Development of the Eating Behaviour Lapse Inventory Survey Singapore (eBLISS):An Exploratory Mixed-method Study
1 other identifier
observational
530
0 countries
N/A
Brief Summary
An exploratory mixed-method study will be conducted to develop an instrument for early detection and prevention of overconsumption.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Apr 2021
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
First Submitted
Initial submission to the registry
April 5, 2021
CompletedFirst Posted
Study publicly available on registry
April 6, 2021
CompletedStudy Start
First participant enrolled
April 12, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 22, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
March 22, 2023
CompletedApril 6, 2021
April 1, 2021
1.9 years
April 5, 2021
April 5, 2021
Conditions
Outcome Measures
Primary Outcomes (1)
Self-regulation of Eating Behaviour Questionnaire (SREBQ)
2021-2023
Interventions
a novel instrument -Eating Behaviour Lapse Inventory Survey Singapore (eBLISS)- will be developed
Eligibility Criteria
Patients who are overweight or obese and are following up at the Centre for Obesity Management and Surgery (COMS) at the National University Hospital (NUH).
You may qualify if:
- Above the legal age of 21 years old
- Have a BMI ≥ 23kg/m2
- Able to understand and read English language
- Uses a smart phone that can download apps
- Able to provide informed consent
You may not qualify if:
- Diagnosed with a pre-existing psychological disorder such as anxiety and depression except binge eating disorder
- Participating in a concurrent weight management intervention that is beside the usual care
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Related Publications (2)
Chew HSJ, Chew NW, Loong SSE, Lim SL, Tam WSW, Chin YH, Chao AM, Dimitriadis GK, Gao Y, So JBY, Shabbir A, Ngiam KY. Effectiveness of an Artificial Intelligence-Assisted App for Improving Eating Behaviors: Mixed Methods Evaluation. J Med Internet Res. 2024 May 7;26:e46036. doi: 10.2196/46036.
PMID: 38713909DERIVEDChew HSJ, Lim SL, Kim G, Kayambu G, So BYJ, Shabbir A, Gao Y. Essential elements of weight loss apps for a multi-ethnic population with high BMI: a qualitative study with practical recommendations. Transl Behav Med. 2023 Apr 3;13(3):140-148. doi: 10.1093/tbm/ibac090.
PMID: 36689306DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- ECOLOGIC OR COMMUNITY
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Research Fellow
Study Record Dates
First Submitted
April 5, 2021
First Posted
April 6, 2021
Study Start
April 12, 2021
Primary Completion
March 22, 2023
Study Completion
March 22, 2023
Last Updated
April 6, 2021
Record last verified: 2021-04
Data Sharing
- IPD Sharing
- Will not share