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The Transdiagnostic Intervention for Sleep and Circadian Dysfunction (TranS-C) for serious mental illness in community mental health part 2: Study protocol for a hybrid type 2 effectiveness-implementation cluster- randomized trial using train-the-trainer.
Callaway, Catherine A; Sarfan, Laurel D; Agnew, Emma R; Dong, Lu; Spencer, Julia M; Hache, Rafael Esteva; Diaz, Marlen; Howlett, Shayna A; Fisher, Krista R; Yates, Heather E Hilmoe; Stice, Eric; Kilbourne, Amy M; Buysse, Daniel J; Harvey, Allison G.
Affiliation
  • Callaway CA; University of California Berkeley.
  • Sarfan LD; University of California Berkeley.
  • Agnew ER; University of California Berkeley.
  • Dong L; RAND Corporation.
  • Spencer JM; University of California Berkeley.
  • Hache RE; University of California Berkeley.
  • Diaz M; University of California Berkeley.
  • Howlett SA; University of California Berkeley.
  • Fisher KR; University of California Berkeley.
  • Yates HEH; University of California Berkeley.
  • Stice E; Stanford University.
  • Kilbourne AM; Ann Arbor VAMC: VA Ann Arbor Healthcare System.
  • Buysse DJ; University of Pittsburgh.
  • Harvey AG; University of California Berkeley.
Res Sq ; 2023 Jun 17.
Article in En | MEDLINE | ID: mdl-37398014
ABSTRACT

Background:

Train-the-trainer (TTT) is a promising method for implementing evidence-based psychological treatments (EBPTs) in community mental health centers (CMHCs). In TTT, expert trainers train locally embedded individuals (i.e., Generation 1 providers) to deliver an EBPT, who then train others (i.e., Generation 2 providers). The present study will evaluate implementation and effectiveness outcomes of an EBPT for sleep and circadian dysfunction-the Transdiagnostic Intervention for Sleep and Circadian Dysfunction (TranS-C)-delivered to CMHC patients with serious mental illness by Generation 2 providers (i.e., trained and supervised within CMHCs via TTT). Specifically, we will investigate whether adapting TranS-C to fit CMHC contexts improves Generation 2 (a) patient outcomes (b) providers' perceptions of fit.

Methods:

TTT will be implemented in nine CMHCs in California, United States (N= 60 providers; N= 130 patients) via facilitation. CMHCs are cluster-randomized by county to Adapted TranS-C or Standard TranS-C. Within each CMHC, patients are randomized to immediate TranS-C or usual care followed by delayed treatment with TranS-C (UC-DT). Aim 1 will assess the effectiveness of TranS-C (combined Adapted and Standard), compared to UC-DT, on improvements in sleep and circadian problems, functional impairment, and psychiatric symptoms for Generation 2 patients. Aim 2 will evaluate whether Adapted TranS-C is superior to Standard TranS-C with respect to Generation 2 providers' perceptions of fit. Aim 3 will evaluate whether Generation 2 providers' perceived fit mediates the relation between TranS-C treatment condition and patient outcomes. Exploratory analyses will (1) evaluate whether the effectiveness of TranS-C for patient outcomes is moderated by generation, (2) compare Adapted and Standard TranS-C on patient perceptions of credibility/improvement and PhenX Toolkit outcomes (e.g., substance use, suicidality); and (3) evaluate other possible moderators.

Discussion:

This trial has potential to inform the process of (a) embedding local trainers and supervisors to expand delivery of a promising transdiagnostic treatment for sleep and circadian dysfunction, (b) adding to the growing body of TTT literature by evaluating TTT outcomes with a novel treatment and population, and (c) advancing our understanding of providers' perceptions of EBPT 'fit' across TTT generations. Trial registration Clinicaltrials.gov identifier NCT05805657. Registered on April 10, 2023. https//clinicaltrials.gov/ct2/show/NCT05805657.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Clinical_trials Language: En Journal: Res Sq Year: 2023 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Clinical_trials Language: En Journal: Res Sq Year: 2023 Type: Article