Evidence map›Paper›PMID 36694765›Full record

ArticlePakistan journal of medical sciences

Latent profile analysis of adaptation types and stress among medical students during the COVID-19 pandemic in South Korea.

Kwi Hwa Park, Sun Ju Im, Sun Young Kyung, So Jung Yune

Open access · goldAbstract read
In one paragraph

Article in Pakistan journal of medical sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 81% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Kwi Hwa ParkKwi Hwa Park, Department of Medical Education, Gachon University College of Medicine Incheon, Rep. of Korea.
Sun Ju ImSun Ju Im, Department of Medical Education, Pusan National University School of Medicine Busan, Rep. of Korea.
Sun Young KyungSun Young Kyung, Department of Internal Medicine, Gachon University College of Medicine Incheon, Rep. of Korea.
So Jung YuneSo Jung Yune, Department of Medical Education, Pusan National University School of Medicine Busan, Rep. of Korea.
Gachon University · KRPusan National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to identify profile groups based on personality traits and coping strategies exhibited by medical students in the context of COVID-19. Methods: We conducted a cross-sectional survey and latent profile analysis to investigate differences in stressors, psychological distress, and stress levels with academic variables. We collected data online (Google survey form) in November and December 2021. The participants included a total of 260 1 Results: The results reveal the three following profile groups: adaptive (lowest neuroticism, low mental disengagement), middle-adaptive (moderate neuroticism, low mental disengagement), and maladaptive (highest neuroticism and mental disengagement), respectively comprising 25.0%, 39.2%, and 35.8% of the study sample. There were no statistically significant intergroup differences regarding grade (χ2=3.345, p=0.188) or gender (χ2=1.197, p=0.550). The maladaptive group was strongly associated with perceived stress during the COVID-19 pandemic (p<0.001). Conclusion: These findings highlight the value of considering profile groups when determining whether students require additional support during pandemics.

Indexed as

Coping strategiesCOVID-19Medical studentsOccupational stressPersonality traits

Identifiers

PMID36694765
PMCPMC9842984
OpenAlexW4309544587

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.