An examination of user and household characteristics associated with adolescents' adoption and usage of a lifestyle behaviour modification app
Bibliographic record
Abstract
BACKGROUND: Adolescent obesity continues to be a major public health problem within Canada; therefore, effective solutions are required. E-health interventions can provide Canadian adolescents (13-17 years old) with personalized support to help them modify their obesogenic behaviours. However, predictors of app adoption and usage among adolescents have not been extensively examined. OBJECTIVE: This study aimed to examine user and household characteristics associated with adolescents’ adoption and usage of the Aim2Be© app; a health behaviour modification intervention delivered through a smartphone app. METHODS: 371 adolescent-parent dyads completed baseline assessment and were provided with access to the Aim2Be© app. Mean adolescent age was 14.9 years and 50.1% were male (n=186). Mean adult age was 44.1 years and 34.7% were male (n=129). Multivariable logistic and linear regressions, along with path analyses, were used to determine characteristics that were significantly associated with app adoption and usage, respectively. Additionally, analyses were stratified by parent’s sex. Univariable analyses were conducted in Stata (v.13.1), while path analyses were conducted in Mplus (v.8). All models were adjusted for adolescent’s age and sex, and a significance level of 5% was used. RESULTS: 79.2% of adolescents (n=294) adopted the Aim2Be© app. When examining user characteristics, adolescent engagement in healthy behaviours was directly associated with increased odds of app adoption (OR=1.08; 95%CI=1.01-1.14). Autonomous motivation was indirectly associated with app adoption (OR=1.02; 95%CI=1.00-1.04). When examining parenting practices, mediated through user characteristics, autonomy supportive practices were associated with increased app usage (β=0.21; 95%CI=0.07-0.36), while structure practices were indirectly associated with increased odds of app adoption (OR=1.02; 95%CI=1.00-1.04). When the analyses were stratified by parent’s sex, differences in the associations emerged. CONCLUSIONS: Both user characteristics and parenting practices were significantly associated with adolescents’ app adoption and/or usage. The findings of this study will help inform future e-health interventions increase user engagement by identifying the characteristics of individuals who are not accessing the intervention, as well as identifying factors of the household environment that support long-term intervention use. This information will fill an important gap within the literature, as high attrition rates are commonly reported among e-health interventions and can consequently jeopardize program effectiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".