{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T09:30:18Z","timestamp":1789810218932,"version":"4.0.1"},"reference-count":67,"publisher":"JMIR Publications Inc.","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Despite the growing number of mobile health (mHealth) interventions targeting childhood obesity, few studies have characterized user typologies derived from individuals\u2019 patterns of interactions with specific app features (digital phenotypes).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to identify digital phenotypes among 214 parent-child dyads who used the Aim2Be mHealth app as part of a randomized controlled trial conducted between 2019 and 2020, and explores whether participants\u2019 characteristics and health outcomes differed across phenotypes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Latent class analysis was used to identify distinct parent and child phenotypes based on their use of the app\u2019s behavioral, gamified, and social features over 3 months. Multinomial logistic regression models were used to assess whether the phenotypes differed by demographic characteristics. Covariate-adjusted mixed-effect models evaluated changes in BMI z scores (zBMI), diet, physical activity, and screen time across phenotypes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among parents, 5 digital phenotypes were identified: socially engaged (35\/214, 16.3%), independently engaged (18\/214, 8.4%) (socially and independently engaged parents are those who used mainly the social or the behavioral features of the app, respectively), fully engaged (26\/214, 12.1%), partially engaged (32\/214, 15%), and unengaged (103\/214, 48.1%) users. Married parents were more likely to be fully engaged than independently engaged (P=.02) or unengaged (P=.01) users. Socially engaged parents were older than fully engaged (P=.02) and unengaged (P=.01) parents. The latent class analysis revealed 4 phenotypes among children: fully engaged (32\/214, 15%), partially engaged (61\/214, 28.5%), dabblers (42\/214, 19.6%), and unengaged (79\/214, 36.9%) users. Fully engaged children were younger than dabblers (P=.04) and unengaged (P=.003) children. Dabblers lived in higher-income households than fully and partially engaged children (P=.03 and P=.047, respectively). Fully engaged children were more likely to have fully engaged (P&lt;.001) and partially engaged (P&lt;.001) parents than unengaged children. Compared with unengaged children, fully and partially engaged children had decreased total sugar (P=.006 and P=.004, respectively) and energy intake (P=.03 and P=.04, respectively) after 3 months of app use. Partially engaged children also had decreased sugary beverage intake compared with unengaged children (P=.03). Similarly, children with fully engaged parents had decreased zBMI, whereas children with unengaged parents had increased zBMI over time (P=.005). Finally, children with independently engaged parents had decreased caloric intake, whereas children with unengaged parents had increased caloric intake over time (P=.02).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Full parent-child engagement is critical for the success of mHealth interventions. Further research is needed to understand program design elements that can affect participants\u2019 engagement in supporting behavior change.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>ClinicalTrials.gov NCT03651284; https:\/\/clinicaltrials.gov\/ct2\/show\/NCT03651284<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>International Registered Report Identifier (IRRID)<\/jats:title>\n                    <jats:p>RR2-10.1186\/s13063-020-4080-2<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/35285","type":"journal-article","created":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T10:45:38Z","timestamp":1655894738000},"page":"e35285","source":"Crossref","is-referenced-by-count":18,"title":["The Aim2Be mHealth Intervention for Children With Overweight or Obesity and Their Parents: Person-Centered 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