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The ROLE OF NON-GOVERNMENTAL ORGANIZATIONS IN HEALTH PROMOTION

2005· dissertation· lt· W7151697497 sur OpenAlexaboutno aff
Rasa Marcinkevičienė

Notice bibliographique

RevueLithuanian University of Health Sciences · 2005
Typedissertation
Languelt
DomaineBusiness, Management and Accounting
ThématiqueGlobal Public Health Policies and Epidemiology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLithuanianHealth promotionPublic healthWork (physics)International healthScope (computer science)Health policyHealth carePromotion (chess)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Non-governmental organizations (NGO) in Lithuania are new juridical subjects in its sovereign society, a new expression of the civic community. As there is no any detailed and classified data base made for the Lithuanian NGO yet, it is difficult to find out what organizations are engaged in health promotion, and to determine the effect of this activity on the Lithuanian health service sector and how NGO programmes and services complement the governmental sector’s activities. Aim of the study: Evaluation of the structure, functions and the role in public health promotion of the existing Lithuanian NGO. Objectives: 1. To determine the functions, work scope and finance principles of the health NGO. 2. To evaluate the sociodemographic characteristics of the managers of health and other NGO, their knowledge and awareness concerning the national health policy, the value of public health promotion for the region population. 3. To define the involvement of the health NGO in the formation of the public health policy. 4. To explore the cooperation of the health NGO with other NGO, offices, partners. Methods. Questionnaires filled by the existing Lithuanian organizations and their managers. 409 questionnaires were sent by post. 157 answers were received. It means a very low activity of the respondents. Inquiry by post was made twice. The first inquiry by random sampling of 200 organizations resulted in only 84 answers (42% of all questionnaires sent). Therefore it was decided to send questionnaires also to the rest 209 organizations that were not included in the first inquiry. Then the second inquiry resulted in 73 more answers (35% of all questionnaires sent). The data of the organizations were corrected in the Lintel data base. It showed that 45 organizations could not be found, the activities of 2 of them were stopped, 4 organizations had no any activities at all, the registration of 2 organizations was finished, or there were no any information. The contacts of only 155 organizations were available. The mathematical-statistical analysis of the accumulated data was made by applying the EpiInfo 6.04 programme. The difference between the groups was measured by using the traditional statistics method χ². The difference is considered to be statistically significant when p<=0.05. Results. The major legal form of the acitvities of the organizations of the questionnaire was a public organization, acting in the Vilnius region (28.4% among all the respondents), having approximately 35 members, not employing any worker nor involving any volunteer in its activities, dealing with health and social matters. These organizations most often have their missions and visions formulated and they are known to all members. Organizations also have the aims of their ativities. Organizations are oriented to their members. Not a few NGO have already gained some experience in the sphere of their acivities or even think they are rather experienced. Mostly NGO plan their activities by making annual (half-yearly) plans. State NGO financing sources are less significant than non-governmental ones. NGO get more funds from Lithuania than foreign countries. Membership fees make up the major part of the NGO earnings. Most NGO have not any prepared visual material for their presentation, they prepare it only as opportunity offers. NGO know similar organizations of their region, country and some foreign ones. Generally respondents consider similar NGO their main partners. They cooperate with these partners in health programmes planning. Most NGO (66.32%) know their regional health policy only in part. Usually they are not involved in the formation of the regional health policy or are involved only on request. The average age of the NGO manager is 45 (±13) years (it ranges from 29 to 81), sex is female, education is higher (66.43%). The present workplace is not the main one for major managers. They are financiers, management specialists, teachers, doctors, etc. by profession. The definitions of the concepts "health policy" and "public health promotion" vary greatly. None of the NGO managers has given a precise definition of these concepts. Most NGO managers have not read international documents concerning health policy (Ottawa Charter, Djakarta Declaration, Verona Declaration, Health for All in the XXIth century). They only know some Lithuanian health policy documents: National Health Programme, Patients’ Rights Law, Primary Health Care Law. There was no significant difference among opinions about the presence of the formed regional health policy. But the dominant point was that there are no published documents regulating the implementation of the regional health policy. The NGO managers think that the community is not involved in the formation of the regional health policy. Conclusions. 1. Most inquired non-governmental organizations relate their activity with health care (45.8%) and social (42.6%) matters. The major legal form of the acitvity is a public organization (61%), mostly acting in the Vilnius region (28.47%). More than one third of these organizations (30.8%) has their missions, visions and aims formulated, and their finance activities are planned for not longer than 1 year’s period. Most often the organizations use two financing sources, among which membership fees and governmental and municipality support are predominant ones. The financial support of their business partners (11%) and commercial activity (6%) make up an insignificant part. 2. The managers of the NGO are of average age (45 ±13 years), with higher education (66.4%), women make up more than a half (65.1%), and for the majority of them (64.3%) the NGO organization is not the main workplace. None of the NGO managers has given a precise definition of the concepts "health policy" and "public health promotion" so these definitions vary greatly. Most NGO managers have not read international documents concerning health policy, they can name only some Lithuanian health policy documents. The NGO managers think that there are no published documents regulating the implementation of the regional health policy. 3. The inquiry of the NGO managers showed that usually their organizations are not involved in the formation of the regional health policy, and their knowledge concerning this policy is rather limited. Very often the managers themselves are not actively involved in the formation of the regional health policy, however, they are involved in this process on request. The NGO managers think that the community is not involved in the formation of the regional health policy. 4. Most organizations (75.6%) know similar existing non-governmental organizations and consider them their main partners. Other major partners are the following: public health care institutions (16%), mass media (14%) and the Ministry of Health Care (13%). Among minor partners, NGO organizations mention state administration institutions (3%) and The National Health Council (7%). Visual organization material for public presentation is not prepared most often or it is not budgeted (78.3%).

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)0,012
score de la tête « metaresearch » (Gemma)0,010
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: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,012
Score d'incertitude au seuil0,064

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0120,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0040,005
Communication savante0,0060,001
Science ouverte0,0010,004
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

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 Opus0,014
Tête enseignante GPT0,277
Écart entre enseignants0,263 · 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
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
Publié2005
Routes d'admission1
Résumé présentoui

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