Measuring sleep in college students with insomnia Jacob M Williams Mentor: Daniel J. Taylor, Ph.D.

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1 Measuring sleep in college students with insomnia Jacob M Williams Mentor: Daniel J. Taylor, Ph.D.

2 Background When treating and diagnosing sleep disorders it is essential to obtain objective as well as subjective reports. The standard measure of sleep, polysomnography (PSG), is very time consuming, invasive, and expensive. Actigraphy (ACT) provide a cheap and non-invasive means of measuring sleep. Five previous studies on the use of actigraphy with ind. suffering from insomnia. These studies were with mostly older populations, predominantly over 40 years Buysse, Ancoli-Israel, Edinger, Lichstein, & Morin, 2006; Jean- Louis, Zizi, Von Gizycki, & Hauri, 1999; Vallieres, 2003; Lichstein, Stone, Donaldson, Nau, Soeffing, Murray et al., 2006;

3 Insomnia in College Students Insomnia is the most common sleep disorder among college students with approx. 17% of college students currently suffering Heightened stress levels and irregular sleep schedules are common among college students There is a need to validate the use actigraphy among the college age population of individuals with insomnia There may be differences from the populations previously studied. Bramoweth, 2006; Jensen, 2003

4 Hypothesis Actigraphy will serve as an accurate measure with college students suffering from insomnia for NWAK, WASO, TST, and SE but will not be effective in measuring SOL, in congruence with previous studies with older adults.

5 Methods Comparing a single night’s data from PSG, ACT and sleep diaries (SD) ACT scorings were computed using 3 different sensitivity thresholds Used AW64 actigraphs by MiniMitter Inc. Ambulatory PSG recordings were obtained with portable devices in the participants home

6 Participants N = 8 females, 4 males Ages: 18-23 (M=19.5) Excluded: Insufficient PSG, Act, or SD data All participants were undergraduates at the University of North Texas

7 Variables of Comparison SOL: Sleep onset latency NWAK: Number of awakenings WASO: Wake after sleep onset TST: Total sleep time SE: Sleep efficiency

8 Results PSG v SD correlations Trend for SOL Not sig. for WASO, NWAK, SE, or TST PSG v Act correlations Strong trend for SOL Sig. for TST and NWAK (both p <.01) on all sensitivity levels Not sig. for WASO and SE

9 Sleep efficiency PSG v SDPSG v Act

10 Conclusions SD alone are poor predictors of actual sleep variables SD frequently used alone in clinical settings Act follows trends of PSG well but may not represent true values In the process of computing differences of variance SD are still necessary to get satisfaction level and other subjective info

11 Limitations and in the future Continuing to score and collect data Direct control over the in and out of bed times Compare different brands of actigraphy with different analyses software

12 Acknowledgements Grants from MiniMitter Company Inc. and the University of North Texas Dr. Daniel J. Taylor Dr. Susan Eve