[Experiences when handling sleep medicines: Group discussions with nursing students about benzodiazepines and Z-drugs].
Stephanie HeinemannAnne-Kathrin Kasper-DeußenVivien WeißGabriella MarxWolfgang HimmelPublished in: Pflege (2021)
Experiences when handling sleep medicines: Group discussions with nursing students about benzodiazepines and Z-drugs Abstract. Background and aims: Helping patients who have difficulties falling or staying asleep is one of the challenges of hospital care. The goal of this study was to explore how nursing students experience patients' sleeping problems as well as the usage of sleep-inducing drugs, especially benzodiazepines and Z-drugs in the hospital setting. Methods: In four focus group discussions, we collected data exploring the experiences of nursing students with regards to sleeping problems and sleep-inducing drugs. The transcripts of the discussion were analysed, using documentary method. Results were finally summarized to main categories, using qualitative content analysis. Results: Students experience a generous distribution of sleep-inducing drugs, which are considered as the best possible solution for sleeping problems - in spite of weak evidence. Non-drug alternatives are seldom taught, are often unavailable on the ward and their use is rarely trained. Pharmacological knowledge is too shallow and / or the transfer of theoretical knowledge to practical action is unsuccessful. Sleep and sleeping problems, e. g. in contrast to pain management, are not a topic of priority in the hospital setting. Conclusions: More knowledge and greater sensibility about sleeping problems is needed. For example, nurses' training should incorporate knowledge about medications and non-drug alternatives and how to apply them in critical situations. Doctors and nurses should offer nursing students good role models in these situations.
Keyphrases
- nursing students
- mental health
- healthcare
- pain management
- sleep quality
- end stage renal disease
- physical activity
- newly diagnosed
- ejection fraction
- chronic kidney disease
- adverse drug
- peritoneal dialysis
- drug induced
- magnetic resonance
- electronic health record
- machine learning
- chronic pain
- quality improvement
- big data
- palliative care
- deep learning
- patient reported