Assessing a measure for Quality of Life in patients with severe Alopecia Areata: a multicentric Italian study

• Main Authors: Giacomo Caldarola (Author), Giulia Raimondi (Author), Tonia Samela (Author), Lorenzo Pinto (Author), Francesca Pampaloni (Author), Michela Valeria Rita Starace (Author), Laura Diluvio (Author), Federica Dall'Oglio (Author), Emanuele Vagnozzi (Author), Maria Beatrice de Felici del Giudice (Author), Riccardo Balestri (Author), Francesca Ambrogio (Author), Giampiero Girolomoni (Author), Silvia Francesca Riva (Author), Francesco Moro (Author), Laura Atzori (Author), Giuseppe Gallo (Author), Simone Ribero (Author), Oriana Simonetti (Author), Stefania Barruscotti (Author), Valeria Boccaletti (Author), Angelo Valerio Marzano (Author), Luca Bianchi (Author), Giuseppe Micali (Author), Bianca Maria Piraccini (Author), Maria Concetta Fargnoli (Author), Damiano Abeni (Author), Ketty Peris (Author)
• Format: Book
• Published: Frontiers Media S.A., 2024-08-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2565; 10.3389/fpubh.2024.1415334
• Keywords: Alopecia Areata (AA); Quality of Life; Bayesian confirmatory factor analysis; psychodermatology; patients reported outcomes; Public aspects of medicine; RA1-1270
• Source: Frontiers in Public Health, Vol 12 (2024)

ObjectiveThe prevalence of anxiety and depression in patients diagnosed with Alopecia Areata (AA) is very high and this significant burden of psychological symptoms threatens the Health-Related Quality of Life (HRQoL) of affected patients. Indeed, AA often does not produce significant physical symptoms, but it nonetheless disrupts many areas of mental health. Clinical assessment of disease severity may not reliably predict patient's HRQoL, nor may it predict the patient's perception of illness. For this reason, considerable effort has been made to apply and develop measures that consider patient's perception and assess the HRQoL of individuals affected by AA. The aim of this multicentric study was to provide the Italian version of the Skindex-16AA and to evaluate its psychometric properties in a clinical sample of consecutive patients with moderate-to-severe AA.MethodsThis is a longitudinal, multicenter, observational study. Patients returned for follow-up visits at 4-, 12-, and 24-weeks. The analyses of the current work aimed to confirm the factorial structure of the Skindex-16AA. In the case of non-fit, an alternative structure for the model was proposed, using an Exploratory Graph Analysis and the Bayesian approach.ResultsThe sample was composed of 106 patients with AA. Alopecia Universalis was the most frequently diagnosed type of alopecia at all time points. The analyses on the Skindex-16AA revealed that a two-factor structure with eight items fit the data best (Bayesian Posterior Predictive Checking using 95% Confidence Interval for the Difference Between the Observed and the Replicated Chi-Square values = −6.246/56.395, Posterior Predictive P-value = 0.06), and reported satisfactory psychometric properties (i.e., internal consistency and convergent validity).ConclusionThe Skindex-8AA demonstrated optimal psychometric properties (i.e., convergent and construct validity, and test-retest reliability) measured in a sample of patients with AA, that may suggest that it is an appropriate tool to measure the HRQoL in AA patients. However, further studies are needed in order to confirm and tested other psychometric features of this tool.