Investigating decision-regret and distress among psychologists impacted by client suicide : a thesis submitted in partial fulfilment of the requirement for the degree of Doctor of Clinical Psychology at Massey University, Auckland, New Zealand
Bibliographic record
Abstract
Background: Mental health professionals are tasked with making critical decisions about their client’s care. It is thus unsurprising that client suicide has been described as a distressing experience among professionals. Significant emotional, cognitive, and professional impacts have been reported which include psychological distress, shock, self-blame, guilt, and absenteeism. Due to the variability of impacts reported across the literature, a novel theoretical approach to understanding the impact of client suicide on psychologists was implemented using two decision-regret theories. \n \nMethods: A quantitative cross-sectional survey design was used to measure the impact of client suicide on psychologists. By using structural equation modelling, the following factors were investigated: regret, distress, self-blame, supervisory support, and beliefs about suicide preventability. Additionally, two regret theories were tested which included the following variables as predictors on regret: decision-regret, decision justification, decision-process quality, and intention-behaviour consistency. Control models were tested to control for carefully selected confounding variables, and a supplementary qualitative analysis was included investigating the factors related to coping following client suicide. A sample of 248 psychologists from New Zealand, Australia, Canada, United Kingdom, and the United States of America was included in this study. \n \nResults: The results identified statistically significant relationships between the following predictor variables on regret: decision-justification, decision-process quality, and beliefs about suicide preventability. Additionally, a significant moderate positive relationship was evidenced between regret (as the predictor) and distress. The qualitative analysis indicated that high-quality supervisory support and understanding the predictive limitations in assessing suicide risk were important factors in coping with client suicide. Additionally, factors identified that were related to poor coping included judgement, counter-factual thinking and blame, and confidentiality limitations preventing seeking support from loved ones. \n \nConclusions: The present study demonstrates support for two factors which appear to influence regret levels: decision-justification and decision-process quality. Additionally, this study also evidenced regret as a significant moderate predictor of distress, highlighting the role that regret may play in influencing a range of affective states among psychologists following client suicide. The findings of the present study highlight the need for the development of robust support structures that acknowledge the impact of client suicide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".