Measurement properties of the ICECAP-A capability well-being instrument among dermatological patients

The Dermatology Life Quality Index (DLQI) used as the benchmark in validation of 101 quality-of-life instruments: A systematic review

BACKGROUND

The validation of psychometric measures requires use of other established and standardized validated measures. The Dermatology Life Quality Index (DLQI) is the most widely used tool to measure the burden of skin diseases and assess effectiveness of interventions based on patients' perspective.

OBJECTIVES

The objective of this study was to systematically analyse peer-reviewed publications describing use of the DLQI in validation of other patient-reported outcome (PRO) and quality-of-life (QoL) measures.

METHODS

Seven databases were searched for papers published between January 1994 and December 2022 for articles containing data using DLQI in the validation of other PRO/QoL measures. The methodology followed PRISMA guidelines. The protocol was prospectively registered on PROSPERO.

RESULTS

Of 1717 screened publications, 122 articles including 30,727 patients from 34 different countries with 41 diseases met the inclusion criteria. The DLQI was used in validation of 101 measures: 80 dermatology-specific QoL measures, mostly disease-specific, and 21 generic measures. Of these studies, 47 were cross-cultural adaptations, 116 single arm, 100 were cross-sectional, 18 longitudinal and six randomized placebo controlled. DLQI was used for 14 known group, and correlation for 10 construct, 101 convergent, 10 concurrent, 10 divergent/discriminant and three criterion validity tests using Mann-Whitney (2), Spearman's (80), Pearson's correlation (26) and Student's t-test (1). The DLQI was used in responsiveness analysis in 13 studies.

CONCLUSIONS

This review identified widespread use of the DLQI in validation of other dermatology PRO/QoL measures and confirmed the central role that the DLQI plays as a benchmark in instrument development and validation across dermatology and beyond. The use of the DLQI by so many developers of other instruments has provided a common standard for comparability.

Validation of the DLQI questionnaire in assessing the disease burden and principal aspects related to life quality of vitiligo patients

According to many studies, vitiligo has a negative psychological influence on the patient's life. Multiple factors contribute to the severity of the vitiligo disease burden, among which the most important are self-esteem, stress, and stigma. We aimed to measure the importance of health-related life quality in assessing disease burden in patients with vitiligo. We formulated an HA, which is the principal hypothesis, claiming a single fundamental factor that characterizes the life quality of patients with vitiligo. We also formulated 10 important research questions related to the quality of life that can be generally formulated for patients with dermatological illnesses but particularly suited for vitiligo patients. These research questions capture fundamental aspects of the health-related quality of life of vitiligo patients influenced by symptoms and feelings, daily activities, leisure, job and education, personal relationships, and treatment. These also cover specific aspects related to the quality of life, such as skin-caused sexual difficulties, difficulties in social relationships, and difficulties in performing sports, among others. The Dermatology Life Quality Index (DLQI) questionnaire measures the health-related quality of life of persons suffering from skin diseases. We applied this generic questionnaire to patients with vitiligo. Following a set of inclusion and exclusion criteria, we obtained 114 carefully selected patients who responded to all the questions. This study also validated the DLQI questionnaire on persons who suffer from vitiligo. We investigated whether DLQI has acceptable internal consistency by applying Cronbach's alpha internal consistency indicator (Cα). The obtained Cα = 0.914 indicates excellent internal consistency. We also examined whether all the questions in the questionnaire were mathematically consistent, which we finally proved. It was not necessary to remove any of the questionnaire questions. To prove our HA, a Principal Axis Factoring (PAF) was applied, verifying the assumptions regarding the Average Variance Extracted (AVE) and Convergent Validity (CV). HA proved that applying PAF on DLQI resulted in extracting a single general vitiligo latent factor of life quality, with an initial eigenvalue = 5.671, SS loadings = 5.2, and 52 % of the total cumulative variance explained. Diverse statistical analyses were applied to analyze the 10 formulated research questions. The results of the analysis of the research questions are presented and discussed in the manuscript. One of the conclusions related to the analysis of a research question was that sex had the lowest correlation with the latent life quality factor identified for vitiligo patients.

Measurement invariance and adapted preferences: evidence for the ICECAP-A and WeRFree instruments

BACKGROUND

Self-report instruments are used to evaluate the effect of interventions. However, individuals adapt to adversity. This could result in individuals reporting higher levels of well-being than one would expect. It is possible to test for the influence of adapted preferences on instrument responses using measurement invariance testing. This study conducts such a test with the Wellbeing Related option-Freedom (WeRFree) and ICECAP-A instruments.

METHODS

A multi-group confirmatory factor analysis was conducted to iteratively test four increasingly stringent types of measurement invariance: (1) configural invariance, (2) metric invariance, (3) scalar invariance, and (4) residual invariance. Data from the Multi Instrument Comparison study were divided into subsamples that reflect groups of participants that differ by age, gender, education, or health condition. Measurement invariance was assessed with (changes in) the Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and Root Mean Square Residual (SRMR) fit indices.

RESULTS

For the WeRFree instrument, full measurement invariance could be established in the gender and education subsamples. Scalar invariance, but not residual invariance, was established in the health condition and age group subsamples. For the ICECAP-A, full measurement invariance could be established in the gender, education, and age group subsamples. Scalar invariance could be established in the health group subsample.

CONCLUSIONS

This study tests the measurement invariance properties of the WeRFree and ICECAP-A instruments. The results indicate that these instruments were scalar invariant in all subsamples, which means that group means can be compared across different subpopulations. We suggest that measurement invariance of capability instruments should routinely be tested with a reference group that does not experience a disadvantage to study whether responses could be affected by adapted preferences.

Normative data and socio-demographic determinants of the Dermatology Life Quality Index in a large online sample of the Hungarian population

BACKGROUND

Population norms are available for several generic health-related quality of life questionnaires, but rarely for disease- or specialty-specific questionnaires.

OBJECTIVES

The aim of our study was to calculate population norms for the Dermatology Life Quality Index (DLQI) score.

METHODS

We conducted an online self-completed questionnaire survey on a large sample of the general Hungarian adult population. Respondents' socio-demographic characteristics and dermatology-related quality of life aspects were recorded.

RESULTS

A total of 2,001 participants completed the questionnaire, with the average age of 48.2 (SD = 16.6) years, half of the respondents in our sample (n = 981) reported long-standing health problems. The average DLQI score was 1.9 (SD = 4.0) with women having a higher average (2.0, SD = 3.9) than men (1.8, SD = 4.0; p=<0.001). The DLQI score differed among age-groups with younger people having relatively higher DLQI averages. When the multivariate linear regression model was applied, it showed that young age, lower income and unemployment status were associated with higher DLQI scores, while controlling for the existence of skin disease (p<0.05).

CONCLUSIONS

This study esthablished DLQI population norms among the general population, which may provide a reference point in health-policy and financing decision-making.