How can digital citizen science approaches improve ethical smartphone use surveillance among youth: Traditional surveys versus ecological momentary assessments
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Notice bibliographique
Résumé
Ubiquitous use of smartphones among youth poses significant challenges related to non-communicable diseases, including poor mental health. Although traditional survey measures can be used to assess smartphone use among youth, they are subject to recall bias. This study aims to compare self-reported smartphone use via retrospective modified traditional recall survey and prospective Ecological Momentary Assessments (EMAs) among youth. This study uses data from the Smart Platform, which engages with youth as citizen scientists. Youth (N = 77) aged 13-21 years in two urban jurisdictions in Canada (Regina and Saskatoon) engaged with our research team using a custom-built application via their own smartphones to report on a range of behaviours and outcomes on eight consecutive days. Youth reported smartphone use utilizing a traditional validated measure, which was modified to capture retrospective smartphone use on both weekdays and weekend days. In addition, daily EMAs were also time-triggered over a period of eight days to capture prospective smartphone use. Demographic, behavioural, and contextual factors were also collected. Data analyses included t-test and linear regression using Python statistical software. There was a significant difference between weekdays, weekends and overall smartphone use reported retrospectively and prospectively (p-value = <0.001), with youth reporting less smartphone use via EMAs. Overall retrospective smartphone use was significantly associated with not having a part-time job (β = 139.64, 95% confidence interval [CI] = 34.759, 244.519, p-value = 0.010) and having more than two friends who are physically active (β = -114.72, 95%[CI] = -208.872, -20.569, p-value = 0.018). However, prospective smartphone use reported via EMAs was not associated with any behavioural and contextual factors. The findings of this study have implications for appropriately understanding and monitoring smartphone use in the digital age among youth. EMAs can potentially minimize recall bias of smartphone use among youth, and other behaviours such as physical activity. More importantly, digital citizen science approaches that engage large populations of youth using their own smartphones can transform how we ethically monitor and mitigate the impact of excessive smartphone use.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
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Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle