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Record W2969155541 · doi:10.14288/1.0379360

An examination of user and household characteristics associated with adolescents' adoption and usage of a lifestyle behaviour modification app

2019· article· en· W2969155541 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuecIRcle (University of British Columbia) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEnergy and Environmental Systems
Canadian institutionsnot available
Fundersnot available
KeywordsLifestyle modificationMobile appsPsychologyInternet privacyGerontologyBusinessComputer scienceMedicineWorld Wide WebObesity

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.177
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it