The training and fieldwork experiences of community health workers conducting population-based, noninvasive screening

Shafika Abrahams-Gessel1, Catalina A Denman2, Carlos Mendoza Montano3

  • 1Center for Health Decision Science, Harvard School of Public Health, Boston, MA, USA.

Global Heart
|March 11, 2015
PubMed

Insights

Community health workers (CHW) can be effectively trained to screen for cardiovascular disease (CVD) risk. Training improved CHW knowledge, with retention up to six months, highlighting the need for culturally adapted programs.

Area of Science:

  • Global Health
  • Public Health
  • Cardiovascular Health

Background:

  • Cardiovascular disease (CVD) is a growing concern in low- and middle-income countries, exacerbated by resource constraints.
  • Task-sharing to community health workers (CHW) offers a strategy to expand CVD screening and mitigate its impact.
  • CHW in Bangladesh, Guatemala, Mexico, and South Africa were trained for noninvasive CVD risk screening.

Purpose of the Study:

  • To quantitatively evaluate CHW performance during CVD screening training.
  • To qualitatively assess CHW training and fieldwork experiences in community-based CVD risk screening.

Main Methods:

  • Written tests assessed CHW knowledge acquisition during training.
  • Focus group discussions captured CHW training and fieldwork experiences.

Main Results:

  • Training significantly improved CHW content knowledge of CVD, with knowledge largely retained for up to six months.
  • Key themes for task-sharing include language, respect, compensation, and deep community knowledge.
  • Successful implementation requires integrating community-specific insights from design to fieldwork.

Conclusions:

  • Effective CVD screening training for CHW requires a strong didactic foundation with culturally tailored instruction.
  • Incorporating expert and intimate community knowledge is crucial for training design and implementation.
  • Addressing challenges like role definition, career paths, and fair remuneration is essential for sustainable programs.
Abstract

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