Factors Associated With Dropout of Participants in an App-Based Child Injury Prevention Study: Secondary Data Analysis of a Cluster Randomized Controlled Trial

Li, Jie; Ning, Peishan; Cheng, Peixia; Schwebel, David C.; Yang, Yang; Wei, Xiang; He, Junyi; Wang, Wanhui; Li, Ruotong; Hu, Guoqing

doi:10.2196/21636

Cited by 5 publications

(2 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The only trial that examined actual changes in injury incidence rate used a six-month intervention period and did not demonstrate the signi cant effectiveness [24] . User fatigue and resultant non-compliance to the intervention, plus substantial attrition from the study, were interpreted as reasons that the intervention was ineffective [27] . So far, long-term effectiveness of mobile health technology in reducing actual child injury incidents has not been assessed in any published study.…”

Section: Many Mhealth Interventions Have Been Developed Already For C...mentioning

confidence: 99%

Assessing the Effectiveness of an App-Based Unintentional Injury Intervention for Caregivers of Rural Chinese Preschoolers: Protocol for a Cluster Randomized Controlled Trial

Wang

Ning

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

BackgroundCompared to urban children, children living in rural areas of most countries, including China, are at higher risk of suffering unintentional injuries. Most proven injury prevention interventions, however, are rarely implemented in rural China due to lack of resources. Mobile health interventions are low-cost and easy-to-implement, facilitating implementing injury prevention in resource-limited areas (e.g., rural areas). This study is designed to examine the effectiveness of an app-based intervention for unintentional injury prevention among rural preschoolers in China. MethodsA single-blind, 18-month, parallel-group cluster randomized controlled trial with 1:1 allocation ratio will be implemented in 2 rural areas of China (Yang County, Shaanxi Province, and Shicheng County, Jiangxi Province). In total, at least 3508 rural caregivers of preschoolers aged 3-6 years old who own a smartphone will be recruited from 24 preschools. Clusters will be randomized at the preschool level and allocated to the control group (receiving routine school-based education plus app-based parenting education excluding unintentional injury prevention) or the intervention group (receiving routine school-based education plus app-based parenting education including unintentional injury prevention). External support strategies will be adopted by local partners to minimize user fatigue, non-compliance, and attrition. Data collection will be conducted at baseline and then every 3 months during the 18-month follow-up time period. Intention-to-treat (ITT) data analysis will be implemented. Missing values will be imputed by using the Expectation Maximization algorithm (EM). Generalized estimation equations (GEE) will test the overall effectiveness of the app-based intervention. A per-protocol (PP) sensitivity analysis will be conducted to test the robustness of results. Subgroup analyses will follow the strategies for primary analyses.ResultsThe primary outcome measure is the incidence rate of unintentional injury among preschoolers during the study period. Secondary outcome measures comprise longitudinal changes in caregiver’s attitudes, caregiver-reported supervision behaviors, and caregiver-assessed home environment safety surrounding child unintentional injury prevention in the last week using a standardized audit instrument.ConclusionThe app-based intervention is expected to be feasible and effective over the 18-month intervention period. If the app is demonstrated effective as hypothesized, we will initiate processes to generalize and popularize it broadly to rural child caregivers across China. Trial registrationChiCTR2000037606, registered on August 29, 2020.

show abstract

Section: Many Mhealth Interventions Have Been Developed Already For C...mentioning

confidence: 99%

Assessing the Effectiveness of an App-Based Unintentional Injury Intervention for Caregivers of Rural Chinese Preschoolers: Protocol for a Cluster Randomized Controlled Trial

Wang

Ning

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The only trial that examined actual changes in injury incidence rate used a 6-month intervention period and did not demonstrate the significant effectiveness [ 24 ]. User fatigue and resultant non-compliance to the intervention, plus substantial attrition from the study, were interpreted as reasons that the intervention was ineffective [ 27 ]. So far, the long-term effectiveness of mobile health technology in reducing actual child injury incidents has not been assessed in any published study.…”

Section: Introductionmentioning

confidence: 99%

Assessing the effectiveness of an app-based child unintentional injury prevention intervention for caregivers of rural Chinese preschoolers: protocol for a cluster randomized controlled trial

Wang

Ning

et al. 2021

BMC Public Health

Self Cite

View full text Add to dashboard Cite

Background Compared to urban children, children living in rural areas of most countries, including China, are at higher risk of suffering unintentional injuries. Most proven injury prevention interventions, however, are rarely implemented in rural China due to lack of resources. Mobile health interventions are low-cost and easy-to-implement, facilitating implementing injury prevention in resource-limited areas (e.g., rural areas). This study is designed and implemented to examine the effectiveness of an app-based intervention for unintentional injury prevention among rural preschoolers in China. Methods A single-blind, 18-month, parallel-group cluster randomized controlled trial with 1:1 allocation ratio will be implemented in 2 rural areas of China (Yang County, Shaanxi Province, and Shicheng County, Jiangxi Province). In total, at least 3508 rural caregivers of preschoolers aged 3–6 years old who own a smartphone will be recruited from 24 preschools. Clusters will be randomized at the preschool level and allocated to the control group (receiving routine school-based education plus app-based parenting education excluding unintentional injury prevention) or the intervention group (receiving routine school-based education plus app-based parenting education including unintentional injury prevention). External support strategies will be adopted by local partners to minimize user fatigue, non-compliance, and attrition. Data collection will be conducted at baseline and then every 3 months during the 18-month follow-up time period. Intention-to-treat data analysis will be implemented. Missing values will be imputed by using the Expectation Maximization algorithm. Generalized estimating equation will test the overall effectiveness of the app-based intervention. A per-protocol sensitivity analysis will be conducted to test the robustness of results. Subgroup analyses will follow the strategies for primary analyses. The primary outcome measure is the incidence rate of unintentional injury among preschoolers during the study period. Secondary outcome measures comprise longitudinal changes in caregiver’s attitudes, caregiver-reported supervision behaviors, and caregiver-assessed home environment safety surrounding child unintentional injury prevention in the last week using a standardized audit instrument. Discussion The app-based intervention is expected to be feasible and effective over the 18-month intervention period. If the app is demonstrated effective as hypothesized, we will initiate processes to generalize and popularize it broadly to rural child caregivers across China. Trial registration ChiCTR2000037606, registered on August 29, 2020.

show abstract

Human-Centered Design Approaches in Digital Mental Health Interventions: Exploratory Mapping Review

Vial¹,

Boudhraâ²,

Dumont³

2022

JMIR Ment Health

View full text Add to dashboard Cite

Background Digital mental health interventions have a great potential to alleviate mental illness and increase access to care. However, these technologies face significant challenges, especially in terms of user engagement and adoption. It has been suggested that this issue stems from a lack of user perspective in the development process; accordingly, several human-centered design approaches have been developed over the years to consider this important aspect. Yet, few human-centered design approaches to digital solutions exist in the field of mental health, and rarely are end users involved in their development. Objective The main objective of this literature review is to understand how human-centered design is considered in e-mental health intervention research. Methods An exploratory mapping review was conducted of mental health journals with the explicit scope of covering e-mental health technology. The human-centered design approaches reported and the core elements of design activity (ie, object, context, design process, and actors involved) were examined among the eligible studies. Results A total of 30 studies met the inclusion criteria, of which 22 mentioned using human-centered design approaches or specific design methods in the development of an e-mental health solution. Reported approaches were classified as participatory design (11/27, 41%), codesign (6/27, 22%), user-centered design (5/27, 19%), or a specific design method (5/27, 19%). Just over half (15/27, 56%) of the approaches mentioned were supported by references. End users were involved in each study to some extent but not necessarily in designing. About 27% (8/30) of all the included studies explicitly mentioned the presence of designers on their team. Conclusions Our results show that some attempts have indeed been made to integrate human-centered design approaches into digital mental health technology development. However, these attempts rely very little on designers and design research. Researchers from other domains and technology developers would be wise to learn the underpinnings of human-centered design methods before selecting one over another. Inviting designers for assistance when implementing a particular approach would also be beneficial. To further motivate interest in and use of human-centered design principles in the world of e-mental health, we make nine suggestions for better reporting of human-centered design approaches in future research.

show abstract

Factors Associated With Dropout of Participants in an App-Based Child Injury Prevention Study: Secondary Data Analysis of a Cluster Randomized Controlled Trial

Cited by 5 publications

References 27 publications

Assessing the Effectiveness of an App-Based Unintentional Injury Intervention for Caregivers of Rural Chinese Preschoolers: Protocol for a Cluster Randomized Controlled Trial

Assessing the Effectiveness of an App-Based Unintentional Injury Intervention for Caregivers of Rural Chinese Preschoolers: Protocol for a Cluster Randomized Controlled Trial

Assessing the effectiveness of an app-based child unintentional injury prevention intervention for caregivers of rural Chinese preschoolers: protocol for a cluster randomized controlled trial

Human-Centered Design Approaches in Digital Mental Health Interventions: Exploratory Mapping Review

Contact Info

Product

Resources

About