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Does appreciative inquiry decrease false positive diagnosis during leprosy case detection campaigns in Bihar, India?

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Appreciative inquiry (AI) may help reduce false positive leprosy diagnoses during community-based case detection campaigns in India. While not statistically significant, a trend towards fewer incorrect diagnoses was observed after AI implementation.

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Area of Science:

  • Public Health
  • Infectious Disease Epidemiology
  • Health Program Implementation

Background:

  • India bears a significant global burden of leprosy.
  • Community-based Leprosy Case Detection Campaigns (LCDC) are periodically conducted.
  • Accurate diagnosis is crucial for effective leprosy control programs.

Purpose of the Study:

  • To evaluate the impact of Appreciative Inquiry (AI) on reducing false positive leprosy diagnoses.
  • To assess diagnostic accuracy changes between two Leprosy Case Detection Campaigns (LCDC).

Main Methods:

  • A mixed-methods approach combining quantitative and qualitative data.
  • Two validation exercises following September 2016 and February 2018 LCDCs.
  • Appreciative Inquiry (AI) intervention implemented between the two campaigns.

Main Results:

  • False positive diagnoses decreased from 29.6% in 2016 to 23.4% in 2018.
  • A -9% reduction in false positive diagnosis proportion was observed post-AI.
  • This reduction was not statistically significant (p=0.068).

Conclusions:

  • False positive diagnoses remain a challenge in leprosy detection campaigns.
  • Appreciative Inquiry shows potential for improving diagnostic accuracy.
  • Further research is warranted to confirm the efficacy of AI in leprosy programs.