The benefits of mindfulness in mental healthcare professionals
Bibliographic record
Abstract
<ns3:p> <ns3:bold>Background:</ns3:bold> Burnout is a widely reported syndrome consisting of emotional exhaustion, depersonalization, and a lowered sense of accomplishment. Mindfulness practices have been shown to be useful in lowering distress and burnout in clinical and non-clinical cohorts. Our aim was to explore the potential personal and occupational benefits of a structured mindfulness intervention on a cohort of mental health professionals. A mixed-methods approach was utilised in order to enhance the exploratory power of the study. <ns3:bold>Methods</ns3:bold> : We conducted a pilot study involving healthcare practitioners employed at a community outpatient mental health clinic. As a pilot, we relied on a single group and implemented a quasi-experimental, simultaneous mixed methods design by incorporating both quantitative pre- and post- testing alongside written qualitative post-test responses. <ns3:bold>Results</ns3:bold> : Analysis of the data demonstrated a significant difference between overall mindfulness when comparing post-test (mean=140.8, standard deviation=18.9) with pre-test data (mean=128.3, standard deviation=28.6). Participants also showed a statistically significant difference in three of the subscales: observation, describing, and non-reactivity. A moderate effect size was seen for each of the above differences. Analysis of the qualitative data revealed a range of potential themes which may be used to explain the differences exhibited across participants’ personal and professional lives, which can be grouped into two thematic overarching groups: emotional reactivity and listening/communicating. <ns3:bold>Conclusions</ns3:bold> : The results of this pilot study indicate that a structured, six-week mindfulness program has the potential to benefit clinicians, personally by reducing emotional reactivity and professionally by promoting deep listening and communication. </ns3:p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".