Faculty Bibliography

The widespread use of actigraphy has led to the recognition that a number of methodological issues have to be addressed to facilitate an increased acceptability of this relatively new method. These methodological issues include actigraph placement, reliability, and sensitivity, and the phenomenon known as the "first night effect." Our findings have demonstrated that actigraphy is a reliable instrument for assessment of sleep and wakefulness. In addition, actigraph placement and reliability do not constitute a significant methodological problem as no differences were found in all of these studies. We have also observed no first-night effects associated with sleep-wake monitoring with actigraphy.

Decades of empirical observations have established the validity of actigraphy primarily in individuals without sleep disorders. Methodological problems encountered thus far coupled with the widespread use of actigraphy signal the need for concentrated efforts to establish a consensus regarding scoring procedures. Currently available scoring methods show less reliability in clinical populations. To address these issues two validation studies were conducted: one for individuals without sleep disorders and the other for patients diagnosed with insomnia. The results of these two studies using the Actigraph Data Analysis Software as the scoring method have shown that the described system is fairly precise. It can be used for actigraphs with different features and mode of operation and is applicable to individuals with insomnia. These findings corroborate previous research showing that actigraphy is a valid instrument for assessment of sleep and wakefulness.

Current evidence has shown that, overall, actigraphy is an excellent tool for unobtrusive documentation of sleep/wake activity in normal individuals. However, a number of methodological issues remain to be resolved to warrant its use in clinical research. In this paper, we report the results of a study aimed at the development of a new scoring software that can accurately identify sleep and wakefulness. Using total sleep time as an index of comparison, the software was optimized on a calibration sample and prospectively tested on a validation sample. A strong correlation coefficient (r = 0.93, p < 0.008), with an average discrepancy value of 10 minutes, was observed for the calibration sample. The application of the optimal software to the validation sample revealed an even higher correlation coefficient (r = 0.97, p < 0.0001), with an average discrepancy value of 12 minutes.