TY - JOUR
T1 - Delivering digital cognitive behavioral therapy for insomnia at scale
T2 - does using a wearable device to estimate sleep influence therapy?
AU - Luik, Annemarie I.
AU - Farias Machado, Pedro
AU - Espie, Colin A.
N1 - Publisher Copyright:
© 2018, The Author(s).
PY - 2018/2/19
Y1 - 2018/2/19
N2 - Contemporary developments, such as digital Cognitive Behavioral Therapy (CBT) and wearable devices estimating sleep, could support the implementation of CBT for insomnia at a large scale. We assessed what characterizes those users who connected a wearable device to the program to estimate sleep diary variables, and whether connecting a wearable device affected insomnia symptom improvement, related well-being, and program interaction. In total, 3551 users (63% female, mean age 44.50 ± 14.78 years) of a dCBT program who completed a post-therapy survey, including 378 users (10.6%) who used a device, were selected. Within-subject, pre-therapy to post-therapy, the Sleep Condition Indicator (SCI, 7 Items) was used to assess insomnia. Two-item measures (depression, anxiety) and single item measures (perceived stress, life satisfaction, work productivity) of well-being were analyzed, in addition to program interaction. For all participants, insomnia symptoms significantly improved following dCBT (t(3504) = 83.33, p < 0.001; Cohen’s d = 1.45), as did depression and anxiety symptoms, perceived stress, life satisfaction and work productivity. Those who did not connect a device reported better sleep and less affected work productivity (all p <.001) than those who did connect a device at baseline and post-treatment; nevertheless treatment effects were largely similar for the two groups. Those who connected a device interacted more with additional program components. In conclusion, improvements in insomnia after completing dCBT are similar in persons choosing to wear a wearable device to estimate sleep and persons completing a subjective sleep diary. Potentially, use of wearable devices can facilitate treatment for those who struggle to complete daily diaries.
AB - Contemporary developments, such as digital Cognitive Behavioral Therapy (CBT) and wearable devices estimating sleep, could support the implementation of CBT for insomnia at a large scale. We assessed what characterizes those users who connected a wearable device to the program to estimate sleep diary variables, and whether connecting a wearable device affected insomnia symptom improvement, related well-being, and program interaction. In total, 3551 users (63% female, mean age 44.50 ± 14.78 years) of a dCBT program who completed a post-therapy survey, including 378 users (10.6%) who used a device, were selected. Within-subject, pre-therapy to post-therapy, the Sleep Condition Indicator (SCI, 7 Items) was used to assess insomnia. Two-item measures (depression, anxiety) and single item measures (perceived stress, life satisfaction, work productivity) of well-being were analyzed, in addition to program interaction. For all participants, insomnia symptoms significantly improved following dCBT (t(3504) = 83.33, p < 0.001; Cohen’s d = 1.45), as did depression and anxiety symptoms, perceived stress, life satisfaction and work productivity. Those who did not connect a device reported better sleep and less affected work productivity (all p <.001) than those who did connect a device at baseline and post-treatment; nevertheless treatment effects were largely similar for the two groups. Those who connected a device interacted more with additional program components. In conclusion, improvements in insomnia after completing dCBT are similar in persons choosing to wear a wearable device to estimate sleep and persons completing a subjective sleep diary. Potentially, use of wearable devices can facilitate treatment for those who struggle to complete daily diaries.
UR - http://www.scopus.com/inward/record.url?scp=85089606079&partnerID=8YFLogxK
U2 - 10.1038/s41746-017-0010-4
DO - 10.1038/s41746-017-0010-4
M3 - Article
C2 - 31304289
AN - SCOPUS:85089606079
SN - 2398-6352
VL - 1
JO - npj Digital Medicine
JF - npj Digital Medicine
IS - 1
M1 - 3
ER -