Telehealth-Delivered Cognitive Behavioral Therapy for Insomnia in Individuals with Multiple Sclerosis: A Pilot Study.
Mult Scler Int
; 2022: 7110582, 2022.
Article
em En
| MEDLINE
| ID: mdl-35281348
Background: Over 50% of individuals with multiple sclerosis (MS) have moderate or severe sleep disturbances, insomnia being the most common. In-person cognitive behavioral therapy for insomnia (F2F-CBTi) is currently the first-line treatment for insomnia. However, given potential limitations to access including mobility difficulty, fatigue, or living in a rural area, telehealth-delivered CBT-I (tele-CBTi) has been considered as an alternative treatment. The purpose of this study was to assess the feasibility and treatment effect of tele-CBTi in people with MS and compare it to outcomes from a F2F-CBTi study in individuals with MS. Methods: 11 individuals with MS and symptoms of insomnia participated in 6 weekly CBT-I sessions with a trained CBT-I provider via live video. Insomnia severity (ISI), sleep quality (PSQI), and fatigue severity (FSS and MFIS) were assessed pre- and posttreatment as primary outcomes. Sleep onset latency (SOL), sleep efficiency (SE) and total sleep time (TST) from the PSQI, depression (PHQ-9), anxiety (GAD-7), sleep self-efficacy (SSES), and quality of life (MSIS-29) were also assessed pre- and posttreatment as secondary outcomes. Results: Participants resided in 9 different states. Retention and adherence rates were 100%. There were significant improvements in ISI, PSQI, MFIS, FSS, SOL, SSES, PHQ-9, and MSIS-29, but not SE, TST, or GAD-7. There were no significant differences between the F2F-CBTi group and tele-CBTi group for magnitude of change in the primary outcomes (ISI, PSQI, MFIS, and FSS) or the secondary outcomes (SOL, SE, TST, SSES, PHQ-9, GAD-7, and MSIS-29). Conclusions: Tele-CBTi is feasible and has outcome measures that are similar to that of in-person CBT-I treatment. Tele-CBTi may increase access to insomnia treatment in individuals with MS.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Mult Scler Int
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos