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Research Ethics

Research Ethics. Levels of Measurement. Ethical Issues Include:. Anonymity – researcher does not know who participated or is not able to match the response with the participant.

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Research Ethics

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  1. Research Ethics Levels of Measurement

  2. Ethical Issues Include: • Anonymity – researcher does not know who participated or is not able to match the response with the participant. • Confidentiality – no information given by individual respondents will be released by anyone. Results will be summarized across respondents. • Informed Consent – respondents will be fully informed about risks and benefits of the study. • Cultural Competency – efforts will be made to make sure research procedures and instruments are cultural and language appropriate. • Participants should not be harmed or harm should be kept to a minimum. • No one should be forced to participate. Participants do not have to answer every question. • Research studies should be reviewed by the employing organization’s institutional review board (IRB) to ensure that the project protects human subjects.

  3. Almost all research studies should: • Give potential respondents information about the study in a cover letter. • Have subjects sign a consent to participate form. For children under 18, parents should sign the form.

  4. Exceptions to this Rule: • In survey research, just returning the questionnaire implies consent. No consent form is needed. • For some practice-related research, clients have already given consent to participate in research when they signed up for the service. • For observational studies, no consent is needed if it takes place in a public setting. • Most types of secondary research (using data already collected) does not require informed consent if individual respondents can not be identified by the researcher.

  5. Information to include in a cover letter or consent form • Purpose of the study and when or where it will take place • Information about possible benefits of the study. • Information about possible risks to participants and how such risks will be minimized. • A statement that participation is voluntary and that people can withdraw at any time. • Information about where the researcher can be contacted for more information. • In some studies, the researcher also offers to give the respondent a report on the results of the study.

  6. Bias: • Quantitative researchers believe that all research should be objective. That the researcher’s own values should not be incorporated into the results or findings. • Qualitative researchers believe that no research is value free – the researcher’s choice of methodology reflects his or her values and that the researcher’s values along with the values of participants are important to the research process.

  7. Qualitative researchers control bias in their studies by: • Stating their values in any articles or reports that they write. • Verifying that the reports are accurate by establishing a feedback loop – involving participants in research design, data collection, and analysis. - having a second person check their results - simply reporting back to participants about what they have found.

  8. Other ethical issues in qualitative research include: • Verifying that participants have consented to participate. Sometimes it is not feasible to have participants sign consent forms – particularly when working with members of marginalized groups. You need to go through a process of gaining trust. • Using the results to promote social change. • Deception – conducting participant observation and not informing the people you have observed about your purpose.

  9. Levels of measurement determine the type of analysis used: • Nominal – Categorical; no implied rankings among the categories. Also includes written observations and written responses from qualitative interviews or open-ended survey questions. • Ordinal – Categorical data with implied rankings or data obtained through respondent ranking of categories. In some cases, a ranking process may be set up for a particular variable. • Interval – No fixed zero point. Data is numerical, not categorical. Rank order among variables is explicit with an equal distance between points in the data set: -2, -1, 0, +1, + 2 • Ratio – Fixed zero point; otherwise the same as interval.

  10. Rules for Determining Levels of Measurement • Any categorical data is either nominal or ordinal. • All qualitative data is nominal. • All scores on standardized scales are either interval or ratio. (Note: almost all the scales we use in social work, except IQ scores, are ratio).

  11. For example: • Nominal: “Respondent #1 said that the services she received did not meet her needs” (Quotation from Interview) • Nominal: Responses to Question – What is your gender – 1) Male 2) Female or • Also nominal: What is your income? • 1) Under $20,000 2) $20,000 to 39,999 3) $40,000 or more

  12. Examples of Ordinal Data • Would you say that your income is: 1) high 2) medium 3) low • Rank order the most important problem facing students today. • Do you engage in advocacy practice for your clients 1) Frequently 2) Seldom 3) Never • Class ranking of graduating students based on course grades

  13. Examples of Interval/Ratio Data • Scores on Standardized Tests – for example IQ or pre-prepared tests created to measures attitude or psychological states such as depression or self-esteem • Asking people for a numerical response in an interview or questionnaire – What is your age ____? What is your income___? • A likert scale – Usually 1-5 – that indicates an equal distance between response categories. For example, 1 = very satisfied, 2 = satisfied, 3 = neutral, 4 = unsatisfied, 5 = very unsatisfied.

  14. Other important terms related to measurement: • Reliability – does the research instrument or tool measure the same thing the same way consistently? (for example, a bathroom scale). • Validity – does the research instrument measure the actual concept it was intended to measure? • Discrete variable. A variable with only one or two categories (for example, yes/no). • Continuous variable - A variable with a large number of possible values. • Data set – All data collected for a study from all of the respondents. • Code book – a list of all possible values for each variable in a data set. (See code book on Dr. Hardina’s webpage).

  15. Exercise • Open SPSS file • Go into Variable View. • Input 5 variables: Code No Categories Gender 1 = Male 2 = Female Age No Categories Achieve 1 = High 2 = Medium 3 = Low Satisfy (Likert scale) 1 = Very Satisfied, 2 = Satisfied, 3 = Neutral, 4 = Unsatisfied, 5 = Very Unsatisfied. Save file on your disk as Mydata.sav On a sheet of paper, for every variable, state the level of measurement.

  16. Next week we will: • Spend more time on differences between qualitative and quantitative methods • Talk about categorical variables. • Talk about a type of descriptive statistic: frequencies • Talk about identifying categories using qualitative data analysis.

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