A Remotely Delivered Weight Management Service to Support Existing Obesity Services in the UK National Health Service: Preliminary Findings From an Early-Stage Service Evaluation
Notice bibliographique
Résumé
BACKGROUND: Specialist weight management services (SWMS) in the UK National Health Service (NHS) face long waiting lists and limited resources. Remotely-delivered SWMSs may support existing NHS services to increase access to treatment for patients living with obesity, however evidence of remotely-delivered services working to support NHS SWMSs in practice remains limited. OBJECTIVE: This service evaluation explored the potential effectiveness, feasibility and acceptability of Second Nature's remotely-delivered SWMS for adults living with obesity referred from existing NHS SWMSs. Preliminary findings from the first phase ('Preparing for weight loss') of a three-phase remotely-delivered SWMS are presented. METHODS: A total of 39 adults (age range 23-74 years, mean age 45.6, SD 12.1; 74% female) completed a 16-week intervention, following referral from NHS SWMS leads. Eligible participants were assessed by a multidisciplinary team and allocated to one of three interventions: 1) a psychologically informed app-based intervention, 2) a Dialectical behavioral Therapy (DBT)-based skills training group intervention and 3) one-to-one psychological support. Primary outcomes were weight change (kg) and percentage weight change following completion of the intervention. Secondary outcomes included psychological distress, emotional eating, health-related quality of life, physical activity, emotion regulation, intervention feasibility and acceptability. RESULTS: At 16-weeks, the mean weight change was -2.2 kg (SD 5.16), or -1.6% of body weight . Participants in the app-based intervention lost the most weight (-2.8kg), and participants in the one-to-one psychological support intervention lost the least weight (-1.3kg). Psychological distress reduced to below the clinical threshold (mean score 0.95, SD 0.62). Emotional eating behaviors and difficulties in emotion regulation also decreased (mean change scores -3.2, SD 6.4 and -11.6, SD 13.9, respectively). Health-related quality of life saw improvements in self-care, usual activities and anxiety/depression , while participants' challenges with mobility and pain/discomfort remained unaffected. Subjective ratings of health status improved by 17.4%. There were no significant changes in physical activity levels, with most participants remaining 'Inactive' or 'Moderately inactive'. Engagement with intervention sessions was high (93.7%) and attrition rate was 27.4%. Participants rated their satisfaction with the intervention at 9/10 and highlighted key benefits including improved mental wellbeing, healthier habits, and supportive coach relationships. Suggested improvements included greater scheduling flexibility, enhanced app functionality, and more accessible physical activity support. CONCLUSIONS: This preliminary service evaluation suggests that a remotely delivered SWMS has the potential to be effective, feasible and acceptable for NHS-referred patients in the UK. Changes observed across several key measures point to clinically significant benefits, reinforcing the potential of this approach. A full evaluation of all three phases of this service with a larger sample size is required to support these early findings.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».