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Record W4417072473 · doi:10.1002/osp4.70106

Long‐Term Weight Loss in Adults With Overweight or Obesity Using a Breath Biofeedback mHealth App: A One‐Year Follow‐Up of a Randomized Trial

2025· article· en· W4417072473 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueObesity Science & Practice · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsCentre for Advancing Health OutcomesBrock UniversityOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMitacsMichael Smith Health Research BC
KeywordsWeight lossmHealthOverweightRandomized controlled trialObesityBiofeedbackClinical trial

Abstract

fetched live from OpenAlex

ABSTRACT Background Long‐term weight loss success with dietary interventions is notoriously limited. Mobile health (mHealth) interventions offering personalized dietary guidance combined with real‐time biofeedback may enhance long‐term adherence and provide a sustainable solution for weight management. Objectives This study reports the prespecified secondary outcome of weight loss at 48 weeks from a parallel‐arm randomized clinical trial (ClinicalTrials.gov: NCT04165707) that aimed to evaluate the long‐term effectiveness and sustainability of a Mediterranean‐style low‐carbohydrate diet delivered via an mHealth application paired with breath biofeedback compared with a calorie‐restricted low‐fat diet application. Methods Adults with overweight or obesity ( N = 155; mean ± SD age, 41 ± 11 years; 71% female; BMI, 33.5 ± 4.7 kg/m 2 ) were randomized to either an intervention promoting a Mediterranean‐style low‐carbohydrate diet combined with biofeedback from a handheld breath acetone device or an evidence‐based comparator promoting a calorie‐restricted, low‐fat diet. Participants recorded their daily weights using Bluetooth scales. Weight loss over 48 weeks was analyzed using a linear mixed‐effects model, incorporating all available daily weight measurements from participants who provided at least one follow‐up measurement. Results At 48 weeks, participants using the breath biofeedback mHealth app achieved clinically meaningful weight loss (−9.54 kg, 95% CI: −12.27 to −6.81 kg). In contrast, participants using the low‐fat diet app did not achieve statistically significant weight loss (−2.68 kg, 95% CI: −5.49 to 0.14 kg), resulting in a statistically significant between‐group difference (−6.9 kg, 95% CI: −10.8 to −2.9, p < 0.001). No adverse effects were reported in either group. Conclusions This study demonstrates that a Mediterranean‐style diet promoting carbohydrate restriction coupled with biofeedback support delivered via an mHealth app results in clinically meaningful sustained weight loss at 48 weeks. Given its practicality and demonstrated effectiveness, this approach presents a promising non‐pharmacological alternative or complement for longer‐term weight management.

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.

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)0.013
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.410
Teacher spread0.374 · 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