Use Intention and User Expectations of Human-Supported and Self-Help eHealth Interventions: Internet-Based Randomized Controlled Trial

Talia R Cohen Rodrigues; Thomas Reijnders; Linda D Breeman; Veronica R Janssen; Roderik A Kraaijenhagen; Douwe E Atsma; Andrea Wm Evers

doi:10.2196/38803

Use Intention and User Expectations of Human-Supported and Self-Help eHealth Interventions: Internet-Based Randomized Controlled Trial

JMIR Form Res. 2024 Feb 15:8:e38803. doi: 10.2196/38803.

Authors

Talia R Cohen Rodrigues¹, Thomas Reijnders¹, Linda D Breeman¹, Veronica R Janssen^{1

2}, Roderik A Kraaijenhagen^{3

4}, Douwe E Atsma², Andrea Wm Evers^{1

5

6}

Affiliations

¹ Health, Medical, and Neuropsychology Unit, Leiden University, Leiden, Netherlands.
² Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands.
³ NDDO Institute for Prevention and Early Diagnostics (NIPED), Amsterdam, Netherlands.
⁴ Vital10, Amsterdam, Netherlands.
⁵ Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands.
⁶ Medical Delta, Leiden University, Technical University of Delft, Erasmus University Rotterdam, Leiden, Delft, Rotterdam, Netherlands.

PMID: 38358784
PMCID: PMC10905349
DOI: 10.2196/38803

Abstract

Background: Self-help eHealth interventions provide automated support to change health behaviors without any further human assistance. The main advantage of self-help eHealth interventions is that they have the potential to lower the workload of health care professionals. However, one disadvantage is that they generally have a lower uptake. Possibly, the absence of a relationship with a health care professional (referred to as the working alliance) could lead to negative expectations that hinder the uptake of self-help interventions. The Unified Theory of Acceptance and Use of Technology (UTAUT) identifies which expectations predict use intention. As there has been no previous research exploring how expectations affect the adoption of both self-help and human-supported eHealth interventions, this study is the first to investigate the impact of expectations on the uptake of both kinds of eHealth interventions.

Objective: This study investigated the intention to use a self-help eHealth intervention compared to a human-supported eHealth intervention and the expectations that moderate this relationship.

Methods: A total of 146 participants were randomly assigned to 1 of 2 conditions (human-supported or self-help eHealth interventions). Participants evaluated screenshots of a human-supported or self-help app-based stress intervention. We measured intention to use the intervention-expected working alliance and the UTAUT constructs: performance expectancy, effort expectancy, and social influence.

Results: Use intention did not differ significantly between the 2 conditions (t₁₄₂=-1.133; P=.26). Performance expectancy (F_1,140=69.269; P<.001), effort expectancy (F_1,140=3.961; P=.049), social influence (F_1,140=90.025; P<.001), and expected working alliance (F_1,140=26.435; P<.001) were positively related to use intention regardless of condition. The interaction analysis showed that performance expectancy (F_1,140=4.363; P=.04) and effort expectancy (F_1,140=4.102; P=.045) more strongly influenced use intention in the self-help condition compared to the human-supported condition.

Conclusions: As we found no difference in use intention, our results suggest that we could expect an equal uptake of self-help eHealth interventions and human-supported ones. However, attention should be paid to people who have doubts about the intervention's helpfulness or ease of use. For those people, providing additional human support would be beneficial to ensure uptake. Screening user expectations could help health care professionals optimize self-help eHealth intervention uptake in practice.

Trial registration: OSF Registries osf.io/n47cz; https://osf.io/n47cz.

Keywords: UTAUT; Unified Theory of Acceptance and Use of Technology; eHealth; human support; use intention; working alliance.

©Talia R Cohen Rodrigues, Thomas Reijnders, Linda D Breeman, Veronica R Janssen, Roderik A Kraaijenhagen, Douwe E Atsma, Andrea WM Evers. Originally published in JMIR Formative Research (https://formative.jmir.org), 15.02.2024.