Who exits? A mixed methods analysis of determinants of turnover intention among Hungarian social workers: Ki hagyja el a szociális szférát? A munkahely elhagyásához vezető tényezők vegyes módszertanon alapuló elemzése a magyar szociális munkások körében

High turnover rates in the social sector pose a significant problem across Europe, including in Hungary. Therefore, understanding the determinants of turnover intention in this sector is pivotal. This mixed-methods study aims to identify predictors of turnover intention among social workers in Hunga...

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Published in:European Journal of Social Work Vol. 28; no. 6; pp. 1331 - 1346
Main Authors: Győri, Ágnes, Perpék, Éva
Format: Article
Published: Taylor & Francis Ltd Nov2025
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Nov2025
      vid: 28
      iid: 6
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      pub: Taylor & Francis Ltd
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        10.1080/13691457.2025.2461619
      ppf: 1331
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        atl: Who exits? A mixed methods analysis of determinants of turnover intention among Hungarian social workers: Ki hagyja el a szociális szférát? A munkahely elhagyásához vezető tényezők vegyes módszertanon alapuló elemzése a magyar szociális munkások körében
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        au:
          Győri, Ágnes
          Perpék, Éva
        affil:
          Institute for Sociology, HUN-REN Centre for Social Sciences, Budapest, Hungary
          Child Opportunities Research Group Budapest, HUN-REN Centre for Social Sciences, Budapest, Hungary
      su:
        Europe
        Hungary
        Social media
        Cross-sectional method
        Social workers
        Labor turnover
        Work environment
        Content analysis
        Social worker attitudes
        Communities
        Social case work
        Reward (Psychology)
        Attention
        Social support
        Commitment (Psychology)
        Pearson correlation (Statistics)
        Research funding
        Multivariate analysis
        Descriptive statistics
        Thematic analysis
        Intention
        Research methodology
        Medical coding
        Research
        Data analysis software
        Confidence intervals
        Hungarians
        Regression analysis
      sug:
        subj:
          Social media
          Cross-sectional method
          Social workers
          Labor turnover
          Work environment
          Content analysis
          Social worker attitudes
          Communities
          Social case work
          Reward (Psychology)
          Attention
          Social support
          Commitment (Psychology)
          Europe
          Hungary
          Other Individual and Family Services
          Pearson correlation (Statistics)
          Research funding
          Multivariate analysis
          Descriptive statistics
          Thematic analysis
          Intention
          Research methodology
          Medical coding
          Research
          Data analysis software
          Confidence intervals
          Hungarians
          Regression analysis
      keyword:
        mix-methods
        social workers
        Turnover intention
        mix-methods
        social workers
        Turnover intention
      ab: High turnover rates in the social sector pose a significant problem across Europe, including in Hungary. Therefore, understanding the determinants of turnover intention in this sector is pivotal. This mixed-methods study aims to identify predictors of turnover intention among social workers in Hungary. A multistage sampling process was used to collect quantitative data through computer-assisted personal interviews, which were analysed using linear regression models. Qualitative data were gathered from social workers' comments in online professional communities on social media platforms. Thematic coding was applied to analyse the qualitative data. Descriptive results indicated that 30% of the 664 respondents had the intention to leave their job. Regression analysis revealed that the variables of greatest importance for mobility intention were the inadequate supervisory support, insufficient workplace infrastructure and atmosphere, and inadequate material rewards. The qualitative analysis of online social media discourses uncovered various issues and tensions, both within and outside the sector, driving turnover and career change decisions, such as inadequate representation and recruitment challenges, retention and professional commitment. Both quantitative and qualitative analyses draw attention to the crisis in the Hungarian social sector and highlight the need to improve working conditions for social workers and enhance their recognition to prevent turnover and ensure the effective recruitment of new professionals.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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