Perceptions of Factors Influencing Engagement With Health and Well-being Apps in the United Kingdom: Qualitative Interview Study

Szinay, Dorothy; Perski, Olga; Jones, Andy; Chadborn, Tim; Brown, Jamie; Naughton, Felix

doi:10.2196/29098

Cited by 38 publications

(33 citation statements)

References 41 publications

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“…A faulty app that presents errors or bugs to the user can also have a negative impact in user engagement ( 63 ). In line with previous findings, the existence of human support is a critical aspect of digital interventions and reinforces the importance of the therapeutic alliance even in digital interventions ( 64 , 65 ). Also, credibility can lead to more engaged users if the app incorporates expertise or clinician encouragement ( 21 ).…”

Section: Discussionsupporting

confidence: 90%

User engagement in mobile apps for people with schizophrenia: A scoping review

Almeida

Marques

2023

Front. Digit. Health

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Over the past decade, there has been an increase in the number of mobile apps designed for mental health proposes and mHealth has been perceived as a promising approach to help people with schizophrenia to manage their condition. However, adoption rates are relatively low and long-term user engagement is a major issue. The aim of this study is to identify and better understand what strategies and factors may influence user engagement and facilitate prolonged use of apps for people with schizophrenia to better manage their illness. A scoping review was conducted in accordance with the Arksey and O’Malley scoping review framework and following PRISMA ScR guidelines. The sources consisted of searching four electronic databases. Rayyan software was used for this study selection process and a narrative approach was used to synthesize the extracted data. A total of 28 studies which met the inclusion criteria were identified. The engagement strategies included push notifications, message prompts, personalization, application customization, goal setting, game-like features, use of different multimedia formats, social connectedness, support (peers and professionals), reliability of content and quality of feedback received. Some demographic factors may influence adherence such as age, gender, education level and socioeconomic status. Other factors also may play a role impacting engagement: health status, data privacy and security, involvement in design process, incentives for participation, app usage fitting in the user routines, initial training, and constant technical support. Included studies present high heterogeneity in outcome measures and thresholds criteria to assess engagement. Understanding what influences engagement and how to measure it is essential to enhance the design of mobile apps and deliver scalable solutions to help people with schizophrenia better manage their illness in their real-world uptake.

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Section: Discussionsupporting

confidence: 90%

User engagement in mobile apps for people with schizophrenia: A scoping review

Almeida

Marques

2023

Front. Digit. Health

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“…In line with these findings, our intervention included morning and evening check-ins and personalization of content. Users received customizable notification-type reminders—a feature that has been identified as useful for engagement with digital health interventions [ 21 , 22 ].…”

Section: Discussionmentioning

confidence: 99%

“…Our achievement of high user retention and engagement with a CA-based, pain-customized, digital mental health intervention has clear implications for addressing issues of suboptimal engagement with digital health interventions and of improving access to care for chronic pain. Research indicates that people with chronic pain are almost twice as likely to drop out from self-guided digital interventions when compared to traditional, guided interventions [ 21 ]. Despite this, the present trial achieved high levels of retention and engagement among a sample of individuals with chronic pain.…”

Section: Discussionmentioning

confidence: 99%

Adherence and Engagement With a Cognitive Behavioral Therapy–Based Conversational Agent (Wysa for Chronic Pain) Among Adults With Chronic Pain: Survival Analysis

Sinha¹,

Cheng²,

Kadaba³

2022

JMIR Form Res

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Background Digital applications are commonly used to support mental health and well-being. However, successfully retaining and engaging users to complete digital interventions is challenging, and comorbidities such as chronic pain further reduce user engagement. Digital conversational agents (CAs) may improve user engagement by applying engagement principles that have been implemented within in-person care settings. Objective To evaluate user retention and engagement with an artificial intelligence–led digital mental health app (Wysa for Chronic Pain) that is customized for individuals managing mental health symptoms and coexisting chronic pain. Methods In this ancillary survival analysis of a clinical trial, participants included 51 adults who presented to a tertiary care center for chronic musculoskeletal pain, who endorsed coexisting symptoms of depression or anxiety (Patient-Reported Outcomes Measurement Information System score of ≥55 for depression or anxiety), and initiated onboarding to an 8-week subscription of Wysa for Chronic Pain. The study outcomes were user retention, defined as revisiting the app each week and on the last day of engagement, and user engagement, defined by the number of sessions the user completed. Results Users engaged in a cumulative mean of 33.3 sessions during the 8-week study period. The survival analysis depicted a median user retention period (i.e., time to complete disengagement) of 51 days, with the usage of a morning check-in feature having a significant relationship with a longer retention period (P=.001). Conclusions Our findings suggest that user retention and engagement with a CBT-based CA built for users with chronic pain is higher than standard industry metrics. These results have clear implications for addressing issues of suboptimal engagement of digital health interventions and improving access to care for chronic pain. Future work should use these findings to inform the design of evidence-based interventions for individuals with chronic pain and to enhance user retention and engagement of digital health interventions more broadly. Trial Registration ClinicalTrials.gov NCT04640090; https://clinicaltrials.gov/ct2/show/NCT04640090

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“…For example, previous studies with shorter follow-up periods have identified that factors such as health literacy, motivation, capabilities, social and environmental structures, and social support have an impact on mHealth engagement [ 51 , 52 ]. However, this study shows that patients’ motivation, capability, and social and environmental factors change over time.…”

Section: Discussionmentioning

confidence: 99%

Examining Use Behavior of a Goal-Supporting mHealth App in Primary Care Among Patients With Multiple Chronic Conditions: Qualitative Descriptive Study

et al. 2022

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Background Although mobile health (mHealth) apps are increasingly being used to support patients with multiple chronic conditions (multimorbidity), most mHealth apps experience low interaction and eventual abandonment. To tackle this engagement issue, when developing an mHealth program, it is important to understand the social-behavioral factors that affect patients’ use behavior. Objective The aim of this study was to explore the social and behavioral factors contributing to patients’ use behavior of an mHealth app called the electronic Patient-Reported Outcome (ePRO). The ePRO app supports goal-oriented care delivery in interdisciplinary primary care models. Methods A descriptive qualitative study was used to analyze interview data collected for a larger mixed methods pragmatic trial. The original 15-month trial was conducted in 6 primary care teams across Ontario, Canada, between 2018 and 2019. The eligibility criteria for patients were being aged ≥60 years with ≥10 visits within the previous 12 months of study enrollment. For this analysis, patients were classified as long-term or short-term users based on their length of use of the ePRO app during the trial. The Social Cognitive Theory by Bandura was used to categorize social-behavioral factors that contributed to patients’ decision to continue or discontinue using the app. Results The patient-provider relationship emerged as a key factor that shaped patients’ experiences with the app and subsequent decision to continue using the app. Other factors that contributed to patients’ decision to continue using the app were personal and social circumstances, perceived usefulness, patients’ previous experience with goal-related behaviors, and confidence in one’s capability. There was an overlap of experience between long- and short-term app users but, in general, long-term users perceived the app to be more useful and their goals to be more meaningful than short-term app users. This observation was complicated by the fact that patient health-related goals were dynamic and changed over time. Conclusions Complex patients’ use behavior of a goal-supporting mHealth app is shaped by an array of sociobehavioral factors that can evolve. To tackle this dynamism, there should be an emphasis on creating adaptable health technologies that are easily customizable by patients and able to respond to their changing contexts and needs. Trial Registration ClinicalTrials.gov NCT02917954; https://clinicaltrials.gov/ct2/show/NCT02917954

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Perceptions of Factors Influencing Engagement With Health and Well-being Apps in the United Kingdom: Qualitative Interview Study

Cited by 38 publications

References 41 publications

User engagement in mobile apps for people with schizophrenia: A scoping review

User engagement in mobile apps for people with schizophrenia: A scoping review

Adherence and Engagement With a Cognitive Behavioral Therapy–Based Conversational Agent (Wysa for Chronic Pain) Among Adults With Chronic Pain: Survival Analysis

Examining Use Behavior of a Goal-Supporting mHealth App in Primary Care Among Patients With Multiple Chronic Conditions: Qualitative Descriptive Study

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