Joelle, a life span developmental psychology graduate student, recently completed an internship at an adult day care facility. The majority of the facility’s clientele were elderly individuals who were living with their adult children and needed assistance with their activities of daily living (ADLs, i.e., eating, toileting, ambulating, bathing). The adult children typically worked during the day and could not afford a fulltime home nurse. In addition, most adult children were concerned that even if they could afford a home nurse, the inability of their parent to interact with others their own age would lead to a feeling of social isolation and eventually to depression. Therefore, while most of these elderly individuals used walkers or were in wheelchairs, they were still able to get around somewhat and interact with others their own age at the facility. However, at some point in the near future, most of the clients would probably have to be referred to a full-time care facility (i.e., a nursing home). 

In the past, each decision to refer a client to a full-time care facility was made on a case-by-case basis. However, a major determinant of whether a client was referred to a full-time care facility was how he or she scored on the standardized ADL scale. This scale measured how much difficulty (from 1 = none at all to 7 = a great extent) the client had performing personal functions such as bathing, ambulating, and eating. Those who scored beyond an established cutoff score were typically referred to nursing homes. However, the adult day care facility had received several complaints from the adult children of several clients that the test was somehow unfair or biased against minority clients. To the adult children, it appeared that minority clients were much more likely to be referred to a nursing home than were Caucasian clients. Therefore, the director of the center, knowing that Joelle had just completed an applied psychometrics course, asked her if she could somehow “determine” if, in fact, the ADL test was biased or unfair to minority clients. Joelle was unsure of where to start. She knew that the predictor was the ADL test, but what was the criterion? In addition, the adult day care facility wasn’t all that big and hadn’t been using the ADL test all that long, so there weren’t many data available on who had and had not been referred, particularly for minority clients. A little unsure of where to even start, Joelle decided it was time to e-mail her psychometrics professor to see if he had any suggestions for her. 

Questions 

1. If you were Joelle, where would you start? What key factors would you want to consider? 

2. What information would you want to know from the test publisher or from reviews conducted of the test? 

3. Does this appear to be more of a test bias or test fairness issue? Why? 

4. If Joelle wanted to examine for test bias, what data would she need? 

5. Which of the models of test fairness presented in the module overview would be most applicable here? Why? 

6. Assuming Joelle actually found the test to be “unfair,” what could she do to make the test fair?