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Enregistrement W2059120605 · doi:10.1186/1471-2458-12-1084

Socio-demographic factors influencing knowledge, attitude and practice (KAP) regarding malaria in Bangladesh

2012· article· en· W2059120605 sur OpenAlexfundno aff
Kabirul Bashar, Hasan Mohammad Al‐Amin, Md Selim Reza, Muzahidul Islam, Asaduzzaman, Touhid Uddin Ahmed

Notice bibliographique

RevueBMC Public Health · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueMalaria Research and Control
Établissements canadiensnon disponible
Organismes subventionnairesJapan Society for the Promotion of ScienceBangabandhu Sheikh Mujibur Rahman Agricultural UniversityPublic Health AgencyPublic Health Agency of Canada
Mots-clésMalariaBiostatisticsResidenceEnvironmental healthObservational studyPublic healthMedicineEpidemiologySocioeconomicsCross-sectional studyInterviewGeographyDemographyNursing

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: A clear understanding of the social and behavioral risk factors, and knowledge gaps, related to exposure to malaria are essential when developing guidelines and recommendations for more effective disease prevention in many malaria endemic areas of the world including Bangladesh and elsewhere in the South East Asia. To-date, the level of knowledge that human populations, residing in moderate to high malaria risk zones, have with respect to the basic pathogen transmission dynamics, risk factors for malaria or disease preventative strategies, has not been assessed in Bangladesh. The purpose of this study was to address this gap by conducting surveys of the knowledge, attitudes and practices (KAP) of people, from variable socio-demographic backgrounds, residing in selected rural malaria endemic areas in Bangladesh. METHODS: The KAP survey was conducted in portions of six different malaria endemic districts in Bangladesh from July to October 2011. The survey consisted of interviewing residence of these malaria endemic districts using a structured questionnaire and interviewers also completed observational checklists at each household where people were interviewed. The study area was further divided into two zones (1 and 2) based on differences in the physical geography and level of malaria endemicity in the two zones. Data from the questionnaires and observational checklists were analysised using Statistical Package for Social Sciences 16.0 (SPSS, Inc., Chicago, IL, USA). RESULTS: A total of 468 individuals from individual households were interviewed, and most respondents were female. Monthly incomes varied within and among the zones. It was found that 46.4% and 41% of respondents' family had malaria within the past one year in zones 1 and 2, respectively. Nearly 86% of the respondents did not know the exact cause of malaria or the role of Anopheles mosquitoes in the pathogen's transmission. Knowledge on malaria transmission and symptoms of the respondents of zones 1 and 2 were significantly (p<0.01) different. The majority of respondents from both zones believed that bed nets were the main protective measure against malaria, but a significant relationship was not found between the use of bed net and prevalence of malaria. A significant relationship (p<0.05) between level of education with malaria prevalence was found in zone 1. There was a positive correlation between the number of family members and the prevalence of malaria. Houses with walls had a strong positive association with malaria. Approximately 50% of the households of zones 1 and 2 maintained that they suffered from malaria within the last year. A significant association (p<0.01) between malaria and the possession of domestic animals in their houses was found in both zones. People who spent time outside in the evening were more likely to contract malaria than those who did not. CONCLUSION: To address the shortcomings in local knowledge about malaria, health personnel working in malaria endemic areas should be trained to give more appropriate counseling in an effort to change certain deeply entrenched traditional behaviors such as spending time outdoors in the evening, improper use of bed nets and irregular use of insecticides during sleep.

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)0,006
score de la tête « metaresearch » (Gemma)0,006
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 enseignants0,089
Score d'incertitude au seuil0,693

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
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 Opus0,069
Tête enseignante GPT0,372
Écart entre enseignants0,303 · 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

Citations40
Publié2012
Routes d'admission1
Résumé présentoui

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