Can Methods From Computational Psychology be Used to Phenotype Individuals Most Likely to be Non-adherent to Fitness Goals?
1 other identifier
observational
200
1 country
1
Brief Summary
This is a longitudinal study combining objective sensor data, with decision-making games and contextual personality traits to identify patterns in exercise decay. The data generated will be used to build computational models to predict digital personas, and help identify those individuals most likely to abandon exercise goals.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jan 2021
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
January 1, 2021
CompletedFirst Submitted
Initial submission to the registry
February 15, 2021
CompletedFirst Posted
Study publicly available on registry
March 5, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2021
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2021
CompletedMarch 5, 2021
March 1, 2021
12 months
February 15, 2021
March 3, 2021
Conditions
Outcome Measures
Primary Outcomes (1)
Change in physical activity measured by an increase in weekly steps measured by Fitbit.
Fitbit is a physical activity tracker worn on the wrist and objectively measures steps taken.
Week 1 and 6 months
Interventions
An application to deliver a series of behavioral questionnaires and decision-making game
Eligibility Criteria
Healthy individuals starting a new exercise regime.
You may qualify if:
- Healthy individuals who have a Fitbit
You may not qualify if:
- Individuals under the age of 18 years of age.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Dublin City University
Dublin, Ireland
Related Publications (1)
McCarthy M, Zhang L, Monacelli G, Ward T. Using Methods From Computational Decision-making to Predict Nonadherence to Fitness Goals: Protocol for an Observational Study. JMIR Res Protoc. 2021 Nov 26;10(11):e29758. doi: 10.2196/29758.
PMID: 34842557DERIVED
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- OTHER
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
February 15, 2021
First Posted
March 5, 2021
Study Start
January 1, 2021
Primary Completion
December 31, 2021
Study Completion
December 31, 2021
Last Updated
March 5, 2021
Record last verified: 2021-03
Data Sharing
- IPD Sharing
- Will not share