Keyword search (4,163 papers available)

"Mixture" Keyword-tagged Publications:

Title Authors PubMed ID
1 Trajectories of Alcohol-Related Problems Among First-Year Nursing Students: Nature, Predictors, and Outcomes Cheyroux P; Morin AJS; O' Connor RM; Colombat P; Vancappel A; Eltanoukhi R; Gillet N; 41797206
PSYCHOLOGY
2 Scientists warning: we must change paradigm for a revolution in toxicology and world food supply Seralini GE; Jungers G; Andersen A; Antoniou M; Aschner M; Bacon MH; Bertrand M; Bohn T; Bonfleur ML; Bücking E; Defarge N; Djemil R; Domingo JL; Douzelet J; Fagan J; Fournier T; Garcia JLY; Gil S; Hervé-Gruyer P; Hilbeck A; Hilty L; Huber D; Joyeux H; Khan I; Kouretas D; Lemarchand F; Loening U; Longo G; Mesnage R; Nikolopoulou DI; Panoff JM; Parente C; Robinson C; Scherber C; Sprangers D; Sultan C; Tsatsakis A; Vandelac L; Wan NF; Wynne B; Zaller JG; Zerrad-Saadi A; Zhang X; 41551494
CHEMBIOCHEM
3 Optimizing Mixtures of Metal-Organic Frameworks for Robust and Bespoke Passive Atmospheric Water Harvesting Harriman C; Ke Q; Vlugt TJH; Howarth AJ; Simon CM; 41427123
CHEMBIOCHEM
4 Deep clustering analysis via variational autoencoder with Gamma mixture latent embeddings Guo J; Fan W; Amayri M; Bouguila N; 39662201
ENCS
5 Developmental heterogeneity of school burnout across the transition from upper secondary school to higher education: A 9-year follow-up study Nadon L; Morin AJS; Gilbert W; Olivier E; Salmela-Aro K; 39645324
PSYCHOLOGY
6 Self-consolidating concrete: Dataset on mixture design and key properties Amine El Mahdi Safhi 38533116
ENCS
7 Unsupervised Mixture Models on the Edge for Smart Energy Consumption Segmentation with Feature Saliency Al-Bazzaz H; Azam M; Amayri M; Bouguila N; 37837127
ENCS
8 Entropy-Based Variational Scheme with Component Splitting for the Efficient Learning of Gamma Mixtures Bourouis S; Pawar Y; Bouguila N; 35009726
ENCS
9 Mixtures of rare earth elements show antagonistic interactions in Chlamydomonas reinhardtii Morel E; Cui L; Zerges W; Wilkinson KJ; 34175518
BIOLOGY
10 BioMiCo: a supervised Bayesian model for inference of microbial community structure. Shafiei M, Dunn KA, Boon E, MacDonald SM, Walsh DA, Gu H, Bielawski JP 25774293
BIOLOGY

 

Title:Developmental heterogeneity of school burnout across the transition from upper secondary school to higher education: A 9-year follow-up study
Authors:Nadon LMorin AJSGilbert WOlivier ESalmela-Aro K
Link:https://pubmed.ncbi.nlm.nih.gov/39645324/
DOI:10.1016/j.jsp.2024.101385
Publication:Journal of school psychology
Keywords:Academic transitionAchievementAchievement goalsDropoutPerson-centeredPiecewise growth mixture analysesSchool burnoutSelf-esteemSubstance useTrajectory profiles
PMID:39645324 Category: Date Added:2024-12-08
Dept Affiliation: PSYCHOLOGY
1 Substantive Methodological Synergy Research Laboratory, Department of Psychology, Concordia University, Montreal, Canada.
2 Substantive Methodological Synergy Research Laboratory, Department of Psychology, Concordia University, Montreal, Canada; Optentia Research Unit, North-West University, Vanderbijlpark, South Africa. Electronic address: alexandre.morin@concordia.ca.
3 Department of Health Sciences, Université du Québec à Rimouski, Rimouski, Canada.
4 Faculté des sciences de l'éducation, Département de psychopédagogie et d'andragogie, Université de Montréal, Montréal, Canada.
5 Department of Educational Sciences, University of Helsinki, Helsinki, Finland.

Description:

This study utilized piecewise linear growth mixture analysis to examine the developmental heterogeneity of school burnout among a sample of 513 (67.6% females) Finnish students as they transitioned from upper secondary school to higher education (ages 17-25 years). Encompassing five measurement points (two before the transition and three after), our results revealed four distinct burnout trajectory profiles, including (a) High and Decreasing (Profile 1), (b) Moderate and Decreasing (Profile 2), (c) Low and Increasing (Profile 3), and (d) Low and Stable (Profile 4). High initial levels of self-esteem and mastery-extrinsic goals served as personal resources and high-performance goals served as personal risk factors, making students more likely to belong to more (i.e., Profile 4) or less (e.g., Profile 1) adaptive profiles of burnout trajectories, respectively. Profile 4 displayed the lowest and most stable levels of burnout, thus protecting students from adverse outcomes like school dropout, underachievement, and substance use. Conversely, Profile 1 displayed the highest and least stable levels of burnout and was associated with higher risk of burnout, lower academic achievement, greater alcohol use and problems, and higher drug use relative to the other trajectory profiles. Together, these findings offer novel person-centered, longitudinal insight into the developmental heterogeneity of burnout across the transition to higher education and lend support for the self-equilibrium hypothesis in the context of school burnout. Importantly, our results underscore the importance of early intervention efforts aimed at increasing mastery goals and self-esteem to prevent burnout and its associated consequences.





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