Evidence map›Paper›PMID 39255009›Full record

ArticleJMIR formative research2024

Challenges Experienced by Health Care Workers During Service Delivery in the Geographically Challenging Terrains of North-East India: Study Involving a Thematic Analysis.

Sumit Aggarwal, Simmy Simmy, Nupur Mahajan, Kuldeep Nigam

Abstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sumit Aggarwal *Indian Council of Medical Research, New Delhi, India.ORCID 0000-0002-0652-1611
Simmy Simmy *Indian Council of Medical Research, New Delhi, India.ORCID 0000-0003-4655-8176
Nupur MahajanIndian Council of Medical Research, New Delhi, India.ORCID 0000-0001-9908-0634
Kuldeep NigamIndian Council of Medical Research, New Delhi, India.ORCID 0000-0003-3113-8857

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe public health landscape in North-East India is marked by the foundational principle of equitable health care provision, a critical endeavor considering the region's intricate geography and proximity to international borders. Health care workers grapple with challenges, such as treacherous routes, limited infrastructure, and diverse cultural nuances, when delivering essential medical services. Despite improvements since the National Rural Health Mission in 2005, challenges persist, prompting a study to identify health care workers' challenges and alternative strategies in Manipur and Nagaland.

objectiveThis study aims to document the challenges experienced by health care workers during service delivery in the geographically challenging terrains of North-East India.

methodsThis study is part of the i-DRONE (Indian Council of Medical Research's Drone Response and Outreach for North East) project, which aims to assess the feasibility of drone-mediated vaccine and medical delivery. This study addresses the secondary objective of the i-DRONE project. In-depth interviews of 29 health care workers were conducted using semistructured questionnaires in 5 districts (Mokokchung and Tuensang in Nagaland, and Imphal West, Bishnupur, and Churachandpur in Manipur). Nineteen health facilities, including primary health care centers, community health centers, and district hospitals, were selected. The study considered all levels of health care professionals who were in active employment for the past 6 months without a significant vacation and those who were engaged in ground-level implementation, policy, and maintenance activities. Data were recorded, transcribed, and translated, and subsequently, codes, themes, and subthemes were developed using NVivo 14 (QSR International) for thematic analysis.

resultsFive themes were generated from the data: (1) general challenges (challenges due to being an international borderline district, human resource constraints, logistical challenges for medical supply, infrastructural issues, and transportation challenges); (2) challenges during the COVID-19 pandemic (increased workload, lack of diagnostic centers, mental health challenges and family issues, routine health care facilities affected, stigma and fear of infection, and vaccine hesitancy and misinformation); (3) perception and awareness regarding COVID-19 vaccination; (4) alternative actions or strategies adopted by health care workers to address the challenges; and (5) suggestions provided by health care workers. Health care workers demonstrated adaptability by overcoming these challenges and provided suggestions for addressing these challenges in the future.

conclusionsHealth care workers in Manipur and Nagaland have shown remarkable resilience in the face of numerous challenges exacerbated by the pandemic. Despite infrastructural limitations, communication barriers, and inadequate medical supply distribution in remote areas, they have demonstrated adaptability through innovative solutions like efficient data management, vaccination awareness campaigns, and leveraging technology for improved care delivery. The findings are pertinent for not only health care practitioners and policymakers but also the broader scientific and public health communities. However, the findings may have limited generalizability beyond Manipur and Nagaland.

Indexed as

Delivery of Health CareHealth PersonnelAdultCOVID-19FemaleHumansIndiaMaleQualitative ResearchSurveys and Questionnairesadaptabilitychallengescommunicationinfrastructureinnovative solutionsresiliencesupply distributionthematic analysisvaccination awareness

Identifiers

PMID39255009
PMCPMC11422737

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.