A comparative analysis of policies addressing rural oral health in eight English-speaking OECD countries
Notice bibliographique
Résumé
INTRODUCTON: Oral health is fundamental to overall health. Poor oral health is largely preventable but unacceptable inequalities exist, particularly for people in rural areas. The issues are complex. Rural populations are characterised by lower rates of health insurance, higher rates of poverty, less water fluoridation, fewer dentists and oral health specialists, and greater distances to access care. These factors inter-relate with educational, attitudinal, and system-level issues. An important area of enquiry is whether and how national oral health policies address causes and solutions for poor rural oral health. The purpose of this study was to examine a series of government policies on oral health to (i) determine the extent to which such policies addressed rural oral health issues, and (ii) identify enabling assumptions in policy language about problems and solutions regarding rural communities. METHODS: Eight current oral health policies were identified from Australia, New Zealand, Canada, the USA, England, Scotland, Northern Ireland, and Wales. Validated content and critical discourse analyses were used to document and explore the concepts in these policy documents, with a particular focus on the frequency with which rural oral health was mentioned, and the enabling assumptions in policy language about rural communities. RESULTS: Seventy-three concepts relating to oral health were identified from the textual analysis of the eight policy documents. The rural concept addressing oral health issues occurred in only 2% of all policies and was notably absent from the oral health policies of countries with substantial rural populations. It occurred most frequently in the policy documents from Australia and Scotland, less so in the policy documents from Canada, Wales, and New Zealand, and not at all in the oral health policies from the US, England, and Northern Ireland. Thus, the oral health needs of rural communities were generally not the focus of, nor included in, the oral health policy documents in this study. When the language of concepts related to rural oral health was examined, the qualitative analysis identified four discourse themes related to both causality and solutions. These ranked discourse themes focused on service models, workforce issues, social determinants of health, and prevention. None of the policies addressed the structural economic determinants of unequal rural oral health, nor did they specifically assert the rights of children in rural communities to equitable oral health care. CONCLUSIONS: This study documented the limited focus on rural oral health that existed in national oral health policies from eight different English-speaking countries. It supports the need for an increased focus on rural oral health issues in oral health policies, particularly as increased oral health is clearly associated with increased general health. It speaks to the critical importance of periodic analysis of the content of oral health policies to ensure that issues of inequality are addressed. Further, it reinforces the need for research findings about effective oral health care to be translated into practice in the development of practical and financially viable policies to make access to oral health care more equitable, particularly for people living in rural and remote areas.
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 | 0,010 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».