A Smartphone App to Restore Optimal Weight (SPAROW) in Women With Recent Gestational Diabetes Mellitus: Randomized Controlled Trial
Bibliographic record
Abstract
Background Women with a history of gestational diabetes mellitus (GDM) are at an increased risk of developing type 2 diabetes mellitus (T2DM). Lifestyle interventions aimed at postpartum weight loss to reduce T2DM risk have been reported, but poor compliance remains a barrier. Smartphone-based interventions may improve compliance, but data on its use in women with recent GDM are limited. Objective This trial aimed to investigate the efficacy of a smartphone app in restoring optimal weight following delivery in women with GDM, in the setting of a population with high rates of GDM and type 2 diabetes. Methods In this unblinded randomized controlled trial, 200 women with GDM were randomized to receive the intervention or standard care following delivery. The intervention enabled logging of weight, meals, and activity, with web-based interaction with a team comprising dieticians, a physiotherapist, and an occupational therapist. The primary outcome was an achievement of optimal weight (defined as the restoration of first trimester weight if first trimester BMI≤23 kg/m2 or weight loss of at least 5% from first trimester weight if first trimester BMI>23 kg/m2) at 4 months post partum. Secondary outcome measures included absolute weight loss, serum metabolic markers, self-reported nutritional intake, health education, and quality of life via questionnaires and user engagement in the intervention group. Results In total, 40% (38/96) of women in the intervention group achieved optimal weight at 4 months post delivery compared with 32% (28/93) in the control group (P=.27). Compared with the control group, women in the intervention group reported significantly reduced caloric intake at 4 months after delivery (P<.001) and higher health-directed behavior scores (P=.045). The intervention group also reported increased emotional distress scores (P=.01). At 4 months, participant engagement with the intervention was maintained at 60.8% (SD 33.9%). Conclusions Although a statistically significant increase in women achieving healthy weight was not observed, this app remains promising, as women in the intervention group reported improved health behaviors and lower caloric intake. Importantly, the high retention rates suggest that a larger study with a longer follow-up period might confirm the effectiveness of this app for weight management. Trial Registration ClinicalTrials.gov NCT03324737; https://clinicaltrials.gov/ct2/show/NCT03324737 International Registered Report Identifier (IRRID) RR2-10.1186/s12889-019-7691-3
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".