Validation of the Skindex-17 quality of life assessment instrument for a Brazilian population

Abstract

Background Health-related quality of life assesses how diseases affect the daily life of people; there are several generic instruments for this assessment in dermatology. Skindex was created in 1996; it is a multidimensional instrument, aiming to encompass some psychological and social aspects not yet addressed by other questionnaires. Among its versions (Skindex-29, 16, and 17), Skindex-17 had not been validated in Brazil. Objectives To validate Skindex-17 for use in Brazilians with dermatological diseases. Methods This was a methodological, cross-sectional, and prospective study of 217 patients attended at the Dermatology Service Outpatient Clinic, Faculdade de Medicina de Botucatu - Universidade Estadual Paulista (Botucatu, SP, Brazil), from December 2017 to September 2019. The following were evaluated: content validity, filling time, internal consistency, dimensional structure, concurrent validity (DLQI), temporal stability, and responsiveness. Results The sample consisted of 71% women, mean age (SD) of 45 (16) years; phototypes II−IV accounted for 95% of the cases. Cronbach's alpha coefficients were 0.82 and 0.93 for the symptoms and psychosocial conditions, respectively. A high correlation was observed with the DLQI score: symptoms (rho = 0.69) and psychosocial conditions (rho = 0.75). The instrument's two-dimensional structure was confirmed through confirmatory factor analysis. Temporal stability (ICC > 0.9) and score responsiveness (p ≤ 0.02) were verified. The instrument was shown to be feasible in clinical practice due to the content validation performed by professionals and patients, as well as the low time spent completing it (< 5 min). Study limitations Single-center study, with patients exclusively from the public healthcare system. Conclusions Skindex-17 was shown to be a valid and consistent instrument for assessing quality of life among patients with dermatological diseases, in Brazil. Its two-dimensional structure was confirmed.

Psychometric Comparison of the Performance of Quality of Life Assessment Instruments in Dermatology—the DLQI, Skindex-16, and Skindex-17—in a Brazilian Population.

“…(4) There are ve possible answers for each item (very much, a lot, a little, not at all, and not relevant); the score for each item ranges from 0 to 3. (2-5) Conventionally, DLQI scores are interpreted based on the algebraic sum of the indexes of the 10 items evaluated: without compromising quality of life (0-1), with mild (2-5), moderate (6-10), severe (11)(12)(13)(14)(15)(16)(17)(18)(19)(20), or very severe (21)(22)(23)(24)(25)(26)(27)(28)(29)(30) impairment. (6)…”

“…The symptom scale result is dichotomized; there are ve response options (never, rarely, sometimes, often, and all the time), and scores greater than or equal to ve indicate that many symptoms are present. (18,19) The development of the Sk-16 and Sk-17 instruments differed, and the two instruments vary in terms of structure, dimensionality, and scores. Despite coincident items, the overall designs of the instruments are different.…”

Analysis of data with dependent measures in clinical and experimental studies

“…[27][28][29][30][31] Along the same lines, analytical designs exist that demand simultaneous study of different variables from the same subject, creating a structure of dependence within the individual, as is the case of quality of life scales that assess more than one dimension (for example, the Venous Insufficiency Epidemiological and Economic Study -Quality of Life/Symptom [VEINES-QoL/Sym], Skindex-17), different sets of symptoms, or different serum markers secreted after a single stimulus. [32][33][34] Quantitative analysis of groups using simultaneous analysis of more than one dependent variable demands the use of methods known as multivariate, such as profile analysis, multivariate analysis of variance (MANOVA), permutational multivariate analysis of variance (PERMANOVA), canonic correlation, or Log-linear models (multivariate), 23,[35][36][37] but their complexity demands supervision by a statistics professional with experience in this type of modeling.…”

Análise de dados com medidas dependentes em estudos clínicos e experimentais

“…Da mesma forma, há desenhos analíticos que demandam o estudo simultâneo de diferentes variáveis do mesmo sujeito, gerando uma estrutura de dependência dentro do indivíduo, como ocorre em escalas de qualidade de vida que avaliam mais de uma dimensão (por exemplo, Venous Insufficiency Epidemiological and Economic Study -Quality of Life/ Symptom [VEINES-QoL/Sym], Skindex-17), diferentes conjuntos de sintomas ou diferentes marcadores séricos secretados após um mesmo estímulo [32][33][34] . A avaliação quantitativa de grupos segundo a análise simultânea de mais de uma variável dependente exige o emprego de métodos chamados multivariados, como análise de perfil, análise multivariada de variância (MANOVA), análise multivariada de variância com permutação (PERMANOVA), correlação canônica ou modelos Log-lineares (multivariados) 23,[35][36][37] , entretanto sua complexidade requer a supervisão de um profissional estatístico experiente com esses tipos de modelagem.…”