Unsupervised Machine Learning–Based Identification of Psychosomatic Susceptibility Profiles Using Big Five Personality Traits, Alexithymia, Coping Flexibility, Sleep Disturbance, and Somatic Symptom Severity
Keywords:
psychosomatic susceptibility, unsupervised machine learning, ig Five personality traits, alexithymia, coping flexibility, sleep disturbance, somatic symptomsAbstract
This study aimed to identify psychosomatic susceptibility profiles among adults in Ireland using unsupervised machine learning based on Big Five personality traits, alexithymia, coping flexibility, sleep disturbance, and somatic symptom severity. A cross-sectional, person-centered study included 713 adults residing in the Republic of Ireland. Participants completed the Big Five Inventory–2 Short Form, Toronto Alexithymia Scale, Coping Flexibility Scale, Pittsburgh Sleep Quality Index, and Patient Health Questionnaire–15. Standardized scores were analyzed using k-means clustering, partitioning around medoids, Gaussian mixture modeling, and hierarchical clustering. Solutions containing two to six profiles were compared using silhouette width, the Calinski–Harabasz index, the Davies–Bouldin index, the gap statistic, bootstrap Jaccard coefficients, and holdout adjusted Rand indices. Profile differences were examined using omnibus tests, adjusted pairwise comparisons, and effect sizes. A four-profile solution provided the strongest and most stable fit, comprising resilient–low susceptibility, emotionally constrained, sleep-disturbed negative affect, and multidimensional high susceptibility profiles. Significant between-profile differences were found for all clustering indicators (all p < .001). The largest effects emerged for somatic symptom severity, F(3, 709) = 344.79, partial η² = .593; negative emotionality, F(3, 709) = 318.57, partial η² = .574; sleep disturbance, F(3, 709) = 301.66, partial η² = .561; alexithymia, F(3, 709) = 283.12, partial η² = .545; and coping flexibility, F(3, 709) = 271.40, partial η² = .535. Profile membership was significantly associated with chronic physical illness, diagnosed mental health conditions, and psychotropic medication use. Psychosomatic susceptibility is best understood as a heterogeneous configuration of personality, emotional processing, coping adaptability, sleep impairment, and somatic burden, supporting profile-based assessment and targeted interventions.
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