Nurses’ Perceptions of Discrimination Towards People Living with Mental Illness in General Medical Hospital Settings
Bibliographic record
Abstract
The research aims were to explore registered nurses’ perceptions of discrimination towards people with mental illness admitted to general medical hospital settings and to better understand the conditions that gave rise to discrimination. An interpretive feminist phenomenological design guided by Merleau-Ponty (1962) philosophy of perception was chosen. Ten semi-structured interviews were conducted in one Canadian urban hospital with registered nurses who cared for people with mental illness and who were admitted to a general medical unit primarily for non-psychiatric health concerns. Interviews were analyzed using Interpretive Phenomenological Analysis. Five major themes emerged: (a) dichotomy of the mind and body, (b) discriminatory nursing practices, (c) tensions between ideals and realities, (d) othering, and (e) gendered perceptions. Discrimination occurred in situations where nurses struggled with balancing the demands of physical nursing care and mental health nursing care, where professional mental health nursing education and training was perceived as lacking, and where work time was insufficient to adequately address patients’ mental health concerns. Consequently, nurses expressed less confidence and feelings of competence in mental health nursing as compared to medical nursing, deferring to more specialized professionals for mental health care. Physical care was prioritized over mental health nursing care with nurses actively and/or passively avoiding, even dismissing psychosocial assessments and interventions. The study findings highlight the challenges of caring for people with mental illness in general medical hospital settings and RN perceptions towards discrimination. A holistic model of health care that emphasizes the importance and contributions of mind body connection to health could guide nursing practices to reduce discrimination towards people living with mental illness. Furthermore, increased mental health training in the workplace and more supportive resources could help foster a non-discriminatory work environment.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".