Substance Use in Registered Nurses: “I Heard About a Nurse Who . . .”
Bibliographic record
Abstract
BACKGROUND: Estimates of substance use (SU) in nurses is on par with that of the general population: between 6% and 8%. However, collecting sensitive information such as SU is difficult based on social desirability and fears of disclosure. AIMS: Part of a larger study surrounding nurses’ self-reports of SU ( n = 1,478), the purpose was to explore open-ended responses of nurses ( n = 373) who were invited to “Please add any additional comments related to substance or alcohol use that you have experienced or witnessed in registered nurses.” METHOD: This qualitative study employed a content analysis of 373 nurses’ open-ended responses collected via an online survey. RESULTS: The majority of nurses ( n = 250) forwarded comments that described SU in other nurses, while 24 comments reflected the nurse’s past or current SU. Content analysis revealed the following four themes: (1) differing social network proximity to SU; (2) individual process: vulnerability to adaptive/maladaptive coping resulting in positive and negative outcomes; (3) bedside, system, and organizational spaces and effects; and (4) there are no SU issues in nursing. CONCLUSIONS: Although direct reports of SU constitute approximately one quarter of the comments forwarded, nurses reported peers’ struggles with SU, including observing nurses working in patient care while impaired and the use of substances to cope with work and personal stressors. Individual factors and system-related failures appear to be contributors to SU in nurses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".