended critically on advanced surveying instruments.

A large fraction of the differences between 19th century, 20th century, and 21st century science stems directly from the instruments available to explore the world. The scope of research that instrumentation enables has expanded considerably, now encompassing not only the natural (physical and biologic) world but

also many facets of human society and behavior. Instrumentation has often been cited as the pacing factor of research; the productivity of researchers is only as great as the tools they have available to observe, measure, and make sense of nature. As one of the committee’s survey respondents commented,

without continued infrastructure support…. We will see many young investigators changing the nature of the projects and science they do to areas that have less impact but assure better chances of success. The lack of instruments or the ability to upgrade aging local facilities simply dictates the science done in the future. 1

Cutting-edge instruments not only enable new discoveries but help to make the production of knowledge more efficient. Many newly developed instruments are important because they enable us to explore phenomena with more precision and speed. The development of instruments maintains a symbiotic relationship with science as a whole; advanced tools enable scientists to answer increasingly complex questions, and new findings in turn enable the development of more powerful, and sometimes novel, instruments.

Instrumentation facilitates interdisciplinary research. Many of the spectacular scientific, engineering, and medical achievements of the last century followed the same simple paradigm of migration from basic to applied science. For example, as the study of basic atomic and molecular physics matured, the instruments developed for those activities were adopted by chemists and applied physicists. That in turn enabled applications in biological, clinical, and environmental science, driven both by universities and by innovative companies. A number of modern tools that are now essential for medical diagnostics, such as magnetic resonance imaging scanners, were originally developed by physicists and chemists for the advancement of basic research.

WHAT IS “ADVANCED RESEARCH INSTRUMENTATION AND FACILITIES”?

Borrowing from the terminology used by Congress in its request, the committee’s study focuses on the issues surrounding a particular category of instruments and collections of instruments, referred to as advanced research instrumentation and facilities. In the charge to the committee, ARIF is defined as instrumentation with capital costs between $2 million and several tens of millions of dollars. In that range, there is no general instrumentation program at either the

National Science Foundation (NSF) or the National Institutes of Health (NIH), yet they are the primary federal agencies that support instrumentation for research outside the national laboratories. The instruments and facilities in this price range fall under neither NSF’s Major Research Instrumentation program nor its Major Research Equipment and Facilities Construction account. The committee found that there are no general ARIF programs at the other federal funding agencies.

The committee identifies other characteristics of ARIF that should be part of its definition. Many qualities distinguish ARIF from more easily acquired instrumentation. The capital cost of ARIF is not its distinguishing factor, and thus many of the characteristics of and challenges associated with ARIF may apply to instruments and facilities costing less than $2 million. ARIF are

Difficult for individual investigators to obtain and more commonly acquired by large-scale centers or research programs; it is often necessary to have the consensus of a field when attempting to find support for such an instrument or collection of instruments.

Often in need of a substantial institutional commitment for its acquisition, including the availability of proper space and continued upkeep. Multiple federal and nonfederal sources are needed to meet the initial acquisition cost, but the costs of operation and maintenance often require a substantial and long-term financial commitment from the host institution. Many academic institutions—even major research universities—have no ARIF, and institutions that do have ARIF generally have no more than a handful of such instruments or facilities.

Often dependent on PhD-level technical research support staff to ensure that researchers are able to take full advantage of the unique capabilities of the instrument and to keep them in proper operating condition.

Dependent on relatively high-level decision-making. The investment process for ARIF is likely to include the head of a directorate of NSF, a division or directorate external advisory committee, and the vice-president or vice-provost of research at a university. Identifying or renovating appropriate space for an instrument may require the approval of a university provost or president.

Managed by institutions, not individual investigators, because their administration requires a large financial commitment.

Often funded in ways that cannot be easily tracked. Acquiring instruments and facilities often requires multiple sources of funding to meet the initial capital cost. As a result, it is difficult to obtain an accurate picture of contributions of institutions, states, federal agencies, and other supporters.

ARIF includes both commercially available instruments and specially designed and developed instruments and both physical and nonphysical tools. Specially developed instruments are assembled from many less expensive components to make a new, more advanced and powerful instrument. ARIF may be single standalone instruments, networks, computational modeling applications, computer databases, systems of sensors, suites of instruments, and facilities that house ensembles of interrelated instruments. A number of different funding mechanisms support the wide diversity of ARIF.

ARIF can be loosely categorized in two distinct types of use. Some are “workhorse” instruments, essential to everyday research and training. Others are “racehorse” instruments, newly developed or constantly developing, that are perched on the cutting edge of research. Racehorse instruments, because they are novel, are often easier to justify to potential funders. Both workhorse and racehorse instruments are vital for research, and finding the right balance between the two is a challenge.

The “facilities” portion of “ARIF” was incorporated by the committee to emphasize that some research fields and problems require collections of advanced research instrumentation. As has been described earlier, the changing face of research has demanded that a wide array of instruments be brought to bear on a single problem. Collections of instruments are often essential for meaningful research to occur. To solve some types of scientific problems or to engineer new materials, multiple instruments are necessary to carry out a series of steps or processes. Complementary instruments are more effective when housed side by side and may be far more productive than each one is individually.

Historically, centralized facilities have played a large role in research involving

ARIF instrumentation by consolidating resources, increasing collaboration, and making available rare or unique resources to a large number of users. Most publicly funded centralized facilities are located at universities and national laboratories. The state of US research facilities is often cited as an indicator of the nation’s long-term international competitiveness in research. For example, a 2000 National Academies Committee on Science, Engineering, and Public Policy study of materials facilities noted that “rapid advances in design and capabilities of instrumentation can create obsolescence in 5–8 years.” The study further noted that the overall quality of characterization services provided by materials facilities supporting universities and industry had “lost substantial ground” to Japan and Europe. 2 The committee distinguishes between facilities and centers . A center is defined as a collection of investigators with a particular research focus. A facility is defined as a collection of equipment, instrumentation, technical support personnel, and physical resources that enables investigators to perform research.

In referring to ARIF, the committee excludes facilities that house large assemblies of unrelated or only loosely related equipment and that generally require no targeted support staff. Different research fields require different types of ARIF, and some fields have a larger demand for ARIF than others. ARIF are not distinguished by the diversity of research fields or geographic regions it supports.

EXAMPLES OF ARIF

The research community recognizes the importance of instruments. The National Science Board (NSB) recently identified eight Nobel prizes in physics that were awarded for the development of new or enhanced instrumentation technologies, including electron and scanning tunneling microscopes, laser and neutron spectroscopy, particle detectors, and the integrated circuit. 3 Nobel prizes for the development of instrumentation have been awarded in chemistry and medicine for instrumentation related to nuclear magnetic resonance (NMR) or magnetic resonance imaging, and many were also awarded at least in part for the development of ARIF. Many of the ground-breaking instruments that qualified for a Nobel prize or contributed to Nobel prize-winning work began as ARIF and through development have become widely available and more affordable.

Table 2-1 lists the types of ARIF reported to the committee in its survey of institutions. The results of this survey are known to be incomplete and not repre-

TABLE 2-1 Examples of ARIF, by Field

sentative of the state of ARIF on university campuses. Notably absent from this table, for example, are cybertools other than supercomputers, which cost much to develop but little to use. Computer modeling programs are used often by the chemistry and biology community. The cost of acquiring these computational modeling programs is often negligibly small, but the cost of creating them is often substantial. The computational chemistry program, NWChem, for example, cost around $10 million to create and is distributed free. Further details about the committee’s survey and the ARIF reported in it can be found in Appendix C . Table 2-1 is followed by descriptions of several types of ARIF.

Imaging Technologies: From Physics to Biology

Imaging technologies provide many of the best-known examples of the evolution of modern instrumentation. Fifty years ago, studies of the effects of magnetic fields on the nuclear spin states of molecules were at the forefront of esoteric physics research. The earliest magnetic resonance spectrometers were inexpensive to build (they could literally be cobbled together by graduate students from spare radar parts); this was fortunate because measuring nuclear spin properties had no conceivable application. If sensitivity and instrument performance had stayed the same, NMR still would have no conceivable application.

Instead, today magnetic resonance is a fundamental technique for biological imaging and the most important spectroscopic method for chemists, the only one that measures the structure of proteins in their natural environment (in solution). Since 1980, the sensitivity of the best commercially available NMR spectrometers

FIGURE 2-1 Historical capability of NMR spectrometers.

Source: Razvan Teodorescu, “Bruker Biospin Magnets.” Presentation to the National Research Council Committee on High Magnetic Field Science, December 8, 2003.

has improved by a factor of 30. With that advance alone, NMR spectra could be acquired 900 times faster today than 25 years ago. Improvements in resolution and pulse sequences make the advances in NMR spectrometry even more dramatic. Figure 2-1 shows how NMR resolution and sensitivity have progressed since 1980.

Modern, very-high-field NMR spectrometers (high fields help to resolve the many atoms found in large molecules) are complex instruments; the most advanced machines today cost millions of dollars. The next generation, which pushes to still higher magnetic field strengths, will require a concerted effort in superconductor physics and radiofrequency design but will create even further dramatic extensions of the applicability of the technique. 4

The pioneers of magnetic resonance would never have dreamed that 50 years later the International Society of Magnetic Resonance in Medicine would have 2,800 papers and 4,500 attendees at its annual meetings. Today, magnetic resonance imaging is a mainstream diagnostic tool, and functional magnetic resonance

imaging (literally, watching people think) promises to revolutionize neuroscience and neurology. Again, the applications and the expense are intimately coupled to the sophistication of the technology: a modern, commercially available 4 Tesla whole-body magnetic resonance imager can easily cost $10 million to acquire and site, and it requires highly specialized technical staffing to maintain its perfor-

mance. For the institutions that responded to the committee’s survey, the annual cost of operation for magnetic resonance imagers averaged 10% of the capital cost.

Modern methods in optical and x-ray imaging also reflect the evolution from physics to more applied science. They are not simply descendants of van Leeuwenhoek’s crude microscope and Röntgen’s x-ray hand picture; they embody

and enhance our understanding of molecular and cellular structure and function. It is only a slight exaggeration to say that the most important application of the crude lasers of the 1960s was as inspiration for science-fiction television and movie weapons. Today, advanced laser systems permit microscopy hundreds of times deeper into tissue than would be possible with an ordinary microscope, and they are central to the rapidly growing field of molecular imaging.

The National Cancer Institute has identified molecular imaging as an “extraordinary opportunity” with high scientific priority for cancer research. The most promising approach is the development of new technologies and methods to improve the imaging and molecular-level characterization of biologic systems.

In the committee’s surveys of researchers and institutions, NMR spectrometers were among the most commonly cited individual instruments, and advanced models were among the most commonly sought. The availability of ARIF in general was of concern to many researchers for whom access to increasingly advanced instruments was the key to advancing science and providing solutions to societal problems. The NMR spectrometer, as it becomes more and more sophisticated, exemplifies the issue. As one researcher noted,

there is an increasing need for advanced research instrumentation in many fields. Many instruments that start out appearing to be expensive and esoteric rapidly become mainstream. The good side of this is that these instruments fuel impressive scientific results. The bad side is that scientists who do not have access to these instruments tend to fall behind in terms of their results and in what experiments they can propose in grant applications.

… Five or six years ago, few labs had access to very high field spectrometers (750 MHz or above), but now the field has been pushed ahead to where many … projects require such instrumentation. A significant number of researchers have access to these machines, but many either don’t have access or must drive/fly long distances to obtain access. While on paper it sounds fine to ask a researcher to travel to a high field spectrometer, in practice this is very cumbersome and does not lead to cutting edge results. For any particular NMR project, a dozen or more different NMR experiments must be carried out on a sample…. Traveling back and forth to a “richer” or better endowed university is not conducive to getting results. 5

High-Speed Sequencers and the Human Genome Project

One of the major accomplishments of science in the 20th century was the deciphering of the human genome. That achievement made it possible to understand the molecular basis of human life in unprecedented detail. The potential for

improving health and curing disease has already been demonstrated, but most of the benefits remain to be seen. The achievement will provide the basis of discoveries far into the future.

The genetic information in DNA is stored as a sequence of bases, and DNA sequencing is the determination of the exact order of the base pairs in a segment of DNA. Two groups, in the United States and the United Kingdom, first accomplished sequencing in 1977 and were awarded the 1980 Nobel prize in chemistry. However, their approaches were time-consuming and labor-intensive. Further

advances came in 1986-1987 with the development of fluorescence-based detection of the bases. That led quickly to automated high-throughput DNA sequencers that were soon commercialized and made generally available to the research community. However, the speed of those devices was still not sufficient to decode the human genome in any reasonable amount of time.

Beginning in 1990, the pressures of approaching the daunting task of sequencing the human genome produced a number of new advances, which resulted in a fully automated high-throughput parallel-processing device that was 10 times faster than the older method. The progress and success of the Human Genome Project constitute a case study in instrumentation and of how, without develop-

ment, it can become a pacing factor for research. The leaders of the sequencing efforts at the Department of Energy Office of Science and NIH recognized that the existing technology was not capable of sequencing fast and cost-effectively. As a result, they invested substantially not only in researchers but in the further development of sequencing technologies. The tandem approach proved very successful.

Genome sequencing requires the assembly of millions of fragments into a complete sequence. By itself, the mechanical process of sequencing was not sufficient to map the human genome in a reasonable time. The project was aided by computer algorithms developed by researchers in the late eighties and early nineties. The confluence of hardware and software development made it possible to complete the human genome sequence years before it had been considered possible. It also provided a general approach to large-scale sequencing that has resulted in the understanding of the genomes of a wide variety of organisms. The knowledge of genomes of a number of organisms has vastly accelerated discovery in basic biology research.

The history of the genome project shows how technology development can influence the course of discovery. Hardware and software were both needed and

were synergistic. The parallel development of sequencers and software demonstrates that not only key insights but also incremental improvements can make a qualitative difference in the progress of science.

Today, computers are vital tools to scientists and engineers. Indispensable for communication and often used in conjunction with many instruments, the computer can also be a scientific instrument itself. This section gives examples of three types of cybertools that are fundamental to several fields of research: software, data collections, and surveys.

Although one of the first scientific applications of digital computers in the 1940s was to try to predict the weather—with grants from the US Weather Service, the Navy, and the Air Force to John von Neumann at the Institute for Advanced Study at Princeton University—scientific applications software aimed at obtaining

a better understanding of physical phenomena did not become widely available until the 1960s and 1970s. Scientists and engineers have since developed a broad array of scientific software applications that are acknowledged to be indispensable in the scientist’s toolkit—the software equivalents of the NMR spectrometer and other instruments described above. Examples of such applications software in use today are Gaussian, a molecular modeling code that is used by experimental and theoretical chemists to understand molecular structure and processes better and more easily by performing computer “experiments” rather than chemistry experiments; the Community Climate System Model, which is used by the climate research community to understand the evolution of past and future climates; and CHARMM and AMBER, used by the biomolecular community to understand the structure and dynamics of proteins and enzymes.

Scientific applications, such as Gaussian, often began as small research projects in the laboratory of a single investigator. However, as the capabilities of computers increased, the applications included models of the physical and chemical processes of higher and higher fidelity, and the software became more and more complex. Today, many of the scientific applications involve hundreds of thousands to millions of lines of code, took hundreds of person-years to design and build, and require substantial continuing support to maintain, port to new computers, and continue to evolve the capabilities of the software as new knowledge accumulates. The cost of developing major new scientific and engineering applications can be more than $10 million, and the cost of continuing maintenance, support, and evolution exceeds $2 million per year. Thus, these software applications are well within the category of advanced research instrumentation being considered in this report.

Digital data collections also provide a fundamentally new approach to research. By gathering data generated in studies on related topics, digital data collections themselves become a new source of knowledge. One of the best examples of a large scientific database that is integral to progress in science and engineering is GenBank, the genetic sequence database maintained for the biomedical research community by NIH. GenBank was born at Los Alamos National Laboratory in 1982, well before the beginning of the Human Genome Project. When the Human Genome Project came into being and the number of available sequences exploded, GenBank became an indispensable repository for the data being generated. Today GenBank contains over 49 billion nucleotide bases in over 45 million sequence records, and the amount of data is increasing exponentially with a doubling time

of less than two years. All sequencing data produced by the Human Genome Project must be deposited in GenBank before it can be published in the literature. Because of the unique role now being played by digital data collections in research and education, the NSB recently drafted a report on the subject, finding that such collections are used in most fields of science, from astronomy (as in the Sloan Digital Sky Survey) to biology (as in The Arabidopsis Information Resource). 6 It concluded that “digital data collections serve as an instrument for performing analysis with an accuracy that was not possible previously or, by combining information in new ways, from a perspective that was previously inaccessible.” The collections are often fundamental tools of the social sciences, housing extensive survey and census results and archived media.

Especially in the social sciences, the survey itself is a scientific instrument that can cost millions of dollars a year to maintain. Longitudinal surveys, large and often decades-long surveys, are analogs to the telescopes and microscopes of the other sciences. These surveys are not created by single investigators; they are often sources of basic data used by arrays of disciplines. Increasingly, surveys collect not only social data but also biomedical data (e.g., cheek swabs for DNA analysis) or are integrated with satellite down feeds or inputs from air quality sensors. The data from these surveys is expensive to collect and document as well as make publicly accessible to researchers while preserving anonymity and confidentiality. They are very expensive to collect in any given round let alone over time. They are also expensive to document and make accessible as public use files, preserving anonymity and confidentiality. Frequently, the data for such surveys can only be collected by one or two survey research centers in the country, such as the Institute for Social Research at the University of Michigan, that possess the ongoing human and local infrastructure to manage them at affordable scale.

Computational technology has advanced to the point where computers can be used as tools not only for remotely accessing databases and collaborating with other researchers but for remotely accessing and controlling scientific instruments. A 900-MHz virtual NMR facility at the Pacific Northwest National Laboratory, for example, supports a national community of users, roughly half of whom use the instrument remotely. The technology can improve and provide less expensive access to instruments for geographically remote users and can permit more effective use of instruments. The openness of this technology and the ability to book at all hours may be a means to generate more revenue from user fees and thus recoup the facility’s operation and maintenance expeditures.

Distributed Advanced Research Instrumentation Systems

Not all advanced research instrumentation is housed in laboratories. Progress in the physics underlying the technological development of modern scientific instruments and their associated cybertools has given rise to an unprecedented explosion in the scope of basic research in the geosciences and biosciences that relies on field observations. Atmospheric scientists, oceanographers, geophysicists, and ecologists are now tackling and solving fundamental problems that require analysis of large numbers of observations that are both time- and space-dependent. Some of the sensors and tools required to make the necessary measurements can be deployed on familiar mobile instrumental platforms, such as oceanographic ships, research aircraft, and earth-orbiting satellites; but many need to be distributed in sensor networks of local, regional, or even global scale. Both physical and wireless networks can be used to transmit data to off-site storage facilities.

A good example of a distributed sensor network is the Global Seismographic Network (GSN), which consists of 130 seismic stations distributed on continental landmasses, oceanic islands, and the ocean bottom. GSN recording and nearly real-time distribution of seismic-wave parameters measurements at numerous sites over the globe serve the needs of basic research in geophysics (such as seismic tomography of the earth’s interior structure) and of applied geosciences (such as earthquake and tsunami monitoring and seismic monitoring of nuclear testing).

Seismometers were originally developed to study earthquakes, but their modern versions, deployed in geographically distributed networks, record data that can be processed with sophisticated computing methods to produce images of the solid earth. The resulting “seismic imaging” is science’s most important source of knowledge about the structure of the earth’s interior and its consequences for humanity with respect to, for example, mineral and energy resources, earthquakes and volcanic hazards.

Today’s seismograph system takes advantage of modern off-the-shelf hardware for many of its components. Global positioning system (GPS) receivers provide the accurate timing required, off-the-shelf electronic amplifiers generate little noise or distortion, and commercial analog-to-digital converters with true 24-bit or higher resolution are an improvement over custom-designed “gain-ranging” systems; but the primary sensor of a modern seismometer still requires unique design to meet a combination of stringent requirements. To detect the smallest signals above the earth’s background “hum,” the self-excitation of the pendulum sensor by Brownian noise must be less than that caused by shaking the instrument’s foundation with an acceleration of 1 nm/s 2 across a wide frequency band of 10 −4 -100 Hz. Furthermore, to make faithful records of the largest earthquakes, the response across the same frequency band must be linear up to excitation amplitudes that are 10 12 times greater than the smallest detectable signals. No company in the United States produces sensors with those capabilities, and no US universities train engineers in seismometer design.

Environmental sensor systems must often be installed in remote field locations, and this poses difficulties not encountered in housing instruments in a laboratory setting. For example, seismometers must be installed in ways that isolate them from drafts, temperature changes, and ambient noise and that protect them from damage by animals and vandalism. Low-power, rugged, and high-capacity data-storage systems are required for remote locations where energy must be provided by fuel cells or batteries recharged by solar or wind-based systems. In locations where Internet service is not available, transmission of data must take advantage of satellites or other telemetry technologies that can substantially add to costs. Although data transmission and interrogation of routine instrument functions can be dealt with remotely, periodic maintenance by technicians is needed

and can account for a large fraction of operation and maintenance costs, especially for large networks with worldwide distribution of stations. Although the combined equipment, installation, and a year of operation and maintenance of an individual station typically will cost between $100,000 and several hundred thousand dollars depending on instrumentation specifications and location (polar regions and ocean-bottom locations are obvious examples of expensive locations), it is clear to the committee that distributed network “instruments” fall well within its definition of ARIF.

Tools for Integrated Circuits

An advanced research instrument may consist of a suite of tools that must be combined to advance a particular field of science and technology and eventually affect society. An excellent example is the microelectronic processing technology

that has been developed over the last 50 years to create integrated circuits (ICs). ICs are found in every electronic product purchased by Americans to enhance our day-to-day living. Communication, education, transportation, defense, health care, and recreation, to name a few examples, have been dramatically transformed by the creation of ICs. In 1947, the first point-contact transistor was demonstrated; it consisted of a sizable chunk of germanium with two gold wires to conduct electricity and enable the demonstration of power gain. A few years later, in 1956, Bardeen, Brattain, and Shockley were awarded the Nobel prize in physics for the discovery of the transistor. Throughout the 1950s and 1960s key technological breakthroughs in crystal growth, ion implantation, photolithography, and planar processing paved the way for the creation of the IC. By fabricating the transistor in a planar form, engineers and scientists could envision methods to interconnect the transistors and begin combining them to perform an unlimited number of functions.

In 1971, Intel introduced its 4004 processor that contained 2,300 integrated and interconnected transistors in a 4 × 5 mm area—about 10,000 transistors/cm 2 . In 1997, the Intel Pentium II processor contained 7.5 million transistors in an area of about 8 × 8 mm. The Pentium III has 28 million transistors; by 2006, the industry projects a logic transistor density of 40-80 million per square centimeter! In 2000, Kilby was awarded the Nobel prize for the invention of the IC. Today, the microelectronic processing technology industry has sales of over $150 billion per year. To create such amazing ultra-high-density, small-area ICs requires a suite of planar processing tools, each of which can be categorized as an advanced research instrument but all of which are needed to build the IC.

As the capability of an instrument increases, its price also increases. For example, in 1982, a physical vapor-deposition tool cost about $400,000; whereas in 2002 a physical vapor-deposition tool cost $7 million. This rise in cost reflects substantial gains in the precision and repeatability of vapor deposition. Similar increases in equipment costs have occurred for other tools in the suite as resolution has increased, feature size has been reduced, and overlay accuracy has been improved. The incredible gains demonstrated by the microelectronic processing technology industry were facilitated by placing the suite of tools within specially designed space or clean rooms to ensure defect-free high-density ICs; such special space adds further to the cost of ownership of these advanced research instruments.

Nanotechnology

Nanotechnology is a broad field that has stemmed from our recently developed ability to manipulate atomic and molecular objects with dimensions 1-100 nm—a length scale that has become increasingly important in pushing the boundaries of operation and performance. It involves the ability to engineer materials on a

nanometer scale by placing atoms into predetermined locations. In light of the broad goals and possible applications of nanotechnology, a large array of synergistic tools has been developed.

A primary need in nanotechnology is the ability to “see” the locations of specific atoms. That has been accomplished largely through the development of scanning probe microscopes. These types of microscopes have the ability to scan or map a surface line by line at atomic resolution. Scanning probe microscopes are distinct from most other microscopes in using mechanical devices, instead of light and lenses, to image surfaces.

The development of scanning probe technology began in 1981 with the scanning tunneling microscope in Zurich. Scanning tunneling microscopes use quantum principles not only to visualize surfaces but also to manipulate them by, for example, initiating chemical reactions. In 1986, the Nobel prize in physics was awarded to the discoverers of this microscopy technique; the remarkably short

time after the initial discovery indicates its importance. Since then, an array of other scanning microcopies have been developed, most notably the atomic-force microscope in 1986 that measured attractive or repulsive forces between a very fine tip and a sample. That approach allowed the imaging of nonconductive surfaces, which the tunneling technique could not do. As is often the case, sophisticated software is required to make sense of the information generated by these tools and to integrate it into a comprehensible image.

The effects of nanotechnology are beginning to be felt, for example, in materials science (nanotubes and nanoparticles), in the development of smaller computer chips, and in the manipulation of biologic components to create nanomotors. Recently, there has been interest in the interaction of “hard” and “soft” materials, which require special facilities where semiconductor fabrication and biomolecular assembly can take place in concert.

Tools for Space Exploration

The exploration of space and the solar system depends on a number of ground-based and space instruments, such as the Supernova Acceleration Probe, a satellite observatory that probes the history of the expansion of the universe over the last 10 billion years. The exploration of space has also become increasingly dependent on diagnostic equipment, whose focus is characterization of samples that have been returned to the earth from space. Such instruments as the MegaSIMS combination spectrometer (see Table 2-1 ), which was specially designed to analyze GENESIS NASA solar wind samples, are ARIF that bridge space and earth exploration and enable us to understand better the materials that make up the world around us and the processes that govern its development.

F2-1: Instrumentation is a major pacing factor for research; the productivity of researchers is only as great as the tools they have available to observe, measure, and make sense of nature. Workhorse instruments, once cutting-edge, now enable scientists to perform routine experiments and procedures much faster. Those tools now have efficiency and sensitivity greater by several orders of magnitude than a decade ago. Research that previously took years to conduct now takes hours. Most of the research funded by the federal government today would be impossible with tools that were developed in decades past.

F2-2: As new research questions are answered, more advanced instrumentation needs to be developed to respond to researcher needs. As a result, the useful life of instruments has shortened dramatically in recent decades, and the demand for new instruments has increased. Instruments that used to be relevant to cutting-edge research for a decade or more today last less than half that time. Older instruments are still useful, but the demand for new instruments is greater and greater.

F2-3: ARIF include both workhorse instruments that are used every day by researchers and racehorse instruments that represent the state of the art or are still developing.

F2-4: ARIF often depend on PhD-level technical research support staff for its proper operation and maintenance and to facilitate use by researchers. ARIF require highly specialized knowledge and training for proper operation and use . Nonspecialists increasingly need ARIF for their research and require dedicated personnel to provide expertise.

RECOMMENDATIONS

R2-1: The committee recommends the following definition of ARIF:

Advanced research instrumentation and facilities (ARIF) are instrumentation and facili ties housing collections of closely related or interacting instruments used for research and includes networks of sensors, data collections, and cyberinfrastructure. ARIF are distinguished from other types of instrumentation by being more commonly acquired by large-scale centers or research programs rather than individual investigators. The acquisition of ARIF by scientists often requires a substantial institutional commitment, depends on high-level decision-making at institutions and federal agencies, and is often managed by institutions. Furthermore, the advanced nature of ARIF often requires ex pert PhD-level technical research support staff for its operation and maintenance.

R2-2: Continued and vigorous federal investment in ARIF is essential to enable cutting-edge research in the future.

In recent years, the instrumentation needs of the nation's research communities have changed and expanded. The need for particular instruments has become broader, crossing scientific and engineering disciplines. The growth of interdisciplinary research that focuses on problems defined outside the boundaries of individual disciplines demands more instrumentation. Instruments that were once of interest only to specialists are now required by a wide array of scientists to solve critical research problems. The need for entirely new types of instruments—such as distributed networks, cybertools, and sensor arrays—is increasing. Researchers are increasingly dependent on advanced instruments that require highly specialized knowledge and training for their proper operation and use. The National Academies Committee on Science, Engineering, and Public Policy Committee on Advanced Research Instrumentation was asked to describe the current programs and policies of the major federal research agencies for advanced research instrumentation, the current status of advanced mid-sized research instrumentation on university campuses, and the challenges faced by each. The committee was then asked to evaluate the utility of existing federal programs and to determine the need for and, if applicable, the potential components of an interagency program for advanced research instrumentation.

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Research Instruments

This Guide provides access to databases and web based resources useful for locating a wide variety of research instruments.   

American Thoracic Society Quality of Life Resource Instruments

The goal of this website is to provide information about quality of life and functional status instruments that have been used in assessing patients with pulmonary disease or critical illness.

Cancer Prevention Research Center

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Rehabilitation Measures Database

The Rehabilitation Measures Database was developed to help clinicians and researchers identify reliable and valid instruments used to assess patient outcomes during all phases of rehabilitation. This database provides evidence based summaries that include concise descriptions of each instrument's psychometric properties, instructions for administering and scoring each assessment as well as a representative bibliography with citations linked to PubMed abstracts. Whenever possible, we have also included a copy of the instrument for users to download or information about obtaining the instrument. This database was developed through collaboration between the Center for Rehabilitation Outcomes Research (CROR) at the Rehabilitation Institute of Chicago and the Department of Medical Social Sciences Informatics group at Northwestern University Feinberg School of Medicine with funding from the National Institute on Disability and Rehabilitation Research. The Rehabilitation Measures Database and its content were created by CROR.   

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Home » Questionnaire – Definition, Types, and Examples

Questionnaire – Definition, Types, and Examples

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Questionnaire

Definition:

A Questionnaire is a research tool or survey instrument that consists of a set of questions or prompts designed to gather information from individuals or groups of people.

It is a standardized way of collecting data from a large number of people by asking them a series of questions related to a specific topic or research objective. The questions may be open-ended or closed-ended, and the responses can be quantitative or qualitative. Questionnaires are widely used in research, marketing, social sciences, healthcare, and many other fields to collect data and insights from a target population.

History of Questionnaire

The history of questionnaires can be traced back to the ancient Greeks, who used questionnaires as a means of assessing public opinion. However, the modern history of questionnaires began in the late 19th century with the rise of social surveys.

The first social survey was conducted in the United States in 1874 by Francis A. Walker, who used a questionnaire to collect data on labor conditions. In the early 20th century, questionnaires became a popular tool for conducting social research, particularly in the fields of sociology and psychology.

One of the most influential figures in the development of the questionnaire was the psychologist Raymond Cattell, who in the 1940s and 1950s developed the personality questionnaire, a standardized instrument for measuring personality traits. Cattell’s work helped establish the questionnaire as a key tool in personality research.

In the 1960s and 1970s, the use of questionnaires expanded into other fields, including market research, public opinion polling, and health surveys. With the rise of computer technology, questionnaires became easier and more cost-effective to administer, leading to their widespread use in research and business settings.

Today, questionnaires are used in a wide range of settings, including academic research, business, healthcare, and government. They continue to evolve as a research tool, with advances in computer technology and data analysis techniques making it easier to collect and analyze data from large numbers of participants.

Types of Questionnaire

Types of Questionnaires are as follows:

Structured Questionnaire

This type of questionnaire has a fixed format with predetermined questions that the respondent must answer. The questions are usually closed-ended, which means that the respondent must select a response from a list of options.

Unstructured Questionnaire

An unstructured questionnaire does not have a fixed format or predetermined questions. Instead, the interviewer or researcher can ask open-ended questions to the respondent and let them provide their own answers.

Open-ended Questionnaire

An open-ended questionnaire allows the respondent to answer the question in their own words, without any pre-determined response options. The questions usually start with phrases like “how,” “why,” or “what,” and encourage the respondent to provide more detailed and personalized answers.

Close-ended Questionnaire

In a closed-ended questionnaire, the respondent is given a set of predetermined response options to choose from. This type of questionnaire is easier to analyze and summarize, but may not provide as much insight into the respondent’s opinions or attitudes.

Mixed Questionnaire

A mixed questionnaire is a combination of open-ended and closed-ended questions. This type of questionnaire allows for more flexibility in terms of the questions that can be asked, and can provide both quantitative and qualitative data.

Pictorial Questionnaire:

In a pictorial questionnaire, instead of using words to ask questions, the questions are presented in the form of pictures, diagrams or images. This can be particularly useful for respondents who have low literacy skills, or for situations where language barriers exist. Pictorial questionnaires can also be useful in cross-cultural research where respondents may come from different language backgrounds.

Types of Questions in Questionnaire

The types of Questions in Questionnaire are as follows:

Multiple Choice Questions

These questions have several options for participants to choose from. They are useful for getting quantitative data and can be used to collect demographic information.

• a. Red b . Blue c. Green d . Yellow

Rating Scale Questions

These questions ask participants to rate something on a scale (e.g. from 1 to 10). They are useful for measuring attitudes and opinions.

• On a scale of 1 to 10, how likely are you to recommend this product to a friend?

Open-Ended Questions

These questions allow participants to answer in their own words and provide more in-depth and detailed responses. They are useful for getting qualitative data.

• What do you think are the biggest challenges facing your community?

Likert Scale Questions

These questions ask participants to rate how much they agree or disagree with a statement. They are useful for measuring attitudes and opinions.

How strongly do you agree or disagree with the following statement:

“I enjoy exercising regularly.”

• a . Strongly Agree
• c . Neither Agree nor Disagree
• d . Disagree
• e . Strongly Disagree

Demographic Questions

These questions ask about the participant’s personal information such as age, gender, ethnicity, education level, etc. They are useful for segmenting the data and analyzing results by demographic groups.

• What is your age?

Yes/No Questions

These questions only have two options: Yes or No. They are useful for getting simple, straightforward answers to a specific question.

Have you ever traveled outside of your home country?

Ranking Questions

These questions ask participants to rank several items in order of preference or importance. They are useful for measuring priorities or preferences.

Please rank the following factors in order of importance when choosing a restaurant:

• a. Quality of Food
• c. Ambiance
• d. Location

Matrix Questions

These questions present a matrix or grid of options that participants can choose from. They are useful for getting data on multiple variables at once.

Dichotomous Questions

These questions present two options that are opposite or contradictory. They are useful for measuring binary or polarized attitudes.

Do you support the death penalty?

How to Make a Questionnaire

Step-by-Step Guide for Making a Questionnaire:

• Define your research objectives: Before you start creating questions, you need to define the purpose of your questionnaire and what you hope to achieve from the data you collect.
• Choose the appropriate question types: Based on your research objectives, choose the appropriate question types to collect the data you need. Refer to the types of questions mentioned earlier for guidance.
• Develop questions: Develop clear and concise questions that are easy for participants to understand. Avoid leading or biased questions that might influence the responses.
• Organize questions: Organize questions in a logical and coherent order, starting with demographic questions followed by general questions, and ending with specific or sensitive questions.
• Pilot the questionnaire : Test your questionnaire on a small group of participants to identify any flaws or issues with the questions or the format.
• Refine the questionnaire : Based on feedback from the pilot, refine and revise the questionnaire as necessary to ensure that it is valid and reliable.
• Distribute the questionnaire: Distribute the questionnaire to your target audience using a method that is appropriate for your research objectives, such as online surveys, email, or paper surveys.
• Collect and analyze data: Collect the completed questionnaires and analyze the data using appropriate statistical methods. Draw conclusions from the data and use them to inform decision-making or further research.
• Report findings: Present your findings in a clear and concise report, including a summary of the research objectives, methodology, key findings, and recommendations.

Questionnaire Administration Modes

There are several modes of questionnaire administration. The choice of mode depends on the research objectives, sample size, and available resources. Some common modes of administration include:

• Self-administered paper questionnaires: Participants complete the questionnaire on paper, either in person or by mail. This mode is relatively low cost and easy to administer, but it may result in lower response rates and greater potential for errors in data entry.
• Online questionnaires: Participants complete the questionnaire on a website or through email. This mode is convenient for both researchers and participants, as it allows for fast and easy data collection. However, it may be subject to issues such as low response rates, lack of internet access, and potential for fraudulent responses.
• Telephone surveys: Trained interviewers administer the questionnaire over the phone. This mode allows for a large sample size and can result in higher response rates, but it is also more expensive and time-consuming than other modes.
• Face-to-face interviews : Trained interviewers administer the questionnaire in person. This mode allows for a high degree of control over the survey environment and can result in higher response rates, but it is also more expensive and time-consuming than other modes.
• Mixed-mode surveys: Researchers use a combination of two or more modes to administer the questionnaire, such as using online questionnaires for initial screening and following up with telephone interviews for more detailed information. This mode can help overcome some of the limitations of individual modes, but it requires careful planning and coordination.

Example of Questionnaire

Title of the Survey: Customer Satisfaction Survey

Introduction:

We appreciate your business and would like to ensure that we are meeting your needs. Please take a few minutes to complete this survey so that we can better understand your experience with our products and services. Your feedback is important to us and will help us improve our offerings.

Instructions:

Please read each question carefully and select the response that best reflects your experience. If you have any additional comments or suggestions, please feel free to include them in the space provided at the end of the survey.

1. How satisfied are you with our product quality?

• Very satisfied
• Somewhat satisfied
• Somewhat dissatisfied
• Very dissatisfied

2. How satisfied are you with our customer service?

3. How satisfied are you with the price of our products?

4. How likely are you to recommend our products to others?

• Very likely
• Somewhat likely
• Somewhat unlikely
• Very unlikely

5. How easy was it to find the information you were looking for on our website?

• Somewhat easy
• Somewhat difficult
• Very difficult

6. How satisfied are you with the overall experience of using our products and services?

7. Is there anything that you would like to see us improve upon or change in the future?

…………………………………………………………………………………………………………………………..

Conclusion:

Thank you for taking the time to complete this survey. Your feedback is valuable to us and will help us improve our products and services. If you have any further comments or concerns, please do not hesitate to contact us.

Applications of Questionnaire

Some common applications of questionnaires include:

• Research : Questionnaires are commonly used in research to gather information from participants about their attitudes, opinions, behaviors, and experiences. This information can then be analyzed and used to draw conclusions and make inferences.
• Healthcare : In healthcare, questionnaires can be used to gather information about patients’ medical history, symptoms, and lifestyle habits. This information can help healthcare professionals diagnose and treat medical conditions more effectively.
• Marketing : Questionnaires are commonly used in marketing to gather information about consumers’ preferences, buying habits, and opinions on products and services. This information can help businesses develop and market products more effectively.
• Human Resources: Questionnaires are used in human resources to gather information from job applicants, employees, and managers about job satisfaction, performance, and workplace culture. This information can help organizations improve their hiring practices, employee retention, and organizational culture.
• Education : Questionnaires are used in education to gather information from students, teachers, and parents about their perceptions of the educational experience. This information can help educators identify areas for improvement and develop more effective teaching strategies.

Purpose of Questionnaire

Some common purposes of questionnaires include:

• To collect information on attitudes, opinions, and beliefs: Questionnaires can be used to gather information on people’s attitudes, opinions, and beliefs on a particular topic. For example, a questionnaire can be used to gather information on people’s opinions about a particular political issue.
• To collect demographic information: Questionnaires can be used to collect demographic information such as age, gender, income, education level, and occupation. This information can be used to analyze trends and patterns in the data.
• To measure behaviors or experiences: Questionnaires can be used to gather information on behaviors or experiences such as health-related behaviors or experiences, job satisfaction, or customer satisfaction.
• To evaluate programs or interventions: Questionnaires can be used to evaluate the effectiveness of programs or interventions by gathering information on participants’ experiences, opinions, and behaviors.
• To gather information for research: Questionnaires can be used to gather data for research purposes on a variety of topics.

When to use Questionnaire

Here are some situations when questionnaires might be used:

• When you want to collect data from a large number of people: Questionnaires are useful when you want to collect data from a large number of people. They can be distributed to a wide audience and can be completed at the respondent’s convenience.
• When you want to collect data on specific topics: Questionnaires are useful when you want to collect data on specific topics or research questions. They can be designed to ask specific questions and can be used to gather quantitative data that can be analyzed statistically.
• When you want to compare responses across groups: Questionnaires are useful when you want to compare responses across different groups of people. For example, you might want to compare responses from men and women, or from people of different ages or educational backgrounds.
• When you want to collect data anonymously: Questionnaires can be useful when you want to collect data anonymously. Respondents can complete the questionnaire without fear of judgment or repercussions, which can lead to more honest and accurate responses.
• When you want to save time and resources: Questionnaires can be more efficient and cost-effective than other methods of data collection such as interviews or focus groups. They can be completed quickly and easily, and can be analyzed using software to save time and resources.

Characteristics of Questionnaire

Here are some of the characteristics of questionnaires:

• Standardization : Questionnaires are standardized tools that ask the same questions in the same order to all respondents. This ensures that all respondents are answering the same questions and that the responses can be compared and analyzed.
• Objectivity : Questionnaires are designed to be objective, meaning that they do not contain leading questions or bias that could influence the respondent’s answers.
• Predefined responses: Questionnaires typically provide predefined response options for the respondents to choose from, which helps to standardize the responses and make them easier to analyze.
• Quantitative data: Questionnaires are designed to collect quantitative data, meaning that they provide numerical or categorical data that can be analyzed using statistical methods.
• Convenience : Questionnaires are convenient for both the researcher and the respondents. They can be distributed and completed at the respondent’s convenience and can be easily administered to a large number of people.
• Anonymity : Questionnaires can be anonymous, which can encourage respondents to answer more honestly and provide more accurate data.
• Reliability : Questionnaires are designed to be reliable, meaning that they produce consistent results when administered multiple times to the same group of people.
• Validity : Questionnaires are designed to be valid, meaning that they measure what they are intended to measure and are not influenced by other factors.

Advantage of Questionnaire

Some Advantage of Questionnaire are as follows:

• Standardization: Questionnaires allow researchers to ask the same questions to all participants in a standardized manner. This helps ensure consistency in the data collected and eliminates potential bias that might arise if questions were asked differently to different participants.
• Efficiency: Questionnaires can be administered to a large number of people at once, making them an efficient way to collect data from a large sample.
• Anonymity: Participants can remain anonymous when completing a questionnaire, which may make them more likely to answer honestly and openly.
• Cost-effective: Questionnaires can be relatively inexpensive to administer compared to other research methods, such as interviews or focus groups.
• Objectivity: Because questionnaires are typically designed to collect quantitative data, they can be analyzed objectively without the influence of the researcher’s subjective interpretation.
• Flexibility: Questionnaires can be adapted to a wide range of research questions and can be used in various settings, including online surveys, mail surveys, or in-person interviews.

Limitations of Questionnaire

Limitations of Questionnaire are as follows:

• Limited depth: Questionnaires are typically designed to collect quantitative data, which may not provide a complete understanding of the topic being studied. Questionnaires may miss important details and nuances that could be captured through other research methods, such as interviews or observations.
• R esponse bias: Participants may not always answer questions truthfully or accurately, either because they do not remember or because they want to present themselves in a particular way. This can lead to response bias, which can affect the validity and reliability of the data collected.
• Limited flexibility: While questionnaires can be adapted to a wide range of research questions, they may not be suitable for all types of research. For example, they may not be appropriate for studying complex phenomena or for exploring participants’ experiences and perceptions in-depth.
• Limited context: Questionnaires typically do not provide a rich contextual understanding of the topic being studied. They may not capture the broader social, cultural, or historical factors that may influence participants’ responses.
• Limited control : Researchers may not have control over how participants complete the questionnaire, which can lead to variations in response quality or consistency.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Reliability vs. Validity in Research | Difference, Types and Examples

Published on July 3, 2019 by Fiona Middleton . Revised on June 22, 2023.

Reliability and validity are concepts used to evaluate the quality of research. They indicate how well a method , technique. or test measures something. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure.opt

It’s important to consider reliability and validity when you are creating your research design , planning your methods, and writing up your results, especially in quantitative research . Failing to do so can lead to several types of research bias and seriously affect your work.

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Understanding reliability vs validity, how are reliability and validity assessed, how to ensure validity and reliability in your research, where to write about reliability and validity in a thesis, other interesting articles.

Reliability and validity are closely related, but they mean different things. A measurement can be reliable without being valid. However, if a measurement is valid, it is usually also reliable.

What is reliability?

Reliability refers to how consistently a method measures something. If the same result can be consistently achieved by using the same methods under the same circumstances, the measurement is considered reliable.

What is validity?

Validity refers to how accurately a method measures what it is intended to measure. If research has high validity, that means it produces results that correspond to real properties, characteristics, and variations in the physical or social world.

High reliability is one indicator that a measurement is valid. If a method is not reliable, it probably isn’t valid.

If the thermometer shows different temperatures each time, even though you have carefully controlled conditions to ensure the sample’s temperature stays the same, the thermometer is probably malfunctioning, and therefore its measurements are not valid.

However, reliability on its own is not enough to ensure validity. Even if a test is reliable, it may not accurately reflect the real situation.

Validity is harder to assess than reliability, but it is even more important. To obtain useful results, the methods you use to collect data must be valid: the research must be measuring what it claims to measure. This ensures that your discussion of the data and the conclusions you draw are also valid.

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Reliability can be estimated by comparing different versions of the same measurement. Validity is harder to assess, but it can be estimated by comparing the results to other relevant data or theory. Methods of estimating reliability and validity are usually split up into different types.

Types of reliability

Different types of reliability can be estimated through various statistical methods.

Types of validity

The validity of a measurement can be estimated based on three main types of evidence. Each type can be evaluated through expert judgement or statistical methods.

To assess the validity of a cause-and-effect relationship, you also need to consider internal validity (the design of the experiment ) and external validity (the generalizability of the results).

The reliability and validity of your results depends on creating a strong research design , choosing appropriate methods and samples, and conducting the research carefully and consistently.

Ensuring validity

If you use scores or ratings to measure variations in something (such as psychological traits, levels of ability or physical properties), it’s important that your results reflect the real variations as accurately as possible. Validity should be considered in the very earliest stages of your research, when you decide how you will collect your data.

• Choose appropriate methods of measurement

Ensure that your method and measurement technique are high quality and targeted to measure exactly what you want to know. They should be thoroughly researched and based on existing knowledge.

For example, to collect data on a personality trait, you could use a standardized questionnaire that is considered reliable and valid. If you develop your own questionnaire, it should be based on established theory or findings of previous studies, and the questions should be carefully and precisely worded.

• Use appropriate sampling methods to select your subjects

To produce valid and generalizable results, clearly define the population you are researching (e.g., people from a specific age range, geographical location, or profession).  Ensure that you have enough participants and that they are representative of the population. Failing to do so can lead to sampling bias and selection bias .

Ensuring reliability

Reliability should be considered throughout the data collection process. When you use a tool or technique to collect data, it’s important that the results are precise, stable, and reproducible .

• Apply your methods consistently

Plan your method carefully to make sure you carry out the same steps in the same way for each measurement. This is especially important if multiple researchers are involved.

For example, if you are conducting interviews or observations , clearly define how specific behaviors or responses will be counted, and make sure questions are phrased the same way each time. Failing to do so can lead to errors such as omitted variable bias or information bias .

• Standardize the conditions of your research

When you collect your data, keep the circumstances as consistent as possible to reduce the influence of external factors that might create variation in the results.

For example, in an experimental setup, make sure all participants are given the same information and tested under the same conditions, preferably in a properly randomized setting. Failing to do so can lead to a placebo effect , Hawthorne effect , or other demand characteristics . If participants can guess the aims or objectives of a study, they may attempt to act in more socially desirable ways.

It’s appropriate to discuss reliability and validity in various sections of your thesis or dissertation or research paper . Showing that you have taken them into account in planning your research and interpreting the results makes your work more credible and trustworthy.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Middleton, F. (2023, June 22). Reliability vs. Validity in Research | Difference, Types and Examples. Scribbr. Retrieved August 5, 2024, from https://www.scribbr.com/methodology/reliability-vs-validity/

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