The re-emergence of infectious diseases has been a rampant public health challenge in the state of Kerala over the past one decade with high rates of mortality and morbidity. In an exploration of the contextual factors determining illness response associated with these diseases, this study employed a mixed methodology including a cross sectional survey of 430 respondents and 30 in-depth interviews. Individuals having one or more cases of selected re-emerging infectious diseases (Chikungunya, Dengue, Malaria and Leptospirosis) from various socio-spatial locations were included in the study to understand the patterns and determinants of illness response across different categories. The findings demonstrated that respondents’ response to illness is jointly determined by individual and household level factors such as gender, parenthood, illness context and spatiality. The article explains the ways in which these factors have interacted and intersected at varying points to create and reinforce multiple layers of vulnerability. Results are pertinent in understanding the pathways and mechanisms through which health inequities are created and sustained among different categories in the population. The findings demonstrate that only interventions concomitantly dealing with these factors and their interactions will produce more equitable results in improving access to health services and management of morbidity associated with re-emerging infectious diseases.
BackgroundThe 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). MethodologyA 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. ResultsThe 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. ConclusionRasch 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.
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 state of 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 answer as a function of person(participants) and item (questions) parameters and calculates the item difficulty in relation with person ability on same unidimensional linear scale. The fitting of the data to Rasch model (Rasch diagnostic) was tested by both numeric (Anderson LR and Wald test) and graphical method. Suitable visualization like Item Characteristic Curve (ICC) and Person Item Map (PIM) were plotted in RA. Further a quadratic allocation of all AWWs into 4 quadrants were done as per the ability estimation (Rasch score) and adjusted numbers of SAM/MAM children in her center. 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 consequential 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 CSAM program. Keywords: Severe Acute Malnutrition, RASCH assessment, data driven monitoring
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