Comparison of Two Analytical Approaches to Dyadic Illness Management Among Patient-Caregiver Dyads in Type 2 Diabetes.
Diletta Fabrizi, Michela Luciani, Maria Grazia Valsecchi and 2 others
PMID 41649939WHAT IT FOUND
In 251 diabetes patient-caregiver pairs, simple raw scores and model-based estimates found the same three patterns: low joint engagement, high joint engagement, and mismatch with patients reporting more than caregivers.
Key findings
01The mixed-effects two-stage approach and the simpler one-stage raw-score approach clustered the same dyads into the same classes, with unchanged fit indices.
02Three dyadic patterns were identified: 14% of dyads had low engagement with small mismatch, 61% had high engagement with small mismatch, and 25% had intermediate engagement with large mismatch and patients reporting higher scores than caregivers.
03The two-stage estimates were shrunk toward the overall mean, so within-class self-care scores looked less different than the raw observed scores.
STILL TO COME
How it was doneWhat they foundWhat it means for RNs
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What it does not show
This is a methodological comparison using existing questionnaire data from one cross-sectional diabetes sample, not a trial of dyadic nursing care or an intervention. The latent classes were exploratory, not tested for stability or replicability, so they should not be treated as definitive patient subgroups. The sample was limited to 251 dyads from four outpatient clinics in Northern Italy, and no confidence intervals were reported for class means. The study had complete data, so the possible advantage of mixed-effects models for missing data was not tested. The two-stage estimates were shrunk toward the overall mean, which reduced the apparent differences between dyads and classes.
The easy way to misread this
Do not conclude that the three classes are proven subgroups or that using them improves diabetes care. The study compared two ways of analyzing questionnaire scores and did not test an intervention or patient outcomes.