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Enregistrement W4391322002 · doi:10.1542/peds.2023-064453

Improving the Effectiveness and Equity of Child Obesity Interventions

2024· editorial· en· W4391322002 sur OpenAlexaff
Laura Rolke, Michelle J. White

Notice bibliographique

RevuePEDIATRICS · 2024
Typeeditorial
Langueen
DomaineMedicine
ThématiqueObesity, Physical Activity, Diet
Établissements canadiensInstitute of Population and Public Health
Organismes subventionnairesnon disponible
Mots-clésMotivational interviewingMedicinePsychological interventionIntervention (counseling)Childhood obesityObesityAffect (linguistics)Equity (law)Family medicineInterviewRandomized controlled trialNursingOverweightPsychology

Résumé

récupéré en direct d'OpenAlex

Effective child obesity interventions remain frustratingly elusive. Obesity continues to affect 1 in 5 children with disproportionate impacts on non-Hispanic Black and Hispanic children.1 In this issue of Pediatrics, Resnicow et al describe the results of a promising multisite randomized controlled trial of a primary care-based, motivational interviewing intervention.2 The multicomponent intervention resulted in a greater increase in BMI percent 95 (BMI percent 95 is the percentage of the 95th percentile and used for tracking change among those with obesity) for intervention children versus children receiving usual care. These findings reflect the complexity of treating obesity in “real-world settings.”First, we need to consider the limitations of motivational interviewing. Motivational interviewing helps parents and their children set goals and identify strategies to motivate themselves to make healthy choices. However, barriers (real and perceived), such as logistics (eg, location, time constraints, transportation), finances (eg, cost of healthy foods and exercise programs), family dynamics, and expectations, can impede motivation.3 To address these barriers, it is important for parents to feel comfortable sharing their challenges with providers and trusting them to help. Additionally, provider knowledge of local resources (eg, programs and organizations that provide free or low-cost health-promoting services) can help support behavior change.4 In the current study, the registered dietitians counseling families were not connected with intervention clinics before the study and lived in communities far away from study participants. This meant that they had to build crucial relationships with parents de novo. Families in obesity treatment prefer tailored recommendations that consider financial resources, logistics, and interpersonal dynamics.3To overcome barriers to behavior change, we must also consider the optimal dose of pediatric obesity interventions and potential consequences. The American Academy of Pediatrics Clinical Practice Guidelines for Pediatric Obesity recommends programs that are high intensity (at least 26 contact hours) and comprehensive (including medical providers, registered dietitians, health behavior specialists, and exercise professionals).5 As Resnicow et al note, their intervention was lower than the recommended number of contact hours. We need to consider whether low-dose pediatric obesity interventions might be detrimental to participants. Adequately addressing a chronic disease as complicated as obesity takes time. Family-based child obesity interventions may disrupt family dynamics, create challenges with navigating social environments, and affect child well-being.6 Further, lack of success in previous obesity treatment programs, because of inadequate dose or other factors, can discourage participation in subsequent treatment opportunities.7Another possible explanation for the study’s outcomes is the internalization of negative body image or weight bias. Even though the authors took measures to minimize weight bias, some aspects of the intervention may have contributed to parents feeling ashamed or judged. For example, during motivational interviewing sessions with providers and registered dietitians, caregivers in the study were asked to grade their child’s behaviors on a scale from A (great/healthy) to F (poor/unhealthy). It is not clear how this practice of self-evaluation affected caregivers’ motivation, expectations, and engagement in the intervention. A qualitative follow-up with participants could reveal how families perceived the intervention and what factors contributed to families’ low fidelity.Most previous studies on motivational interviewing for children with overweight and obesity have been conducted with non-Hispanic white children.8 The subgroup analysis in the current study found that Black and non-Hispanic other children who received the intervention had a significantly greater increase in their BMI versus those who received usual care. The previous efficacy trial by Resnicow et al did not report subgroup analyses.9 The results of the current study suggest that it is important to evaluate how interventions affect different populations, especially those who are disproportionately affected by a condition. Child obesity intervention researchers must closely examine implementation, including reach and efficacy, in groups that are disproportionately affected by child obesity early in intervention development to reduce the likelihood of adverse effects in these groups. Although early-stage studies may lack sufficient power to rigorously examine effect modification by race or ethnicity, qualitative and mixed methods approaches can be used to better elucidate how interventions are experienced by specific populations.10 Additionally, the inclusion of members of populations who experience a disproportionate prevalence of obesity as partners in intervention development and implementation may increase the likelihood that an intervention will improve disparities.11Although pandemics are (we hope) rare, the social, environmental, and economic factors that lead to child obesity are ubiquitous. Interventions focused on individual or family behavior change alone are unlikely to overcome them. Moreover, such interventions may place too much onus on the caregiver to initiate and maintain behavior change against a powerful current of adverse factors. The current study by Resnicow et al reflects the urgent need for child obesity interventions that target the structural factors which contribute to child obesity including socioeconomic, built environment and food policies.12 Such interventions have the potential to yield both effectiveness and equity in real world settings.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,157
score de la tête « metaresearch » (Gemma)0,243
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,157
Score d'incertitude au seuil0,833

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1570,243
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0010,004
Communication savante0,0040,008
Science ouverte0,0040,008
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0140,001

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,312
Écart entre enseignants0,299 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2024
Routes d'admission1
Résumé présentoui

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