The Aim2Be mHealth Intervention for Children With Overweight or Obesity and Their Parents: Person-Centered Analyses to Uncover Digital Phenotypes (Preprint)
Authors: De-Jongh González Olivia , Tugault-Lafleur Claire N , Buckler E Jean , Hamilton Jill , Ho Josephine , Buchholz Annick , Morrison Katherine M , Ball Geoff DC , Mâsse Louise C 
Published: June 2022

BACKGROUND

Despite the growing number of mobile health (mHealth) interventions targeting childhood obesity, few studies have characterized user typologies derived from individuals’ patterns of interactions with specific app features (digital phenotypes).

OBJECTIVE

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’ characteristics and health outcomes differed across phenotypes.

METHODS

Latent class analysis was used to identify distinct parent and child phenotypes based on their use of the app’s 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 <i>z</i> scores (<i>z</i>BMI), diet, physical activity, and screen time across phenotypes.

RESULTS

Among parents, 5 digital phenotypes were identified: <i>socially engaged</i> (35/214, 16.3%), <i>independently engaged</i> (18/214, 8.4%) (<i>socially</i> and <i>independently engaged</i> parents are those who used mainly the social or the behavioral features of the app, respectively), <i>fully engaged</i> (26/214, 12.1%), <i>partially engaged</i> (32/214, 15%), and <i>unengaged</i> (103/214, 48.1%) users. Married parents were more likely to be <i>fully</i> <i>engaged</i> than <i>independently engaged</i> (<i>P</i>=.02) or <i>unengaged</i> (<i>P</i>=.01) users. <i>Socially engaged</i> parents were older than <i>fully</i> <i>engaged</i> (<i>P</i>=.02) and <i>unengaged</i> (<i>P</i>=.01) parents. The latent class analysis revealed 4 phenotypes among children: <i>fully engaged</i> (32/214, 15%), <i>partially engaged</i> (61/214, 28.5%), <i>dabblers</i> (42/214, 19.6%), and <i>unengaged</i> (79/214, 36.9%) users. <i>Fully engaged</i> children were younger than <i>dabblers</i> (<i>P</i>=.04) and <i>unengaged</i> (<i>P=</i>.003) children. <i>Dabblers</i> lived in higher-income households than <i>fully</i> and <i>partially</i> <i>engaged</i> children (<i>P</i>=.03 and <i>P</i>=.047, respectively). <i>Fully engaged</i> children were more likely to have <i>fully</i> engaged (<i>P</i>&lt;.001) and <i>partially</i> <i>engaged</i> (<i>P</i>&lt;.001) parents than <i>unengaged</i> children. Compared with <i>unengaged</i> children, <i>fully</i> and <i>partially</i> <i>engaged</i> children had decreased total sugar (<i>P</i>=.006 and <i>P</i>=.004, respectively) and energy intake (<i>P</i>=.03 and <i>P</i>=.04, respectively) after 3 months of app use. <i>Partially engaged</i> children also had decreased sugary beverage intake compared with <i>unengaged</i> children (<i>P</i>=.03). Similarly, children with <i>fully engaged</i> parents had decreased <i>z</i>BMI, whereas children with <i>unengaged</i> parents had increased <i>z</i>BMI over time (<i>P</i>=.005). Finally, children with <i>independently engaged</i> parents had decreased caloric intake, whereas children with <i>unengaged</i> parents had increased caloric intake over time (<i>P</i>=.02).

CONCLUSIONS

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’ engagement in supporting behavior change.

CLINICALTRIAL

ClinicalTrials.gov NCT03651284; https://clinicaltrials.gov/ct2/show/NCT03651284

INTERNATIONAL REGISTERED REPORT

RR2-10.1186/s13063-020-4080-2