Identify the major limitation of the psychologist's research design in terms of measurement frequency. Then, explain how transitioning to an interrupted time-series design would address this limitation and why it would lead to a more valid conclusion.
Case context: A clinical psychologist wants to test whether a new weekly therapy session reduces self-reported stress levels in college students. She measures students' stress levels once at the beginning of Week 7 (pretest), administers the therapy session, and measures their stress levels again at the beginning of Week 8 (posttest). She observes a drop in stress scores and concludes the therapy session was highly effective. However, historical data shows that students' stress levels naturally fluctuate significantly from week to week depending on their assignment schedules.
Question: Identify the major limitation of the psychologist's research design in terms of measurement frequency. Then, explain how transitioning to an interrupted time-series design would address this limitation and why it would lead to a more valid conclusion.
Sample answer: The major limitation of the psychologist's one-group pretest-posttest design is that it uses only one measurement before and one measurement after the treatment. This single comparison cannot distinguish between normal, week-to-week fluctuations in stress and the actual effect of the therapy session. Transitioning to an interrupted time-series design would address this by collecting multiple measurements of stress both before and after the therapy is introduced. These multiple measurements establish a baseline trend, allowing the researcher to determine if the stress reduction is a true effect of the therapy or simply a reflection of normal weekly variation.
Key points:
- A single pretest and posttest measurement cannot distinguish between a treatment effect and normal, ongoing fluctuations in the dependent variable.
- An interrupted time-series design involves collecting multiple measurements both before and after the intervention.
- Multiple measurements establish a baseline trend that helps rule out normal variation as the cause of the observed change.
Rubric: To receive full credit, the answer must: 1) Identify that the single pretest and posttest measurements cannot account for normal, ongoing fluctuations in the dependent variable. 2) Explain that transitioning to an interrupted time-series design involves collecting multiple measurements both before and after the intervention. 3) Explain that these multiple measurements establish a baseline trend to rule out normal variation, thereby leading to a more valid conclusion.
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