Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis

Wang, Tong; Wang, Wei; Liang, Jun; Nuo, Mingfu; Wen, Qinglian; Wei, Wei; Han, Hongbin; Lei, Jianbo

doi:10.1038/s41746-022-00692-9

Cited by 37 publications

(13 citation statements)

References 78 publications

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“…This excess usage early may lead to a drop in app engagement over time perhaps because of the e-attainment effect or boredom with the app. 27–29 This resulted in a higher app engagement in the first week compared to that of the guide group. Despite this, the guide group ended up completing more activities overall suggesting that the extra guidance facilitated not only increased app engagement, but also more consistent app use over time.…”

Section: Discussionmentioning

confidence: 99%

The impact of guided versus supportive coaching on mental health app engagement and clinical outcomes

Camacho,

Chang,

Currey

et al. 2023

Health Informatics J

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Although mobile mental health apps have the unique potential to increase access to care, evidence reveals engagement is low unless coupled with coaching. However, most coaching protocols are limited in their scalability. This study assesses how human support and guidance from a Digital Navigator (DN), a scalable coach, can impact mental health app engagement and effectiveness on anxiety and depressive symptoms. This study aims to detach components of coaching, specifically personalized recommendations versus general support, to inform scalability of coaching models for mental health apps. 156 participants were split into the DN Guide versus DN Support groups for the 6-week study. Both groups utilized the mindLAMP app for the duration of the study and had equal time with the DN, but the Guide group received personalized app recommendations. The Guide group completed significantly more activities than the Support group. 34% (49/139) of all participants saw a 25% decrease in PHQ-9 scores and 38% (53/141) saw a 25% decrease in GAD-7 scores. These findings show mental health apps, especially when supported by DNs, can reduce depression and anxiety symptoms when coupled with coaching, suggesting a feasible path for large-scale deployment.

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Section: Discussionmentioning

confidence: 99%

The impact of guided versus supportive coaching on mental health app engagement and clinical outcomes

Camacho,

Chang,

Currey

et al. 2023

Health Informatics J

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“…Nevertheless, adherence is most important. For continuous use, risk perception and performance expectation [ 48 ] as well as user experience and intent [ 49 ], next to influencing factors already presented in this paper such as age and perceived usefulness [ 50 ] are key. In future app developments such values should be considered.…”

Section: Discussionmentioning

confidence: 99%

Characterization of adults concerning the use of a hypothetical mHealth application addressing stress-overeating: an online survey

Lurz,

Gemesi,

Holzmann

et al. 2024

BMC Public Health

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Background About 40% of people respond to stress by consuming more unhealthy foods. This behavior is associated with increased energy intake and the risk of obesity. As mobile health (mHealth) applications (apps) have been shown to be an easy-to-use intervention tool, the characterization of potential app users is necessary to develop target group-specific apps and to increase adherence rates. Methods This cross-sectional online survey was conducted in the spring of 2021 in Germany. Sociodemographic data and data on personality (Big Five Inventory, BFI-10), stress-eating (Salzburg Stress Eating Scale, SSES), and technology behavior (Personal Innovativeness in the Domain of Information Technology, PIIT; Technology Acceptance Model 3, TAM 3) were collected. Results The analysis included 1228 participants (80.6% female, mean age: 31.4 ± 12.8 years, mean body mass index (BMI): 23.4 ± 4.3 kg/m2). Based on the TAM score, 33.3% (409/1228) of the participants had a high intention to use a hypothetical mHealth app to avoid stress-overeating. These persons are characterized by a higher BMI (24.02 ± 4.47 kg/m2, p < 0.001), by being stress-overeaters (217/409, 53.1%), by the personality trait “neuroticism” (p < 0.001), by having specific eating reasons (all p < 0.01), and by showing a higher willingness to adopt new technologies (p < 0.001). Conclusion This study suggests that individuals who are prone to stress-overeating are highly interested in adopting an mHealth app as support. Participants with a high intention to use an mHealth app seem to have a general affinity towards new technology (PIIT) and appear to be more insecure with conflicting motives regarding their diet. Trial registration This survey was registered in the German Clinical Trials Register (Registration number: DRKS00023984).

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“…The International Organization for Standardization defines usability as “the extent to which a system, product or service can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use.” 47 If researchers design an app with high usability, users will be more likely to continually use the app and even recommend it to peers. 48 – 50 …”

Section: Discussionmentioning

confidence: 99%

Understanding the research on tracking, diagnosing, and intervening in sleep disorders using mHealth apps: Bibliometric analysis and systematic reviews

et al. 2023

Self Cite

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Objectives In solving the global challenge of sleep disorders, Mobile Health app is one of the important means to monitor, diagnose, and intervene in sleep disorders. This study aims to (1) summarize the status and trends of research in this field; (2) assess the production and usage of sleep mHealth apps; (3) calculate the conversion rate of grants that the proportion of newly developed apps from being funded and developed to published on application stores. Methods Using bibliometric and content analysis methods, based on “Research Paper-Product Output-Product Application” chain and considering the “Research Grants” of articles, we conducted a systematic review of eight databases, to identify relevant studies over the last decade. Results Over the past decade, 1399 authors published 313 papers in 182 journals and conferences. The number of publications increased with an average annual growth of 41.6%. The current focus area is research using cognitive behavioral therapy to intervene in sleep. Sleep-staging tracking is a shortcoming of this field. A total 368 sleep mHealth apps (233 newly developed and 135 existing) were examined in 313 papers; 323 grants supported 178 articles (56.9%). Only 12 of the newly developed apps are used in the real world, resulting in a 9% grant conversion rate. Conclusions In the last decade, the field of tracking, diagnosing, and intervening in sleep disorders using mHealth apps has shown a trend of rapid development. However, the conversion rate of products from being funded and developed for use by end-users is low.

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Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis

Cited by 37 publications

References 78 publications

The impact of guided versus supportive coaching on mental health app engagement and clinical outcomes

The impact of guided versus supportive coaching on mental health app engagement and clinical outcomes

Characterization of adults concerning the use of a hypothetical mHealth application addressing stress-overeating: an online survey

Understanding the research on tracking, diagnosing, and intervening in sleep disorders using mHealth apps: Bibliometric analysis and systematic reviews

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