Using the K-Means Node Clustering Method and ROC Curve Analysis to Define Cut-Off Scores for the Caregiving System Scale
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View abstract on PubMed
Summary
This summary is machine-generated.Researchers established cut-off scores for the Caregiving System Scale (CSS) using clustering and ROC analysis. This method identifies distinct caregiving profiles and their links to attachment styles, even without gold-standard measures.
Area Of Science
- Psychology
- Gerontology
- Sociology
Background
- The Caregiving System Scale (CSS) is a tool used to assess caregiving dynamics.
- Establishing reliable cut-off scores is crucial for accurately interpreting CSS subscale results.
- Previous research has lacked a standardized method for deriving these cut-off scores, especially when gold-standard measures are unavailable.
Purpose Of The Study
- To establish validated cut-off scores for the subscales of the Caregiving System Scale (CSS).
- To identify distinct caregiving profiles within Italian adult populations.
- To explore the relationship between identified caregiving profiles and attachment orientations.
Main Methods
- Utilized K-means node clustering and Receiver Operating Characteristic (ROC) curve analyses on a sample of 682 Italian adults.
- Calculated cut-off scores to classify participants into identified caregiving profiles.
- Validated findings using a second sample (N=227) that completed the CSS and the Attachment Style Questionnaire.
Main Results
- Four distinct caregiving profiles were identified using the CSS.
- Validated cut-off scores were successfully calculated for classifying individuals into these profiles.
- Significant associations were found between the identified CSS profiles and various attachment orientations.
Conclusions
- The study successfully established cut-off scores for the CSS, enabling more precise classification of caregiving styles.
- The findings confirm the existence of unique caregiving profiles and their meaningful connection to attachment styles.
- This research provides a practical methodology for determining scale cut-off scores in the absence of traditional gold-standard measures, enhancing the utility of the CSS.
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