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Record W4396883113 · doi:10.1001/jama.2024.7064

Text Messages With Financial Incentives for Men With Obesity

2024· article· en· W4396883113 on OpenAlexaff
Pat Hoddinott, Catriona O’Dolan, Lisa Macaulay, Stephan U Dombrowski, James Swingler, Seonaidh Cotton, Alison Avenell, Abraham M. Getaneh, Cindy M. Gray, Kate Hunt, Frank Kee, Alice MacLean, Michelle C. McKinley, Claire Torrens, Katrina Turner, Marjon van der Pol, Graeme MacLennan

Bibliographic record

VenueJAMA · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMedicineWeight lossBody mass indexPsychological interventionRandomized controlled trialPedometerObesityWeight managementIncentivePhysical therapyInternal medicinePhysical activityPsychiatry

Abstract

fetched live from OpenAlex

Importance: Effective weight loss interventions are needed for men with obesity. Objective: To determine whether an intervention that combined text messaging with financial incentives attained significant weight loss at the 12-month follow-up compared with the control group and whether an intervention of text messaging alone attained significant weight loss at the 12-month follow-up compared with the control group. Design, Setting, and Participants: An assessor-blinded randomized clinical trial conducted in Belfast, Bristol, and Glasgow areas in the UK. A total of 585 men with body mass index (BMI) of 30 or more were enrolled between July 2021 and May 2022. Final follow-up occurred June 2023. Interventions: Participants were randomly assigned to 12 months of behavioral focused text messages combined with financial incentives (n = 196), 12 months of behavioral focused text messages alone (n= 194), or a waiting list (control group; n= 195). The financial incentive consisted of a monetary reward that was lost if weight loss targets were not met. All participants received weight management information and a pedometer at baseline. Main Outcomes and Measures: The 2 primary comparisons were the 12-month comparison of within-participant weight change between the text messaging with financial incentive group and the control group and the comparison between the text messaging alone group and the control group (minimum clinically important difference, 3%). The P value defined for statistical significance was P < .025 for each comparison. Results: Of the 585 men (mean [SD] age, 50.7 [13.3] years; mean weight, 118.5 [19.9] kg; mean BMI, 37.7 [5.7]; 525 [90%] White), 227 (39%) lived in postal code areas with lower socioeconomic status, and 426 (73%) completed the 12-month follow-up. At the 12-month follow-up, compared with the control group, the mean percent weight change was significantly greater in the text messaging with financial incentive group (mean difference, -3.2%; 97.5% CI, -4.6% to -1.9%; P < .001) but was not significantly greater in the text messaging alone group (mean difference, -1.4%; 97.5% CI, -2.9% to 0.0, P = .05). The mean (SD) weight changes were -5.7 (7.4) kg for the text messaging with financial incentives group, -3.0 (7.5) kg for the text messaging alone group, and -1.5 (6.6) kg for the control group. The 12-month mean (SD) percentage weight changes from baseline were -4.8% (6.1%) for the text messaging with financial incentives group, -2.7% (6.3%) for text messaging alone group, and -1.3% (5.5%) for the control group. Of 366 adverse events reported, the most common were infections (83 [23%]). Of the 23 serious adverse events (6.3%), 12 (52%) occurred in the text messaging with financial incentives group, 5 (22%) in the texts messaging alone group, and 6 (26%) in the control group. None were considered related to participating in a trial group. Conclusion and Relevance: Among men with obesity, an intervention with text messaging with financial incentive significantly improved weight loss compared with a control group, whereas text messaging alone was not significantly better than the control condition. These findings support text messaging combined with financial incentives to attain weight loss in men with obesity. Trial Registration: isrctn.org Identifier: ISRCTN91974895.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.387
Teacher spread0.362 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations24
Published2024
Admission routes1
Has abstractyes

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