Qual Life Res DOI 10.1007/s11136-015-1033-4
BRIEF COMMUNICATION
Health-related quality of life in a sample of Australian adolescents: gender and age comparison Tanya Meade1 • Elizabeth Dowswell1
Accepted: 28 May 2015 Ó Springer International Publishing Switzerland 2015
Abstract Purpose The primary purpose of this study was to profile the health-related quality of life (HRQoL) in a sample of secondary school-aged children in Australia. The secondary purpose was to contribute to the international literature on the HRQoL of adolescents using the KIDSCREEN instrument. Methods The KIDSCREEN-27 Questionnaire was completed by 1111 adolescents aged between 11 and 17 from six Australian secondary schools. MANCOVA analysis was employed to examine age and gender differences. Results Over 70 % of participants reported high levels of HRQoL across all five dimensions. Age patterns were identified with younger adolescents reporting greater HRQoL than older adolescents. Similarly, gender differences were noted with male adolescents reporting higher scores than female adolescents on three out of five dimensions of HRQoL. Conclusions This is the first study to measure HRQoL in Australian adolescents using the KIDSCREEN instrument. Consistent with previous research, gender and age differences were found across most dimensions of HRQoL. These results highlight the importance of comprehensively measuring the HRQoL in adolescents to capture developmental shifts and to inform preventative and supportive programs as needed.
& Tanya Meade [email protected] 1
School of Social Sciences and Psychology, University of Western Sydney, PO Box 1797, Penrith, NSW 2751, Australia
Keywords Health-related quality of life (HRQoL) Adolescents KIDSCREEN Age Gender Physical and mental health
Introduction Mental health problems are a leading cause of health-related disability for children and adolescents worldwide, and these problems can have ongoing effects across the lifespan [1]. In Australia, young adults (16–24 years of age) have been found to have the highest prevalence of mental health problems, across all age groups [2]. Further, psychosocial difficulties in childhood are also predictive of future physical and biological problems in adulthood [3]. Australian data indicate that as many as one in four adolescents has a mental health disorder and yet only 23 % access mental health services [2]. It is commonly understood that mental health is critical to overall health [4], and the relationship between physical and mental health is likely to be dynamic and bidirectional. Adolescents, in particular, are faced by developmental challenges that may impact their overall quality of life [5]. Child and adolescent mental health, therefore, does not occur in isolation, and thus deficits in physical and mental health may have implications for their overall well-being [6]. Health-related quality of life (HRQoL) is a multidimensional construct which refers to an individual’s perception of well-being (physical, psychological, and social) in the context of their values, beliefs, expectations, goals, and cultural environment [7]. The KIDSCREEN European project developed a standardised HRQoL questionnaire for children and adolescents aged 8–18 with normative data collected across 13 European countries [8] and found age and gender differences within and across countries [9, 10].
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Irrespective of gender, children reported higher quality of life than adolescents, particularly in physical and psychological well-being, and more so for males than females [9]. Similar findings were reported in another, larger study, across 12 European countries [10] as well as North America [11]. In an Australian context, two studies have revealed both gender and age differences in HRQoL, with males and younger adolescents reporting higher scores than females and older adolescents [12, 13]. However, these two studies used different HRQoL measures and were limited to specific populations: adolescents on remand and adolescents with excess weight. While there is comprehensive assessment of HRQoL across European countries [9, 10], there is limited international data. The aim of this study therefore was to assess levels of HRQoL in a broader sample of secondary school-based Australian students. This examination will explore age and gender differences across the KIDSCREEN dimensions of HRQoL and will contribute to the body of research currently using the KIDSCREEN questionnaires to measure the HRQoL of children and adolescents.
Methods Sample and study design The current study was part of a broader longitudinal study focusing on social capital, psychosocial, and socio-economic outcomes. Students (n = 1111) were recruited from comprehensive public high schools (n = 6) in the Sydney metropolitan (five schools) and regional (one school) communities of New South Wales, Australia. The targeted schools were located within multicultural areas, and data were collected across academic years 7–11. Grade 7 marks the year of students’ transition from primary to secondary school, with junior secondary school being comprised of grades 7, 8, 9, and 10 encompassing ages 12 through to 16. At the end of year 10, students transit to senior secondary school where they complete years 11 and 12, aged between 16 and 18. Due to the intensive nature of the higher school certificate (HSC) completed in year 12, students from this grade were not recruited. Data collection All students in grades 7–11 who provided consent and were present on the day of data collection completed the KIDSCREEN-27 Questionnaire. This was done as part of a larger battery of measures for a broader study. Of the 1933 students who were eligible and initially contacted, 1379 provided consent (response rate of 71 %). Of the students
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who provided consent, 1111 completed the questionnaire, leading to a response rate of 81 %. The questionnaire was administered to the students via a pen-and-paper self-report process. A member of the research team read the questionnaire items out loud, and the students recorded their answers on the questionnaire. Measures The KIDSCREEN-27 instrument was used to measure HRQoL. The 27-item questionnaire was developed as a shorter version of the KIDSCREEN-52 and measures HRQoL across five dimensions: physical well-being (five items); psychological well-being (seven items); autonomy and parents relations (seven items); social support and peers (four items); and school environment (four items) [14]. The KIDSCREEN instruments are not intended to be used as clinical diagnostic tools. The KIDSCREEN-27 self-report version requires respondents to answer the 27 items on a five-point Likert scale ranging from never/not at all, to always. Scoring of the instrument does not provide an overall score of HRQoL, but rather, a total score for each of the five dimensions which can be used to make comparisons with norm-referenced data [14]. On the self-report version of the KIDSCREEN-27, internal consistency values (Cronbach’s alpha) are satisfactory for all five dimensions: physical well-being (.80); psychological well-being (.84); autonomy and parents relations (.81); social support and peers (.81); and school environment (.81). At a 2-week interval, test–retest reliability varies between .61 (social support and peers) and .74 (school environment) [14]. Furthermore, in all European countries, the dimensions fulfil the assumptions of the Rasch model for both genders and age groups [14]. According to the KIDSCREEN manual [14], the KIDSCREEN-27 can be used to detect gender and age differences in HRQoL, and as such, will be used to measure these differences in an Australian sample of adolescents. Statistical analyses The self-report algorithm outlined in the KIDSCREEN manual [14] was used to convert the total raw scores from the five dimensions to Rasch scores, and then to convert these Rasch scores to t values. These t values can then be compared to ‘international t values’ based on 14 European countries, which are normed to a mean of 50 and a standard deviation of 10. All analyses were conducted using IMB SPSS Statistics (21.0), with statistical significance set at p \ .05 (two-tailed). A multivariate analysis of covariance (MANCOVA) was performed to investigate gender and grade (age) differences on each of the five KIDSCREEN27 dimensions. To determine the effect of each
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independent variable on the five dimensions, the remaining independent variable served as a covariate in each MANCOVA analysis. For example, when examining the impact of gender on the five dimensions, grade was used as a covariate, and when examining grade, gender served as the covariate. Power calculations revealed that a sample size of 917 subjects is sufficient to detect moderate effects (0.13) [15], with 90 % power at a .05 level of significance [16].
Results All students attended comprehensive public co-educational and single-sex secondary schools in the Sydney metropolitan or regional areas of NSW. The data from three participants were identified as outliers as their scores appeared spurious. After removing these outliers, a total of 1108 students comprised the final sample. However, due to missing values, the MANCOVAs were run on data from 1000 participants (47 % female; mean age 13.97 years). Seventy percent of participants spoke a language other than English at home; with Arabic being the most commonly spoken language (45 %) followed by other languages (8.1 %) and Pacific Islander dialects (6.4 %). Islam was the most common religion (55.1 %), followed by Christianity (22.4 %), and no religious orientation (14.2 %). Participants were assessed across the five HRQoL dimensions, and participants scores were grouped into low, middle, and high ranges (Table 1). The KIDSCREEN manual groups score into high and low categories which specify the range of each KIDSCREEN dimension by its extreme ends [14]. In order to examine the data further in
detail, the authors also included a middle-range score, which encompassed scores from 11 to 15. The MANCOVA for males versus females controlling for grade found significant main effects for three of the five KIDSCREEN dimensions (Table 2). Males scored significantly higher than females on the physical well-being dimension, F(1, 997) = 53.37, p B .001, g2 = .051, the psychological well-being dimension, F(1, 997) = 8.83, p = .003, g2 = .009, and the autonomy and parent relations dimension F(1, 997) = 13.99, p = \ .001, g2 = .014. Of these, only the physical well-being effect size was in the moderate range. The MANCOVA for each year (grade) group controlling for gender found significant main effects for each of the five KIDSCREEN dimensions (Table 3). On the physical well-being dimension, year 7 students scored significantly higher than students in years 8, 9, 10, and 11, F(4, 994) = 9.48, p B .001, g2 = .037. Students in years 7, 8, and 9 scored significantly higher than year 11 students on the psychological well-being dimension, F(4, 994) = 4.67, p = .001, g2 = .018. On the autonomy and parent relations dimension, year 7, 8, and 9 students scored significantly higher than those in year 11, F(4, 994) = 3.16, p = .013, g2 = .013. Students in years 7 and 9 scored significantly higher than those in year 11 on the social support and peers dimension F(4, 994) = 4.12, p = .003, g2 = .016. On the school environment dimension, students in year 7 scored significantly higher than students in years 8, 9, 10, and 11, F(4, 994) = 6.99, p B .001, g2 = .027. While significant, the effect sizes for those differences were only small [15]. The gender by grade interaction was not significant across all KIDSCREEN dimensions, (all Fs B .794, ps C .529, g2p B .003).
Table 1 Range of scores across each KIDSCREEN dimension and their meaning (The KIDSCREEN Group Europe, 2006) KIDSCREEN dimension
Low
Middle
High
Low score indicates
High score indicates
Physical wellbeing
6% (0–10)
19 % (11–15)
75 % (16–25)
Physically exhausted, physically unwell, feeling unfit, having low energy
Physically fit, active, healthy, energetic
Psychological well-being
5% (0–14)
21 % (15–21)
74 % (22–35)
No pleasure in life, feeling depressed, feeling unhappy, having a low self-esteem
Happy, viewing life positively, satisfied with life, emotionally balanced
Autonomy and parent relations
6% (0–14)
23 % (15–21)
71 % (22–35)
Feeling restricted, feeling overlooked, not appreciated, feeling finances are restricting lifestyle
Feeling positive about relationship with parents and having enough age-appropriate freedom to choose, feeling satisfied with financial resources, feeling well-off
Social support and peers
6% (0–8)
23 % (9–12)
71 % (13–20)
Feeling excluded, not accepted by peers
Feeling accepted, supported and included in peer group
School environment
8% (0–8)
23 % (9–12)
70 % (13–20)
Disliking school, negative feelings about school, not doing well
Feeling happy at school and doing well
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Qual Life Res Table 2 Gender comparisons with KIDSCREEN dimensions (n = 1000)
KIDSCREEN dimension
Male
Female
F
p
.000*
n
Mean
SD
n
Mean
SD
Physical well-being
524
51.33
12.06
476
46.11
9.92
53.37
Psychological well-being
524
46.97
10.73
476
44.94
9.85
8.83
.003*
Autonomy and parent relations
524
50.66
13.84
476
47.51
11.99
13.99
.000*
Social support and peers
524
50.55
12.65
476
51.76
10.83
3.11
.078
School environment
524
49.27
12.13
476
49.16
10.37
.001
.974
* p \ .05
Table 3 Grade (age) comparisons with KIDSCREEN dimensions (n = 1000) KIDSCREEN dimension Grade (age)
n
Year 7 (12–13)
270
Physical well-being
Psychological well-being
Autonomy and parent relations
Social support and peers
School environment
Mean
51.92*
47.52*
49.79*
52.42*
52.11*
SD
10.93
10.02
13.43
12.04
11.68
Year 8 (13–14)
252
Mean
48.21*
45.79*
49.66*
51.00
48.27*
Year 9 (14–15)
239
SD Mean
10.88 48.63*
10.42 46.40*
12.84 50.16*
11.46 52.09*
10.47 48.70*
SD
11.80
10.22
12.84
11.20
11.40
Year 10 (15–16)
184
Mean
46.98*
44.90
47.86
49.41
47.99*
SD
10.53
10.78
11.80
11.37
10.20
Year 11 (16–17)
55
Mean
43.87*
41.47*
43.79*
46.95*
45.69*
SD
13.43
9.54
16.21
14.94
13.91
F = 9.48, p B .001*
F = 4.67, p = .001*
F = 3.16, p = .013*
F = 4.12, p = .003*
F = 6.99, p B .001*
MANCOVA Results * p \ .05
Discussion The aim of this study was to examine the HRQoL in a school-based sample of Australian adolescents, by exploring age and gender differences across the KIDSCREEN dimensions. The majority of participants reported high levels of HRQoL; however, a small percentage of participants reported concerning scores indicative of poor HRQoL. Consistent with other international studies [9, 10, 17–20], gender differences, while controlling for age, were found in this Australian sample on three of the five dimensions of HRQoL: physical well-being, psychological well-being, and autonomy and parental relations: with females reporting lower levels of HRQoL. Despite these gender differences being statistically significant, only one of the three was in the moderate effect size range, and likely to be perceived as clinically meaningful [21]. Nonetheless, these gender differences may be due to diverse social expectations, puberty being
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a more significant experience for females (i.e. menstruation and fluctuating hormones), and females having more frequent physical health problems [22, 23]. These findings are comparable to European norms and contribute to the international data on similarities and differences in HRQoL across countries outside of Europe. This study also found significant age differences, with the youngest participants (year 7, age range 11–13) scoring higher across all five dimensions of HRQoL compared to older participants (particularly year 10 and 11, age range 15–17), with incremental decreases in HRQoL across ages. However, these effect sizes were small and therefore unlikely to be clinically meaningful. Although the sample size for the oldest group of students was smaller, the pattern of declining HRQoL, with the oldest participants being the most different to all other age groups, is consistent with previous studies [9, 10, 13, 19, 24]. This study, the first of its kind in Australia to use a KIDSCREEN questionnaire to measure HRQoL, is not
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without limitations, namely uneven age representation and a relatively small sample population. However, the sample in this study is representative of the Australian multicultural population as 24 % of Australia’s population was born overseas and 43 % of people have at least one overseas-born parent [25]. Nevertheless, future research is required to conduct a nationwide examination of the HRQoL of Australian adolescents, to broaden the population representativeness in terms of cultural, geographical, and economic diversity. Furthermore, while HRQoL scores in this sample were consistent with the European norms, the KIDSCREEN instruments are not designed to be used as a diagnostic tool and therefore individual variations cannot be interpreted as clinically significant. Notwithstanding these limitations, this study confirms the pattern of gender and age differences in adolescent HRQoL identified in European studies using the KIDSCREEN measure, and adds Australian data to the body of international literature. Given the recognition of the multifactorial aetiology of mental problems in children and adolescents [26] and the close link between mental and physical health [27], overall quality of life may be an important and informative indicator of adolescents’ well-being. It may also provide an early indication of vulnerability and inform preventative measures that could be delivered within a school setting. Future research may build on these preliminary findings by further investigation of age, gender, and socio-economic influences on HRQoL across time, and a broader sample of Australian adolescents. This knowledge may then inform appropriate physical and mental health literacy at the school level, such as wellness and resilience-building programs. Acknowledgments This study was funded by the Australian Research Council, Grant No. LP100100369 titled ‘Bridging the gap on locational disadvantage: Impact of community-identified interventions on social capital, psychosocial and socioeconomic outcomes’. The research was conducted by the University of Western Sydney research team headed by Professor Rhonda G Craven and chief investigators A/Prof Geoffrey E Munns and A/Prof Tanya Meade in partnership with The Benevolent Society and partner investigators Dr Genevieve Nelson, Mr Andrew Anderson. We thank the six schools for participating in this study. We also thank Dr Michael Hough for statistical advice and assistance. Conflict of interest flict of interest.
All the authors declare that they have no con-
Compliance with ethical standards This study was approved by the University of Western Sydney Human Ethics Committee and the Department of Education, New South Wales Ethics Committee. The study was conducted according to the Helsinki ethical principles of research. Informed consent All participants provided informed consent prior to their participation in the research.
References 1. Kieling, C., Baker-Henningham, H., Belfer, M., Conti, G., Ertem, I., Omigbodun, O., et al. (2011). Child and adolescent mental health worldwide: Evidence for action. The Lancet, 378(9801), 1515–1525. doi:10.1016/S0140-6736(11)60827-1. 2. Australian Bureau of Statistics. (2008). National Survey of Mental Health and Wellbeing: Summary of Results, 2007 (cat. no. 4326.0). Retrieved from http://www.abs.gov.au/ausstats/abs@. nsf/mf/4326.0. 3. Power, C., Thomas, C., Li, L., & Hertzman, C. (2012). Childhood psychosocial adversity and adult cortisol patterns. British Journal of Psychiatry, 201(3), 199–206. 4. Prince, M., Patel, V., Saxena, S., Maj, M., Maselko, J., Phillips, M. R., et al. (2007). No health without mental health. The Lancet, 370(9590), 859–877. 5. Goldbeck, L., Schmitz, T. G., Besier, T., Herschbach, P., & Henrich, G. (2007). Life satisfaction decreases during adolescence. Quality of Life Research, 16(6), 969–979. 6. Petersen-Ewert, C., Erhart, M., & Ravens-Sieberer, U. (2011). Assessing health-related quality of life in European children and adolescents. Neuroscience and Biobehavioral Reviews, 35(8), 1752–1756. 7. Kuyken, W. (1995). The World Health Organization Quality of Life assessment (WHOQOL): Position paper from the World Health Organization. Social Science and Medicine, 41(10), 1403–1409. 8. Ravens-Sieberer, U., Gosch, A., Rajmil, L., Erhart, M., Bruil, J., Duer, W., et al. (2005). KIDSCREEN-52 quality-of-life measure for children and adolescents. Expert Review of Pharmacoeconomics and Outcomes Research, 5(3), 353–364. 9. Bisegger, C., Cloetta, B., von Bisegger, U., Abel, T., & RavensSieberer, U. (2005). Health-related quality of life: Gender differences in childhood and adolescence. Sozial- und Pra¨ventivmedizin, 50(5), 281–291. 10. Michel, G., Bisegger, C., Fuhr, D. C., & Abel, T. (2009). Age and gender differences in health-related quality of life of children and adolescents in Europe: A multilevel analysis. Quality of Life Research, 18(9), 1147–1157. 11. Torsheim, T., Ravens-Sieberer, U., Hetland, J., Valimaa, R., Danielson, M., & Overpeck, M. (2006). Cross-national variation of gender differences in adolescent subjective health in Europe and North America. Social Science and Medicine, 62(4), 815–827. 12. Sawyer, M. G., Guidolin, M., Schulz, K. L., McGinnes, B., Zubrick, S. R., & Baghurst, P. A. (2010). The mental health and wellbeing of adolescents on remand in Australia. Australian and New Zealand Journal of Psychiatry, 44(6), 551–559. 13. Bolton, K., Kremer, P., Rossthorn, N., Moodie, M., Gibbs, L., Waters, E., et al. (2014). The effect of gender and age on the association between weight status and health-related quality of life in Australian adolescents. BMC Public Health, 14, 898. doi:10.1186/1471-2458-14-898. 14. The KIDSCREEN Group Europe. (2006). The KIDSCREEN questionnaires—Quality of life questionnaires for children and adolescents. Handbook. Lengerich: Pabst Science Publishers. 15. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale (NJ): Erlbaum. 16. Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. 17. Amr, M. A., Amin, T. T., & Al-Omair, O. A. (2011). Health related quality of life among adolescents with sickle cell disease in Saudi Arabia. The Pan African Medical Journal, 8(10).
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23. Ross, C. E., Masters, R. K., & Hummer, R. A. (2012). Education and the gender gaps in health and mortality. Demography, 49(4), 1157–1183. doi:10.1007/s13524-012-0130-z. 24. Gaspar, T., Gaspar Matos, M., Pais, R., Jose, L., Leal, I., & Ferreira, A. (2009). Health related quality of life in children and adolescents and associated factors. Journal of Cognitive and Behavioral Psychotherapies, 9(1), 33–48. 25. Australian Bureau of Statistics. (2011). Census of Population and Housing: Details of Undercount, 2011 (cat. no. 2940.0). Retrieved from http://www.abs.gov.au/ausstats/[email protected]/mf/2940.0. 26. Rajmil, L., Herdman, M., Ravens-Sieberer, U., Erhart, M., & Alonso, J. (2014). Socioeconomic inequalities in mental health and health-related quality of life (HRQoL) in children and adolescents from 11 European countries. International Journal of Public Health, 59(1), 95–105. 27. Martinez, C. J., Martin, A. J., Liem, G. A. D., & Colmar, S. (2012). A longitudinal analysis of physical and psychological wellbeing amongst late adolescents: Exploring the transition from school to postschool life. The Australian Educational and Developmental Psychologist, 29(1), 17–43.
BRIEF COMMUNICATION
Health-related quality of life in a sample of Australian adolescents: gender and age comparison Tanya Meade1 • Elizabeth Dowswell1
Accepted: 28 May 2015 Ó Springer International Publishing Switzerland 2015
Abstract Purpose The primary purpose of this study was to profile the health-related quality of life (HRQoL) in a sample of secondary school-aged children in Australia. The secondary purpose was to contribute to the international literature on the HRQoL of adolescents using the KIDSCREEN instrument. Methods The KIDSCREEN-27 Questionnaire was completed by 1111 adolescents aged between 11 and 17 from six Australian secondary schools. MANCOVA analysis was employed to examine age and gender differences. Results Over 70 % of participants reported high levels of HRQoL across all five dimensions. Age patterns were identified with younger adolescents reporting greater HRQoL than older adolescents. Similarly, gender differences were noted with male adolescents reporting higher scores than female adolescents on three out of five dimensions of HRQoL. Conclusions This is the first study to measure HRQoL in Australian adolescents using the KIDSCREEN instrument. Consistent with previous research, gender and age differences were found across most dimensions of HRQoL. These results highlight the importance of comprehensively measuring the HRQoL in adolescents to capture developmental shifts and to inform preventative and supportive programs as needed.
& Tanya Meade [email protected] 1
School of Social Sciences and Psychology, University of Western Sydney, PO Box 1797, Penrith, NSW 2751, Australia
Keywords Health-related quality of life (HRQoL) Adolescents KIDSCREEN Age Gender Physical and mental health
Introduction Mental health problems are a leading cause of health-related disability for children and adolescents worldwide, and these problems can have ongoing effects across the lifespan [1]. In Australia, young adults (16–24 years of age) have been found to have the highest prevalence of mental health problems, across all age groups [2]. Further, psychosocial difficulties in childhood are also predictive of future physical and biological problems in adulthood [3]. Australian data indicate that as many as one in four adolescents has a mental health disorder and yet only 23 % access mental health services [2]. It is commonly understood that mental health is critical to overall health [4], and the relationship between physical and mental health is likely to be dynamic and bidirectional. Adolescents, in particular, are faced by developmental challenges that may impact their overall quality of life [5]. Child and adolescent mental health, therefore, does not occur in isolation, and thus deficits in physical and mental health may have implications for their overall well-being [6]. Health-related quality of life (HRQoL) is a multidimensional construct which refers to an individual’s perception of well-being (physical, psychological, and social) in the context of their values, beliefs, expectations, goals, and cultural environment [7]. The KIDSCREEN European project developed a standardised HRQoL questionnaire for children and adolescents aged 8–18 with normative data collected across 13 European countries [8] and found age and gender differences within and across countries [9, 10].
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Irrespective of gender, children reported higher quality of life than adolescents, particularly in physical and psychological well-being, and more so for males than females [9]. Similar findings were reported in another, larger study, across 12 European countries [10] as well as North America [11]. In an Australian context, two studies have revealed both gender and age differences in HRQoL, with males and younger adolescents reporting higher scores than females and older adolescents [12, 13]. However, these two studies used different HRQoL measures and were limited to specific populations: adolescents on remand and adolescents with excess weight. While there is comprehensive assessment of HRQoL across European countries [9, 10], there is limited international data. The aim of this study therefore was to assess levels of HRQoL in a broader sample of secondary school-based Australian students. This examination will explore age and gender differences across the KIDSCREEN dimensions of HRQoL and will contribute to the body of research currently using the KIDSCREEN questionnaires to measure the HRQoL of children and adolescents.
Methods Sample and study design The current study was part of a broader longitudinal study focusing on social capital, psychosocial, and socio-economic outcomes. Students (n = 1111) were recruited from comprehensive public high schools (n = 6) in the Sydney metropolitan (five schools) and regional (one school) communities of New South Wales, Australia. The targeted schools were located within multicultural areas, and data were collected across academic years 7–11. Grade 7 marks the year of students’ transition from primary to secondary school, with junior secondary school being comprised of grades 7, 8, 9, and 10 encompassing ages 12 through to 16. At the end of year 10, students transit to senior secondary school where they complete years 11 and 12, aged between 16 and 18. Due to the intensive nature of the higher school certificate (HSC) completed in year 12, students from this grade were not recruited. Data collection All students in grades 7–11 who provided consent and were present on the day of data collection completed the KIDSCREEN-27 Questionnaire. This was done as part of a larger battery of measures for a broader study. Of the 1933 students who were eligible and initially contacted, 1379 provided consent (response rate of 71 %). Of the students
123
who provided consent, 1111 completed the questionnaire, leading to a response rate of 81 %. The questionnaire was administered to the students via a pen-and-paper self-report process. A member of the research team read the questionnaire items out loud, and the students recorded their answers on the questionnaire. Measures The KIDSCREEN-27 instrument was used to measure HRQoL. The 27-item questionnaire was developed as a shorter version of the KIDSCREEN-52 and measures HRQoL across five dimensions: physical well-being (five items); psychological well-being (seven items); autonomy and parents relations (seven items); social support and peers (four items); and school environment (four items) [14]. The KIDSCREEN instruments are not intended to be used as clinical diagnostic tools. The KIDSCREEN-27 self-report version requires respondents to answer the 27 items on a five-point Likert scale ranging from never/not at all, to always. Scoring of the instrument does not provide an overall score of HRQoL, but rather, a total score for each of the five dimensions which can be used to make comparisons with norm-referenced data [14]. On the self-report version of the KIDSCREEN-27, internal consistency values (Cronbach’s alpha) are satisfactory for all five dimensions: physical well-being (.80); psychological well-being (.84); autonomy and parents relations (.81); social support and peers (.81); and school environment (.81). At a 2-week interval, test–retest reliability varies between .61 (social support and peers) and .74 (school environment) [14]. Furthermore, in all European countries, the dimensions fulfil the assumptions of the Rasch model for both genders and age groups [14]. According to the KIDSCREEN manual [14], the KIDSCREEN-27 can be used to detect gender and age differences in HRQoL, and as such, will be used to measure these differences in an Australian sample of adolescents. Statistical analyses The self-report algorithm outlined in the KIDSCREEN manual [14] was used to convert the total raw scores from the five dimensions to Rasch scores, and then to convert these Rasch scores to t values. These t values can then be compared to ‘international t values’ based on 14 European countries, which are normed to a mean of 50 and a standard deviation of 10. All analyses were conducted using IMB SPSS Statistics (21.0), with statistical significance set at p \ .05 (two-tailed). A multivariate analysis of covariance (MANCOVA) was performed to investigate gender and grade (age) differences on each of the five KIDSCREEN27 dimensions. To determine the effect of each
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independent variable on the five dimensions, the remaining independent variable served as a covariate in each MANCOVA analysis. For example, when examining the impact of gender on the five dimensions, grade was used as a covariate, and when examining grade, gender served as the covariate. Power calculations revealed that a sample size of 917 subjects is sufficient to detect moderate effects (0.13) [15], with 90 % power at a .05 level of significance [16].
Results All students attended comprehensive public co-educational and single-sex secondary schools in the Sydney metropolitan or regional areas of NSW. The data from three participants were identified as outliers as their scores appeared spurious. After removing these outliers, a total of 1108 students comprised the final sample. However, due to missing values, the MANCOVAs were run on data from 1000 participants (47 % female; mean age 13.97 years). Seventy percent of participants spoke a language other than English at home; with Arabic being the most commonly spoken language (45 %) followed by other languages (8.1 %) and Pacific Islander dialects (6.4 %). Islam was the most common religion (55.1 %), followed by Christianity (22.4 %), and no religious orientation (14.2 %). Participants were assessed across the five HRQoL dimensions, and participants scores were grouped into low, middle, and high ranges (Table 1). The KIDSCREEN manual groups score into high and low categories which specify the range of each KIDSCREEN dimension by its extreme ends [14]. In order to examine the data further in
detail, the authors also included a middle-range score, which encompassed scores from 11 to 15. The MANCOVA for males versus females controlling for grade found significant main effects for three of the five KIDSCREEN dimensions (Table 2). Males scored significantly higher than females on the physical well-being dimension, F(1, 997) = 53.37, p B .001, g2 = .051, the psychological well-being dimension, F(1, 997) = 8.83, p = .003, g2 = .009, and the autonomy and parent relations dimension F(1, 997) = 13.99, p = \ .001, g2 = .014. Of these, only the physical well-being effect size was in the moderate range. The MANCOVA for each year (grade) group controlling for gender found significant main effects for each of the five KIDSCREEN dimensions (Table 3). On the physical well-being dimension, year 7 students scored significantly higher than students in years 8, 9, 10, and 11, F(4, 994) = 9.48, p B .001, g2 = .037. Students in years 7, 8, and 9 scored significantly higher than year 11 students on the psychological well-being dimension, F(4, 994) = 4.67, p = .001, g2 = .018. On the autonomy and parent relations dimension, year 7, 8, and 9 students scored significantly higher than those in year 11, F(4, 994) = 3.16, p = .013, g2 = .013. Students in years 7 and 9 scored significantly higher than those in year 11 on the social support and peers dimension F(4, 994) = 4.12, p = .003, g2 = .016. On the school environment dimension, students in year 7 scored significantly higher than students in years 8, 9, 10, and 11, F(4, 994) = 6.99, p B .001, g2 = .027. While significant, the effect sizes for those differences were only small [15]. The gender by grade interaction was not significant across all KIDSCREEN dimensions, (all Fs B .794, ps C .529, g2p B .003).
Table 1 Range of scores across each KIDSCREEN dimension and their meaning (The KIDSCREEN Group Europe, 2006) KIDSCREEN dimension
Low
Middle
High
Low score indicates
High score indicates
Physical wellbeing
6% (0–10)
19 % (11–15)
75 % (16–25)
Physically exhausted, physically unwell, feeling unfit, having low energy
Physically fit, active, healthy, energetic
Psychological well-being
5% (0–14)
21 % (15–21)
74 % (22–35)
No pleasure in life, feeling depressed, feeling unhappy, having a low self-esteem
Happy, viewing life positively, satisfied with life, emotionally balanced
Autonomy and parent relations
6% (0–14)
23 % (15–21)
71 % (22–35)
Feeling restricted, feeling overlooked, not appreciated, feeling finances are restricting lifestyle
Feeling positive about relationship with parents and having enough age-appropriate freedom to choose, feeling satisfied with financial resources, feeling well-off
Social support and peers
6% (0–8)
23 % (9–12)
71 % (13–20)
Feeling excluded, not accepted by peers
Feeling accepted, supported and included in peer group
School environment
8% (0–8)
23 % (9–12)
70 % (13–20)
Disliking school, negative feelings about school, not doing well
Feeling happy at school and doing well
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Qual Life Res Table 2 Gender comparisons with KIDSCREEN dimensions (n = 1000)
KIDSCREEN dimension
Male
Female
F
p
.000*
n
Mean
SD
n
Mean
SD
Physical well-being
524
51.33
12.06
476
46.11
9.92
53.37
Psychological well-being
524
46.97
10.73
476
44.94
9.85
8.83
.003*
Autonomy and parent relations
524
50.66
13.84
476
47.51
11.99
13.99
.000*
Social support and peers
524
50.55
12.65
476
51.76
10.83
3.11
.078
School environment
524
49.27
12.13
476
49.16
10.37
.001
.974
* p \ .05
Table 3 Grade (age) comparisons with KIDSCREEN dimensions (n = 1000) KIDSCREEN dimension Grade (age)
n
Year 7 (12–13)
270
Physical well-being
Psychological well-being
Autonomy and parent relations
Social support and peers
School environment
Mean
51.92*
47.52*
49.79*
52.42*
52.11*
SD
10.93
10.02
13.43
12.04
11.68
Year 8 (13–14)
252
Mean
48.21*
45.79*
49.66*
51.00
48.27*
Year 9 (14–15)
239
SD Mean
10.88 48.63*
10.42 46.40*
12.84 50.16*
11.46 52.09*
10.47 48.70*
SD
11.80
10.22
12.84
11.20
11.40
Year 10 (15–16)
184
Mean
46.98*
44.90
47.86
49.41
47.99*
SD
10.53
10.78
11.80
11.37
10.20
Year 11 (16–17)
55
Mean
43.87*
41.47*
43.79*
46.95*
45.69*
SD
13.43
9.54
16.21
14.94
13.91
F = 9.48, p B .001*
F = 4.67, p = .001*
F = 3.16, p = .013*
F = 4.12, p = .003*
F = 6.99, p B .001*
MANCOVA Results * p \ .05
Discussion The aim of this study was to examine the HRQoL in a school-based sample of Australian adolescents, by exploring age and gender differences across the KIDSCREEN dimensions. The majority of participants reported high levels of HRQoL; however, a small percentage of participants reported concerning scores indicative of poor HRQoL. Consistent with other international studies [9, 10, 17–20], gender differences, while controlling for age, were found in this Australian sample on three of the five dimensions of HRQoL: physical well-being, psychological well-being, and autonomy and parental relations: with females reporting lower levels of HRQoL. Despite these gender differences being statistically significant, only one of the three was in the moderate effect size range, and likely to be perceived as clinically meaningful [21]. Nonetheless, these gender differences may be due to diverse social expectations, puberty being
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a more significant experience for females (i.e. menstruation and fluctuating hormones), and females having more frequent physical health problems [22, 23]. These findings are comparable to European norms and contribute to the international data on similarities and differences in HRQoL across countries outside of Europe. This study also found significant age differences, with the youngest participants (year 7, age range 11–13) scoring higher across all five dimensions of HRQoL compared to older participants (particularly year 10 and 11, age range 15–17), with incremental decreases in HRQoL across ages. However, these effect sizes were small and therefore unlikely to be clinically meaningful. Although the sample size for the oldest group of students was smaller, the pattern of declining HRQoL, with the oldest participants being the most different to all other age groups, is consistent with previous studies [9, 10, 13, 19, 24]. This study, the first of its kind in Australia to use a KIDSCREEN questionnaire to measure HRQoL, is not
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without limitations, namely uneven age representation and a relatively small sample population. However, the sample in this study is representative of the Australian multicultural population as 24 % of Australia’s population was born overseas and 43 % of people have at least one overseas-born parent [25]. Nevertheless, future research is required to conduct a nationwide examination of the HRQoL of Australian adolescents, to broaden the population representativeness in terms of cultural, geographical, and economic diversity. Furthermore, while HRQoL scores in this sample were consistent with the European norms, the KIDSCREEN instruments are not designed to be used as a diagnostic tool and therefore individual variations cannot be interpreted as clinically significant. Notwithstanding these limitations, this study confirms the pattern of gender and age differences in adolescent HRQoL identified in European studies using the KIDSCREEN measure, and adds Australian data to the body of international literature. Given the recognition of the multifactorial aetiology of mental problems in children and adolescents [26] and the close link between mental and physical health [27], overall quality of life may be an important and informative indicator of adolescents’ well-being. It may also provide an early indication of vulnerability and inform preventative measures that could be delivered within a school setting. Future research may build on these preliminary findings by further investigation of age, gender, and socio-economic influences on HRQoL across time, and a broader sample of Australian adolescents. This knowledge may then inform appropriate physical and mental health literacy at the school level, such as wellness and resilience-building programs. Acknowledgments This study was funded by the Australian Research Council, Grant No. LP100100369 titled ‘Bridging the gap on locational disadvantage: Impact of community-identified interventions on social capital, psychosocial and socioeconomic outcomes’. The research was conducted by the University of Western Sydney research team headed by Professor Rhonda G Craven and chief investigators A/Prof Geoffrey E Munns and A/Prof Tanya Meade in partnership with The Benevolent Society and partner investigators Dr Genevieve Nelson, Mr Andrew Anderson. We thank the six schools for participating in this study. We also thank Dr Michael Hough for statistical advice and assistance. Conflict of interest flict of interest.
All the authors declare that they have no con-
Compliance with ethical standards This study was approved by the University of Western Sydney Human Ethics Committee and the Department of Education, New South Wales Ethics Committee. The study was conducted according to the Helsinki ethical principles of research. Informed consent All participants provided informed consent prior to their participation in the research.
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