Mobile apps for healthy living: Factors influencing continuance intention for health apps

Yan, Min; Filieri, Raffaele; Raguseo, Elisabetta; Gorton, Matthew

doi:10.1016/j.techfore.2021.120644

Cited by 113 publications

(95 citation statements)

References 116 publications

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“…Moreover, the findings affirm the results of DT research applied in areas such as healthcare ( Alam et al., 2020 ; Rodger, 2014 ; Yan et al., 2021 ), education ( Navaridas-Nalda et al., 2020 ; Taghizadeh et al., 2021 ), digital services ( Jain et al., 2021 ; Jaklič et al., 2018 ; Thakurta et al., 2020 ), blockchain ( Queiroz and Fosso Wamba, 2019 ), Internet of Things ( Aldossari and Sidorova, 2020 ), and artificial intelligence ( Cabrera-Sá nchez et al., 2021 ).…”

Section: Discussionsupporting

confidence: 73%

Drivers of digital transformation adoption: A weight and meta-analysis

Cavalcanti

Oliveira

Santini

2022

Heliyon

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An update of digital transformation (DT) through a weight and meta-analysis. Contribution to DT literature by surpassing biases and limitations of size estimates. Identification of promising and best predictors for further DT adoption research. Behavioral intentions, satisfaction, and habit are best predictors for DT use. Usefulness and ease of use are pivotal, being moderated by culture and innovation.

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Section: Discussionsupporting

confidence: 73%

Drivers of digital transformation adoption: A weight and meta-analysis

Cavalcanti

Oliveira

Santini

2022

Heliyon

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“…In recent years, many scholars have focused on adopting and using information technology (IT)/information systems (IS) products or services (Franque et al, 2021;Jain et al, 2021;Yan et al, 2021). Such IT/IS scholars have been interested in studying users' usage behavior toward IT/IS products or services.…”

Section: Review Of It/is Continuance Studiesmentioning

confidence: 99%

“…Thus, a quantitative study was conducted in China. Using some major platforms such as WeChat and QQ (Yan et al, 2021), data from Ant Forest users were collected based on a convenience sampling technique. Participants were also asked to share the questionnaire's link with their friends, coworkers and various WeChat and QQ groups.…”

Section: Data Collection and Proceduresmentioning

confidence: 99%

“…Furthermore, this research offers several new correlates that augment our understanding of the important roles of personal attributes-related constructs (affection and altruism) and motivational-related constructs (reward for activities and selfpromotion) that drive users' continuance intentions in the Ant Forest setting. There is a substantial body of research in the technological environment on the factors that influence continuance intention (Ashfaq et al, 2021b;Shiau et al, 2020;Yan et al, 2021;Zhang et al, 2020); however, not much is known about how affection, altruism, reward for activities and self-promotion drive continuance intention. In this respect, the current study theorizes these factors in the context of Ant Forest and confirms that they are all important antecedents that positively influence Ant Forest users' continuance intentions, thereby uniquely contributing to the existing literature.…”

Section: Understandingmentioning

confidence: 99%

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Understanding Ant Forest continuance: effects of user experience, personal attributes and motivational factors

Ashfaq

Zafar

Malik

et al. 2021

IMDS

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PurposeTechnology has emerged as a leading tool to address concerns regarding climate change in the recent era. As a result, the green mobile application – Ant Forest – was developed, and it has considerable potential to reduce negative environmental impacts by encouraging its users to become involved in eco-friendly activities. Ant Forest is a novel unexplored green mobile gaming phenomenon. To address this gap, this study explores the influence of user experience (cognitive experience and affective experience), personal attributes (affection and altruism) and motivational factors in game play (reward for activities and self-promotion) on the continuation intention toward Ant Forest.Design/methodology/approachThe authors assessed the data using partial least squares structural equation modeling (PLS-SEM) for understanding users' continuation intention toward Ant Forest.FindingsThrough a survey of 337 Ant Forest users, the results reveal that cognitive and affective experiences substantially affect Ant Forest continuation intention. Personal attributes and motivational factors also stimulate users to continue using Ant Forest.Originality/valueThe authors build and confirm a conceptual framework to understand users' continuation intention toward a novel unexplored Ant Forest phenomenon.

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“…Thus, the positive outcomes of health apps may not be maximized. Due to the importance of continuing use of health technology, including health apps, continuous use behavior has been researched among general users; however, insufficient research targeting older adults has been conducted [ 10 ]. Therefore, it is critical to investigate older adults’ usage behavior toward health apps to provide better health interventions for them.…”

Section: Introductionmentioning

confidence: 99%

Determinants of Continuance Intention to Use Health Apps among Users over 60: A Test of Social Cognitive Model

Kim

Han

2021

IJERPH

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Promoting healthy behavior among seniors is important in reducing the burden of care and healthcare expenses in a rapidly aging society. Health apps can play an important role in health promotion for older adults, but the level of user retention in health apps is low. To increase continued health app use among older adults, this study examined the factors influencing older users’ continuance intentions to use health apps. The research model was developed based on the social cognitive theory of health behavior, which integrates cognitive, environmental, and behavioral perspectives. To test the research model, an anonymous online survey was conducted among respondents aged 60 to 79 years who were using health apps. The measurement items in the questionnaire were developed based on validated scales from the literature. A total of 250 samples were analyzed. The assessment of the measurement model indicates that the reliability and validity of the items are satisfactory. The results of testing the structural model illustrate the determinants of health app continuance intention: health technology self-efficacy, self-evaluative outcome expectations, self-regulation, and privacy risk. The interrelationships among determinants are also investigated. Theoretical and practical implications are suggested to encourage older adults’ continued health app use and promote their health behavior over the long term.

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Mobile apps for healthy living: Factors influencing continuance intention for health apps

Cited by 113 publications

References 116 publications

Drivers of digital transformation adoption: A weight and meta-analysis

Drivers of digital transformation adoption: A weight and meta-analysis

Understanding Ant Forest continuance: effects of user experience, personal attributes and motivational factors

Determinants of Continuance Intention to Use Health Apps among Users over 60: A Test of Social Cognitive Model

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