A dual-process model of early career researchers’ well-being: Satisfaction and frustration of basic psychological needs as central mechanism

Abstract Early-career researchers are simultaneously subject to a work environment that offers academic freedom but also requires juggling teaching, research, and administration, which can be particularly challenging for this population. As such, higher education systems provide both resources that could foster well-being and demands that could enhance feelings of strain. To further understand these factors, we synthesize central tenets of job-demands-resources-models and self-determination theory into a dual-process model of early-career researchers’ well-being. We argue that the needs for autonomy, competence, and relatedness are central to psychological functioning in academia. Furthermore, we view need satisfaction as a key resource fostering job satisfaction and need frustration as a central demand contributing to work strain. We investigated these dual processes in a sample of 367 German early-career researchers. In doing so, we used bi-factor structural equation modeling to address shared and unique associations of the three needs with the investigated criteria simultaneously. The sampled early-career researchers reported high job satisfaction alongside moderate work strain. Need satisfaction was a stronger predictor for satisfaction with work tasks, while need frustration was more strongly tied to work strain. Our findings underscore the utility of self-determination theory in developing dual process models of well-being and highlight the relevance of such models for understanding the psychological functioning of academic staff.

Institutions

Publication Details

Journal
Higher Education
Published
2025-10-18
DOI
https://doi.org/10.1007/s10734-025-01520-1
Primary Topic
Motivation and Self-Concept in Sports
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A dual-process model of early career researchers’ well-being: Satisfaction and frustration of basic psychological needs as central mechanism

Higher Education
Motivation and Self-Concept in Sports
article

A dual-process model of early career researchers’ well-being: Satisfaction and frustration of basic psychological needs as central mechanism

article en

Abstract

Abstract Early-career researchers are simultaneously subject to a work environment that offers academic freedom but also requires juggling teaching, research, and administration, which can be particularly challenging for this population. As such, higher education systems provide both resources that could foster well-being and demands that could enhance feelings of strain. To further understand these factors, we synthesize central tenets of job-demands-resources-models and self-determination theory into a dual-process model of early-career researchers’ well-being. We argue that the needs for autonomy, competence, and relatedness are central to psychological functioning in academia. Furthermore, we view need satisfaction as a key resource fostering job satisfaction and need frustration as a central demand contributing to work strain. We investigated these dual processes in a sample of 367 German early-career researchers. In doing so, we used bi-factor structural equation modeling to address shared and unique associations of the three needs with the investigated criteria simultaneously. The sampled early-career researchers reported high job satisfaction alongside moderate work strain. Need satisfaction was a stronger predictor for satisfaction with work tasks, while need frustration was more strongly tied to work strain. Our findings underscore the utility of self-determination theory in developing dual process models of well-being and highlight the relevance of such models for understanding the psychological functioning of academic staff.

Higher Education
University of Mannheim (DE), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 40%
Motivation and Self-Concept in Sports
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.