Background

Quality of life (QoL) is defined by the World Health Organization (WHO) as ''the perception that an individual has of his or her place in life, within the context of the culture and system values in which he or she lives, and in relation to the objectives, expectations, standards and concerns of this individual'' [1]. Health-related quality of life' (HRQoL) [2, 3] can be defined ''as an integrative measure of physical and emotional well-being, level of independence, social relationships and their relationship to salient features of their environment'' [1]. The conceptualization of HRQoL is both objective and subjective, so its measurement requires reference to varied and complex areas, depending on the perspective. For example, social workers will assess QoL from a different perspective than medical workers. HRQoL measurement can also be very personal because experiences, beliefs, and expectations and perceptions influence how individuals think and behave [4].

HRQoL is a multidimensional concept that relates specifically to a person's health, to the measure of its functioning, well-being and general health perception in physical, psychological, and social domains [2]. HRQoL measures are used to determine the burden of disease in economic analyses [5, 6] and have become an important target in medical care for assessing treatment outcomes in chronic disease and an important outcome criterion in randomised clinical trials, especially oncology [1]. In addition, HRQoL instruments can be used in medical practice to improve the physician-patient relationship, in health services evaluation, in research and in policy making.

Many HRQOL instruments, both generic and specific for various illnesses, have been developed to survey the various domains of life that ill health can affect [7].

Most generic instruments are for adults, such as the WHOQOL [8], the Sickness Impact Profile [9], the Nottingham Health Profile [10], the SF-36 [11], and the Duke Health Profile (DUKE) [12–14]. However, whether such generic instruments are suitable for young French people is unknown. To compare the adolescent and adult quality of life, the French Committee for Health Promotion, in 1998, 2000 and in 2005 [15], used a version of the DUKE suited to assess quality of life in the 12-19 age group.

The DUKE is a cross-culturally adapted, valid and useful measure of perceived health in adolescents and adults [12]. One of the obstacles to the success of large surveys is the extensive time needed to complete them (by phone conversations or self-administered). The DUKE is a 17-item short questionnaire, self-administered or interviewer-administered, developed and validated in primary care to measure patient-reported HRQoL, or functional health status, during 1 week [13, 14] and may be more suitable than the SF-36 for older inpatients [16–18]. Its feasibility and acceptability were reported to be good for patients with dementia [19]. As well, another study found the DUKE significantly better accepted than the SF-36 by young patients [20]. Finally, the DUKE allows for briefly exploring dimensions of self-perceived health such as self-esteem, anxiety and depression not proposed by other tools [21].

There is an interest in finding a simple short, self-reporting measure of HRQoL in healthy adolescents that is in the French language. The DUKE score has been used primarily for research in the clinical setting, both as a predictor of health-related outcomes and as an outcome [22–24]. The original DUKE was developed in English (United States) and was validated primarily in the United States. Subsequently, the DUKE has been translated into 17 other languages and language variations such as Afrikaans, Chinese, Dutch, Dutch (Belgium), English (UK), French, French (Canada), German, Italian, Korea, Norwegian, Polish, Portuguese, Spanish, Swedish, Thai and Vietnamese. It has been translated in French and used extensively by the Public Health School of Nancy (France) [12, 25–29].

Medical and scientific committees need validated instruments to assess HRQoL, but general population norms are lacking, which limits their full use in research and clinical practice. Community norms of HRQoL are important because they provide a base level of HRQoL to compare illness groups or individuals' HRQoL to expected values. To our knowledge, norms for the DUKE for all countries are lacking.

We aimed to use the DUKE to determine HRQoL norms for French adolescents and adults and analyze these by gender, age and self-reported chronic disease.

Methods

Data source

Since 1992, the French National Health Barometer, a 5-year periodic study by the French National Institute for Prevention and Health Education (INPES), has surveyed behaviours, attitudes, opinions and knowledge about health (e.g., alcohol consumption, tobacco use, drug consumption, physical activity) and evolution of the health of adolescents and adults in France. The whole questionnaire includes more than 400 questions. Data for the 2005 National Health Barometer were collected between October 14, 2005 and February 12, 2005. This survey was carried out in France by use of a computer-assisted telephone interview (CATI) system with a sample of 30,514 people aged 12 to 75 years who spoke French. Households received a letter in advance to explain the purpose of the survey and to encourage people in the household to take part. The eligible subject within each household whose next birthday was nearest the interview day was selected to answer the questions [30]. All data collected were anonymous and self-reported. Subjects were asked to isolate themselves before the interview began. The mean duration of an interview was about 40 minutes for landline phones.

Young people (younger than 15 years) had to be accompanied by their mother or father to participate. Parents were asked to consent to their child's participation and that the child could be isolated to speak more freely.

The INPES commissioned the "EA4360 Apemac", a French research team specialised in HRQoL studies (School of Public Health, Nancy, France), to analyse the data and determine norms [15].

This population-based survey was approved by the French National Institutional Review Board (Commission Nationale Informatique et Liberté).

Sampling

Of 30,514 participants in the 2005 Health Barometer survey, 26,672 were contacted by landline phone to answer all questions of the Health Barometer, and 3,842 persons, without a landline phone, were contacted by their mobile phone to answer questions related only to tobacco, alcohol and illegal drug use because by the year 2000, more people had only a mobile phone. When the Barometer started, questioning all participants by mobile phone for more than 20 minutes was difficult (problems with the battery, attention, satellite range). So, the researchers decided to ask questions about sociodemographic characteristics and tobacco, alcohol, and illegal drug consumption only to limit the duration of the interview.

Among the 26,672 participants contacted by landline phone, 17,783 (two-thirds of the sample) were randomly selected to participate in the QoL survey by the DUKE. Among these, 17,733 responded to the DUKE. The 8,889 participants not randomized responded to another HRQoL questionnaire (WHOQOL-brief) (see figure 1).

Figure 1
figure 1

Selection of the participants in the health-related quality-of-life survey.

Full size image

Duke Health Profile questionnaire

HRQoL was assessed by use of a French validated version of the DUKE (Table 1), a 17-item generic self-reporting instrument, with question responses according to a 3-point Likert scale, which covers a 1-week time frame [12]. The DUKE includes 10 domains. Six domains are about health function: physical health (items 8-12), mental health (items 1, 4, 5, 13, 14), social health (items 2, 6, 7, 15, 16), general health (aggregation of physical, mental and social health measures to indicate overall well-being) (15 items), perceived health (item 3) and self-esteem (items 1, 2, 4, 6, 7), with high scores indicating better HRQoL; and 4 are about health dysfunction: anxiety (items 2, 5, 7, 10, 12, 14), depression (items 4, 5, 10, 12, 13), pain (item 11) and disability (item 17), with high scores indicating greater dysfunction. The DUKE is suitable for computerised telephone administration by a trained interviewer. It can be completed in a short time and has good acceptability [14, 31].

Table 1 Content of the Duke Health Profile questionnaire
Full size table

Other data collected

Like many other authors [7, 32], we considered age, gender and self-reported chronic disease to determine norms.

Statistical analysis

Questionnaires were coded and calculated according to instructions in the DUKE manual [14]. The score for each dimension is the sum of the scores for the items, standardized from 0 to 100. For the 6 health dimension scores, 100 indicates the best HRQoL, whereas for the 4 dysfunction dimension scores, 100 indicates the greatest dysfunction. Missing dimension scores were imputed if scores were missing for < 50% of items for a dimension, using the mean score of the items completed within that dimension. Scores were analysed for the whole sample and then after stratification by gender, age and self-reported chronic disease.

Norms for the DUKE for French adolescents and adults are presented as means, standard deviation (SD), standard error of the mean (SEM), median (interquartile range), minimum, maximum, and percentage of floor and ceiling effect. In this study, with lack of consensus, floor and ceiling effects were considered present if more than 10% of the respondents achieved the highest or lowest score, and strong effects if more than 30% of the respondents achieved the highest or lowest score.

Qualitative variables were compared by Student's t test, with Bonferroni correction. Interaction of gender, age groups and self-perceived chronic disease with HRQoL was analyzed by linear regression models. Only strong interactions are presented (p < 0.01).

Data and t test values were weighted by the number of eligible persons in the household and by the French population structure imputed from 1999 INSEE (National Institute for Statistic and Economic surveys) National Census data. In this way, the sample was representative of the French general population between 12 and 75 years old who speak French and have a landline phone.

Internal consistency was assessed by Cronbach's α, an inter-item correlation statistic ranging from 0-1, except for perceived health, pain and disability domains, which contain only one item. Higher values indicate that items on a domain are correlated and therefore the scale measures an underlying single dimension of the questionnaire. A Cronbach α of ≥ 0.5 is usually considered acceptable [33], but Nunnally recommends values of ≥ 0.7 [34].

Statistical analysis involved use of SAS v9.1 (SAS Inc., Cary, NC).

Results

Description of the sample

Table 2 shows the characteristics of the observed sample and after weighting by gender, age, geographic area and size of community. The response rate to the HRQoL survey was close to 100%. Among 17,783 randomly selected people, completed questionnaires were obtained from 17,733 subjects questioned by the CATI system. Participants of the HRQoL survey (n = 17,733) and people not randomly selected (n = 9,539) did not differ in age, gender or self-reported chronic disease. After weighting by the 1999 INSEE National Census data, 49.1% of the sample were males. Adolescents (12-17 years old) represented 10.5% of the sample, young adults (18-24 years old) 11.1% and elderly people (65-75 years old) 12%. Self-reported chronic disease prevalence was 21.7%.

Table 2 Characteristics of the sample
Full size table

Internal consistency

Internal consistency ranged from poor to good. The Cronbach α was 0.34 for social health, 0.46 for self-esteem, 0.57 for anxiety, 0.61 for depression, 0.62 for physical health, 0.63 for mental health, and 0.71 for general health. The Cronbach α for adolescents was lower than or equal to that for adults for dimensions.

Description of norms by gender, age and self-reported chronic disease

The HRQoL norms globally, by gender and by age are in Table 3. In summary, mean function scores for physical, mental, social, and general health, as well as perceived health and self-esteem, were 72.3 (SEM 0.2), 74.6 (0.2), 66.8 (0.1), 71.3 (0.1), 71.3 (0.3), 76.5 (0.1), respectively. Dysfunction scores for anxiety, depression, pain and disability were 30.9 (0.1), 27.6 (0.2), 34.3 (0.3), 3.1 (0.1), respectively. Scores for men were always higher than those for women, except for social health and disability dimensions.

Table 3 HRQoL norms* in French general population from 12 to 75 years old (n = 17,733)
Full size table

Mean disability, depression, self-esteem and mental health scores were low for men (2.8 ± 15.6, 21.4 ± 19.5, 78.8 ± 18.4, 78.6 ± 19.6, respectively), and disability, mental health, self-esteem and physical health scores were low for women (3.5 ± 14.9, 74.6 ± 20.2, 74.4 ± 17.2, 72.3 ± 20.3, respectively). The most affected dimension was social health for men (64.4 ± 19.2) and pain for women (38.31 ± 33.4).

Tables 4 and 5 provide the HRQoL norms by gender, age and self-reported chronic disease. Self-reported chronic disease was associated with a mean decrease of 12.5 points in the score for physical health, 4.6 for mental health, 2.3 for social health, 6.5 for general health, 19.3 for perceived health, and 3.2 for self-esteem and a mean increase of 4.8 points in the score for anxiety, 5.1 for depression, 18.4 for pain and 2.5 for disability (for the last 4 dimensions, the interpretation of the score is inversed). All differences were statistically significant (p < 0.001), whatever the gender and age. After adjustment for gender and age, significant interactions were found between self-reported chronic disease and age for perceived health (p < 0.0001) and depression (p < 0.0001): increase in age had a lower effect on HRQoL score in the group with a self-reported chronic disease. We also observed a significant interaction between gender and self-reported chronic disease, with greater effects for women than men in score for physical health (-14 points and -11 points, respectively, p = 0.003), general health (-7 points and -5.7 points, respectively, p = 0.002), and pain (+23.6 points and 15.9 points, respectively, p = 0.001).

Table 4 HRQoL norms* in French general population from 12 to 75 years old with self-reported chronic disease (n = 4,153)
Full size table
Table 5 HRQoL norms* in French general population from 12 to 75 years old with no self-reported chronic disease (n = 13559)
Full size table

We found a floor effect for anxiety, perceived health and depression scores (6.4, 11.3 and 12.4%, respectively) and a strong floor effect for pain and disability scores (44.6 and 95.4%, respectively) (Table 3). Ceiling effects were moderate for physical health (11.3%), self-esteem (16%) and mental health (16.2%) and strong for perceived health (53.9%).

Discussion

The DUKE questionnaire has been used for many years to describe HRQoL in different patient populations but has not been used for a general population. This is the first study presenting norms for the DUKE for French adolescents and adults. These normative data will be useful to researchers who wish to use the DUKE for health assessment and to clinical practitioners in daily practice.

The production of HRQoL community norms is important because they provide expected reference values to evaluate groups or individuals' HRQoL. Norms allow for appreciating the impact of diseases on HRQoL by comparing patients' HRQoL with normative data. However, some authors have suggested that norm-based interpretation in this situation may be irrelevant [35, 36] because the impact of the disease could be underestimated. This situation would be the case mainly in longitudinal studies if patients changed their way of estimating HRQoL over time because of their experience with disease or treatment, the response-shift phenomenon. Humans actively construct meaning from their environment and display a range of cognitive mechanisms to continually adapt to changing circumstances. Response shift refers to a change in the meaning of one's evaluation of a construct as a result of a change in one's internal standards of measurement, values or construct definition. Therefore, people might give different answers on patient-reported outcome measures over time, because their HRQoL has changed and because they might have changed their perception on what health or HRQoL means to them [37, 38]. However, comparing values between patients and the general population can be problematic with scales that have been developed in a hospital setting, but is not the case for the DUKE.

In public health, the continual monitoring of population HRQoL with validated instruments gives public health agencies data on current health for assessing, protecting, and promoting population health. Tracking population HRQoL over time also helps identify health disparities, evaluate progress on achieving broad health goals, and inform healthy public policy makers. These applications complement those of clinical research and practice, where HRQOL assessment measures patient-reported outcomes from medical, surgical, and behavioural interventions. In epidemiological research, these measures are particularly relevant to the field of chronic disease epidemiology by providing direct evidence of the considerable population burden of long-term health conditions such as disability, arthritis, obesity, asthma or diabetes. As previously mentioned, clinicians and researchers should carefully define their research questions related to patient-reported outcomes before selecting the instrument to use, by structure and content criteria and perhaps according to the availability of normative data.

Methodological considerations

We found relatively low internal consistency and a strong floor effect with the DUKE. Similar limitations were reported in young people [39] and in dementia [16], and in the French validity study of a cohort of 963 people from the general population, in which the Cronbach α varied from 0.63 to 0.81 [12]. However, this limitation should be moderately weighed because the use of the Cronbach α to assess the psychometric qualities of a HRQoL questionnaire might be inappropriate when the construct validity generates dimensions with few items. The Cronbach α is sensitive to the number of items in the dimension; with increasing number of items, the Cronbach α is likely to increase. In addition, the lower the mean inter-item correlation, the lower the Cronbach α.

We also showed some moderate and high floor effects in dysfunction measures (anxiety, depression, pain and disability) of the DUKE, which indicates poor discrimination properties. This finding was not surprising in a sample from a general population, which is, on average, in good health. These dimension scores are probably sensitive to the impact of disease, as we observed in other studies in patient samples [21, 40].

The response rate of the 2005 Health Barometer telephone survey was about 64% (30,514 participants in the 2005 Health Barometer of almost 48,000 contacted), which is lower than the response rate of mail surveys. To be representative of French population, data collected from 2005 Health Barometer have been weighted by number of eligible persons in the household (and by the number of landline phones in the household) and imputed from 1999 INSEE National Census data on gender, age, geographic area and size of agglomeration. In this way, the sample used for this study was representative of these criteria of the French population aged 12 to 75 years old, who speak French and have a landline phone. Characteristics of subjects selected (n = 17,733) and not selected (n = 8,889) for the HRQoL survey group were similar, but despite these precautions and checks, we cannot totally exclude the existence of selection bias.

Finally, the "next-birthday" method used in this national survey [30] to select the person to answer the questions can generate a low "self-selection" phenomenon. However, the results of the selection obtained with this method were very close to those expected. We could have used the Kish method, but it requires, before the selection, describing exactly the whole family, more time and more risk of generating refusals than does the next-birthday method.

Conclusions

We present HRQoL norms for all dimensions of the DUKE for adolescents and adults in France. These norms could be used as a reference for other studies assessing HRQoL, for specific illnesses, and for international comparisons.