4.7 Article

Assessing Therapeutic Alliance in the Context of mHealth Interventions for Mental Health Problems: Development of the Mobile Agnew Relationship Measure (mARM) Questionnaire

Journal

JOURNAL OF MEDICAL INTERNET RESEARCH
Volume 20, Issue 4, Pages -

Publisher

JMIR PUBLICATIONS, INC
DOI: 10.2196/jmir.8252

Keywords

mobile health; health care provider; digital interventions; therapeutic alliance; mental health; measure development

Funding

  1. MRC [MR/L005301/1, MR/P026664/1] Funding Source: UKRI

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Background: Digital health interventions in the form of smartphone apps aim to improve mental health and enable people access to support as and when needed without having to face the stigma they may experience in accessing services. If we are to evaluate mobile health (mHealth) apps and advance scientific understanding, we also need tools to help us understand in what ways mHealth interventions are effective or not. The concept of therapeutic alliance, a measure of the quality of the relationship between a health care provider and a service user, is a key factor in explaining the effects of mental health interventions. The Agnew Relationship Measure (ARM) is a well-validated measure of therapeutic alliance in face-to-face therapy. Objective: This study presented the first attempt to (1) explore service users' views of the concept of relationship within mHealth mental health interventions and (2) adapt a well-validated face-to-face measure of therapeutic alliance, the Agnew Relationship Measure (ARM), for use with mHealth interventions. Methods: In stage 1, we interviewed 9 mental health service users about the concept of therapeutic alliance in the context of a digital health intervention and derived key themes from interview transcripts using thematic analysis. In stage 2, we used rating scales and open-ended questions to elicit views from 14 service users and 10 mental health staff about the content and face validity of the scale, which replaced the word therapist with the word app. In stage 3, we used the findings from stages 1 and 2 to adapt the measure with the support of a decision-making algorithm about which items to drop, retain, or adapt. Results: Findings suggested that service users do identify relationship concepts when thinking about mHealth interventions, including forming a bond with an app and the ability to be open with an app. However, there were key differences between relationships with health professionals and relationships with apps. For example, apps were not as tailored and responsive to each person's unique needs. Furthermore, apps were not capable of portraying uniquely human-like qualities such as friendliness, collaboration, and agreement. We made a number of changes to the ARM that included revising 16 items; removing 4 items due to lack of suitable alternatives; and adding 1 item to capture a key theme derived from stage 1 of the study (The app is like having a member of my care team in my pocket). Conclusions: This study introduces the mHealth version of the ARM, the mARM, that has good face and content validity. We encourage researchers to include this easy-to-use tool in digital health intervention studies to gather further data about its psychometric properties and advance our understanding of how therapeutic alliance influences the efficacy of mHealth interventions.

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