The Supportive Accountability Inventory: Psychometric properties of a measure of supportive accountability in coached digital interventions

Jonah Meyerhoff*, Shefali Haldar, David C. Mohr

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: One of the most widely used coaching models is Supportive Accountability (SA) which aims to provide intervention users with clear expectations for intervention use, regular monitoring, and a sense that coaches are trustworthy, benevolent, and have domain expertise. However, few measures exist to study the role of the SA model on coached digital interventions. We developed the Supportive Accountability Inventory (SAI) and evaluated the underlying factor structure and psychometric properties of this brief self-report measure. Method: Using data from a two-arm randomized trial of a remote intervention for major depressive disorder (telephone CBT [tCBT] or a stepped care model of web-based CBT [iCBT] and tCBT), we conducted an Exploratory Factor Analysis on the SAI item pool and explored the final SAI's relationship to iCBT engagement as well as to depression outcomes. Participants in our analyses (n = 52) included those randomized to a receive iCBT, but were not stepped up to tCBT due to insufficient response to iCBT, had not remitted prior to the 10-week assessment point, and completed the pool of 8 potential SAI items. Results: The best fitting EFA model included only 6 items from the original pool of 8 and contained two factors: Monitoring and Expectation. Final model fit was mixed, but acceptable (χ2(4) = 5.24, p = 0.26; RMSR = 0.03; RMSEA = 0.091; TLI = 0.967). Internal consistency was acceptable at α = 0.68. The SAI demonstrated good convergent and divergent validity. The SAI at the 10-week/mid-treatment mark was significantly associated with the number of days of iCBT use (r = 0.29, p =.037), but, contrary to expectations, was not predictive of either PHQ-9 scores (F(2,46) = 0.14, p =.89) or QIDS-C scores (F(2,46) = 0.84, p =.44) at post-treatment. Conclusion: The SAI is a brief measure of the SA framework constructs. Continued development to improve the SAI and expand the constructs it assesses is necessary, but the SAI represents the first step towards a measure of a coaching protocol that can support both coached digital mental health intervention adherence and improved outcomes.

Original languageEnglish (US)
Article number100399
JournalInternet Interventions
Volume25
DOIs
StatePublished - Sep 2021

Keywords

  • Behavioral intervention technology
  • Digital mental health
  • Human support
  • mHealth

ASJC Scopus subject areas

  • Health Informatics

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