Intention to Use a Mental Health App for Menopause: Health Belief Model Approach.

Autor:	Martin-Key NA; Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom., Funnell EL; Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom., Benacek J; Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom., Spadaro B; Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom., Bahn S; Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.
Jazyk:	angličtina
Zdroj:	JMIR formative research [JMIR Form Res] 2024 Oct 16; Vol. 8, pp. e60434. Date of Electronic Publication: 2024 Oct 16.
DOI:	10.2196/60434
Abstrakt:	Background: Menopause presents a period of heightened vulnerability for mental health issues. Despite this, mental health screening is not consistently integrated into menopausal health care, and access to psychological interventions is limited. Digital technologies, such as web and smartphone apps, may offer a way to facilitate and improve mental health care provision throughout menopause. However, little is known about potential users' intention to use such technologies during this critical phase of life. Objective: To examine the factors that impact the intention of potential users to use a mental health app during menopause, we used the Health Belief Model (HBM), a psychological framework widely used to understand and predict individuals' health-related behaviors. Methods: An online survey was generated. Convenience sampling was used, with participants recruited via social media and email, through relevant foundations and support groups, and by word of mouth. Structural equation modeling with maximum likelihood estimation was conducted to explore whether the factor structure of the HBM is a good fit for predicting the intention to use a mental health app for menopause. A Cronbach α value of .05 was used for determining statistical significance. Results: A total of 1154 participants commenced the survey, of which 82.49% (n=952) completed at least 97% of the survey. Of these, 86.76% (n=826) expressed that their menopausal symptoms had negatively affected their mental health, and went on to answer questions regarding their experiences and interest in using a web or smartphone app for mental health symptoms related to menopause. Data from this subgroup (N=826) were analyzed. In total, 74.09% (n=612) of respondents sought online help for mental health symptoms related to menopause. The most common topics searched for were symptom characteristics (n=435, 52.66%) and treatment or therapy options (n=210, 25.42%). Psychoeducation (n=514, 62.23%) was the most desired mental health app feature, followed by symptom tracking (n=499, 60.41%) and self-help tips (n=469, 56.78%). In terms of the intention to use a mental health app, the Satorra-Bentler-scaled fit statistics indicated a good fit for the model (χ2278=790.44, P<.001; comparative fit index=0.933, root mean square error of approximation=0.047, standardized root mean square residual=0.056), with cues to action emerging as the most significant predictor of intention (β=.48, P<.001). This was followed by perceived barriers (β=-.25, P<.001), perceived susceptibility (β=.15, P<.001), and perceived benefits (β=.13, P<.001). Perceived severity (β=.01, P=.869) and self-efficacy (β=.03, P=.286) were not significantly associated with behavioral intention. Conclusions: This study reveals important factors that influence the intention to use a mental health app during menopause. It emphasizes the need to address barriers to app usage, while highlighting the impact of credible endorsements and psychoeducation. Furthermore, the study underscores the significance of improving accessibility for users with lower digital literacy or limited resources. (©Nayra A Martin-Key, Erin L Funnell, Jiri Benacek, Benedetta Spadaro, Sabine Bahn. Originally published in JMIR Formative Research (https://formative.jmir.org), 16.10.2024.)
Databáze:	MEDLINE
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