Evidence map›Paper›PMID 34088306›Full record

ArticleBMC public health2021

Experiences and expectations regarding COVID-19 prevention and control measures among the hill tribe population of northern Thailand: a qualitative study.

Siwarak Kitchanapaibul, Anusorn Udplong, Tawatchai Apidechkul, Ratipark Tamornpark, Thanatchaporn Mulikaburt, Peeradone Srichan, Soontaree Suratana, Fatima Yeemard, Pilasinee Wongnuch

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Siwarak KitchanapaibulSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand.
Anusorn UdplongSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand.
Tawatchai ApidechkulSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand. tawatchai.api@mfu.ac.th.
Ratipark TamornparkSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand.
Thanatchaporn MulikaburtSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand.
Peeradone SrichanSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand.
Soontaree SuratanaSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand.
Fatima YeemardCenter of Excellence for Hill Tribe Health Research, Mae Fah Luang University, Chiang Rai, Thailand.
Pilasinee WongnuchSchool of Health Sciences, Mae Fah Luang University, Chiang Rai, Thailand.
Mae Fah Luang University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 has been a major human threat for a year. A large number of people have been infected and killed globally, including hill tribe people living in remote and border areas between Thailand and Myanmar. Different expectations of and experiences with the implemented disease prevention and control measures by local, national and international organizations have been widely reported. This study aimed to understand the experiences and expectations regarding the disease prevention and control measures that were implemented among hill tribe people in Thailand.

methodsQualitative data were collected from participants aged 20 and older who belonged to the hill tribes living on the border of northern Thailand and Myanmar. A semistructured questionnaire was used to guide interviews. Information was extracted for thematic analysis by the NVivo program.

resultsFifty-seven participants (36 female, 21 male) were interviewed; 27 participants were Thai Yai, 14 participants were Yunnan Chinese, 8 participants were Akha, and 8 participants were from other tribes. The average age was 45.8 years (min = 20 years, max = 90 years). Thirty participants had never attended school, and the other 27 participants had received education at different levels, from primary school to higher education. Forty participants were unemployed, 13 worked as agriculturists, and the other 4 were attending school. Both positive experiences, such as improving personal hygiene practices, maintaining close contact and increasing relationships among family members and demonstrating the leadership of the villager leaders, and negative experiences, including interruption of social interactions, family financial problems, poor access to medical care services, and invisible people to the government, were found. Different expectations were observed regarding organizations at the local, national, and international levels. Expectations at the local level included villagers and community leaders taking action to strongly contribute to prevention and control measures and to prevent unscreened people from entering the village. Obtaining accurate information about the disease and being financially supported were expectations at the national level, while closing borders to protect cases from overflowing into their villages was an international-level expectation.

conclusionAlthough hill tribes reside in very remote rural areas, they experience both positive and negative effects of the disease prevention and control measures implemented by organizations. Their expectations are formally and informally voiced to policy makers at the local, national and international levels.

Indexed as

COVID-19MotivationChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedMyanmarRisk FactorsSARS-CoV-2ThailandCOVID-19ExpectationExperienceHill tribePrevention and control

Identifiers

PMID34088306
PMCPMC8176874
OpenAlexW3164359582

What OpenQuestion holds

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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.