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Enregistrement W4245637152 · doi:10.4073/csr.2015.17

Strategies to Increase the Ownership and Use of Insecticide‐Treated Bednets to Prevent Malaria

2015· article· en· W4245637152 sur OpenAlexafffund
Lana Augustincic Polec, Jennifer Petkovic, Vivian Welch, Erin Ueffing, Elizabeth Tanjong Ghogomu, Jordi Pardo Pardo, Mark Grabowsky, Amir Attaran, George A. Wells, Peter Tugwell

Notice bibliographique

RevueCampbell Systematic Reviews · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueMalaria Research and Control
Établissements canadiensOttawa HospitalCentre for Global Health ResearchInstitute of Population and Public HealthCochraneBruyèreUniversity of Ottawa
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésMalariaIncentiveBusinessSubsidyEnvironmental healthPromotion (chess)Public economicsMedicineEconomicsPolitical science

Résumé

récupéré en direct d'OpenAlex

This Campbell systematic review assesses the effectiveness of economic and educational strategies for ownership and appropriate use of insecticide-treated bednets (‘ITN’) in developing countries. The review also examines whether changes in ITN ownership and use affect malaria-specific morbidity rates. The review summarises findings from 10 studies, nine of which were conducted in rural Africa and one in rural India. Compared to providing ITNS at full market or a subsidized price, giving away ITNs for free increases the number of people owning an ITN. However, the provision of free ITNs increases their use only slightly or not at all. Providing education in the appropriate use of ITNs increases the number of people sleeping under bednets compared to a control group which didn't receive the education. Combining these strategies with unspecified incentives does not increase ITN ownership, leading to little or no differences in their appropriate use. Embedding the promotion of ITNs within specific health- or finance-focused marketing messages only leads to small or no differences in bednet ownership and use. There is some evidence of improved malaria-specific morbidities among children and adults as a result of increased ITN ownership and use. However, the evidence supporting this finding is of low certainty and should be interpreted with caution. Plain language summary STRATEGIES TO INCREASE THE OWNERSHIP AND USE OF INSECTICIDE-TREATED BEDNETS TO PREVENT MALARIA Researchers in the Cochrane and Campbell Collaborations conducted a review of the effect of different strategies to increase people's ownership and use of insecticide-treated bednets to prevent malaria. In February 2013 they identified 10 relevant studies. Their findings are summarized below. What is malaria and how can insecticide-treated bednets prevent it? Malaria is a life-threatening disease caused by a parasite. A person becomes infected from being bitten by a mosquito carrying the parasite. People with malaria may have symptoms such as chills, fever, vomiting, diarrhea, and jaundice. About 40 percent of the world's population is at risk of malaria, mostly in the poorest countries. Insecticide-treated bednets fit over a bed and act as a barrier between insects and the person sleeping. The bednets are dipped in insecticide, a chemical that kills or repels mosquitoes, and effectively prevent malaria. Insecticide-treated bednets cost money and it is important to find ways of ensuring that people who need them own them. Even when people own bednets they may not always use them properly. To be effective, bednets need to be used every night. They must also hang properly and be treated with enough insecticide. It is important to measure whether different strategies not only increase people's ownership but also people's use of bednets. What this research says: The studies included in this review took place in Africa and India. In five of the studies, people were either given insecticide-treated bednets free, or could buy them at a subsidized price or full market price. In the other five studies, people were educated about how to use the bednets properly, for instance through visits at home or through information on the radio, on television and in the community. The included studies show the following: Providing free insecticide-treated bednets: - Probably increases the number of people who own bednets compared to providing subsidized bednets or bednets offered at full market price. - Probably leads to little or no difference in the use of bednets compared to providing subsidized bednets or bednets offered at full market price. Providing education for the appropriate use of insecticide- treated bednets: - May increase the number of adults and children under five using bednets (sleeping under bednets). Providing incentives to encourage use of insecticide-treated bednets: - Probably leads to little or no difference in ownership or use of bednets compared to those who did not receive an incentive. A possible side effect when providing free or subsidized insecticide-treated bednets may be that the governments and institutions who pay for the bednets take this money from other priority issues. However, none of the included studies measured whether these or any other side effects had occurred. Abstract BACKGROUND Malaria is a life-threatening parasitic disease and 40 percent of the world's population lives in areas affected by malaria. Insecticide-treated bednets (ITNs) effectively prevent malaria, however, barriers to their use have been identified. OBJECTIVES To assess the evidence on the effectiveness of available strategies that focus on delivery and appropriate use of ITNs. SEARCH METHODS We searched the EPOC Register of Studies, CENTRAL, MEDLINE, EMBASE, HealthStar, CINAHL, PubMed, Science Citation Index, ProQuest Dissertations and Theses, African Index Medicus (AIM), World Health Organization Library and Information Networks for Knowledge (WHOLIS), LILACS, Virtual Health Library (VHL), and the World Health Organization Library Information System (WHOLIS). Initial searches were conducted in May 2011, updated in March 2012 and February 2013. Authors contacted organizations and individuals involved in ITN distribution programs or research to identify current initiatives, studies or unpublished data, and searched reference lists of relevant reviews and studies. SELECTION CRITERIA Randomized controlled trials (RCTs), non-randomized controlled trials, controlled before-after (CBA) studies, and interrupted time series evaluating interventions focused on increasing ITN ownership and use were considered. The populations of interest were individuals in malaria-endemic areas. DATA COLLECTION AND ANALYSIS Two authors independently screened studies to be included. They extracted data from the selected studies and assessed the risk of bias. For RCTs, we used the Cochrane Collaboration's ‘Risk of bias’ tool and we used the risk of bias criteria suggested by EPOC for other study designs. When consensus was not reached, any disagreements were discussed with a third author. The magnitude of effect and quality of evidence for each outcome was assessed. MAIN RESULTS Of the 3,032 possibly relevant records identified, 10 studies were included in this review; eight cluster RCTs, one RCT, and one CBA study. Overall, three studies were assessed as having moderate risk of bias and seven studies were assessed as high risk of bias. Effect of ITN cost on ownership: Four studies including 4,566 households and another study comprising 424 participants evaluated the effect of ITN price on ownership. These studies suggest that providing free ITNs probably increases ITN ownership when compared to subsidized ITNs or ITNs offered at full market price.

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)0,008
score de la tête « metaresearch » (Gemma)0,043
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,041

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,043
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0040,007
Bibliométrie0,0060,005
Études des sciences et des technologies0,0000,001
Communication savante0,0030,002
Science ouverte0,0020,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

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 Opus0,131
Tête enseignante GPT0,342
Écart entre enseignants0,211 · 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'étudeRevue systématique
Domainenon disponible
GenreSynthèse

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
Publié2015
Routes d'admission2
Résumé présentoui

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