Evidence map›Paper›PMID 27871303›Full record

ArticleMalaria journal2016

Geographically-weighted regression of knowledge and behaviour determinants to anti-malarial recommending and dispensing practice among medicine retailers in western Kenya: capacitating targeted interventions.

Andria Rusk, Linda Highfield, J Michael Wilkerson, Melissa Harrell, Andrew Obala, Benjamin Amick

Abstract read
In one paragraph

Article in Malaria journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Andria RuskDominican University of California, San Rafael, CA, USA. Andria.Rusk@Dominican.edu.ORCID http://orcid.org/0000-0003-3485-084X
Linda HighfieldThe University of Texas School of Public Health, Pressler Dr, Houston, TX, USA.
J Michael WilkersonThe University of Texas School of Public Health, Pressler Dr, Houston, TX, USA.
Melissa HarrellThe University of Texas School of Public Health, Pressler Dr, Houston, TX, USA.
Andrew ObalaMoi University School of Medicine, Nandi Rd, Eldoret, Kenya.
Benjamin AmickDepartment of Health Policy and Management, Robert Stempel College of Public Health & Social Work, Florida International University, Miami, FL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost patients with malaria seek treatment first in retail drug shops. Myriad studies have examined retailer behaviours and characteristics to understand the determinants to these behaviours. Geospatial methods are helpful in discovering if geographic location plays a role in the relationship between determinants and outcomes. This study aimed to discover if spatial autocorrelation exists in the relationship between determinants and retailer behaviours, and to provide specific geographic locations and target behaviours for tailoring future interventions.

methodsRetailer behaviours and characteristics captured from a survey deployed to medicine retailers in the Webuye Demographic and Health Surveillance Site were analysed using geographic weighted regression to create prediction models for three separate outcomes: recommending the first-line anti-malarial therapy to adults, recommending the first-line anti-malarial therapy to children, and selling that therapy more than other anti-malarials. The estimated regression coefficients for each determinant, as well as the pseudo R

resultsThe relationships explored were found to be non-stationary, indicating that spatial heterogeneity exist in the data. The association between having a pharmacy-related health training and recommending the first-line anti-malarial treatment to adults was strongest around the peri-urban centre: comparing those with training in pharmacy to those without training (OR = 5.75, p = 0.021). The association between knowing the first-line anti-malarial and recommending it to children was strongest in the north of the study area compared to those who did not know the MOH-recommended anti-malarial (OR = 2.34, p = 0.070). This is also the area with the strongest association between attending a malaria workshop and selling the MOH-recommended anti-malarial more than other anti-malarials, compared to retailers who did not attend a workshop (OR = 2.38, p = 0.055).

conclusionEvidence suggests that spatial heterogeneity exists in these data, indicating that the relationship between determinants and behaviours varies across space. This is valuable information for intervention design, allowing efforts to focus on those factors that have the strongest relationship with their targeted behaviour within that geographic space, increasing programme efficiency and cost-effectiveness.

Indexed as

Health Knowledge, Attitudes, PracticePharmaciesAdultAntimalarialsFemaleHumansKenyaMalariaMaleSpatial RegressionSurveys and QuestionnairesAntimalarialsAntimalarial drugsBehaviorGeographically weighted regressionMalariaPrivate sector

Identifiers

PMID27871303
PMCPMC5117492

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.