Psychosocial risk factors in development of low back pain in nurses working in intensive care unit of Clinical center of Montenegro
Bibliographic record
Abstract
Introduction. Low back pain is common in adult population, especially in nurses working in the intensive care units. In our country, the subject has not been investigated so far. The aim of the paper is to examine the frequency of low back pain and its connection to psychosocial characteristics. Methods. The questionnaire consisting of general demographic data, questions concerning low back pain, the Beck Inventory of Depression, as well as of the Quebec Back Pain Disability Scale, was created. The sample consisted of 50 nurses working in different areas of intensive care unit in the Clinical Center of Montenegro. Results. The incidence of low back pain (82%) was in accordance with the data collected all around the world, while the incidence of severe low back pain was significantly higher (46%). There was a statistically significant correlation between low back pain measured by the Quebec Back Pain Disability Scale and age and length of service in the intensive care unit. The average results on the Quebec Back Pain Disability Scale were significantly higher in respondents aged ≥40 years compared with the younger groups. Nurses whose length of service was ≥20 years had higher scores on the Quebec Back Pain Disability Scale than those whose length of service was ≤ 5 years. There was also a significant correlation between the score on the Quebec Back Pain Disability Scale and the Beck Inventory of Depression (0.44). Conclusion. It was considered that the lack of medical equipment in the intensive care units was one of the causes of low back pain. Furthermore, insufficient amount of knowledge concerning the importance of protective position use while working with patients reduced their use, which in turn influenced the incidence and severity of low back pain. These two factors had cumulative effect and were observed more frequently in the older respondents, i.e. in those nurses whose length of service was ≥20 years.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".