MyBehavior: Persuasion by Adapting to User Behavior and User Preference
Panoramica dello studio
Stato
Condizioni
Intervento / Trattamento
Descrizione dettagliata
A dramatic rise in self-tracking applications for smartphones has occurred recently. Rich user interfaces make manual logging of users' behavior easier and more pleasant; sensors make tracking effortless. To date, however, feedback technologies have been limited to providing counts or attractive visualization of tracked data. Human experts (health coaches) have needed to interpret the data and tailor make customized recommendations. No automated recommendation systems like Pandora, Netflix or personalized search for the web have been available to translate self-tracked data into actionable suggestions that promote healthier lifestyle without needing to involve a human interventionist.
MyBehavior aims to fill this gap. It takes a deeper look into physical activity and dietary intake data and reveal patterns of both healthy and unhealthy behavior that could be leveraged for personalized feedback. Based on common patterns from a user's life, suggestions are created that ask users to continue, change or avoid existing behaviors to achieve certain fitness goals. Such an approach is different from existing literature in two important aspects: (1) suggestions are contextualized to a user's life and are built on existing user behaviors. As a result, users can act on these suggestions easily, with minimal effort and interruption to daily routines; (2) unique suggestions are created for each individual. This personalized approach differs from traditional one-size-fits-all or targeted intervention models where identical suggestions are applied for groups of similar people or the entire population.
Tipo di studio
Iscrizione (Effettivo)
Fase
- Non applicabile
Contatti e Sedi
Luoghi di studio
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New York
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Ithaca, New York, Stati Uniti, 14850
- Cornell University
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Criteri di partecipazione
Criteri di ammissibilità
Età idonea allo studio
Accetta volontari sani
Sessi ammissibili allo studio
Descrizione
Inclusion Criteria:
- In relatively healthy condition. Also, users must be interested in health and fitness.
Exclusion Criteria:
- Individuals with physical disability and dietary problems are excluded.
Piano di studio
Come è strutturato lo studio?
Dettagli di progettazione
- Scopo principale: Prevenzione
- Assegnazione: Randomizzato
- Modello interventistico: Assegnazione parallela
- Mascheramento: Separare
Armi e interventi
Gruppo di partecipanti / Arm |
Intervento / Trattamento |
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Comparatore attivo: Generic suggestions
Control group participants received suggestions generated by the a nutritionist and exercise trainer.
These suggestions didn't relate to user's life or their past behavior.
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A nutritionist and an exercise trainer jointly created 45 food and exercise suggestions based on guidelines posted by the NIH.
These suggestions ask users to walk for 30 minutes or eat healthier foods.
These suggestions however doesn't personalize to users daily behavior into account.
An Android Smartphone with operating system version higher than 2.2
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Sperimentale: MyBehavior
Experiment group participants received personalized suggestions from MyBehavior that relates their life and past behavior.
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An Android Smartphone with operating system version higher than 2.2
The intervention automatically provides personalized suggestions based on users behavior and user context.
Suggestions relates to users life and how often they have done them in the past.
Since the suggestions relate to users' lives, they are easy to follow.
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Cosa sta misurando lo studio?
Misure di risultato primarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
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User intentions to follow automated suggestions and behavior change
Lasso di tempo: 3 weeks
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The primary outcome is to measure efficacy of MyBehavior suggestions. Efficacy will be measured in two dimensions (1) whether users intend to follow the automated suggestions from MyBehavior (2) effectiveness of automated suggestions in actual behavior change. User intentions towards following MyBehavior suggestions are measured using a 5 point likert scale. The investigators will ask users to rate whether they can follow the suggestions on an average day within a scale of 1-5 (1- I can't follow the suggestion, 5 - I can easily follow the suggestion). On the other hand, behavior change is measured from food (calories in per meal consumed) and activity (walking, running or exercise durations per day etc.) log collected using their smartphone. Regarding physical activity, how much physical activity users are performing will be compared across experiment conditions. Similarly, calorie consumption change in food will be used to compare dietary behavior change. |
3 weeks
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Misure di risultato secondarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
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Usability improvements of automated suggestions
Lasso di tempo: 3 weeks
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MyBehavior is the first system to provide health suggestions for food and activity automatically.
Thus there are scopes of usability improvement on how to effectively present the automatically generated information to the user.
Qualitative interviews at the end of study will be conducted to gather user experience of using MyBehavior.
This interviews will help to build a better and more usable version of MyBehavior for future larger scale deployments.
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3 weeks
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Collaboratori e investigatori
Sponsor
Investigatori
- Investigatore principale: Mashfiqui Rabbi, BS, Cornell University
Pubblicazioni e link utili
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Inizio studio
Completamento primario (Effettivo)
Completamento dello studio (Effettivo)
Date di iscrizione allo studio
Primo inviato
Primo inviato che soddisfa i criteri di controllo qualità
Primo Inserito (Stima)
Aggiornamenti dei record di studio
Ultimo aggiornamento pubblicato (Stima)
Ultimo aggiornamento inviato che soddisfa i criteri QC
Ultimo verificato
Maggiori informazioni
Termini relativi a questo studio
Parole chiave
Termini MeSH pertinenti aggiuntivi
Altri numeri di identificazione dello studio
- 1302003617
Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .