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Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework

Background The success of the Community Based Management of Severe Malnutrition (CSAM) programme largely depends on the knowledge and skills of Front-Line Workers (FLWs). A robust supportive supervision system in CSAM should be tailored to individualistic learning needs by distinguishing the FLWs as...

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Autores principales: Joshi, Ankur, Pakhare, Abhijit P, Nair, Sivaja K, G, Revadi, Chouhan, Manoj, Pandey, Deepak, Kokane, Arun M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572322/
https://www.ncbi.nlm.nih.gov/pubmed/34760426
http://dx.doi.org/10.7759/cureus.18589
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author Joshi, Ankur
Pakhare, Abhijit P
Nair, Sivaja K
G, Revadi
Chouhan, Manoj
Pandey, Deepak
Kokane, Arun M
author_facet Joshi, Ankur
Pakhare, Abhijit P
Nair, Sivaja K
G, Revadi
Chouhan, Manoj
Pandey, Deepak
Kokane, Arun M
author_sort Joshi, Ankur
collection PubMed
description Background The success of the Community Based Management of Severe Malnutrition (CSAM) programme largely depends on the knowledge and skills of Front-Line Workers (FLWs). A robust supportive supervision system in CSAM should be tailored to individualistic learning needs by distinguishing the FLWs as per their ability and simultaneously identifying the task domains to be emphasized more in supervisory visits. This paper details the ability assessment strategy developed and employed in the selected geographical locations in Madhya Pradesh (Central India) among the 197 Anganwadi workers (FLWs involved in CSAM implementation). Methodology A 25 items tool was developed based on an analytical construct for ability estimation through Rasch Analysis (RA). RA models the probability of right/wrong answers as a function of a person (participants) and item (questions) parameters and calculates the item difficulty in relation to personability on the same unidimensional linear scale. Suitable visualization like item characteristic curve (ICC), person item map (PIM) and quadratic allocation were plotted in RA. The data fitting to the Rasch model (Rasch diagnostic) was tested by numeric (Anderson LR and Wald test) and graphical methods. Results The item easiness parameter (β) value related to Diarrhoeal assessment was lowest (-2.32, -2.91 to -1.73) and related to peer assessment meaningful action (2.009, 1.669- 2.348)) was highest (most difficult). Anderson LR test (LR=31.32, df=24, p=0.079) showed the absence of global outliers. Quadrant analysis using the permutations of ability score and adjusted burden of malnutrition further mapped 41/197 (20.8%) FLWs to low ability -high burden quadrant and 44/197(25%) as low ability low burden quadrant. Conclusion Rasch assessment may address the innate challenges to maintain homogeneity, discrimination capacity and linearity in a raw score-based measurement construct. The monitoring strategy developed on this thus may offer a judicious, pragmatic and thematic approach to supportive supervision in the CSAM program. 
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spelling pubmed-85723222021-11-09 Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework Joshi, Ankur Pakhare, Abhijit P Nair, Sivaja K G, Revadi Chouhan, Manoj Pandey, Deepak Kokane, Arun M Cureus Public Health Background The success of the Community Based Management of Severe Malnutrition (CSAM) programme largely depends on the knowledge and skills of Front-Line Workers (FLWs). A robust supportive supervision system in CSAM should be tailored to individualistic learning needs by distinguishing the FLWs as per their ability and simultaneously identifying the task domains to be emphasized more in supervisory visits. This paper details the ability assessment strategy developed and employed in the selected geographical locations in Madhya Pradesh (Central India) among the 197 Anganwadi workers (FLWs involved in CSAM implementation). Methodology A 25 items tool was developed based on an analytical construct for ability estimation through Rasch Analysis (RA). RA models the probability of right/wrong answers as a function of a person (participants) and item (questions) parameters and calculates the item difficulty in relation to personability on the same unidimensional linear scale. Suitable visualization like item characteristic curve (ICC), person item map (PIM) and quadratic allocation were plotted in RA. The data fitting to the Rasch model (Rasch diagnostic) was tested by numeric (Anderson LR and Wald test) and graphical methods. Results The item easiness parameter (β) value related to Diarrhoeal assessment was lowest (-2.32, -2.91 to -1.73) and related to peer assessment meaningful action (2.009, 1.669- 2.348)) was highest (most difficult). Anderson LR test (LR=31.32, df=24, p=0.079) showed the absence of global outliers. Quadrant analysis using the permutations of ability score and adjusted burden of malnutrition further mapped 41/197 (20.8%) FLWs to low ability -high burden quadrant and 44/197(25%) as low ability low burden quadrant. Conclusion Rasch assessment may address the innate challenges to maintain homogeneity, discrimination capacity and linearity in a raw score-based measurement construct. The monitoring strategy developed on this thus may offer a judicious, pragmatic and thematic approach to supportive supervision in the CSAM program.  Cureus 2021-10-07 /pmc/articles/PMC8572322/ /pubmed/34760426 http://dx.doi.org/10.7759/cureus.18589 Text en Copyright © 2021, Joshi et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Public Health
Joshi, Ankur
Pakhare, Abhijit P
Nair, Sivaja K
G, Revadi
Chouhan, Manoj
Pandey, Deepak
Kokane, Arun M
Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework
title Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework
title_full Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework
title_fullStr Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework
title_full_unstemmed Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework
title_short Data-Driven Monitoring in Community Based Management of Children With Severely Acute Malnutrition (SAM) Using Psychometric Techniques: An Operational Framework
title_sort data-driven monitoring in community based management of children with severely acute malnutrition (sam) using psychometric techniques: an operational framework
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572322/
https://www.ncbi.nlm.nih.gov/pubmed/34760426
http://dx.doi.org/10.7759/cureus.18589
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