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Enregistrement W4321639901 · doi:10.22374/jfasd.v4isp1.13

At a Juncture: Exploring Patterns and Trends in FASD Prevention Research from 2015 – 2021 Using the Four-Part Model of Prevention

2022· article· en· W4321639901 sur OpenAlexaffabout
Lindsay Wolfson, Nancy Poole, Kelly D. Harding, Julie Stinson

Notice bibliographique

RevueJournal of Fetal Alcohol Spectrum Disorder · 2022
Typearticle
Langueen
DomaineMedicine
ThématiquePrenatal Substance Exposure Effects
Établissements canadiensBritish Columbia Centre of Excellence for Women's HealthLaurentian UniversityBC Research (Canada)
Organismes subventionnairesnon disponible
Mots-clésPsychological interventionThematic analysisMedicinePregnancyPrevention sciencePsychologyFamily medicineEnvironmental healthNursingQualitative researchSocial scienceSociology

Résumé

récupéré en direct d'OpenAlex

Background and objective Fetal Alcohol Spectrum Disorder (FASD) prevention efforts have grown in the last 25 years to go beyond the moral panic that guided the early public awareness campaigns and policy responses. In Canada, a four-part model of FASD prevention has been developed and used that describes a continuum of multisectoral efforts for women, girls, children, and their support networks, including broad awareness campaigns, safe and respectful conversations around pregnancy and alcohol use, and holistic and wraparound support services for pregnant and postpartum women with alcohol, and other health and social concerns. The purpose of this article is to describe the state of the evidence on FASD prevention from 2015 – 2021, including the prevalence and influences on alcohol use during pregnancy, interventions at each of the four levels of the fourpart model, as well as systemic, destigmatizing, and ethical considerations. Materials and methods Using EBSCO Host, seven academic databases were annually searched for articles related to FASD prevention from 2015 – 2021. English language articles were screened for relevance to alcohol use in pregnancy and FASD prevention. Using outlined procedures for thematic analysis, the findings were categorized within the following key themes: prevalence and influences on women's drinking; Level 1 prevention; Level 2 prevention; Level 3 prevention; Level 4 prevention; and systemic, destigmatizing, and ethical considerations. Results From January 2015 – December 2020, 532 (n = 532) articles were identified that addressed the prevalence and influences on alcohol use during pregnancy, interventions at each of the four levels, and systemic, destigmatizing, and ethical considerations. The most recent research on FASD prevention published in English was generated in the United States (US; n = 216, 40.6%), Canada (n = 91, 17.1%), United Kingdom (UK; n = 60, 11.3%), and Australia (n = 58, 10.9%). However, there was an increase in the studies published from other countries over the last six years. The literature heavily focused on the prevalence and influences on alcohol use during pregnancy (n = 182, 34.2%) with an increase in prevalence research from countries outside of Canada, the US, Australia, and the UK and on Level 2 prevention efforts (n = 174, 32.7%), specifically around the efficacy and implementation of brief interventions. Across Level 1 and Level 2 prevention efforts, there was an increase in literature published on the role of technology in supporting health promotion, education, screening, and brief interventions. Attention to Levels 3 and 4 demonstrated nuanced multiservice, traumainformed, relational, and holistic approaches to supporting women and their children. However, efforts are needed to address stigma, which acted as a systemic barrier to care across each level of prevention. Conclusion Research and practice of FASD prevention has continued to grow. Through our generated deductive themes, this review synthesized the findings and demonstrated how the work on FASD prevention has been amplified in the recent years and how efforts to support women and children's health are complex and interconnected. The findings highlight the opportunities for prevention through research and evidenceinformed policy and practice.

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)0,002
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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,329
Score d'incertitude au seuil0,639

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
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 recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,148
Tête enseignante GPT0,364
Écart entre enseignants0,216 · 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'étudeObservationnel
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

Citations8
Publié2022
Routes d'admission2
Résumé présentoui

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