Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Subsequent to the demonstrated potential of community health workers (CHWs) in strengthening health systems to improve health outcomes, recent literature has defined context and guidelines for integrating CHW programs into mainstream health systems. However, quantitative measures for assessing the extent of CHW program integration into national health systems need to be developed. The purpose of this study was to validate a newly developed scale, Community Health Worker Program Integration Scorecard Metrics (CHWP-ISM), for assessing the degree of integration of CHW programs into national health systems in Sub-Saharan Africa (SSA).
Methods: Data obtained through a pilot study involving a purposively selected sample of 41 participants selected from populations involved in CHW programs work in selected countries of SSA formed the basis of a 31-item bifactor model. Data were collected between June and December 2019. By applying a latent variable approach implemented with structural equation modeling, data analysis was mainly done using the R statistical environment, applying factor analysis procedures.
Results: Dimensionality, construct validity, and the CHWP-ISM scale's internal consistency were assessed. Confirmatory factor analysis of the CHW-ISM bifactor model supported a co-occurring CHW integration general factor and six unique domain-specific factors. Both the comparative fit index (CFI) and Tucker-Lewis Index (TLI) fit indices were above 0.9, while the root mean square of the residuals (RMSR) was 0.02. Cronbach's alpha (α), Guttman 6 (Lambda 6), and Omega total (ω) were above 0.8, indicating good scale reliability.
Conclusion: Statistical significance of the bifactor model suggests that CHW integration has to be examined using factors that reflect a single common underlying integration construct, as well as factors that reflect unique variances for the identified six subject-specific domains. The validated CHWP-ISM could be useful to inform policy advisers, health systems, donors, non-governmental organizations, and other CHW program stakeholders with guidance on how to quantitatively assess the integration status of different components of CHW programs into respective critical functions of the health system. Improved integration could increase CHW program functionality, which could in turn strengthen the healthcare systems to improve health outcomes in the region.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9822652 | PMC |
http://dx.doi.org/10.3389/fpubh.2022.907451 | DOI Listing |
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