Date Approved


Date Posted


Degree Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department or School


Committee Member

David C. S. Richard, Ph.D., Chair

Committee Member

Joseph Himle, Ph.D.

Committee Member

John Knapp, Ph.D.

Committee Member

Ellen Koch, Ph.D.

Committee Member

James Thornton, Ph.D.


Numerous studies have demonstrated the pervasiveness of inaccuracies in patients’ retrospective recall of their symptoms (e.g., Stone, Broderick, Shiffman, & Schwartz, 2004). Assessment methods that rely heavily on retrospective recall may lead to faulty clinical inferences should a patient’s recall be biased or inaccurate. Despite lingering concerns about the accuracy of retrospective recall in a variety of clinical and nonclinical populations, investigators have not studied individuals diagnosed with obsessive-compulsive disorder (OCD). This is troubling given findings from laboratory studies that OCD patients may have deficits in episodic memory (Muller & Roberts, 2005). This study investigated memory accuracy in OCD patients using an ecological momentary assessment (EMA) research methodology. By using handheld computers to collect self-monitoring data in real time, EMA data served as a criterion against which retrospective recall was tested for accuracy. Thirty-five patients diagnosed with OCD used a handheld computer to rate presence of OCD and related symptoms four times per day for a week. Patients estimated the frequency and duration of their behavior during the EMA self-monitoring phase. Results indicated that contrary to a priori hypotheses, OCD patients’ retrospective recall of their EMA recorded symptoms were relatively accurate. Consistent with hypotheses and previous studies, reactivity to the EMA data collection procedure was not observed. Finally, the results suggest that despite participants’ accuracy when recalling frequency and duration of symptoms, participants were inaccurate in estimating symptom covariance with supplemental items that measured non-OCD functioning (e.g., amount of sleep, current level of stress, etc.).