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To identify distinct sleep quality patterns among patients with heart failure (HF) using a person-centred approach and explore demographic and clinical predictors of these patterns.
Secondary analysis of baseline cross-sectional data from the MOTIVATE-HF (MOTIVATional intErviewing to improve self-care in Heart Failure patients) randomised controlled trial. Latent class analysis (LCA) was applied to Pittsburgh Sleep Quality Index (PSQI) component scores to identify distinct subgroups of patients. Demographic, clinical and psychological variables were examined as potential predictors of cluster membership.
Three healthcare settings in Italy: hospital, outpatient and community-based care.
510 adult patients diagnosed with HF (New York Heart Association (NYHA) class II–IV) with poor self-care were included. Patients with severe cognitive impairment or recent myocardial infarction were excluded.
Primary outcome: Sleep quality, measured using the PSQI, analysed through LCA to identify sleep disturbance clusters. Secondary outcomes included demographic and clinical characteristics predicting cluster membership.
The mean age was 72.4 years (SD=12.3), with most participants married or partnered (62%) and retired or unemployed (83.9%). Mild comorbidities were present in 53.3% of the sample (mean Charlson Comorbidity Index (CCI)=2.91, SD=1.98), and 61.4% were classified in NYHA class II. Three sleep quality clusters emerged: (1) adequate sleep duration but disturbed sleep and daytime dysfunction (46.1%); (2) severe sleep problems with low use of sleeping medications (25.3%); and (3) minor sleep problems with mild disturbances (28.6%). Patients in Cluster 1 were older (mean age=73.3 years), had lower physical and mental quality of life (Short-Form 12 Physical Component Summary=33.66; Mental Component Summary=42.65), and higher anxiety (Hospital Anxiety and Depression Scale-A=8.82). Patients in Cluster 2 had more severe comorbidities (CCI=3.55), poorer cognitive function (Montreal Cognitive Assessment (MoCA)=21.5) and lower ejection fraction (mean=40%). Patients in Cluster 3 were younger (mean age=68.2 years), had better cardiac function (ejection fraction=46.6%), better cognitive status (MoCA=24.5) and the highest quality of life (Kansas City Cardiomyopathy Questionnaire=63.1).
Patients with HF exhibit heterogeneous sleep quality patterns with specific clinical and psychological profiles. These findings highlight the need for personalised interventions, systematic sleep assessments and the integration of cardiac rehabilitation strategies into standard HF care.
To describe and compare generic and disease-specific self-care measures in patients with multiple chronic conditions (MCCs) in the three dimensions of self-care maintenance, monitoring, and management.
Multicentre cross-sectional study.
Patients aged 65 and over with MCCs. We used Self-Care of Chronic Illness Inventory to measure generic self-care, Self-care of Diabetes Inventory to measure self-care in diabetes mellitus, Self-Care of Heart Failure (HF) Index to measure self-care in HF, and Self-Care of Chronic Obstructive Pulmonary Disease Inventory to measure self-care in chronic lung diseases.
We recruited 896 patients. Multimorbid patients with diabetes had lower scores on the self-care maintenance scale, and diabetic patients in insulin treatment on the generic management scale than on the disease-specific instrument. Multimorbid patients with HF or chronic lung diseases scored higher on generic self-care maintenance and monitoring scales than disease-specific ones. There was a partial consistency between the generic and disease-specific self-care maintenance and management. Inadequate behaviours were recorded in disease-specific self-care monitoring rather than generic ones.
Older patients affected by MCCs scored differently in the generic and disease-specific instruments, showing inadequate self-care in some of the three self-care dimensions.
The choice between generic and disease-specific instruments to use in clinical practice and research should be made considering the specific aims, settings, patients characteristics, and knowledge of the different performance of the instruments by users.
No study has described and compared generic and specific self-care measures in patients affected by MCCs. Knowing these differences can help nurses choose the most suitable measure for their aims, context, and patients and plan generic and disease-specific self-care educational interventions for those behaviours in which MCCs patients perform poorly.
Patients were informed about the study, provided informed consent, and answered questionnaires through interviews.
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