This paper is in the following e-collection/theme issue:

Instruments and Questionnaires for Physical Activity and Lifestyle (114) Research Instruments, Questionnaires, and Tools (738) Focus Groups and Qualitative Research for Human Factors Research (1220) Validity, Reliability, and Bias (110) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (997) Qualitative Methods (131) Supporting Home Care and Family Caregivers (262)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72590, first published .
Quality of Life Among Family Caregivers of Individuals With Rare Diseases: Web-Based Population Study on the Validity and Reliability of the Polish World Health Organization Quality of Life-BREF Questionnaire

Quality of Life Among Family Caregivers of Individuals With Rare Diseases: Web-Based Population Study on the Validity and Reliability of the Polish World Health Organization Quality of Life-BREF Questionnaire

Quality of Life Among Family Caregivers of Individuals With Rare Diseases: Web-Based Population Study on the Validity and Reliability of the Polish World Health Organization Quality of Life-BREF Questionnaire

Authors of this article:

Piotr Jabkowski1 Author Orcid Image ;   Jan Domaradzki2 Author Orcid Image ;   Dariusz Walkowiak3 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

    1Faculty of Sociology, Adam Mickiewicz University, Poznan, Poland

    2Department of Social Sciences and Humanities, Poznan University of Medical Sciences, Rokietnicka 7, Poznań, Poland

    3Department of Organization and Management in Health Care, Poznan University of Medical Sciences, Poznan, Poland

    *all authors contributed equally

    Corresponding Author:

    Jan Domaradzki, PhD


    Background: Caring for individuals with rare diseases (RDs) presents unique challenges that can significantly impact caregivers’ quality of life (QoL). The World Health Organization Quality of Life-BREF (WHOQOL-BREF) is a widely used tool for assessing QoL across different populations.

    Objective: This study examines the QoL of caregivers of individuals with RDs and evaluates the psychometric properties of the WHOQOL-BREF in this population.

    Methods: A self-administered, anonymous, computer-assisted web-based survey was conducted among family caregivers of individuals with RDs in Poland between March and August 2024. Due to the lack of a national registry of patients with RDs, participants were recruited through convenience sampling via associations, foundations, and organizations of patients with RDs. Eligibility criteria included being 18 years and older of age, speaking Polish, being a caregiver of a person with a confirmed RD diagnosis, and providing informed consent. The survey included sociodemographic questions and the Polish version of the WHOQOL-BREF, which assesses QoL across 4 domains: physical health, psychological health, social relationships, and environment. Internal consistency was assessed using Cronbach α, and confirmatory factor analysis was conducted to examine the instrument’s structural validity.

    Results: A total of 942 caregivers of individuals with various RDs participated in the study. Confirmatory factor analysis supported the 4-domain structure, with further improvement in a finally modified WHOQOL-BREF model (χ2243=1043.0; P<.001; Comparative Fit Index=0.919; Tucker-Lewis Index=0.907; root-mean-square error of approximation=0.059). Internal consistency was satisfactory, with Cronbach α values ranging from 0.70 (social relationships) to 0.84 (psychological health). Mean domain scores on a scale of 0‐100 were 50.2 (SE 0.59; physical health), 54.9 (SE 0.59; psychological health), 51.3 (SE 0.67; social relationships), and 52.1 (SE 0.56; environment), with minimal floor and ceiling effects (≤1.4%) across domains. Younger female caregivers reported significantly lower psychological health (eg, mean 43.6, SE 0.59 vs mean 59.9, SE 10.0 for younger male caregivers) and social relationships (mean 39.3, SE 3.34 vs mean 55.0, SE 4.75) well-being compared to other groups. Exactly 151 (16%) of caregivers rated their overall QoL as poor or very poor, and 289 (30.7%) were dissatisfied or very dissatisfied with their health, with female caregivers reporting more dissatisfaction (n=263, 32.4%) than male caregivers (n=26, 20%). Overall, our findings demonstrate the robust psychometric properties of the WHOQOL-BREF among caregivers of people with RDs and provide domain-specific normative data to guide future research and interventions.

    Conclusions: The WHOQOL-BREF is a reliable and valid instrument for assessing QoL among caregivers of individuals with RDs, though the social relationship domain may require further refinement. Caregivers experience varying QoL outcomes depending on demographic factors, highlighting the need for targeted support interventions. Future research should explore cultural adaptations and potential supplementary modules to enhance the instrument’s applicability in caregiver populations.

    JMIR Public Health Surveill 2025;11:e72590

    doi:10.2196/72590

    Keywords

    quality of life; rare diseases; caregivers; WHOQOL-BREF; World Health Organization Quality of Life-BREF; validation 


    Quality of life (QoL) is a multidimensional construct that reflects an individual’s overall well-being, encompassing physical health, psychological health, social relationships, and environmental factors. In 1991, the World Health Organization (WHO) initiated a project to develop an internationally applicable measure of QoL, leading to the creation of the World Health Organization Quality of Life (WHOQOL) instrument. The WHO defined QoL as an individual’s perception of their position in life within the context of their cultural and value systems as well as their personal goals, expectations, standards, and concerns. This definition highlights the subjective nature of QoL, emphasizing that it is shaped by personal experiences and influenced by broader social and environmental contexts. Importantly, QoL assessment provides valuable insights into health outcomes, treatment effectiveness, and overall well-being across diverse populations [1-3].

    A subset of QoL research, health-related quality of life (HRQoL), has gained increasing attention in clinical and public health research. HRQoL focuses specifically on the impact of health conditions on an individual’s well-being, playing a critical role in health care decision-making, policy development, and patient-centered care [4-6]. Over the past 3 decades, numerous HRQoL assessment tools have been developed, including both generic instruments applicable across populations and disease-specific measures tailored to particular conditions. Despite the proliferation of these tools, a significant limitation remains—the lack of internationally validated instruments capable of capturing HRQoL across diverse cultural and socioeconomic settings [7,8].

    To address this challenge, the WHO developed the WHOQOL-100 consisting of 100 questions, an instrument designed to assess subjective well-being while ensuring cross-cultural validity. This instrument was developed through extensive research conducted across 15 field centers worldwide, incorporating perspectives from patients, caregivers, health care professionals, and the general population. The psychometric properties of the WHOQOL-100, including its validity and reliability, were rigorously tested in multiple cultural and linguistic contexts [1]. Recognizing the need for a shorter, more practical instrument, the WHO subsequently introduced the World Health Organization Quality of Life-BREF (WHOQOL-BREF) in 1998, a 26-item version that assesses 4 key domains of HRQoL: physical health, psychological health, social relationships, and environment. The WHOQOL-BREF has since been widely adopted in epidemiological studies, clinical trials, and public health research, demonstrating strong psychometric properties and cross-cultural applicability [2,4,7,9].

    Although the WHOQOL-BREF has been validated in numerous populations, its application in certain groups remains underexplored. In Poland, the WHOQOL-BREF was validated in 2006 using a sample of healthy individuals and patients with various diseases and health conditions [6]. However, this validation process overlooked caregivers, an essential yet often neglected population in HRQoL research. Caregivers play a vital role in the health care system, providing continuous support to individuals with chronic illnesses and disabilities. Despite their crucial contributions, caregivers often experience significant physical, emotional, and financial burdens, which in turn affect their own QoL [10-13].

    Caregivers of persons with RDs face particularly severe challenges. RDs are often characterized by delayed diagnoses, limited treatment options, and a lack of specialized health care resources, placing an immense strain on families [10,13-17]. Studies suggest that caregivers of persons with RDs report lower QoL compared to those caring for individuals with more common chronic conditions, mainly due to increased caregiving demands, emotional distress, social isolation, and financial hardship. The unpredictable nature of many RDs, coupled with the complexity of care required, exacerbates stress and negatively affects the physical and mental health of caregivers [5,13,18].

    The burden of caregiving is multifaceted, affecting various domains of QoL. Physically, caregivers frequently experience chronic fatigue, sleep disturbances, headaches, and weakened immune function due to the demands of continuous care. Psychologically, they are at increased risk for anxiety, depression, burnout, and emotional exhaustion, with some studies indicating higher rates of suicidal ideation among caregivers [17-20]. Socially, caregivers often face reduced participation in social activities, strained relationships, and isolation, as caregiving responsibilities limit their ability to engage with friends and family. Financially, many caregivers are forced to reduce work hours or leave employment altogether, exacerbating economic difficulties and increasing reliance on social support systems. Given these profound challenges, assessing QoL in caregivers of persons with RDs is essential for understanding their specific needs and designing effective interventions to support them [14,16,19,21-23].

    Despite the growing recognition of caregiver burden as a public health concern, research validating HRQoL assessment tools specifically for this population remains limited. The WHOQOL-BREF, although widely used across various patient populations, has not been systematically evaluated for its appropriateness in assessing the QoL of caregivers, particularly in the context of rare diseases (RDs). While WHOQOL-BREF is often used in studies on caregivers of individuals with RDs, the resulting QoL domain scores are typically interpreted abstractly—detached from the scale itself—or, less commonly, compared against national normative data [17,24,25]. A validated, standardized tool tailored to caregivers would offer valuable insights for clinical practice, inform health policy, and support the development of targeted interventions, ensuring that the specific needs of caregivers are effectively addressed [2,13,25,26].

    To bridge this research gap, this study aims to validate the WHOQOL-BREF for caregivers of persons with RDs and establish population norms specific to this group. By generating normative data, this study seeks to enhance the clinical utility of the WHOQOL-BREF in caregiver research and contribute to the development of targeted support programs and health care policies. A comprehensive understanding of caregiver QoL is crucial for improving the well-being of both caregivers and the care recipients they support, ultimately leading to better health outcomes for families affected by RDs.


    Study Design

    A cross-sectional study was conducted in 2024 in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines (Checklist 1) [27].

    This study used data from a self-administered, anonymous, computer-assisted web-based survey examining the association between caregiving for a person with an RD and caregivers’ perceived QoL. The survey targeted family caregivers of individuals with RDs. Given the absence of a Polish registry of patients with RD and the unknown exact number of affected individuals, a convenience sampling approach was used. Several associations, foundations, and organizations of patients with RD assisted in participant recruitment by sharing the survey link on their websites and Facebook pages.

    At the same time, it should be stressed that convenience sampling used in this study introduces selection bias, as participants may not represent the broader population, limiting the generalizability of findings. However, given the specific nature of the study population—namely, the small size of the groups of particular RDs, the absence of a national registry of patients with RD in Poland, and the wide geographic dispersion of caregivers—convenience sampling appeared to be the most practical and, indeed, the only feasible method. However, it is important to acknowledge several limitations associated with this approach. Most importantly, participants recruited via patient organizations may not reflect the full diversity of the broader population. This type of sampling could affect the study outcomes, potentially skewing results based on the demographics of the sample, such as age, sex, socioeconomic status, or disease severity. Consequently, this method introduces selection bias and limits the reliability and generalizability of the findings. Thus, although this strategy was appropriate under the circumstances, future research should aim to use more representative sampling techniques—such as random or stratified sampling—that may better capture the heterogeneity of caregivers of individuals with RDs and allow for a more accurate reflection of the realities of the population as a whole. Nonetheless, again, it should be stressed that due to the unique challenges of studying this population of caregivers of individuals with RDs, the use of other sampling methods is very difficult, if at all feasible.

    Setting and Recruitment

    The survey targeted family caregivers of individuals diagnosed with RDs. Due to the absence of a national registry of patients with RD in Poland and the unknown exact number of patients with RD, the study used convenience sampling. Recruitment was supported by various patient organizations, foundations, and advocacy groups via their websites and Facebook profiles.

    At the first stage of recruitment, the study coordinator contacted several associations, foundations, and organizations of patients with RD to determine whether they were interested in participating in the study. After receiving their consent, a letter with detailed information about the purpose and method of the study, together with an invitation, was published on the organization’s Facebook pages and sent out via an internal mailing to members, by which all affiliated caregivers who met the inclusion criteria were invited to participate in the study.

    Eligible participants were required to be at least 18 years of age, fluent in Polish, and a parent or family caregiver of a person with a confirmed RD diagnosis. Additionally, participants needed access to the internet, the ability to use electronic devices to complete the survey, and had to provide written informed consent before participation.

    The questionnaire consisted of sociodemographic questions concerning both caregivers and persons with RD along with the abbreviated Polish version of the WHOQOL-BREF [6]. This 24-item instrument assesses QoL across 4 domains: physical health, psychological health, social relationships, and environment. Two additional items do not constitute any of the 4 dimensions but are set up to measure the overall QoL and satisfaction with health.

    Data Collection Procedure

    The survey was conducted between March and August 2024. Initially, the research coordinator contacted multiple associations, foundations, and organizations of patients with RDs to obtain permission for distribution. Upon approval, an invitation letter containing a link to the web-based questionnaire was shared via these platforms. Participants who provided written informed consent completed the survey electronically. To enhance response rates, 3 follow-up reminders were sent in January, March, and June. The survey required approximately 20‐25 minutes to complete.

    Data Analysis

    All statistical analyses were conducted using R Statistical Software (version 4.3.1; R Foundation for Statistical Computing). The study used a quantitative research design to analyze the psychometric properties of the WHOQOL-BREF questionnaire for the Polish population of caregivers of people with RDs. Descriptive statistics were calculated to summarize the demographic characteristics of the sample and the overall QoL scores in 4 domains: physical health, psychological health, social relationships, and environment. Reliability analysis was performed using Cronbach α to assess the internal consistency of the questionnaire. Confirmatory factor analysis (CFA) was used to test the hypothesized factor structure of the WHOQOL-BREF by examining the fit of the data to the model. Goodness-of-fit indices, including the Comparative Fit Index (CFI) and root mean-square-error of approximation (RMSEA), were reported to assess model adequacy.

    Ethical Considerations

    This study was conducted according to the Declaration of Helsinki and was approved by the Poznan University of Medical Sciences Bioethics Committee (KB 228/24, March 13, 2024). All participants were informed about the objectives and methodology of the study in an invitation letter. Informed consent was obtained electronically through the web-based questionnaire by selecting the “I agree” option. Participants were assured that their participation was voluntary, anonymous, and confidential and that they had the right to withdraw at any time or omit any question without consequence. To ensure privacy, no personal identifying information or images were collected. Participants were also informed that, although some questions may be emotionally sensitive, they could pause or discontinue the survey at any time. Since participation did not involve any direct intervention or additional burden, no financial compensation was offered.


    Overview

    In this section, we present a validation of the WHOQOL-BREF scale and provide insights into its empirical structure, psychometric properties, and latent score characteristics. We have implemented CFA by comparing a unidimensional baseline model with the established 4D model of the WHOQOL-BREF. Statistical fit indices such as CFI and RMSEA are provided to assess model adequacy, along with modifications to improve dimensional alignment. This section then highlights the robustness of the 4D structure, and the Structural Validity section focuses on the reliability of the WHOQOL-BREF scale, which is examined through the lens of internal consistency across the 4 domains. A descriptive analysis of the scores derived from the 4 dimensions of the WHOQOL-BREF is also presented. Finally, norms for the QoL domains in a Polish population of caregivers of persons with RDs are provided. The norms for the WHOQOL-BREF are presented as mean values, SE of the mean, 25th percentile, median, 75th percentile, minimum, maximum, and percentage of floor and ceiling effect. These norms were estimated by sex and age group.

    Study Participants

    Table 1 presents characteristics of the sample by sex and age category of caregivers.

    Table 2 outlines the demographic and diagnostic characteristics of 942 patients with RDs. Most patients were male (n=586, 62.2%), with a wide age range (0.2‐78 years), a mean age of 12 (SE 0.32) years, and a median of 10 (IQR 6.0-15.0) years. The most frequently reported conditions included Duchenne muscular dystrophy or Becker muscular dystrophy (n=211, 22.4%), 22q11.2 deletion syndrome (n=131, 13.9%), and Angelman syndrome (n=120, 12.7%). A total of 191 (20.3%) patients were diagnosed with one of 144 other rare or ultrarare conditions. Time to diagnosis varied considerably: while 165 (17.5%) were diagnosed within 3 months, 226 (24%) received a diagnosis within 1‐2 years, and 130 (13.9%) waited more than 5 years. A small group (n=18, 1.9%) was still in the asymptomatic phase of the disease. These data highlight the diagnostic challenges and heterogeneity of RD populations.

    Table 1. General characteristics of family caregivers of individuals with rare disease.
    Age (years)Male, n (%)Female, n (%)Total, n (%)
    16‐292 (1.5)32 (3.9)34 (3.6)
    30‐3944 (33.8)337 (41.5)381 (40.4)
    40‐4964 (49.2)350 (43.1)414 (43.9)
    50 and more20 (15.4)93 (11.5)113 (12.0)
    Total130 (13.8)812 (86.2)942 (100)
    Table 2. Characteristics of individuals with rare disease.
    CharacteristicsTotal (N=942), n (%)
    Sex
    Female356 (37.8)
    Male586 (62.2)
    Age (years)
    Mean (SE)12 (0.32)
    Range0.2‐78
    Median (IQR)10 (6.0-15.0)
    Disease
    22q11.2 deletion syndrome131 (13.9)
    Angelman syndrome120 (12.7)
    DMDa or BMDb211 (22.4)
    Dravet syndrome106 (11.3)
    Ehlers-Danlos syndrome19 (2)
    Glycogen storage disease10 (1.1)
    Kabuki syndrome11 (1.2)
    Neurofibromatosis33 (3.5)
    Niemann-Pick disease10 (1.1)
    PANSc or PANDASd14 (1.5)
    Prader-Willi syndrome10 (1.1)
    Tuberous sclerosis complex14 (1.5)
    Turner syndrome14 (1.5)
    Williams syndrome48 (5.1)
    144 other diseases191 (20.3)
    Time spent before the correct diagnosis was made
    0‐3 months165 (17.5)
    4‐6 months106 (11.3)
    7‐12 months140 (14.9)
    1‐2 years226 (24.0)
    3‐5 years157 (16.7)
    6‐10 years82 (8.7)
    11‐15 years29 (3.1)
    16‐20 years10 (1.1)
    20+ years9 (1.0)
    Asymptomatic phase of the disease18 (1.9)

    aDMD: Duchenne muscular dystrophy.

    bBMD: Becker muscular dystrophy.

    cPANS: pediatric acute-onset neuropsychiatric syndrome.

    dPANDAS: pediatric autoimmune neuropsychiatric disorders associated with streptococcal infection.

    Confirmatory Factor Analysis

    The CFA results illustrate a comparative assessment of 3 models for the WHOQOL-BREF: the baseline unidimensional model, the original 4D WHO model, and a modified 4D model. The fit indices provide a comprehensive evaluation of the models’ performance and structural validity of the WHOQOL-BREF 4D scale (Table 3).

    The baseline unidimensional model yielded unsatisfactory fit indices, suggesting a poor representation of the scale’s underlying structure. The chi-square statistic (χ2252=1602.8; P<.001) was significant, and the χ2/df ratio (6.360) exceeded the acceptable threshold of 5. The CFI (0.862) and Tucker-Lewis Index (TLI=0.849) indicated a suboptimal model fit, while the RMSEA (0.075; 90% CI 0.072‐0.079) was marginally above the acceptable upper limit. Conversely, the standardized root-mean-square residual (SRMR=0.050) remained within acceptable limits, indicating an adequate residual-based fit. In practical terms, these results suggest that treating the WHOQOL-BREF as a single-factor measure does not fully capture the complexities of caregivers’ QoL, as evidenced by the modest CFI or TLI and moderately elevated RMSEA.

    Table 3. Comparison of fit indices for different WHOQOL-BREFa latent models for family caregivers of individuals with rare disease.
    ModelChi-square (df)χ2/dfCFIbTLIcSRMRdRMSEAeRMSEA−95% CIRMSEA+95% CI
    Baseline model1602.8 (252)6.40.8620.8490.0500.0750.0720.079
    Original WHOQOL-BREF1343.9 (246)5.50.8880.8750.0470.0690.0650.072
    Modified WHOQOL-BREF1043.0 (243)4.30.9190.9070.0410.0590.0550.063

    aWHOQOL-BREF: World Health Organization Quality of Life-BREF.

    bCFI: Comparative Fit Index.

    cTLI: Tucker-Lewis Index.

    dSRMR: standardized root-mean-square residual.

    eRMSEA: root-mean-square error of approximation.

    In contrast, the initial 4D model demonstrated substantial improvements across all fit indices (χ2246=1343.9; P<.001). The χ2/df ratio decreased to 5.463, and the CFI (0.888) and TLI (0.875) approached recommended levels. The RMSEA (0.069; 90% CI 0.065‐0.072) and SRMR (0.047) further suggested enhanced fit. Adjustments were made based on modification indices to optimize model fit; that is, correlated error terms were introduced between questions 3 and 4 (modification index equals 164.9), questions 12 and 23 (modification index equals 64.8), and questions 19 and 20 (modification index equals 56.4). While these modifications enhanced statistical compatibility, they also entailed conceptual implications. Specifically, it can be posited that each of these item pairs is likely to tap into closely related dimensions of caregiver well-being (eg, physical or psychological strain or environmental or social considerations). Consequently, the modification indices suggest that some questions, though intended to measure slightly different constructs, may elicit overlapping responses from caregivers who face similar daily challenges across multiple domains of life. Rather than perceiving these errors as mere statistical artifacts, it is more fruitful to interpret them as potential indicators of content overlap or a shared contextual factor (eg, stress or time pressure) that influences the way participants interpret these items. For researchers using the WHOQOL-BREF in caregiver populations, acknowledging and examining these correlated errors can foster a more nuanced understanding of how caregiving experiences merge otherwise distinct QoL facets. Future studies could investigate whether such overlaps are unique to certain subgroups or care contexts or if item wording could be refined to differentiate better between seemingly related aspects of QoL.

    The modified 4D model demonstrated a significant enhancement (χ2243=1043.0; P<.001), exhibiting a reduced χ2/df ratio of 4.292. The CFI (0.919) and TLI (0.907) exceeded the conventional threshold for adequate fit, while the RMSEA (0.059; 90% CI 0.055‐0.063) and SRMR (0.041) substantiated the model’s robustness. The findings suggest that the targeted modifications serve to enhance the correlation between items within their respective dimensions, thereby producing a more robust and precise measurement structure with fit indices that approach commonly accepted benchmarks.

    Structural Validity

    This section presents a reliability analysis of the items within the WHOQOL-BREF across its 4 dimensions. The analysis uses Cronbach α to evaluate internal consistency, with findings indicating satisfactory to high reliability across domains. Specifically, α values ranged from 0.69 for the social relationships domain to 0.84 for the psychological health domain, demonstrating varying but overall strong consistency (Table 4).

    Item-level analyses provide further insight into the impact of individual items on the overall reliability of each domain. Most items contribute positively to reliability, with suggestions for potential refinement in some areas.

    Table 4. Internal consistency scores of the 4 WHOQOL-BREF domains obtained for Polish family caregivers of individuals with rare diseases.
    DomainItems, nCronbach α
    Physical health70.818
    Psychological health60.843
    Social relationships30.700
    Environment80.807

    aWHOQOL-BREF: World Health Organization Quality of Life-BREF.

    Normalized Scores for Domains of WHOQOL-BREF

    This section presents a descriptive analysis of the normalized scores derived from the 4D-modified WHOQOL-BREF scale. Following the recommendations of the WHO, responses to each item were coded from 1 to 5 and transformed to a scale from 0 (lowest QoL) to 100 (highest QoL). Each item was weighted by standardized factor loadings derived from a CFA model before calculating the overall domain score (Table 5).

    The factor loadings range from 0.363 to 0.801, indicating varying degrees of item contribution to their respective latent constructs. The physical health domain exhibits robust item representation, with loadings such as question 18 (0.801) and question 16 (0.794) suggesting substantial explanatory power for the physical health construct. The psychological health domain also exhibits high loadings, particularly for question 26 (0.747) and question 19 (0.688), suggesting that these items are key indicators of psychological health. Items in the environmental domain display more variability, with question 12 having the lowest loading (0.456) and question 8 the highest (0.763). The social relationships domain demonstrates moderate item loadings, with question 22 (0.619) being the most influential item and question 20 (0.477) contributing the least.

    Table 5. Standardized factor loadings for the items comprising the 4 WHOQOL-BREF domains for Polish family caregivers of individuals with rare diseases.
    WHOQOL-BREF domains and itemsStandardized factor loadings
    Physical health
    Question 30.456
    Question 40.363
    Question 100.794
    Question 150.673
    Question 160.562
    Question 170.801
    Question 180.658
    Psychological health
    Question 50.747
    Question 60.689
    Question 70.600
    Question 110.631
    Question 190.795
    Question 260.688
    Social relationships
    Question 200.776
    Question 210.603
    Question 220.619
    Environment
    Question 80.763
    Question 90.677
    Question 120.622
    Question 130.564
    Question 140.675
    Question 230.477
    Question 240.395
    Question 250.380

    aWHOQOL-BREF: World Health Organization Quality of Life-BREF.

    Figure 1 presents histograms and density plots for the 4 dimensions of the WHOQOL-BREF scale: physical health, psychological health, social relationships, and environment domains. Each plot illustrates the distribution of normalized scores (ranging from 0 to 100) for the respective dimension. The overlaid density curves provide a smoothed visualization of the score distribution, highlighting its approximate normality across all domains, with slight deviations observed, particularly in the psychological health and social relationships domains. The detailed descriptive statistics for the distribution of scores within each domain of the WHOQOL-BREF are delineated in Table 6.

    The psychological health domain demonstrated the highest mean score (mean 54.9, SE 0.59), indicating relatively better perceived psychological well-being among respondents. Conversely, the physical health domain exhibited the lowest mean score (mean 50.2, SE 0.59). The environment and social relationships domains showed mean scores of 52.1 (SE 0.56) and 51.3 (SE 0.67), respectively. The SEs of the mean were relatively consistent, ranging from 0.56 to 0.67, indicating precision in the central tendency estimates.

    Concerning the normality of the data, the skewness and kurtosis values are within acceptable ranges, thereby supporting the visual interpretation from the density plots. However, the Shapiro-Wilk test reveals statistically significant deviations from normality for the physical health, psychological health, and social relationships dimensions (P<.01), while the environment domain demonstrates borderline nonsignificance (P=.05), suggesting a near-normal distribution.

    ‎
    Figure 1. Histogram and density plots for domains of the WHOQOL-BREF (World Health Organization Quality of Life-BREF) for Polish family caregivers of individuals with rare disease.
    Table 6. Descriptive characteristics of the latent scores for WHOQOL-BREF domains for Polish family caregivers of individuals with rare disease.
    StatisticEnvironmentPhysical healthPsychological healthSocial relationships
    Mean (SE)52.1 (0.56)50.2 (0.59)54.9 (0.59)51.3 (0.67)
    Range6.8-97.84.8-100.00.0-100.00.0-100.0
    Skewness−0.060−0.023−0.155−0.137
    Kurtosis2.6242.5512.6292.681
    Shapiro-Wilk statistic0.9970.9950.9940.989
    Shapiro-Wilk P value.05.006<.001<.001
    Median (IQR)52.2 (40.4-64.5)50.0 (37.8-63.9)54.6 (42.6-67.2)51.9 (34.9-67.3)
    Floor effect (%)000.11.4
    Ceiling effect (%)00.101.3

    aWHOQOL-BREF: World Health Organization Quality of Life-BREF.

    The analysis of floor and ceiling effects reveals minimal clustering at the extremes, with the social relationships domain exhibiting a 1.4% floor effect and a 1.3% ceiling effect, the highest among all domains. These negligible effects ensure the scale’s capacity to capture a wide range of responses without response saturation.

    Normative Data for Domains of WHOQOL-BREF

    Prior to the presentation of normative data for the domains of the WHOQOL-BREF, an examination of the overall assessment of the QoL and satisfaction with health among Polish caregivers of individuals with RDs is warranted. The data presented in Table 7 reveal notable differences by sex.

    Concerning the overall evaluation of QoL, the predominant response among male and female caregivers was “good,” with 42.3% (n=55) of male and 39.5% (n=321) of female caregivers indicating this as their response. The second most prevalent response was “neither poor nor good,” with 31.5% (n=41) of male and 39.5% (n=321) of female caregivers choosing this option. However, a higher proportion of female caregivers reported a “poor” QoL (n=108, 13.3%) compared to male caregivers (n=19, 14.6%). The percentage of caregivers who rated their QoL as “very poor” was relatively low overall, at 2.5% (n=24), with male caregivers (n=7, 5.4%) more likely to report this than female caregivers (n=17, 2.1%). Conversely, only a small percentage of caregivers reported a “very good” QoL (male: n=8, 6.2% and female: n=45, 5.5%). These findings suggest that perception of the overall QoL is more likely to be situated toward the middle or lower end of the scale for both sexes. Satisfaction with health, however, revealed more pronounced differences between male and female caregivers. While 45.4% (n=59) of male caregivers reported being “satisfied” with their health, this proportion was significantly lower for female caregivers, at 29.2% (n=237). Instead, more female caregivers expressed dissatisfaction (n=237, 29.2% compared to n=22, 16.9% of male caregivers) or were “neither satisfied nor dissatisfied” (female: n=293, 36.1% vs male: n=41, 31.5%). A small proportion of caregivers described themselves as “very satisfied” with their health (male: n=4, 3.1% and female: n=19, 2.3%), while 3.2% (n=30) of caregivers overall reported being “very dissatisfied.” These results suggest that male caregivers generally report a higher QoL and greater health satisfaction than female caregivers. The elevated incidence of dissatisfaction and neutral responses among female caregivers may indicate the supplementary burdens they encounter in their caregiving roles or inherent disparities in perceived health status and well-being.

    Table 7. Overall evaluation of the quality of life and satisfaction with the health of family caregivers of individuals with rare diseases by sex.
    Male, n (%)Female, n (%)Total, n (%)
    How would you rate your quality of life?
    Very poor7 (5.4)17 (2.1)24 (2.5)
    Poor19 (14.6)108 (13.3)127 (13.5)
    Neither poor nor good41 (31.5)321 (39.5)362 (38.4)
    Good55 (42.3)321 (39.5)376 (39.9)
    Very good8 (6.2)45 (5.5)53 (5.6)
    How satisfied are you with your health?
    Very dissatisfied4 (3.1)26 (3.2)30 (3.2)
    Dissatisfied22 (16.9)237 (29.2)259 (27.5)
    Neither satisfied nor dissatisfied41 (31.5)293 (36.1)334 (35.5)
    Satisfied59 (45.4)237 (29.2)296 (31.4)
    Very satisfied4 (3.1)19 (2.3)23 (2.4)

    Normative data for the 4 dimensions of the WHOQOL-BREF—physical health, psychological health, social relationships, and environment—segmented by sex and age group are presented in Table 8.

    Male caregivers demonstrated higher mean scores in physical health than female caregivers across all age groups. The highest mean score was observed in the youngest male group (16‐29 years: mean 59.9, SE 10.04), gradually decreasing with age, reaching its lowest value in the 50+ year group (mean 50.4, SE 4.72). Among female caregivers, the 16‐ to 29-year age group exhibited the lowest mean score (mean 43.6, SE 2.72), while the 40‐ to 49-year age group demonstrated the highest (mean 51.0, SE 1.00). The absence of floor or ceiling effects in this domain indicates that the scale effectively captured a comprehensive range of physical health outcomes without concentrating on the extremes. The observed decline in physical health scores with age is consistent with patterns reported in other populations, suggesting a cumulative impact of caregiving and aging.

    Psychological health scores demonstrated relative stability across age groups for both male and female caregivers. Male caregivers exhibited scores ranging from 57.4 to 58.4, while female caregivers displayed scores from 49.5 (16‐29 years) to 56.2 (40‐49 years). Notwithstanding the overall consistency, female caregivers in the 16‐ to 29-year age group reported significantly lower psychological well-being. No ceiling effects were observed, and only minimal floor effects were present (1.1%) among female caregivers aged 50+ years, indicating that extreme values were rare.

    Table 8. WHOQOL-BREF norms for the Polish population of caregivers of individuals with rare diseases by sex and age.
    MaleFemale
    16‐29 years30‐39 years40‐49 years50+ years16‐29 years30‐39 years40‐49 years50+ years
    Physical health
    Mean (SE)59.9 (10.04)58.1 (2.92)54.0 (2.29)50.4 (4.72)43.6 (2.72)49.5 (0.91)51.0 (1.00)45.6 (1.79)
    Range49.9-69.921.2-91.57.2-92.814.5-85.017.9-73.76.9-92.44.8-100.07.4-81.7
    Median (IQR)59.9 (54.9-64.9)60.8 (43.8-72.9)54.2 (42.9-68.3)51.6 (33.7-67.4)44.6 (34.3-52.6)48.9 (38.7-60.8)50.0 (38.1-65.6)47.4 (33.4-57.4)
    Floor effect (%)00000000
    Ceiling effect (%)0000000.30
    Psychological health
    Mean (SE)57.8 (12.33)58.2 (3.26)57.4 (2.00)58.4 (3.98)49.5 (2.77)53.6 (0.99)56.2 (0.96)52.8 (1.87)
    Range45.5-70.27.2-95.515.9-91.417.9-90.721.2-87.73.6-95.911.7-100.00.0-90.7
    Median (IQR)57.8 (51.7-64.0)63.1 (43.5-71.9)58.3 (46.1-70.2)58.0 (48.9-72.3)49.5 (37.6-60.1)53.8 (41.4-66.9)57.7 (45.2-70.4)54.0 (41.9-66.4)
    Floor effect (%)00000001.1
    Ceiling effect (%)00000000
    Social relationships
    Mean (SE)55.0 (4.75)52.4 (3.21)50.8 (2.67)52.1 (4.82)39.3 (3.34)51.2 (1.17)52.5 (1.05)50.9 (1.91)
    Range50.2-59.77.7-92.30.0-100.017.3-100.00.0-75.00.0-100.00.0-100.00.0-84.5
    Median (IQR)55.0 (52.6-57.3)57.5 (40.3-67.3)52.3 (40.9-65.8)57.4 (33.5-67.3)41.3 (25.0-50.1)50.0 (34.7-67.5)52.2 (40.1-67.5)52.2 (34.9-67.3)
    Floor effect (%)004.706.21.20.91.1
    Ceiling effect (%)001.6501.81.10
    Environment
    Mean (SE)52.8 (2.02)57.5 (2.39)55.3 (1.84)51.5 (4.09)48.8 (2.73)51.1 (0.92)53.0 (0.93)48.5 (1.91)
    Range50.8-54.824.5-87.215.8-83.423.0-84.714.2-73.36.8-97.89.5-94.29.1-87.8
    Median (IQR)52.8 (51.8-53.8)59.5 (47.2-68.8)54.1 (46.3-65.4)50.2 (34.6-65.4)48.0 (38.2-61.8)51.3 (39.8-62.5)52.0 (41.5-65.5)50.2 (36.0-62.9)
    Floor effect (%)00000000
    Ceiling effect (%)00000000

    aWHOQOL-BREF: World Health Organization Quality of Life-BREF.

    The social relationships domain displayed greater variability, particularly among female caregivers. The lowest mean score was found in the youngest female group (16‐29 years: mean 39.3, SE 3.34), suggesting social challenges in this group. In contrast, male caregivers demonstrated more stability, with scores ranging from 50.8 to 55.0 across all age groups. Significant floor effects were observed among female caregivers aged 16‐29 years (6.2%) and male caregivers aged 40‐49 years (4.7%), suggesting that many respondents experienced severe difficulties in social relationships. Ceiling effects were generally minimal, with the highest occurrence (5%) observed among male caregivers aged 50 years and older.

    The scores in the environment domain demonstrated greater consistency across age groups. The mean score was highest among male caregivers aged 30‐39 years (mean 57.5, SE 2.39) and lowest among female caregivers aged 50+ years (mean 48.5, SE 1.91). The absence of floor or ceiling effects indicated that responses were distributed uniformly across the scale. This dimension reflects a stable perception of environmental support and resources among caregivers, irrespective of age or sex.

    The study’s results indicate significant disparities in HRQoL within the sex and age categories of caregivers. Specifically, younger female caregivers exhibited lower scores in various domains of WHOQOL-BREF. These disparities can be attributed to the unique challenges associated with caregiving roles, personal health, and social support systems, particularly for specific demographic groups.


    Principal Findings

    The WHOQOL-BREF is a widely used instrument for assessing QoL across diverse populations [4,28]. Its psychometric properties have been extensively studied, confirming its reliability and validity. However, certain aspects warrant further discussion, including its applicability across cultural contexts, domain-specific reliability concerns, and its use in both general and disease-specific populations [8,9,26,29-32].

    Our study demonstrated that the WHOQOL-BREF is an appropriate tool for assessing QoL among caregivers of individuals with RDs. The instrument exhibited good internal consistency, with Cronbach α values generally exceeding 0.70. Internal consistency analysis showed values ranging from 0.69 for the social relationships domain to 0.84 for psychological health, indicating satisfactory to high reliability across domains. The item-level analysis identified specific areas where refinements could enhance reliability. Nevertheless, previous studies have reported lower reliability in the social relationships domain, highlighting a potential need for further refinement [6,8,33].

    The construct validity of the WHOQOL-BREF is well established, with CFAs generally supporting its 4-domain structure. The instrument also demonstrates strong convergent and discriminant validity, correlating well with other health measures and effectively distinguishing between groups with differing health conditions [34-37]. Consistent with prior research, our findings confirm that the WHOQOL-BREF generally maintains good internal consistency, with Cronbach α values frequently exceeding 0.70. For instance, one study reported an α of 0.898 for the total score [33].

    However, lower α values have often been observed in the social relationship domain, occasionally falling below 0.70. A Thai study reported a Cronbach α of 0.62 for this domain, while the other domains ranged from 0.81 to 0.85 [38]. Similarly, a Greek study found an α of 0.65 for social relationships, with other domains ranging from 0.66 to 0.87 [36]. Several factors may account for this pattern. The social relationships domain comprises only 3 items, which naturally limits internal consistency compared to domains with more items. Additionally, the items assess complex and sensitive aspects of life—such as personal relationships and sexual activity—which may be interpreted differently across individuals, particularly among caregivers of persons with RDs. Cultural, sex-based, and situational factors (eg, emotional exhaustion, social withdrawal, and limited time for interpersonal interaction) may further influence caregivers’ responses, contributing to variability in this domain.

    Factor analysis has been widely used to evaluate the underlying structure of the WHOQOL-BREF [6,39]. CFA results indicate that a unidimensional model yields poor fit indices, whereas the 4-domain model significantly improves model fit. Further refinements, including correlated error terms, have led to an optimized model with improved goodness-of-fit measures (χ2/df, CFI, TLI, RMSEA, and SRMR). These findings confirm the structural validity of the WHOQOL-BREF and reinforce its intended dimensional structure [8,32]. Although CFA generally supports the 4-domain model (physical health, psychological health, social relationships, and environment domains), some studies have questioned this structure, reporting that certain items do not clearly discriminate between domains or correlate more strongly with an unintended domain [32,34,36,38]. Exploratory factor analysis in a Norwegian study also resulted in a 4-component solution, partially supporting the established domain structure [8]. Some studies suggest that the physical health domain contributes most significantly to overall QoL [33].

    The WHOQOL-BREF has demonstrated strong psychometric properties across various countries and cultures. Research supports its discriminant validity, content validity, internal consistency, and test-retest reliability across different cultural settings, suggesting its suitability for cross-cultural comparisons [4,8,36,38,40]. The instrument has been translated and adapted for multiple languages, including Polish [6], Korean [33], Spanish [35,40], Portuguese [41], Thai [38], Bahasa Indonesia [42], Mongolian [43], Persian [39], Danish [32], Norwegian [8], and French [9]. The translation process generally adheres to rigorous methodologies, such as forward and backward translation and cultural adaptation procedures. Some adaptations have been proposed to enhance cultural relevance, including the incorporation of additional items related to work satisfaction, social activities, and nutrition [36]. While these modifications may improve local applicability, they could also impact comparability across studies [40].

    In studies conducted within the general population, the WHOQOL-BREF has been used to establish normative QoL scores, facilitating demographic comparisons [7,9,44]. Factors such as age, sex, education level, and health status have been identified as influential [4,7,9,32,42,44,45]. For instance, some studies suggest that female caregivers report higher social QoL [26,46], while male caregivers tend to report better psychological QoL [7,9,46]. Physical health scores typically decline with age, reflecting the natural progression of age-related health issues [3,4,46,47].

    In clinical settings, the WHOQOL-BREF has been validated or used for various disease groups, including cancer, chronic conditions, mental disorders, HIV/AIDS, Huntington disease, Prader-Willi syndrome, hemophilia, neurofibromatosis, rheumatoid arthritis, and spinal cord injury [4,30,31,34,36,48-54]. It serves as a valuable tool for evaluating the impact of illness on QoL and monitoring treatment effectiveness [4,28]. However, some validation studies have raised concerns regarding the internal consistency of the social relationships domain [8,29]. The instrument’s generic nature allows for comparisons across different medical conditions, ensuring broad applicability in health research. Factorial invariance testing has confirmed that the WHOQOL-BREF consistently measures QoL across different patient groups [4,8,34].

    Despite its strengths, certain limitations of the WHOQOL-BREF should be acknowledged. The social relationships domain has exhibited weaker reliability in some studies, suggesting a need for refinement or supplementation with additional items. While the environment domain is a notable strength of the instrument, some researchers have recommended incorporating more sensitive response options to improve measurement precision [6,28,29,46].

    The WHOQOL-BREF’s reliance on self-report data enhances respondent acceptability but also introduces potential biases, such as social desirability and response tendencies. Adherence to standardized scoring guidelines is essential for ensuring accurate interpretation, and researchers should consider variations in response patterns across different populations [6,29,32].

    In our study, QoL domain scores were normalized to a 0‐100 scale. Factor loadings ranged from 0.363 to 0.801, indicating varying contributions of items to their respective constructs. The psychological health domain demonstrated the highest mean score (mean 54.9, SE 0.59), while the physical health domain had the lowest (mean 50.2, SE 0.59). Normality tests showed slight deviations, particularly in the psychological health and social relationships domains, though skewness and kurtosis values remained within acceptable limits. Minimal floor and ceiling effects ensured adequate response distribution. QoL norms were established for a Polish population of caregivers for individuals with RDs, stratified by sex and age group. Male caregivers generally reported higher physical and psychological health scores than female caregivers. Younger female caregivers (16‐29 years) exhibited the lowest scores in several domains, suggesting potential vulnerabilities in social and psychological well-being. These findings highlight disparities related to caregiving burden, sex, and age-related factors.

    Limitations

    It is important to consider the limitations of this study before interpreting its results. First, although 942 caregivers replied and completed the survey, the number of caregivers of persons with RDs in Poland is significantly higher. It should be noted, however, that although it can be difficult to extend the results to the total population of caregivers of persons with RDS in Poland, to date, there is no register of individuals with rare conditions in the country. Second, since convenience sampling was used in this survey and the study sample was self-selected, it could further compromise the sample’s representativeness and the results’ generalizability. Third, since caregivers of persons with different RDs took part in the study, there is a possible bias related to challenges related to different conditions, symptoms, and prognoses. However, since most RDs are small in numbers, it would be difficult, if possible at all, to validate the questionnaire for a single RD. Moreover, despite some differences in caregivers’ experiences, numerous previous studies demonstrated that most parents of persons with RDs face similar challenges and express similar needs. Consequently, we believe that the results may still apply to the entire population of family caregivers of persons with RDs in Poland. Especially because the sample is quite diverse, encompassing both mothers and fathers as well as various age groups. Fourth, the self-administering nature of the WHOQOL-BREF is part of its design. However, although the administration may elicit varying degrees of true responses, this bias is consistent across all questionnaires and has no bearing on the accuracy of the psychometric analyses, which are primarily comparative in nature. Fifth, we gathered our data before the Rare Disease Plan for 2024‐2025 was formally approved by the Council of Ministers in August 2024. Sixth, a comparable sample of caregivers of healthy individuals or those experiencing more common chronic diseases could have been beneficial to the study. Seventh, because the study was conducted as a web-based survey, there is a risk that it did not reach caregivers who lived in distant areas without internet access, who were hesitant to use technological devices and social media, or who did not belong to digital associations, foundations, and organizations of patients with RDs or support groups that aided in collecting the data. Consequently, while there is no direct generalizability of the results shown here to other cross-national samples, it is challenging to evaluate bias and the causes of nonresponses when using web-based survey data. Eighth, a potential bias is also present because only 130 fathers responded to the survey. However, it should be explained that while the sample was obtained through convenience sampling, it is well-documented that in the population of family caregivers, there is a significant underrepresentation of male caregivers. Thus, while these sex differences in caregiving could affect how respondents report their QoL, particularly in areas like psychological health and social relationships due to the small number of male respondents, sex-based factor analysis was not possible. Future research should ensure more balanced sex representation and explore sex differences in WHOQOL-BREF performance. Moreover, the 2006 Polish validation of WHOQOL-BREF did not account for sex, age differences, or caregivers of individuals with RDs, highlighting the need for validation in specific populations and subgroup adaptations. Another limitation of this study is the inclusion of caregivers of individuals with 158 different RDs, which prevented detailed clinical characterization of care recipients. However, only some syndromes, that is, Dravet, Angelman, Williams, 22q11DS, and Duchenne or Becker muscular dystrophy, were represented by multiple caregivers; most conditions had only a few or even single respondents. This reflects the nature of rare, ultrarare, and hyperrare disorders, which affect very small patient populations and make it difficult to validate any tool. Future studies should consider focusing on more homogeneous caregiver groups. Next, since no other QoL instrument has ever been validated in the population of family caregivers of persons with RDs in Poland, this lack of external validation constitutes a limitation of our study and highlights the need for future research dedicated specifically to this group. Finally, this study is also limited by the WHOQOL-BREF’s potential insufficiency in capturing social aspects of caregiving; future research should consider using complementary tools like the Zarit Burden Interview.

    Conclusions

    The WHOQOL-BREF remains a reliable and valid instrument for assessing QoL across diverse populations. Its 4D structure is robust, and normative data provide valuable benchmarks for assessing QoL in specific groups, such as caregivers. Future research should focus on refining the social relationships domain and addressing minor fit inconsistencies to enhance the scale’s applicability further. An important question arises regarding whether the social relationships domain, due to inherent differences between societies, patient groups, and caregivers of various conditions, can be conceptualized as a universal construct. While the WHOQOL-BREF remains a valuable tool for assessing QoL in diverse populations, careful consideration of item profiles and potential supplementary modules for specific age groups may further optimize its utility.

    Acknowledgments

    The authors thank all the caregivers who participated in the study. No generative artificial intelligence tool was used in the writing of this manuscript, calculation, or visualizing the study results. All text, calculation, table, and figures were prepared by the authors themselves.

    Data Availability

    The datasets generated or analyzed during this study are not publicly available due to reasons of sensitivity but are available from the corresponding author on reasonable request.

    Authors' Contributions

    JD and DW conceptualized the study. JD, PJ, and DW developed the methodology. JD collected the data. DW curated the data and contributed to validation. PJ performed the formal analysis, software development, validation, and visualization. JD, PJ, and DW had full access to the data, wrote the original draft, and approved the final manuscript. JD administrated and supervised the study. All authors contributed equally to this work.

    Conflicts of Interest

    None declared.

    Checklist 1

    STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist.

    DOCX File, 34 KB
    1. The World Health Organization Quality of Life assessment (WHOQOL): position paper from the World Health Organization. Soc Sci Med. Nov 1995;41(10):1403-1409. [CrossRef] [Medline]
    2. The World Health Organization Quality of Life Assessment (WHOQOL): development and general psychometric properties. Soc Sci Med. Jun 1998;46(12):1569-1585. [CrossRef] [Medline]
    3. Saxena S, Carlson D, Billington R, WHOQOL Group. World Health Organisation Quality Of Life. The WHO Quality of Life assessment instrument (WHOQOL-Bref): the importance of its items for cross-cultural research. Qual Life Res. 2001;10(8):711-721. [CrossRef] [Medline]
    4. Hawthorne G, Herrman H, Murphy B. Interpreting the WHOQOL-Brèf: preliminary population norms and effect sizes. Soc Indic Res. May 2006;77(1):37-59. [CrossRef]
    5. ten Hoedt AE, Maurice-Stam H, Boelen CCA, et al. Parenting a child with phenylketonuria or galactosemia: implications for health-related quality of life. J Inherit Metab Dis. Apr 2011;34(2):391-398. [CrossRef] [Medline]
    6. Jaracz K, Kalfoss M, Górna K, Baczyk G. Quality of life in Polish respondents: psychometric properties of the Polish WHOQOL-Bref. Scand J Caring Sci. Sep 2006;20(3):251-260. [CrossRef] [Medline]
    7. West EC, Williams LJ, Stuart AL, Pasco JA. Quality of life in south-eastern Australia: normative values for the WHOQOL-BREF in a population-based sample of adults. BMJ Open. Dec 10, 2023;13(12):e073556. [CrossRef] [Medline]
    8. Hanestad BR, Rustøen T, Knudsen O, Lerdal A, Wahl AK. Psychometric properties of the WHOQOL-BREF questionnaire for the Norwegian general population. J Nurs Meas. 2004;12(2):147-159. [CrossRef] [Medline]
    9. Baumann C, Erpelding ML, Régat S, Collin JF, Briançon S. The WHOQOL-BREF questionnaire: French adult population norms for the physical health, psychological health and social relationship dimensions. Rev Epidemiol Sante Publique. Feb 2010;58(1):33-39. [CrossRef] [Medline]
    10. Angelis A, Tordrup D, Kanavos P. Socio-economic burden of rare diseases: a systematic review of cost of illness evidence. Health Policy. Jul 2015;119(7):964-979. [CrossRef] [Medline]
    11. Walkowiak D, Domaradzki J. Parental experiences and needs of caring for a child with 22q11.2 deletion syndrome. Orphanet J Rare Dis. Dec 4, 2023;18(1):379. [CrossRef] [Medline]
    12. Domaradzki J, Walkowiak D. Quality of life and caregiving burden associated with parenting a person with Duchenne/Becker muscular dystrophy in Poland. Orphanet J Rare Dis. Nov 30, 2024;19(1):450. [CrossRef] [Medline]
    13. Michalík J. Rare diseases and the quality of life of caregivers. Soc Welf. Jun 29, 2012;2(1):8-17. [CrossRef]
    14. Walkowiak D, Domaradzki J, Mozrzymas R, Kałużny Ł, Walkowiak J. Navigating the unique challenges of caregiving for children with rare diseases: are the care experiences of all caregivers the same? A focus on life-limiting rare diseases. J Clin Med. Aug 1, 2024;13(15):4510. [CrossRef] [Medline]
    15. Domaradzki J, Walkowiak D. Emotional experiences of family caregivers of children with Dravet syndrome. Epilepsy Behav. May 2023;142:109193. [CrossRef] [Medline]
    16. Chung CCY, Ng NYT, Ng YNC, et al. Socio-economic costs of rare diseases and the risk of financial hardship: a cross-sectional study. Lancet Reg Health West Pac. May 2023;34:100711. [CrossRef] [Medline]
    17. Ouattara A, Resseguier N, Cano A, et al. Individual and family determinants for quality of life in parents of children with inborn errors of metabolism requiring a restricted diet: a multilevel analysis approach. J Pediatr. Mar 2023;254:39-47. [CrossRef] [Medline]
    18. Boettcher J, Denecke J, Barkmann C, Wiegand-Grefe S. Quality of life and mental health in mothers and fathers caring for children and adolescents with rare diseases requiring long-term mechanical ventilation. Int J Environ Res Public Health. Dec 2, 2020;17(23):33276595. [CrossRef] [Medline]
    19. Bamber MD, Mahony H, Spratling R. Mothers of children with special health care needs: exploring caregiver burden, quality of life, and resiliency. J Pediatr Health Care. 2023;37(6):643-651. [CrossRef] [Medline]
    20. Trickett J, Heald M, Oliver C. Sleep in children with Angelman syndrome: parental concerns and priorities. Res Dev Disabil. Oct 2017;69:105-115. [CrossRef] [Medline]
    21. Iskrov G, Stefanov R, Ferrelli RM. Health systems for rare diseases: financial sustainability. Ann Ist Super Sanita. 2019;55(3):270-275. [CrossRef] [Medline]
    22. Filosto M, Mancuso M, Federico A, Padovani A. Unravelling the mysteries: a reflection on rare neurological diseases. Neurol Sci. Mar 2024;45(3):833-835. [CrossRef] [Medline]
    23. Feudtner C, Nye RT, Boyden JY, et al. Association between children with life-threatening conditions and their parents’ and siblings’ mental and physical health. JAMA Netw Open. Dec 1, 2021;4(12):e2137250. [CrossRef] [Medline]
    24. Guarany NR, Vanz AP, Wilke M, Instituto Genética Para Todos (IGPT), et al. Mucopolysaccharidosis: caregiver quality of life. J Inborn Errors Metab Screen Latin American Society Inborn Errors and Neonatal Screening (SLEIMPN). 2015;3:e150001. [CrossRef]
    25. Silva IMW, Gil-da-Silva-Lopes VL. Comprehensive insights into health services accessibility and quality of life of families with individuals with 22q11.2 deletion syndrome in Brazil. Orphanet J Rare Dis. Jul 6, 2024;19(1):255. [CrossRef] [Medline]
    26. von Steinbüchel N, Lischetzke T, Gurny M, Eid M. Assessing quality of life in older people: psychometric properties of the WHOQOL-BREF. Eur J Ageing. Jun 2006;3(2):116-122. [CrossRef] [Medline]
    27. von Elm E, Altman DG, Egger M, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. Oct 20, 2007;335(7624):806-808. [CrossRef] [Medline]
    28. Development of the World Health Organization WHOQOL-BREF quality of life assessment. The WHOQOL Group. Psychol Med. May 1998;28(3):551-558. [CrossRef] [Medline]
    29. Young CA, Mills R, Al-Chalabi A, et al. Measuring quality of life in ALS/MND: validation of the WHOQOL-BREF. Amyotroph Lateral Scler Frontotemporal Degener. Jun 27, 2020;21(5-6):364-372. [CrossRef] [Medline]
    30. Pietrzykowski MO, Vranceanu AM, Macklin EA, Mace RA. Minimal clinically important difference in the World Health Organization Quality of Life Brief (WHOQOL-BREF) for adults with neurofibromatosis. Qual Life Res. May 2024;33(5):1233-1240. [CrossRef] [Medline]
    31. Alilović M, Peros-Golubicić T, Radosević-Vidacek B, et al. WHOQOL-BREF questionnaire as a measure of quality of life in sarcoidosis. Coll Antropol. Sep 2013;37(3):701-706. [Medline]
    32. Noerholm V, Groenvold M, Watt T, Bjorner JB, Rasmussen NA, Bech P. Quality of life in the Danish general population—normative data and validity of WHOQOL-BREF using Rasch and item response theory models. Qual Life Res. Mar 2004;13(2):531-540. [CrossRef] [Medline]
    33. Min SK, Kim KI, Lee CI, Jung YC, Suh SY, Kim DK. Development of the Korean versions of WHO Quality of Life scale and WHOQOL-BREF. Qual Life Res. Sep 2002;11(6):593-600. [CrossRef] [Medline]
    34. Yao G, Wu CH. Factorial invariance of the WHOQOL-BREF among disease groups. Qual Life Res. Oct 2005;14(8):1881-1888. [CrossRef] [Medline]
    35. Lucas-Carrasco R. The WHO Quality of Life (WHOQOL) questionnaire: Spanish development and validation studies. Qual Life Res. Feb 2012;21(1):161-165. [CrossRef] [Medline]
    36. Ginieri-Coccossis M, Triantafillou E, Tomaras V, Soldatos C, Mavreas V, Christodoulou G. Psychometric properties of WHOQOL-BREF in clinical and health Greek populations: incorporating new culture-relevant items. Psychiatriki. 2012;23(2):130-142. [Medline]
    37. Krägeloh CU, Kersten P, Rex Billington D, et al. Validation of the WHOQOL-BREF quality of life questionnaire for general use in New Zealand: confirmatory factor analysis and Rasch analysis. Qual Life Res. Aug 2013;22(6):1451-1457. [CrossRef] [Medline]
    38. Kangwanrattanakul K, Krägeloh CU. Psychometric evaluation of the WHOQOL-BREF and its shorter versions for general Thai population: confirmatory factor analysis and Rasch analysis. Qual Life Res. Feb 2024;33(2):335-348. [CrossRef] [Medline]
    39. Yousefy AR, Ghassemi GR, Sarrafzadegan N, Mallik S, Baghaei AM, Rabiei K. Psychometric properties of the WHOQOL-BREF in an Iranian adult sample. Community Ment Health J. Apr 2010;46(2):139-147. [CrossRef] [Medline]
    40. Benitez-Borrego S, Guàrdia-Olmos J, Urzúa-Morales A. Factorial structural analysis of the Spanish version of WHOQOL-BREF: an exploratory structural equation model study. Qual Life Res. Oct 2014;23(8):2205-2212. [CrossRef] [Medline]
    41. Silva WD, Bonafé FSS, Marôco J, Maloa BFS, Campos J. Psychometric properties of the World Health Organization Quality of Life Instrument-Abbreviated version in Portuguese-speaking adults from three different countries. Trends Psychiatry Psychother. 2018;40(2):104-113. [CrossRef]
    42. Purba FD, Hunfeld JAM, Iskandarsyah A, et al. Quality of life of the Indonesian general population: test-retest reliability and population norms of the EQ-5D-5L and WHOQOL-BREF. PLoS One. 2018;13(5):e0197098. [CrossRef] [Medline]
    43. Bat-Erdene E, Hiramoto T, Tumurbaatar E, et al. Quality of life in the general population of Mongolia: normative data on WHOQOL-BREF. PLoS One. 2023;18(9):e0291427. [CrossRef] [Medline]
    44. Cruz LN, Polanczyk CA, Camey SA, Hoffmann JF, Fleck MP. Quality of life in Brazil: normative values for the WHOQOL-bref in a southern general population sample. Qual Life Res. Sep 2011;20(7):1123-1129. [CrossRef] [Medline]
    45. Perera HN, Izadikhah Z, O’Connor P, McIlveen P. Resolving dimensionality problems with WHOQOL-BREF item responses. Assessment. Dec 2018;25(8):1014-1025. [CrossRef] [Medline]
    46. Skevington SM, Lotfy M, O’Connell KA, WHOQOL Group. The World Health Organization’s WHOQOL-BREF quality of life assessment: psychometric properties and results of the international field trial. A report from the WHOQOL group. Qual Life Res. Mar 2004;13(2):299-310. [CrossRef] [Medline]
    47. Baumann M, Couffignal S, Le Bihan E, Chau N. Life satisfaction two-years after stroke onset: the effects of gender, sex occupational status, memory function and quality of life among stroke patients (Newsqol) and their family caregivers (Whoqol-bref) in Luxembourg. BMC Neurol. Sep 25, 2012;12(1):105. [CrossRef] [Medline]
    48. Taylor WJ, Myers J, Simpson RT, McPherson KM, Weatherall M. Quality of life of people with rheumatoid arthritis as measured by the World Health Organization Quality of Life Instrument, short form (WHOQOL-BREF): score distributions and psychometric properties. Arthritis Rheum. Jun 15, 2004;51(3):350-357. [CrossRef] [Medline]
    49. Manee F, Ateya Y, Rassafiani M. A comparison of the quality of life of Arab mothers of children with and without chronic disabilities. Phys Occup Ther Pediatr. Aug 2016;36(3):260-271. [CrossRef] [Medline]
    50. Blay SL, Marchesoni MSM. Association among physical, psychiatric and socioeconomic conditions and WHOQOL-Bref scores. Cad Saude Publica. Apr 2011;27(4):677-686. [CrossRef] [Medline]
    51. Junca E, Pino M, Santamaría-García H, Baez S. Brain, cognitive, and physical disability correlates of decreased quality of life in patients with Huntington’s disease. Qual Life Res. Jan 2023;32(1):171-182. [CrossRef] [Medline]
    52. Trindade GC, Viggiano LGDL, Brant ER, et al. Evaluation of quality of life in hemophilia patients using the WHOQOL-bref and Haemo-A-Qol questionnaires. Hematol Transfus Cell Ther. 2019;41(4):335-341. [CrossRef] [Medline]
    53. Chiu VY, Tsai LP, Wei JT, Tzeng IS, Wu HC. Motor performance in Prader-Willi syndrome patients and its potential influence on caregiver’s quality of life. PeerJ. 2017;5:e4097. [CrossRef] [Medline]
    54. Ihara H, Ogata H, Sayama M, et al. QOL in caregivers of Japanese patients with Prader-Willi syndrome with reference to age and genotype. Am J Med Genet A. Sep 2014;164A(9):2226-2231. [CrossRef] [Medline]

    ‎
    CFA: confirmatory factor analysis
    CFI: Comparative Fit Index
    HRQoL: health-related quality of life
    QoL: quality of life
    RD: rare disease
    RMSEA: root-mean-square error of approximation
    SRMR: standardized root-mean-square residual
    STROBE: Strengthening the Reporting of Observational Studies in Epidemiology
    TLI: Tucker-Lewis Index
    WHO: World Health Organization
    WHOQOL: World Health Organization Quality of Life
    WHOQOL-BREF: World Health Organization Quality of Life-BREF

    Edited by Amaryllis Mavragani; submitted 12.02.25; peer-reviewed by Adekunle Adeoye, Miguel Canete-Lairla; final revised version received 16.04.25; accepted 08.05.25; published 18.07.25.

    Copyright

    © Piotr Jabkowski, Jan Domaradzki, Dariusz Walkowiak. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 18.7.2025.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.