Impact of an educational intervention in enhancing nurses’ knowledge towards psychiatric patients’ ethical and legal rights
Bibliographic record
Abstract
Background and objective: The management of psychiatric patients and the law of ethic already exists. Therefore, nursing ethics are necessary for psychiatric nurses since they are involved in providing services that impact human life. The aim was to evaluate the effectiveness of an educational program in enhancing nurses’ knowledge regarding their responsibilities toward psychiatric patients’ ethical and legal rights.Methods: A quasi experimental study design with one group pre/post was used with 30 nurses recruited conveniently from Psychiatric Hospital Jeddah, Saudi Arabia. Nurses were questioned using 5 short answer questions, 11 multiple choice questions and the Structured Knowledge Questionnaire developed by Kumar, Mehta, and Kalra (2011).Results: A total of 30 nurses were recruited, with their age ranging between 25-54 years old; the majority (59.4%) were married, while 78.1% neither have psychiatric nursing experiences nor did they study ethics during their undergraduate years. The total mean score of pre-knowledge questionnaire was 27.2 ± 2.97 compared to 30.2 ± 2.40 in post assessment, with a significant difference between pre and post assessment. On the other hand, the total mean percentage of nurse’s theoretical background in pre assessment was 25% compared with 29% with no significant difference between pre and post interventions.Conclusions: Nurses’ knowledge was inadequate regarding ethical and legal rights. The current study findings evidenced the effectiveness of the educational intervention in changing the nurses’ knowledge significantly. Therefore, it is a necessity to ensure that nurses working in psychiatric hospitals have the necessary expertise regarding the legal and ethical issues involved with caring for psychiatric patients, to decrease the effects of malpractices and negligence in psychiatric nursing practice.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".