ArticleInternational journal of environmental research and public health2023
Academic Burnout of Polish Students: A Latent Profile Analysis.
Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Academic burnout profiles and their correlates: a latent profile analysis of Chinese university students.Frontiers in psychology · 2026Article
- Identifying foreign language learning burnout: latent profiles, cutoff points, and an explainable web-based calculator.Frontiers in psychology · 2026Article
- Stress, student burnout and study engagement - a cross-sectional comparison of university students of different academic subjects.BMC psychology · 2025Article
- Determinants of burnout syndrome among undergraduate nursing students in Poland: a cross-sectional study.BMC medical education · 2025Article
- Article
- Analyzing Latent Burnout Profiles in a Sample of Spanish Nursing and Psychology Undergraduates.Healthcare (Basel, Switzerland) · 2024Article
- Burnout and Its Relationship with Work Engagement in Healthcare Professionals: A Latent Profile Analysis Approach.Healthcare (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
According to Maslach and Leiter, burnout syndrome consists of three elements: exhaustion, cynicism, and a sense of ineffectiveness experienced by individuals in the work environment. However, burnout does not only apply to professional activity but can also be experienced by students pursuing higher education. This is important because the consequences of student burnout can be related to students' mental and physical health. Until recently, the dominant diagnostic trend in the studies of burnout syndrome was based on a variable-focused approach. This approach focuses primarily on identifying subgroups in the population and presents different configurations of the various dimensions of burnout. However, there is emerging research using a person-centered approach and including the analysis of latent profiles to study professional and student burnout. This approach allows us to isolate subgroups of individuals in the study sample who have a similar burnout pattern. It focuses on the differences between individuals, which helps us to look at the phenomenon of professional burnout from a different perspective and shows the individuality of its experience. Our research aimed at identifying latent profiles, was conducted on a sample of 1519 Polish students, and partly confirms reports from other countries. We identified four profiles: low burnout, moderate below-average burnout, moderate above-average burnout, and very high burnout groups.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.