Measurement equivalence of the self-care of chronic illness inventory across time: longitudinal structural equation models.

Background and Objectives The Self-Care of Chronic Illness Inventory (SC-CII) is a theoretically grounded instrument comprising three scales measuring self-care maintenance, monitoring and management behaviors in adults with chronic illnesses. Although its validity and reliability have been demonstr...

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Publicado en:Gerontologist Vol. 66; no. 7; pp. 1 - 11
Autores principales: Maria, Maddalena De, Iacono, Irene Dello, Ferro, Federico, Vellone, Ercole, Ausili, Davide, Riegel, Barbara, Barbaranelli, Claudio, Matarese, Maria
Formato: Artículo
Publicado: Oxford University Press / USA Jul2026
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Acceso en línea:Ver este registro en EBSCOhost
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          Maria, Maddalena De
          Iacono, Irene Dello
          Ferro, Federico
          Vellone, Ercole
          Ausili, Davide
          Riegel, Barbara
          Barbaranelli, Claudio
          Matarese, Maria
        affil:
          Department of Life Science, Health, and Health Professions, Link Campus University, Rome, Italy
          Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
          Department of Internal Medicine, Endocrine-Metabolic Sciences and Infectious Diseases, Policlinico Umberto I, Rome, Italy
          Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, ItalyDepartment of Nursing, Wroclaw Medical University, Wroclaw, Poland
          Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Monza, Italy
          Center for Home Care Policy & Research at VNS Health, Philadelphia, Pennsylvania, United StatesSchool of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, United States
          Department of Psychology, Sapienza University of Rome, Rome, Italy, Rome, Italy
          School of Nursing, Campus Bio-Medico of Rome University, Rome, Italy
      su:
        Health self-care
        Self-management (Psychology)
        Interviewing
        Chronic diseases
        Psychometrics
        Health behavior
        Psychology of caregivers
        Diabetes
        Research funding
        Research evaluation
        Statistical sampling
        Scientific observation
        Probability theory
        Structural equation modeling
        Heart failure
        Descriptive statistics
        Chi-squared test
        Longitudinal method
        Obstructive lung diseases
        Research
        Research methodology
        Factor analysis
        Data analysis software
      sug:
        subj:
          Health self-care
          Self-management (Psychology)
          Interviewing
          Chronic diseases
          Psychometrics
          Health behavior
          Psychology of caregivers
          Diabetes
          Marketing Research and Public Opinion Polling
          Research funding
          Research evaluation
          Statistical sampling
          Scientific observation
          Probability theory
          Structural equation modeling
          Heart failure
          Descriptive statistics
          Chi-squared test
          Longitudinal method
          Obstructive lung diseases
          Research
          Research methodology
          Factor analysis
          Data analysis software
      keyword:
        Chronic conditions
        chronic disease
        Comorbidity
        copyrightHolder:The Gerontological Society of America
        copyrightYear:2026
        https://dx.doi.org/10.1093/geront/gnag067
        inLanguage:en
        Measurement equivalence
        publisher:Oxford University Press
        sameAs:https://pubmed.ncbi.nlm.nih.gov/42057263/
        self care
        Self-care
        Structural equation models
        Chronic conditions
        chronic disease
        Comorbidity
        copyrightHolder:The Gerontological Society of America
        copyrightYear:2026
        https://dx.doi.org/10.1093/geront/gnag067
        inLanguage:en
        Measurement equivalence
        publisher:Oxford University Press
        sameAs:https://pubmed.ncbi.nlm.nih.gov/42057263/
        self care
        Self-care
        Structural equation models
      ab: Background and Objectives The Self-Care of Chronic Illness Inventory (SC-CII) is a theoretically grounded instrument comprising three scales measuring self-care maintenance, monitoring and management behaviors in adults with chronic illnesses. Although its validity and reliability have been demonstrated in cross-sectional studies, the stability of its psychometric properties over time has not been examined. This study aimed to test the longitudinal measurement equivalence of the three SC-CII Scales. Research Design and Methods Longitudinal measurement equivalence was assessed over a 12-month period using a Confirmatory Factor Analysis (CFA) approach. Patients aged 65 or older with multiple chronic conditions (MCCs) were enrolled. Four increasingly restrictive level of invariance were tested: configural, metric, scalar and strict invariance at the first and second-order level. Results Participants (N  = 630) had a mean age of 77 years, were mostly female. For the Self-Care Maintenance scale, full metric invariance and partial scalar and strict invariance were achieved at both first- and second-order levels. For the Self-Care Monitoring scale, full metric and scalar invariance, and partial strict invariance were established. For the Self-Care Management scale, full metric, full scalar (first-order), partial scalar (second-order) and partial strict (first- and second-order) were achieved. Discussion and Implications The SC-CII proved to be longitudinally stable, confirming its suitability for repeated assessments of self-care. The SC-CII can be confidently used by nurses to monitor self-care behaviors and evaluate changes during the disease trajectory, supporting the development of tailored interventions. This study demonstrated the SCCII's temporal equivalence, strengthening its use in clinical and research settings.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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