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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».