Evidence map›Paper›PMID 39457787›Full record

ArticleBehavioral sciences (Basel, Switzerland)2024

The Evaluation of a Mindful Coaching Programme to Reduce Burnout in Social Workers in Hong Kong-A Pilot Study.

Camille K Y Chan, Paul W C Wong

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Camille K Y ChanDepartment of Social Science and Social Administration, The University of Hong Kong, Hong Kong SAR, China.ORCID 0000-0003-2971-7542
Paul W C WongDepartment of Social Science and Social Administration, The University of Hong Kong, Hong Kong SAR, China.ORCID 0000-0003-3388-6285

Funding

Dreams Possible Limited N/A
6 · The paper itself

Abstract

Social work professionals experience high levels of burnout, emotional exhaustion, and secondary traumatic stress (STS). This paper reports the findings of a pilot test of the Burn-Not-Out programme that aimed to reduce social workers' burnout, STS, and depressive symptoms and to enhance compassion satisfaction (CS), using the mixed methods evaluation methodology. Hong Kong social workers participated in the programme between December 2023 and March 2024 and completed pre- and post-programme self-administered online surveys including the Professional Quality of Life (ProQOL) and Patient Health Questionnaire (PHQ-9), healthy alongside self-constructed questions on boundary setting, and post-programme online focus group discussions. The results from 94 paired surveys revealed a concerning mental health profile of the participants at baseline, and, after programme participation, there were statistically significant reductions in burnout (Cohen's d = 0.73) and depressive symptoms (Cohen's d = 0.57) among the participants. The participants in the focus group reported that they valued the programme's emphasis on healthy boundaries, one-on-one coaching, and the sense of being cared for, which contributed to their mental health improvement. This study highlights the urgent need for more research on the role of psychological capital in social workers' resilience and calls for more empirical systemic interventions that can promote social workers' mental wellness, with sustainable policies that ensure manageable workloads and adequate workplace support.

Indexed as

burnoutcompassion fatiguecompassion satisfactiondepressionhealthy boundarieshelping professionalsProQOLsecondary traumatic stresssocial workers

Identifiers

PMID39457787
PMCPMC11505587

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Registered trials

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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.