ArticleAnnals of global health2018
Determining whether Community Health Workers are 'Deployment Ready' Using Standard Setting.
Article in Annals of global health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Performance measurement systems in primary health care: a systematic literature review.BMC health services research · 2025Pooled it
- Competency-based education and training for Community Health Workers: a scoping review.BMC health services research · 2025Article
- Community health worker perspectives: examining current responsibilities and strategies for success.Archives of public health = Archives belges de sante publique · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundCommunity Health Workers (CHWs) provide basic health screening and advice to members of their own communities. Although CHWs are trained, no CHW programmes have used a formal method to identify the level of achievement on post-training assessments that distinguishes "safe" from "unsafe". Objectives: The aim of this study was to use Ebel method of standard setting for a post-training written knowledge assessment for CHWs in Neno, Malawi.
methods12 participants agreed the definitions of a "just-deployment ready" and an "ideal" CHW. Participants rated the importance and difficulty of each question on a three-point scale and also indicated the proportion of "just-deployment ready" CHWs expected to answer each of the nine question types correctly. Mean scores were used to determine the passing standard, which was reduced by one standard error of measurement (SEM) as this was the first time any passing standard had been employed.The level of agreement across participants' ratings of importance and difficulty was calculated using Krippendorf's alpha. The assessment results from the first cohort of CHW trainees were analysed using classical test theory.
findingsThere was poor agreement between participants on item ratings of both importance and difficulty (Krippendorf's alphas of 0.064 and 0.074 respectively). The pass mark applied to the assessment, following adjustment using the SEM, was 53.3%. Based on this pass mark, 68% of 129 CHW trainees were 'clear passes', 11% 'borderline passes', 9% 'borderline fails' and 12% 'clear fails'.
conclusionsDetermining whether a CHW is deployment-ready is an important, but difficult exercise, as evidenced by a lack of agreement regarding question importance and difficulty. Future exercises should allow more time for training, discussion and modification of ratings. Based on the assessment, most CHWs trained could be considered deployment-ready, but following-up their performance in the field will be vital to validate the pass mark set.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.