MétaCan
Menu
← Back to cohort
Record W4245748835 · doi:10.32920/ryerson.14662866

Adapted motivational interviewing for bariatric surgery patients: a pilot study

2021· preprint· en· W4245748835 on OpenAlexaffabout
Lauren David

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsToronto Metropolitan UniversityQueen's University
Fundersnot available
KeywordsMotivational interviewingMedicineRepeated measures designPilot trialPhysical therapyAnalysis of varianceIntervention (counseling)Randomized controlled trialProtocol (science)Clinical trialSession (web analytics)InterviewSurgeryInternal medicineAlternative medicineNursing

Abstract

fetched live from OpenAlex

The current pilot trial examined the efficacy of a single-session Adapted Motivational Interviewing (AMI) protocol for improving outcomes for bariatric surgery patients. Forty-six post-operative patients from the Bariatric Surgery Program at Toronto Western Hospital were randomly assigned to either an AMI group (n = 23) or a wait list group (n = 23). From pre- to post-intervention, paired samples t-tests found that participants reported greater readiness and self-efficacy for change, as well as improvements to binge eating characteristics and to some measures of adherence to dietary guidelines at the 4-week follow-up. Repeated measures ANOVAs found that the behavioural changes were maintained over the 12-week follow-up but mixed model ANOVAs suggest that these changes may not be as marked next to patients receiving standard bariatric care. These preliminary findings suggest that AMI is an acceptable and feasible intervention that might be effective for some bariatric patients. Future research is warranted.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.121
GPT teacher head0.348
Teacher spread0.227 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

Same topicEating Disorders and Behaviors→French-language works237,207→