Hemodialysis patients constitute a vulnerable population. Their health needs are considerable and they often present psychological symptoms such as depression and anxiety. Empirical studies have demonstrated the efficacy of positive psychology interventions to enhance the well-being of patients and alleviate their depressive symptoms. One such intervention consists in identifying and mobilizing patient resources to activate their recovery. An intervention of the sort was implemented in Switzerland with hemodialysis nurses using AERES, a novel self-assessment instrument. AERES covers 31 domains under three dimensions: personal characteristics/qualities, hobbies/passions, and social/environmental resources. The aim of this qualitative study was to explore hemodialysis nurse perceptions of the use of this instrument. Sixteen hemodialysis nurses were recruited in six hospitals in French-speaking Switzerland and interviewed after delivering the intervention. A consensual qualitative research method was used to analyze the data. Results showed that the resources instrument was easy to administer and beneficial to patients and health professionals. Patient wellbeing became the top priority for the nurses and new interventions centered on patient resources were undertaken. Quality of patient care was improved. Nurses perceived this positive psychology instrument as a means of creating a positive relationship with patients and supporting them emotionally. Assessing the resources of this vulnerable population can provide health professionals with a powerful tool to understand patient intact resources, which can be used to alleviate symptoms and foster wellbeing.
Keyphrases
- end stage renal disease
- healthcare
- chronic kidney disease
- peritoneal dialysis
- mental health
- depressive symptoms
- patient reported outcomes
- ejection fraction
- randomized controlled trial
- newly diagnosed
- prognostic factors
- physical activity
- primary care
- palliative care
- public health
- systematic review
- risk assessment
- big data
- climate change
- pain management
- human health
- sleep quality
- social support
- deep learning
- clinical evaluation