Smartphone apps for mental health and wellbeing: A usage survey and machine learning analysis of psychological and behavioral predictors.
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2023
- doi: 10.1177/20552076231152164
- issn: 2055-2076
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info:eu-repo/semantics/altIdentifier/doi/10.1177/20552076231152164
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info:eu-repo/semantics/altIdentifier/pmid/36714544
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info:eu-repo/semantics/altIdentifier/pissn/2055-2076
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info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_61093F7C9AEE4
info:eu-repo/semantics/openAccess , CC BY-NC-ND 4.0 , https://creativecommons.org/licenses/by-nc-nd/4.0/
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Mental hygiene Emotional health Mental physiology and hygieneCiter ce document
G. Vera Cruz et al., « Smartphone apps for mental health and wellbeing: A usage survey and machine learning analysis of psychological and behavioral predictors. », Serveur académique Lausannois, ID : 10.1177/20552076231152164
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Despite the availability of thousands of mental health applications, the extent to which they are used and the factors associated with their use remain largely unknown. The present study aims to (a) assess in a representative US-based population sample the use of smartphone apps for mental health and wellbeing (SAMHW), (b) determine the variables predicting the use of SAMHW, and (c) explore how a set of variables related to mental health, smartphone use, and smartphone "addiction" may be associated with the use of SAMHW. Data was collected via online questionnaire from 1989 adults. The data gathered included information on smartphone use behavior, mental health, and the use of SAMHW. Latent class analysis was used to categorize participants. Machine learning and logistic regression analyses were used to determine the most important predictors of SAMHW use and associations between predictors and outcome variables. While two-thirds of participants had a statistically high probability for using SAMHW, nearly twice more had high probability for using them to improve wellbeing compared to using them to address mental health problems (43% vs. 18%). In both groups, these participants were more likely to be female and in the younger adult age bracket than male and in the adult or older adult age bracket. According to the machine learning model, the most important predictors for using the relevant smartphone apps were variables associated with smartphone problematic use, COVID-19 impact, and mental health problems. Findings from the present study confirm that the use of SAMHW is growing, particularly among younger adult and female individuals who are negatively impacted by problematic smartphone use, COVID-19, and mental health problems. These individuals tend to bypass traditional care via psychotherapy or psychopharmacology, relying instead on smartphones to address mental health conditions or improve wellbeing. Advising users of these apps to also seek professional help and promoting efforts to prove the efficacy and safety of SAMHW would seem necessary.