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Personal, social and relational predictors of UK postgraduate researcher mental health problems

Published online by Cambridge University Press:  15 November 2021

Clio Berry*
Affiliation:
Brighton and Sussex Medical School, University of Sussex, UK
Jeremy E. Niven
Affiliation:
School of Life Sciences, University of Sussex, UK
Cassie M. Hazell
Affiliation:
School of Psychology, University of Westminster, UK
*
Correspondence: Clio Berry. Email: c.berry@bsms.ac.uk
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Abstract

Background

Emerging evidence demonstrates that postgraduate researchers have high rates of mental health problems. These problems are distressing, affect PhD studies, and have longer-term potential effects beyond the duration of the PhD. Yet large-scale studies of multiple risk and protective factors are rare.

Aims

We aimed to test the predictive validity of a comprehensive set of potential determinants of mental health symptoms (depression, anxiety and suicidality) among postgraduate researchers in the UK, including personal, study-related, and supervision characteristics.

Method

We used regression models applied to data obtained from a national online survey of UK postgraduate researchers (Understanding DOCtoral researcher mental health; U-DOC, 2018–2019) to test predictors of mental health symptoms.

Results

These models show that postgraduate researchers' mental health symptoms are predicted by demographic, occupational, psychological, social and supervisory relationship factors. Greater perfectionism, more impostor thoughts and reduced supervisory communion most strongly and consistently predict mental health symptoms.

Conclusions

Institutions training postgraduate researchers should focus interventions intended to improve depression, anxiety, suicidality, on self-beliefs and social connectedness. Moreover, supervisors should be provided with training that improves the degree of agency, and especially communion, in the relationships they form with postgraduate researchers.

Information

Type
Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists
Figure 0

Table 1 Sample demographic and occupational characteristics

Figure 1

Table 2 Continuous putative predictor characteristics and bivariate correlations

Figure 2

Table 3 t-Tests and ANOVAs of associations between categorical study variables and mental health symptom scores

Figure 3

Table 4 Hierarchical regression models predicting depression, anxiety and suicidality

Figure 4

Fig. 1 Effect sizes for multivariate predictors of depression, anxiety and suicidality. Markers represent standardised beta coefficients. Lines depict 95% confidence intervals for standardised beta coefficients. CIPS, Clance Impostor Phenomenon Scale; MGM, Multiple Group Memberships; SAPS-D, Short Almost Perfect Scale – Discrepancy; SAPS-S, Short Almost Perfect Scale – Standards; QSDI-A, Questionnaire on Supervisor–Doctoral Student Interaction- Agency dimensionXXX; QSDI-C, Questionnaire on Supervisor–Doctoral Student Interaction – Communion dimension; UCLA, University of California, Los Angeles Loneliness Scale.

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