Meyerhoff Jonah, Haldar Shefali, Mohr David C
Center for Behavioral Intervention Technologies (CBITs), Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, 750 North Lake Shore Drive, 10 Floor, Chicago, IL 60611, United States of America.
Internet Interv. 2021 May 4;25:100399. doi: 10.1016/j.invent.2021.100399. eCollection 2021 Sep.
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.
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 ( = 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.
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 ( (4) = 5.24, = 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 ( = 0.29, = .037), but, contrary to expectations, was not predictive of either PHQ-9 scores (() = 0.14, = .89) or QIDS-C scores (() = 0.84, = .44) at post-treatment.
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.
支持性问责制（SA）是应用最为广泛的指导模式之一，旨在为干预措施使用者提供有关干预措施使用的明确期望、定期监测，并让使用者感觉到指导者值得信赖、仁慈且具备专业领域知识。然而，用于研究SA模式在指导数字干预措施中作用的方法很少。我们开发了支持性问责制量表（SAI），并评估了这种简短的自我报告量表的潜在因子结构和心理测量特性。
利用一项针对重度抑郁症的远程干预双臂随机试验（电话认知行为疗法[tCBT]或基于网络的认知行为疗法[iCBT]与tCBT的阶梯式护理模式）的数据，我们对SAI项目库进行了探索性因子分析，并探讨了最终版SAI与iCBT参与度以及抑郁结果之间的关系。我们分析中的参与者（n = 52）包括那些被随机分配接受iCBT，但由于对iCBT反应不足而未升级到tCBT、在10周评估点之前未缓解且完成了8个潜在SAI项目库的人。
最佳拟合的探索性因子分析模型仅包括原始8个项目库中的6个项目，包含两个因子：监测和期望。最终模型拟合情况喜忧参半，但可以接受（χ²(4) = 5.24，p = 0.26；RMSR = 0.03；RMSEA = 0.091；TLI = 0.967）。内部一致性在α = 0.68时可以接受。SAI显示出良好的收敛效度和区分效度。在10周/治疗中期时的SAI与iCBT使用天数显著相关（r = 0.29，p = 0.037），但与预期相反，在治疗后它并不能预测PHQ - 9评分（r = 0.14，p = 0.89）或QIDS - C评分（r = 0.84，p = 0.44）。
SAI是对SA框架结构的一种简短测量方法。有必要持续改进SAI并扩展其评估的结构，但SAI是迈向衡量一种能够支持数字心理健康干预措施依从性和改善结果的指导方案的第一步。
