The Investigation of Mobile Health Stickiness: The Role of Social Support in a Sustainable Health Approach

Yin, Meng; Tayyab, Syed Muhammad Usman; Xu, Xiaoyu; Jia, Shuo-Wei; Wu, Chih‐Lun

doi:10.3390/su13041693

Cited by 18 publications

(9 citation statements)

References 78 publications

(192 reference statements)

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“…Although the scientific community has generally accepted the multidimensional nature of social support [49], its internal structure has yet to be reliably tested in order to confirm whether it is a hierarchical construct [21] or if each dimension is independent [22]. There are many reasons for this, including the fact that it is difficult to analyze a model which requires different measurement instruments or methods due to the dispersed nature of the proposed dimensions.…”

Section: Introductionmentioning

confidence: 99%

Perceived Social Support for a Sustainable Adolescence: A Theoretical Model of Its Sources and Types

et al. 2021

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Despite the growing interest in perceived social support as a means of achieving sustainable psychological development and well-being in the various contexts of the adolescent, its definition and composition remain unclear. The aim of this study is to test both the hierarchical order and the types and sources of a theoretical model of the social support perceived by adolescents. The model is based on the theories of Tardy and Lin, as well as on the findings of recent studies on the construct. Three theoretical models are compared using the structural equations method. The participants were 1081 randomly selected secondary school students (aged 12–18 years) from the north of Spain, who completed the APIK Perceived Social Support Questionnaire. The model positing that perceived social support comprises a hierarchical first level formed by sources of support (family, friends and teachers) and a lower second level derived from the first one, formed by types of support (emotional, material and informational), proved to be the first-choice solution. The results establish a solid theoretical base for both future studies on perceived social support during adolescence and possible educational interventions designed to improve social support for teenagers.

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Section: Introductionmentioning

confidence: 99%

Perceived Social Support for a Sustainable Adolescence: A Theoretical Model of Its Sources and Types

et al. 2021

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“…Furthermore, consumers' past performance in the freemium app also influenced (Shi et al, 2015;Tondello et al, 2019). Based on the research contexts investigated in existing research, IAPs have been examined using different forms of social dynamics, like social competition (Hamari et al, 2019), para-social interactions (Tseng and Lee, 2018), social norms (Rauschnabel et al, 2017), social interactions (Jang et al, 2021) and social stickiness (Yin et al, 2021). However, in the context of a gamified service, where challenge-based gamification is often utilized (Koivisto and Hamari, 2019;Legaki et al, 2020), social competition is a significant motivator of need-based interaction with the services (Landers et al, 2017).…”

Section: Determinants Of In-app Purchases In Freemium Servicesmentioning

confidence: 99%

The super engagers of freemium gamified services: using multimethod approach to examine why highly interactive consumers become paying consumers

Gupta

Kunkel

et al. 2022

INTR

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PurposeOnline services are increasingly utilizing gamification techniques to encourage consumer loyalty and engagement. However, the majority of the gamified services fail to be financially sustainable. Existing freemium and gamified services literature provides scant knowledge on behavioral predictors of in-app purchases in freemium gamified services. The research examines highly interactive consumers' in-app behaviors using competition-based motivational affordances, daily usage behavior and social competition motivation that convert them into super engagers.Design/methodology/approachThe authors applied a multimethod approach by using Multivariate Logistic Regression (n = 685) to analyze in-app behavioral data and Qualitative Comparative Analysis (n = 94) to examine survey and in-app behavioral data of highly interactive consumers of a freemium gamified service to explain paying behaviors.FindingsResults reveal highly interactive consumers that elicit heavy daily usage of the application or excel at in-app challenges are less likely to convert to super engagers. Among super engagers, some are socially competitive, and their inability to advance in the leaderboard corresponds to in-app purchases, while non-socially competitive consumers make purchases to collect extrinsic rewards. Additionally, highly interactive consumers who possess more knowledge about the gamified service become super engagers to increase their chances to be socially competitive.Originality/valueThis research examines in-app behaviors of highly interactive consumers of a freemium gamified service that lead to in-app purchases following varying levels of daily usage behavior and social competition motivation. The authors contribute to the previous literature by defining and examining a new consumer segment – super engagers – that is financially beneficial for freemium services because of their in-app purchases. The authors provide insight on in-app behaviors that convert highly interactive consumers to super engagers and demonstrate that the reason for highly interactive consumers to make in-app purchases is a function of acquiring specific internal and external rewards based on their level of social competition.

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“…Alternatively, stickiness in mental health apps may be more strongly associated with user engagement [ 18 , 19 ]. In the context of psychotherapy, greater engagement in therapy is associated with better outcomes after counseling interventions [ 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

Human-to-Computer Interactivity Features Incorporated Into Behavioral Health mHealth Apps: Systematic Search

Collier¹,

Hagemann²,

Trinidad³

et al. 2023

JMIR Form Res

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Background While there are thousands of behavioral health apps available to consumers, users often quickly discontinue their use, which limits their therapeutic value. By varying the types and number of ways that users can interact with behavioral health mobile health apps, developers may be able to support greater therapeutic engagement and increase app stickiness. Objective The main objective of this analysis was to systematically characterize the types of user interactions that are available in behavioral health apps and then examine if greater interactivity was associated with greater user satisfaction, as measured by app metrics. Methods Using a modified PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) methodology, we searched several different app clearinghouse websites and identified 76 behavioral health apps that included some type of interactivity. We then filtered the results to ensure we were examining behavioral health apps and further refined our search to include apps that identified one or more of the following terms: peer or therapist forum, discussion, feedback, professional, licensed, buddy, friend, artificial intelligence, chatbot, counselor, therapist, provider, mentor, bot, coach, message, comment, chat room, community, games, care team, connect, share, and support in the app descriptions. In the final group of 34 apps, we examined the presence of 6 types of human-machine interactivities: human-to-human with peers, human-to-human with providers, human-to–artificial intelligence, human-to-algorithms, human-to-data, and novel interactive smartphone modalities. We also downloaded information on app user ratings and visibility, as well as reviewed other key app features. Results We found that on average, the 34 apps reviewed included 2.53 (SD 1.05; range 1-5) features of interactivity. The most common types of interactivities were human-to-data (n=34, 100%), followed by human-to-algorithm (n=15, 44.2%). The least common type of interactivity was human–artificial intelligence (n=7, 20.5%). There were no significant associations between the total number of app interactivity features and user ratings or app visibility. We found that a full range of therapeutic interactivity features were not used in behavioral health apps. Conclusions Ideally, app developers would do well to include more interactivity features in behavioral health apps in order to fully use the capabilities of smartphone technologies and increase app stickiness. Theoretically, increased user engagement would occur by using multiple types of user interactivity, thereby maximizing the benefits that a person would receive when using a mobile health app.

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The Investigation of Mobile Health Stickiness: The Role of Social Support in a Sustainable Health Approach

Cited by 18 publications

References 78 publications

Perceived Social Support for a Sustainable Adolescence: A Theoretical Model of Its Sources and Types

Perceived Social Support for a Sustainable Adolescence: A Theoretical Model of Its Sources and Types

The super engagers of freemium gamified services: using multimethod approach to examine why highly interactive consumers become paying consumers

Human-to-Computer Interactivity Features Incorporated Into Behavioral Health mHealth Apps: Systematic Search

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