Pathways leading to self-perceived general health and overall quality of life in burned adults

burns 38 (2012) 1157–1164

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Pathways leading to self-perceived general health and overall quality of life in burned adults Asgjerd L. Moi a,b,*, Roy M. Nilsen c a

Faculty of Health and Social Sciences, Bergen University College, Bergen, Norway Department of Plastic Surgery and Burn Center, Haukeland University Hospital, Bergen, Norway c Centre for Clinical Research, Haukeland University Hospital, Bergen, Norway b

article info

abstract

Article history:

Purpose: The aim of the study was to explore pathways leading to self-perceived general

Received 21 February 2012

health and overall quality of life in burn patients.

Received in revised form

Materials and methods: Data on burn-specific health, generic health, overall quality of life,

23 April 2012

injury characteristics and socio-demographics were obtained from 95 adult burn patients

Accepted 6 May 2012

47.0 (23.8) [mean (SD)] months after injury. A theoretical path model was established based on the concepts of Wilson and Cleary’s model on health-related quality of life [1], and the proposed model was examined by structural equation modelling.

Keywords:

Results: Two main paths were identified, one leading to general health perception and the

Burns

other leading to overall quality of life. Together, direct and indirect paths explained 63% of

Quality of life

the variance of perceived general health and 43% of the variance in overall quality of life. The

Health status

total effects of the SF-36 domain Vitality on perceived general health and overall quality of

Patient-reported outcomes

life were 0.62 and 0.66, respectively. No statistically significant path could be revealed between general health perception and overall quality of life. Conclusion: The results indicate that self-perceived general health and overall quality of life are related but distinct constructs. Moreover, vitality seems to be an important factor for the perception of both general health and overall quality of life in burned adults. # 2012 Elsevier Ltd and ISBI. All rights reserved.

1.

Introduction

The quality of burn care has traditionally been related to mortality rates and length of hospital stays [2]. However, during the last decades, measures based on patient selfreports have gradually been established as important adjuncts [3,4], with quality of life used as an umbrella term, comprising a broad range of aspects of life after burn injury. In the 1980s, a burn-specific health scale (BSHS) was developed, and this questionnaire has later been used both in translated and modified versions [5–8]. The validated versions

of the BSHS have allowed for studies on burn patient outcome, and could also possibly be used for the study of the relative effectiveness of interventions. In addition, other burn patient outcome studies have used generic health status measures, also named health-related quality of life instruments [9–13], and questionnaires assessing overall quality of life in terms of satisfaction with life [12,14–16]. The use of generic health status and overall quality of life instruments allows for the comparison with other groups of patients or norm populations. Consequently, it may be of value to use disease-specific, generic health status and overall quality of life instruments in combination [17].

* Corresponding author at: Department of Nursing, Faculty of Health and Social Sciences, Bergen University College, Møllendalsveien 6, N-5009 Bergen, Norway. Tel.: +47 55587211. E-mail address: [email protected] (A.L. Moi). 0305-4179/$36.00 # 2012 Elsevier Ltd and ISBI. All rights reserved. http://dx.doi.org/10.1016/j.burns.2012.05.004

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In the burn literature, the concepts of health status, healthrelated quality of life, and quality of life seem to have been used interchangeably [18], and a recent review on core outcomes after burns called attention to the diversity of questionnaires and item contents being named ‘‘quality of life’’ [4]. This may be an obstacle for further understanding of burn patient reported outcomes and calls for more clarity in the form of conceptual definitions and models [19,20]. One such model was described by Wilson and Cleary [1], and in their model, health status and overall quality of life are separate concepts. We previously published data on burn-specific health, generic health and overall quality of life in a population of Norwegian burn patients [6,12,21]. The aim of this study was to use these data sets and the concepts of the Wilson and Cleary model to study pathways leading to self-perceived health and overall quality of life after burn. Structural equation modelling (SEM) was applied to unravel these pathways.

2.

Material and methods

2.1.

Participants, study design and ethics

As this study was part of a larger investigation, the sample characteristics have been described in detail elsewhere [6,12,21]. Briefly, all surviving patients (n = 189) aged 18 years or more that were hospitalized for burn injury at the national Burn Center, Haukeland University Hospital, Bergen from 1995 to 2000 were included. Of the 162 patients still alive at the time of inquiry in 2001–2002, 19 patients were excluded because they were not fluent in Norwegian (n = 10), had severe brain damage (n = 1) or dementia (n = 2), or could not be located (n = 6). Ninety-five of the 143 eligible patients agreed to take part in the questionnaire study (Table 1), giving a response rate of 66.4%. A comparison between responders and nonresponders on demographics and injury characteristics

Table 1 – Patient characteristics.

Demographics Age (years) Sex (M/F) Living alone Housing or economic problems Unemployeda Burn characteristics Flame burn Scald burn Electrical burn Contact burn TBSAb burn (%) FTIc (%) Inhalation injury Number of operations Length of hospital stay (days) a

N

%

78/17 25 11 19

82/18 26 12 20

56 23 13 3

59 24 14 3

Mean (SD) 43.7 (14.5)

18.5 (14.2) 7.4 (9.3) 9

10 1.8 (2.0) 23.2 (21.0)

Unemployed means out of work, receiving social security and being less than 67 years of age. b Total body surface area. c Full thickness injury.

revealed no significant differences between the two groups [6]. The mean time from injury to inclusion was 47 (SD: 23.8; range: 11–82) months. Data on the injury and treatment were obtained from the medical records of each participant, whereas demographic information and data on patients reported burn-specific health, generic health and overall quality of life were obtained from questionnaires completed by the participants at the time of query. The study was approved by the Regional Committee for Medical and Health Research Ethics, the Norwegian Registry of Data-Security and the Norwegian Directorate for Health and Social Welfare.

2.2.

Measurements of patient reported outcomes

Data on burn-specific health were obtained using the validated Norwegian version of the abbreviated Burn-Specific Health Scale (BSHS-N) [6,21]. This questionnaire comprises 80 items divided into four domains, asking for physical (20 items), mental (30 items), social (15 items) and general health (15 items). The first three domains comprise seven subdomains, i.e. Mobility and Self-care, Hand Function, Role Activities, Body Image, Affective, Family and Friends, and Sexual Activity. A summated score of two items (number 69 and 70) asking for symptoms of itch and pain respectively, was also computed and named PainItch. Responses to the items are given on a scale from 0 (extremely) to 4 (not at all). The answers were given as percentages of maximum scores (i.e. 0–100) for the whole questionnaire or each domain or subdomain, where higher scale scores indicated better burn-specific health. The Norwegian version of the SF-36 questionnaire and Norwegian norm data were used to assess burn patient reported generic health [12,22,23]. Recently, this instrument has also been validated in a burn population [17]. The SF-36 comprises 36 items addressing eight different health concepts, with the domains Physical Functioning, Role Physical, Bodily Pain, Mental Health, Role Emotional, Social Functioning, Vitality and General Health. The answers were transformed into scale scores 0–100 for each of the SF-36 domains, where higher scores represented better self-perceived health status. The Norwegian version of The Quality of Life Scale (QOLS) and Norwegian norm data were used to assess overall quality of life [12,24,25]. This questionnaire comprises 16 items asking for degree of satisfaction with important aspects of people’s lives. The answers are given on a 7 point scale, from very dissatisfied to very satisfied. The total sum score was transformed into a 0–100 scale score, and higher scores represented better overall quality of life. Health, measured by the questionnaires BSHS-N and SF-36, was defined according to the World Health Organisation as: ‘‘A state of complete physical, mental and social wellbeing and not merely the absence of disease and infirmity’’[26], whereas overall quality of life, assessed by QOLS, was operationally defined as: ‘‘Satisfaction with physical and material wellbeing, relations to others, social and community activities, personal development, fulfilment and recreation, as well as independence’’ [24]. The scores of BSHS-N, SF-36 and QOLS domains and subdomains used in the model testing are given in Table 2. The

burns 38 (2012) 1157–1164

Table 2 – Burn patient BSHS-N, SF-36 and QOLS domain and subdomain scores selected for the SEM analyses. N BSHS-Na

SF-36

QOLSb

Physical health Mobility and self-care Role activities Mental health Body image Affective General health PainItch Physical functioning Mental health Bodily pain Vitality Role emotional Role physical Social functioning General health

94 94 94 94 94 94 94 94 93 94 95 94 94 94 95 95 95

Mean observed score (SD) 88.8 94.0 73.8 83.8 86.0 83.1 81.3 78.8 78.9 75.3 72.5 57.0 73.1 68.0 79.2 67.4 70.4

(15.3) (13.1) (27.6) (17.4) (18.9) (18.6) (16.7) (22.1) (26.3) (19.1) (30.2) (23.1) (38.6) (40.9) (26.3) (25.8) (13.7)

a

The Norwegian version of the abbreviated burn-specific health scale. b The quality of life scale.

Functioning, comprising both physical, social, role and psychological functioning [1], was represented in the SEM analyses by the BSHS-N domain Physical Function, as well as the subdomains Mobility and Self-care and Role Activities. The SF-36 domains tested were Physical Functioning, Social Function, Role Emotional and Role Physical. General health perception was, according to Wilson and Cleary, a subjective rating integrating the other health concepts [1]. The SF-36 domain General Health represents the person’s evaluation of his/her health, and this domain was therefore chosen to represent self-perceived health in the path analyses. Overall quality of life has typically been evaluated as overall satisfaction or happiness with life as a whole [1,24]. Hence, data obtained by QOLS were used as indicator of overall quality of life in the SEM analyses. Factors of the persons and the environment that were tested in the model included the participants’ age and sex, and whether they were suffering from non-burn physical or psychological illness, were living alone, had housing or economic problems or were unemployed.

2.4. Cronbach’s alpha for total scores, as well as domain and subdomain scores of the three questionnaires ranged from 0.77 to 0.97. Detailed data on burn-specific health, generic health and overall quality of life in this population of Norwegian burn patients can be found elsewhere [6,12,21].

2.3.

Variables for the path analyses

The Wilson and Cleary model formed the conceptual basis for the exploration of pathways [1], as well as the selection of variables to be tested at each level of the model for health status and overall quality of life using SEM (see also below). Wilson and Cleary described quality of life as existing on a continuum of increasing biological, social and psychological complexity from biological factors influencing on symptoms which again influence on functional status and subsequently on general health perception and overall quality of life [1]. In addition, factors of the person and the environment may influence on all levels, from symptoms to overall quality of life. The model has been empirically tested, and it has also been used for clarifying purposes in other studies of quality of life [27,28]. In this study, we tested the following as indicators of biological and physiological variables related to the burn injury and its severity: Total body surface area burn, extent of full thickness injury, the presence or absence of inhalation injury, number of operations and length of hospital stays (Fig. 1). Symptoms were, according to the Wilson and Cleary model, interpreted as patient perception of an abnormal state, both physical and mental [1]. Consistently, data from the self-report questionnaires included at this level were those obtained from the General Health, Body Image, Affective domains and the composed PainItch of the BSHS-N. Moreover, the SF-36 domains Bodily Pain, Mental Health and Vitality were tested at this level.

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Statistical analyses

SEM was used to examine model pathways leading to overall quality of life. SEM is a powerful statistical tool for path analyses allowing for confirmatory testing of complex relationships [29]. In addition, the analyses contain explorative and model generating elements. In this study, a theoretical path model was established based on the concepts of the Wilson and Cleary model (Fig. 1) [1], and the proposed model was then tested via observed variable path analyses using maximum likelihood parameter estimation. Because the majority of the participants reported good health and quality of life, the data was negatively skewed. Consequently, all continuous variables except SF-36 domain Vitality and QOLS were transformed according to recommendations before model testing [30]. Then, we tested the proposed model with various combinations of variables at each conceptual level. Due to the sample size, the maximal number of variables included in each preliminary model tested was eight [31]. If collinearity between two variables was demonstrated, we kept the variable that gave the best model fit and omitted the other. When one conceptual level comprised more than one observed variable, a covariance between the estimated residuals, a disturbance correlation, was included in the model based on an assumption of at least one shared underlying cause [30]. Paths between all conceptual levels were tested, with the main direction of measurement being that of increasing bio-psycho-social complexity according to the Wilson and Cleary model. Only significant paths were retained in the model. The above described steps allowed for gradual improvement of the path model leading to the model described below. Standardized path coefficients were used as an effect estimate (range, 1.0 to 1.0), with absolute values <0.10 indicating a small effect, values around 0.30 as a medium effect and >0.50 as a large effect [32]. The effect sizes were evaluated in combination with tests of significance. The total

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Characteristics of the individual: • Age • Sex • Non-burn physical illness • Psychiatric illness

Biological and p y physiolo ggical variables:

Symptom status:

Functional status:

•

•

•

•

• • • •

Total body surface area burn Full thickness injury Inhalation injury Number of operations Length of hospital stays

• • • • •

Pain and itch (BSHS-N) General health (BSHS-N) Body Image (BSHS-N) Affective (BSHS-N) Mental health (SF-36) Bodily pain (SF-36) Vitality (SF-36)

• • • • • •

Physical health (BSHS-N) Mobility and Self-care (BSHS-N) Role Activities (BSHS-N) y Physical function (SF-36) Social function (SF-36) Role emotional (SF-36) Role physical (SF-36)

General health p eption perc p :

Overall quality of life:

•

•

Characteristics of the environment: • Living alone • Housing or economical problems • Unemployment

General health (SF-36)

The Quality of Health Scale (QOLS)

Nonmedical factors: testedd • Not teste

Fig. 1 – The theoretical path model listing the variables tested at each conceptual level. The model was based on Wilson and Cleary’s model of health-related quality of life [1].

effect of one variable can be estimated by the product of the indirect effects, summated with the direct effect [33]. Model fit was tested with the following performance measures: (a) the x2 statistics estimates the goodness of fit and the null-hypothesis represents that the hypothesized model is valid [29]. Values of the x2/degrees of freedom <2 indicates satisfactory fit [29]; (b) the goodness of fit index (GFI) estimates the proportion of covariances in the data matrix explained by the model with values close to 1 indicating good fit [29,30]; (c) the Bentler Comparative Fit Index (CFI) which is a measure of the complete covariance in the data. A value of 1.0 indicates a perfect fit, whereas and CFI >0.95 indicates a very good model fit [29]; (d) the root mean square error of approximation (RMSEA) which is one of the most informative criteria of model fit. A values of RMSEA < 0.05 indicates a close and good fit, whereas values >0.10 indicates poor fit [29]. Pearson’s correlations were used for describing the associations between factors in the model, whereas univariate and multivariate linear regression analyses of general health perception and overall quality of life were performed to supplement the SEM analyses. The latter models were also used to examine collinearity between variables. The statistical package SPSS version 19 (SPSS Inc., IL, USA) was used for the correlation and regression analyses, whereas the SAS (Statistical Analysis System) version 9.2 (SAS Institute, Inc., Cary, North Carolina) software for Windows was used for the SEM analysis. All tests were two-sided, and p < 0.05 was considered statistically significant.

3.

Results

The bivariate correlation analyses demonstrated statistically significant associations between all self-reported health and quality of life measures in the final model, except for a near significant association between PainItch and QOLS (Table 3). Living alone was inversely and significantly associated with all self-reported health and quality of life scores except for PainItch. Length of hospital stays was significantly correlated with PainItch and the BSHS-N subdomain Role Activities. The final path model is given in Fig. 2, and the corresponding descriptive statistics and correlations are given in Tables 2 and 3. The best model fit was obtained when length of hospital stay was used as indicator of injury-related biological variable (Fig. 2), and this variable resulted in better model fit when compared to the variables extent of total body surface area burn, full thickness injury, the number of operations and the presence of inhalation injury. Furthermore, at the level of symptoms, the combined PainItch variable based on data from the BSHS-N improved the model fit significantly together with the SF-36 domain Vitality (Fig. 2). At the functional level, the BSHS-N subdomain Role Activities and the SF-36 domain Social Function gave better model fit than the SF-36 domains Physical Functioning, Role Emotional and Role Physical, as well as the subdomain Mobility and Self-care from the BSHS-N. The SEM analyses revealed two main pathways in the model, one ending at general health perception (in the model

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Table 3 – Correlations of path model variables. Parameter

Age

Age Sex Living alone Length of hospital stays PainItch Vitality (SF-36) Role activities (BSHS-N) Social function (SF-36) General health (SF-36) QOLS

–

* y z

Sex

.177* .237* .023 .059 .032 .280y .132 .204* .055

Living alone

– .095 .196* .213* .101 .347y .075 .103 .008

Length of hospital stays

PainItch

Vitality (SF-36)

Role activities (BSHS-N)

Social function (SF-36)

General health (SF-36)

QOLS

– .134 .145 .245* .334y .290y .215* .285y

– .295y .030 .286y .071 .146 .013

– .356z .559z .291y .406z .199

– .482z .605z .683z .661z

– .635z .699z .400z

– .693z .546z

– .527z

–

p < 0.05. p < 0.01. p < 0.001.

represented by the SF-36 domain General health) and the other ending at overall quality of life (in the model represented by the QOLS) (Fig. 2). Notably, no significant path could be demonstrated between these two conceptual levels. The final model included only statistically significant paths and showed satisfactory model fit with x2 of 20.217 with 17 degrees of freedom, giving a ratio of 1.189. Further, the GFI was 0.948, the Bentler CFI was 0.989 and the RMSEA was 0.046. Moreover, the effect of BSHS-N subdomain Role Activities on SF-36 domain General Health, as well as the effects of the SF-36 domain Vitality on SF-36 Social Function and QOLS were all strong with standardized coefficients above 0.50 (Fig. 2). The total effects of the SF-36 domain Vitality (i.e. direct and indirect) on perceived general health and overall quality of life were 0.62 and 0.66, respectively. Length of hospital stays, living alone and PainItch had all statistically significant indirect effects on the SF-36 domain General Health, whereas the SF-36 domain Vitality had both significant indirect and direct effects on SF-

36 General Health. The direct and indirect paths explained 63% of the variance in general health perception. The variance of the QOLS was in the model explained by the direct effect of the SF36 domain Vitality and the indirect effect of living alone. Together these effects explained 43% of the variance in overall quality of life in this model. To supplement the SEM analyses, unadjusted regressions showed that the domains age, living alone, PainItch, BSHS-N Role Activities, as well as the SF-36 domains Vitality and Social Function were all significantly associated with SF-36 General Health (Table 4). Only BSHS-N Role Activities, SF-36 Vitality and Social Function from the self-report measures were significantly associated with SF-36 General Health in the adjusted linear regression analysis (Table 4). The multipleregression model explained 71% of the variance in general health perception. Finally, unadjusted regression analyses of overall quality of life showed that all self-reported outcomes and Living alone

-0.26 0.13

Length of hospital stays

-0.37 0.37

0.37

0.25

PainItch (BSHS-N)

Role Activities (BSHS-N) 0.29

0.63

0.50

General health (SF-36) 0.43

0.40

0.38

0.28

Quality of Life Scale (QOLS)

Social functioning (SF-36) 0.05

0 63 0.63 0.43

Vitality (SF-36)

0.66

-0.23

Living alone Fig. 2 – The final model describing paths leading to perceived general health and quality of life after burn injury. Each path is displayed as a single headed arrow and the corresponding standardized path coefficient. Double headed arrows illustrate covariance between errors, whereas the numbers in italics represent squared multiple correlations (R-squared).

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Table 4 – Unadjusted and adjusted associations between health indicators and general health perception. SF-36 general health (general health perception) Unadjusted analysisa

Living alone Length of hospital stays PainItchc Vitality (SF-36) Role activities (BSHS-N) Social function (SF-36)

Adjusted analysisa,b

Adj. B

p

Adj. B

p

.215 .146 .406 .683 .483 .693

.037 .159 <.001 <.001 <.001 <.001

.024 .094 .002 .424 .401 .199

.780 .143 .981 <.001 <.001 .025

a

Adjusted for age and sex. R2 = 0.71; R2 adj = 0.68. c Summated score of the two items ‘‘pain’’ and ‘‘itch’’ from the BSHS-N. b

were significantly associated with QOLS (Table 5). In the adjusted linear regression analysis, SF-36 Vitality remained as the only significant factor associated with overall quality of life. The adjusted analysis explained 49% of the variance in overall quality of life.

4.

Discussion

In the present study, the concepts of a model on health-related quality of life described by Wilson and Cleary [1], and data on burn-specific health, generic health, overall quality of life, injury characteristics and socio-demography obtained from the same patient cohort [6,12,21], allowed for the study of paths leading to patient perceived health and quality of life in a population of burn patients. A model including biological variables, symptoms, functioning, health and quality of life was tested using SEM analyses, and this permitted the unravelling of distinct and separate potential causal pathways leading to self-perceived health and overall quality of life.

Table 5 – Unadjusted and adjusted associations between health indicators and overall quality of life. QOLS (overall quality of life) Unadjusted analysisa

Living alone Length of hospital stays PainItchc Vitality (SF-36) Role activities (BSHS-N) Social function (SF-36) General health (SF-36) a

Adjusted analysisa,b

Adj. B

p

Adj. B

p

.285 .013 .199 .661 .400 .546 .527

.005 .905 .056 <.001 <.001 <.001 <.001

.101 .043 .079 .500 .030 .146 .095

.246 .619 .428 <.001 .832 .230 .520

Adjusted for age and sex. R2 = 0.49; R2 adj = 0.44. c Summated score of the two items ‘‘pain’’ and ‘‘itch’’ from the BSHS-N. b

Length of hospital stays turned out to be the best indicator of biological and physiological variables in the model, and resulted in improved model fit compared to the other indicators of burn severity tested, i.e. the total surface area burn, the extent of full thickness injury, the presence of inhalation injury and the number of operations. Length of hospitalization is known to increase linearly in relation to total body surface area burn, and also to increase with age and comorbidities [34–36]. The present study indicates that length of hospital stays, probably reflecting both burn severity and complications during hospitalization, is associated with long term effects on symptoms, functioning and health. After evaluations of model fit, PainItch and SF-36 Vitality turned out to be the best indicators of symptom status. Pain and itch had a significant direct effect on BSHS-N Role Activities and a significant indirect effect on perceived general health, whereas vitality both had a significant direct and indirect effect on perceived general health, as well as a direct effect on overall quality of life. Pain and itch have earlier been reported to be common symptoms also in patients with healed burns [12,37–39], whereas reduced vitality have been shown to be associated with joint contractures or psychological distress after burn injury [40,41]. In this study, reduced vitality influenced on the burn patients’ evaluations of their perceived general health both directly and through social functioning and role functioning. In our model, living alone had a moderate, but significant, inverse effect on vitality, whereas the effects of unemployment and problems with housing or economy were insignificant and gave poorer model fit. An association between fatigue and living without a partner has previously been reported in a study of the general Danish population [42], and, in addition, increased fatigue was associated with reduced quality of life in a Norwegian population based study [43]. The present study adds to these findings by demonstrating that reduced vitality represents a threat to long term overall quality of life in burn injured adults. In our model, significant paths could only be demonstrated from functional status to generic health perception and not from the functional level to overall quality of life. This pattern is consistent with outcome data from patients with chronic diseases [44], and the results of an empirical testing of the Wilson and Cleary model using data from patients with HIVinfection [27]. Hence, the level of functioning seems to be mainly related with evaluations of health status, and less to the evaluation of overall quality of life. The SEM analyses demonstrated two main significant pathways in the model, one ending at general health perception and the other ending at overall quality of life, and, notably, no significant path could be demonstrated between these two conceptual levels of the model. This suggest that although vitality was an important indicator of both health and quality of life, the burn population hold perceived general health as mostly related to their physical health and level of functioning, and quality of life, as more related to their symptoms, especially vitality. This pattern was also confirmed in the adjusted linear regression. Moreover, the lack of a significant direct relationship between health perception and overall quality of life may further support the holding that perceived general health and quality of life are

burns 38 (2012) 1157–1164

distinct constructs [1,12,44]. Hence, burn patients may not necessarily feel that their quality of life is reduced if their perceived health is poor and vice versa. Similar observations have been made in patients with diabetes mellitus [45], rheumatic arthritis [46], as well as in survivors of non-CNS childhood cancers [47]. From a clinical point of view, the present data suggest that lack of vitality represents a significant threat to both self-perceived health and satisfaction in life for burn patients. Consistently, burn care professionals should acknowledge and look for fatigue, explore its underlying physical and mental causes, as well as initiate adequate interventions. Lack of conceptual clarity in the area of patient-reported outcomes in general, and of quality of life in health care more specifically, has been claimed to threaten the impact and communication of study findings [20]. Based on the results of this and other studies [12,48], we recommend to make a distinction between questionnaires that mainly ask for descriptions of symptoms, functioning and health (e.g. BSHS and SF-36), and questionnaires or items asking for evaluations of quality of life, operationalized as satisfaction, happiness or achievement of personal goals [19]. The strengths of this study include the large panel of data on burn-specific health, generic health and quality of life from the same patient population which allowed for testing of a path model based on the concepts of Wilson and Cleary’s model on health-related quality of life [1]. Moreover, the study was population based, and the responders did not differ significantly from the non-responders on socio-demographic or injury characteristics; thus, strengthening the generalizability of our findings. On the other hand, the sustained nonnormal distribution of a few transformed data may have impacted slightly on parameter estimates in SEM analyses, and the sample size did not allow for models including more than eight variables. It is also possible that advances in the care and follow up of burn patients the last 15 years may have influenced patient outcome. Finally, supplementary information on personality or coping, as well as knowledge on the level of social or economic support may have strengthened this study. In conclusion, our findings in burn injured adults support the suggestion of Wilson and Cleary that general health perception and overall quality of life are related but distinct constructs. This should be taken into con sideration in clinical practice, when evaluating the current outcome literature, as well as when future studies are designed.

Conflict of interest The authors have no conflicts of interest to disclose.

Acknowledgements The participating burn patients are thanked for their contributions to the study. Tom Backer Johnsen is thanked for valuable methodological discussions.

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