ArticlePLoS neglected tropical diseases2018
Does appreciative inquiry decrease false positive diagnosis during leprosy case detection campaigns in Bihar, India? An operational research study.
Article in PLoS neglected tropical diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review and narrative synthesis of the impact of Appreciative Inquiry in healthcare.BMJ open quality · 2022Pooled it
- Participatory development of Indonesia's national action plan for zero leprosy: strategies and interventions.Frontiers in public health · 2025Article
- Integrating Community Engagement in Zero Leprosy Efforts: A Pathway to Sustainable Early Detection, Control and Elimination.Tropical medicine and infectious disease · 2024Article
- Field-friendly anti-PGL-I serosurvey in children to monitorFrontiers in medicine · 2023Article
- Operational Research in Health-care Settings.Indian journal of community medicine : official publication of Indian Association of Preventive & Social MedicineArticle
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9 authors.
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Abstract
backgroundIndia contributes ~60% to the global leprosy burden. The country implements 14-day community-based leprosy case detection campaigns (LCDC) periodically in all high endemic states. Paramedical staff screen the population and medical officers of primary health centres (PHCs) diagnose and treat leprosy cases. Several new cases were detected during the two LCDCs held in September-2016 and February-2018. Following these LCDCs, a validation exercise was conducted in 8 Primary health centres (PHCs) of 4 districts in Bihar State by an independent expert group, to assess the correctness of case diagnosis. Just before the February 2018 LCDC campaign, we conducted an "appreciative inquiry" (AI) involving the health care staff of these 8 PHCs using the 4-D framework (Discovery-Dream-Design-Destiny).
objectivesTo assess whether the incorrect case diagnosis (false positive diagnosis) reduced as a result of AI in the 8 PHCs between the two LCDC conducted in September-2016 and February-2018. METHODOLOGY/PRINCIPAL
findingsA three-phase quantitative-qualitative-quantitative mixed methods research (embedded design) with the two validation exercises conducted following September-2016 and February-2018 LCDCs as quantitative phases and AI as qualitative phase. In September-2016 LCDC, 303 new leprosy cases were detected, of which 196 cases were validated and 58 (29.6%) were false positive diagnosis. In February-2018 LCDC, 118 new leprosy cases were detected of which 96 cases were validated and 22 cases (23.4%) were false positive diagnosis. After adjusting for the age, gender, type of cases and individual PHCs fixed effects, the proportion of false positive diagnosis reduced by -9% [95% confidence intervals (95%CI): -20.2% to 1.7%, p = 0.068].
conclusionFalse positive diagnosis is a major issue during LCDCs. Though the decline in false positive diagnosis is not statistically significant, the findings are encouraging and indicates that appreciative inquiry can be used to address this deficiency in programme implementation.
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