Assessing College Students' Perceptions of and Intentions to Use a Mobile App for Mental Health

Predicting Therapists' Intentions to Use Innovations: Comparing the Role of Individual, Organizational, and Innovation Characteristics

Theories emphasize the role of individual and organizational characteristics in implementation outcomes, yet research indicates that these characteristics account for only a small amount of variance in those outcomes. Innovation characteristics might be important proximal determinants of implementation outcomes but are infrequently examined in mental health services research. This study examined the relative variance explained by individual, organizational, and innovation characteristics on behavioral intentions, a central implementation outcome in implementation theories. Data were collected from 95 therapists and 28 supervisors who participated in a cluster randomized trial that tested the effectiveness of two clinical decision-making innovations. Multilevel models compared individual, organizational, and innovation characteristics as predictors of therapists' intentions to use the innovations. Subsequent mediational path analyses tested whether innovation characteristics mediated the effect of innovation type on intentions. Individual and organizational characteristics explained 29% of the variability in therapists' intentions. Approximately 75% of the variability in therapists' intentions was accounted for by innovation characteristics. Individual and organizational characteristics were not statistically significant predictors of intentions after controlling for innovation characteristics. The indirect effect of innovation type on intentions through therapists' beliefs was statistically significant (B = 0.410, 95% Bootstrapped CI = [0.071, 0.780]), but the direct effect of innovation type was not (B = 0.174, p = .365). Innovation characteristics are related to therapist intentions and might explain why some innovations are received more favorably than others. Future studies should explore the complex interrelationships between these beliefs alongside other individual or organizational characteristics.

Young adults' adoption and use of mental health apps: efficient, effective, but no replacement for in-person care

Objective: Millions of people use mobile phone or computer-based applications-apps-to maintain their mental health and connect with treatment providers through text- and video-based chat functions. The present study sought to understand young adults' motivations for adopting this technology using the unified theory of acceptance and use of technology (UTAUT), how they use mental health apps, and the gratifications they receive from using mental health apps. Participants: One hundred-eighteen mental health app users responded to an online survey. Methods: A survey was conducted with students at a Midwestern university. The survey included questions regarding current mental health services, mental health apps used, UTAUT and gratifications survey items. Results: A regression analysis suggested users' performance expectancies, effort expectancies, and facilitating conditions predicted the adoption of mental health apps. Young adults most often use mental health apps for stress relief. While they preferred in-person treatment, users described mental health apps as efficient and helpful. Conclusion: Overall, the results reinforce the sense of optimism for the future of mental health apps, suggesting the potential for apps to supplement-but not necessarily replace-in-person care.

Factors Predicting Older People's Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

BACKGROUND

Mobile health (mHealth) services enable real-time measurement of information on individuals' biosignals and environmental risk factors; accordingly, research on health management using mHealth is being actively conducted.

OBJECTIVE

The study aims to identify the predictors of older people's intention to use mHealth in South Korea and verify whether chronic disease moderates the effect of the identified predictors on behavioral intentions.

METHODS

A cross-sectional questionnaire study was conducted among 500 participants aged 60 to 75 years. The research hypotheses were tested using structural equation modeling, and indirect effects were verified through bootstrapping. Bootstrapping was performed 10,000 times, and the significance of the indirect effects was confirmed through the bias-corrected percentile method.

RESULTS

Of 477 participants, 278 (58.3%) had at least 1 chronic disease. Performance expectancy (β=.453; P=.003) and social influence (β=.693; P<.001) were significant predictors of behavioral intention. Bootstrapping results showed that facilitating conditions (β=.325; P=.006; 95% CI 0.115-0.759) were found to have a significant indirect effect on behavioral intention. Multigroup structural equation modeling testing the presence or absence of chronic disease revealed a significant difference in the path of device trust to performance expectancy (critical ratio=-2.165). Bootstrapping also confirmed that device trust (β=.122; P=.039; 95% CI 0.007-0.346) had a significant indirect effect on behavioral intention in people with chronic disease.

CONCLUSIONS

This study, which explored the predictors of the intention to use mHealth through a web-based survey of older people, suggests similar results to those of other studies that applied the unified theory of acceptance and use of technology model to the acceptance of mHealth. Performance expectancy, social influence, and facilitating conditions were revealed as predictors of accepting mHealth. In addition, trust in a wearable device for measuring biosignals was investigated as an additional predictor in people with chronic disease. This suggests that different strategies are needed, depending on the characteristics of users.

Leveraging Mobile Health to Manage Mental Health/Behavioral Health Disorders: Systematic Literature Review

BACKGROUND

Mental health is a complex condition, highly related to emotion. The COVID-19 pandemic caused a significant spike in depression (from isolation) and anxiety (event related). Mobile Health (mHealth) and telemedicine offer solutions to augment patient care, provide education, improve symptoms of depression, and assuage fears and anxiety.

OBJECTIVE

This review aims to assess the effectiveness of mHealth to provide mental health care by analyzing articles published in the last year in peer-reviewed, academic journals using strong methodology (randomized controlled trial).

METHODS

We queried 4 databases (PubMed, CINAHL [Cumulative Index to Nursing and Allied Health Literature], Web of Science, and ScienceDirect) using a standard Boolean search string. We conducted this systematic literature review in accordance with the Kruse protocol and reported it in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 checklist (n=33).

RESULTS

A total of 4 interventions (mostly mHealth) from 14 countries identified improvements in primary outcomes of depression and anxiety as well as in several secondary outcomes, namely, quality of life, mental well-being, cognitive flexibility, distress, sleep, self-efficacy, anger, decision conflict, decision regret, digestive disturbance, pain, and medication adherence.

CONCLUSIONS

mHealth interventions can provide education, treatment augmentation, and serve as the primary modality in mental health care. The mHealth modality should be carefully considered when evaluating modes of care.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022343489; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=343489.

Psychological Help-Seeking Among College Students: Applying the Multi-Theory Model of Health Behavior Change in Assessing Telehealth Use for Psychological Help-Seeking

Background

Due to the deleterious effects on psychological health and wellbeing spurred by the pandemic, utilization of telehealth-based care increased over the past few years. The rapid transition from in-person to telehealth-based health service delivery has yet to be fully understood. The aim of the current study was to examine telehealth use for psychological help-seeking among college students using the Multi-theory Model of health behavior change (MTM) as a theoretical framework.

Methods

A cross-sectional and survey-based study was conducted among students at a large US university (N = 356). Valid and reliable scales were used to measure domains of psychological distress and MTM constructs. Participants were grouped based on past 12-month utilization of telehealth for any mental, emotional, or substance use problems.

Results

Roughly 67% of the sample reported that they needed help dealing with psychological distress, and 56.1%,43.3%, and 38.7% screened positive for anxiety, depression, and suicidal ideation, respectively. Depression, anxiety, and suicidal ideation were positively associated with past 12-month telehealth-based help-seeking. Past 12-month telehealth users reported greater advantages, confidence, and emotion direction toward telehealth-based psychological help-seeking than their counterparts. Participants also perceived higher exhibition of behavioral skills and greater social support to aid help-seeking than their counterparts. Advantages and disadvantages as well as behavioral confidence predicted intentions for telehealth-based help-seeking after controlling for anxiety, depression, suicidal ideation, perceived stigma, and perceived need for help among both groups.

Conclusion

The MTM theoretical framework is a valuable framework for predicting telehealth-based psychological help-seeking among college students. Such framework can be used to design and implement mental health programing.