MétaCan
Menu
Retour à la cohorte
Enregistrement W2122891860 · doi:10.1590/s0042-96862003000600004

Health impact assessment--how to start the process and make it last.

2003· editorial· en· W2122891860 sur OpenAlexaboutno aff
Reiner Banken

Notice bibliographique

RevuePubMed · 2003
Typeeditorial
Langueen
DomaineEnvironmental Science
ThématiqueEnvironmental and Social Impact Assessments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHealth impact assessmentPublic healthHealth policyHealth promotionAction (physics)Public relationsInstitutionalisationPopulationPolitical scienceHealth carePopulation healthSocial determinants of healthMedicineEnvironmental healthNursingLaw

Résumé

récupéré en direct d'OpenAlex

Since the Lalonde Report in 1974 on beyond health in Canada, awareness of non-health sector determinants of health has been increasing (1). The World health report 2000 proposed population health as a central objective of health care systems (2) but there are few signs of the concrete mechanisms for intersectoral action that this requires. In 2000, at the Fifth Global Conference for Health Promotion, Mittelmark argued that high-sounding, general calls to improve social responsibility for health are not sufficient to stimulate action. He proposed health impact assessment (HIA) as a device for forcing the relevant bodies to take action in favour of healthy public policies (3). HIA has the potential to catalyse intersectoral action for health by providing information on the foreseeable consequences, both positive and negative, of proposed policies, programmes and projects. To do this, HIA would have to become part of the rules and procedures normally followed by the different decision-making bodies involved. This integration of HIA into the existing procedures has come to be known as institutionalization (4). In this sense entails setting up patterns which condition the perception of interests, obviating some choices and facilitating others (5). After analysing the practice of influencing government decision-making through institutionalized impact analysis, Bartlett concludes: it makes a difference how impact assessment is institutionalized in the policy system; its policy impact is neither simple nor assured. Impact assessment does not influence policy through some magic inherent in its techniques or procedures. More than methodology or substantive focus, what determines the success of impact assessment is the appropriateness and effectiveness in particular circumstances of its implicit policy strategy.(6) What the best strategy is for institutionalizing HIA will depend on the particular political, administrative and economic context of each country. Experience with project HIA has made clear the importance of administrative frameworks for establishing the active practices involved. Legal frameworks for environmental impact assessment (EIA) in many countries already include health impacts as a compulsory element although in practice this is often poorly done. Translating the legal framework into practice seems to require an administrative framework. For example, a memorandum of understanding signed in 1987 in Quebec, Canada, between the Ministry of Health and the Ministry of the Environment has been the key element in the subsequent development of a systematic and active HIA/EIA practice in Quebec. Mutual understanding and trust have been achieved through regular contacts between the professionals in the public health network and those in the Ministry of the Environment (7). For the HIA of policies, the history is still too short to furnish any conclusions as to the role of administrative frameworks, though we can assume that they are important. The policy HIA process which has recently emerged in Quebec as part of a new Public Health Act may provide useful lessons for industrialized countries. The evolving experience in Thailand, described by Phoolcharoen et al. in this issue (pp. 465-467), should be followed closely, as will provide important lessons for institutionalizing HIA in similar contexts. Although institutionalizing HIA seems desirable in order to make a concern for the improvement of health a routine part of decision-making, HIA can become inefficient in a bureaucratic environment. …

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 candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,401
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
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 Opus0,013
Tête enseignante GPT0,305
Écart entre enseignants0,293 · 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.

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

Citations16
Publié2003
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revuePubMedMême sujetEnvironmental and Social Impact AssessmentsTravaux en français237 207