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Enregistrement W4414971784 · doi:10.1017/s0029665125101602

Characterising studies to inform dietary recommendations for shift workers – a systematic review

2025· article· en· W4414971784 sur OpenAlexaboutno aff
A. Booker, Steven Powell, Jonathan Fallowfield, Rachel Gibson

Notice bibliographique

RevueProceedings of The Nutrition Society · 2025
Typearticle
Langueen
DomainePsychology
ThématiqueSleep and Work-Related Fatigue
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésObservational studySystematic reviewPsychological interventionGrey literatureMeta-analysisRandomized controlled trialMEDLINEInclusion (mineral)Intervention (counseling)

Résumé

récupéré en direct d'OpenAlex

This abstract was awarded the student prize for best oral presentation. Shift work is integral to the operational function of emergency service and first responder professions. However, it is associated with health consequences due to chronic disruptions in circadian rhythms, (1) sleep patterns (2) and less healthy diets. (3-4) Modifiable health behaviour interventions, such as improving diet quality, may be effective to prevent, mitigate or delay the onset of non-communicable diseases linked to shift work. (5) However, there is a lack of consensus on evidence-based guidelines. (3) This review aims to evaluate the evidence to support nutritional interventions in this population. A systematic review (PROSPERO CRD42023421400) was conducted to evaluate the literature that may inform dietary guidance for shift workers. Four databases were searched (Embase, Cochrane Library, Web of Science, PubMed). An additional three databases (Police MyAthens, ProQuest, Clinical Trials registries) were searched for relevant grey literature alongside a physical search at the National Police Library. Studies were screened by two researchers and included if of a randomised controlled trial (RCT), crossover-RCT, observational study design, conducted in free-living shiftwork populations or laboratory-controlled shiftwork setting. Papers were accepted where the intervention included a dietary component, and health-related outcomes were reported. Quality assessment was assessed using the Cochrane Risk of Bias Tools. Observational studies were evaluated using the Ottawa Scale. From the 6909 articles retrieved, 43 met the inclusion criteria. Most articles reported using a crossover design (49%), followed by observational studies (33%). Where specified, most studies involved free-living participants (67%) and were carried out with nursing and healthcare professionals (40%). Of included studies, 30% were conducted under simulated conditions. Only 9% of studies were conducted in first responder groups. Years in shift work were often not reported (40%) and, likely due to the prevalence of simulated protocols, a moderate number of studies involved participants with no shift work experience (28%). The quality assessment highlighted that 66% of the included papers were judged to be of concern (15%) or a high risk of bias (51%), signifying challenges to conducting research in shift working populations. The most frequently reported intervention components were Time-Restricted Eating (21%), macronutrient adjustments (21%), and food diaries (19%). The most frequently reported outcomes were cardiometabolic health (39.5%), cognitive performance (27.9%), and sleep quality (11.6%). Heterogeneity in interventions, outcome measures and reporting across studies made it difficult to synthesise findings to inform shift worker dietary guidelines. There was an under representation of studies conducted in first responder occupations and limited studies conducted in the UK. The high risk of bias re-iterates a requirement for more rigorous research to understand the complex relationship between shift work and first responders’ health. Addressing these limitations will help contextualise findings and inform development of evidence-based dietary strategies to mitigate the adverse health effects of shift work in this critical workforce.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,770
Score d'incertitude au seuil0,405

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,063
Tête enseignante GPT0,387
Écart entre enseignants0,323 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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