Public Health
Deterioration Is Not the Only Prospect for Adolescents’ Health:
Improvement in Self-reported Health Status Among Boys and Girls From
Age 15 to Age 19
Ferdinand Salonna1 , Berrie Middel2, Maria Sleskova1 , Andrea Madarasova
Geckova1 , Sijmen A. Reijneveld2, Johan W. Groothoff2, Jitse P. van Dijk1,2
1
Department of Educational
Psychology and Health
Psychology, Košice Institute
for Society and Health, Faculty
of Arts, P.J. Safarik University,
Košice, Slovakia
2
Department of Social Medicine,
University Medical Center
Groningen, University of
Groningen, the Netherlands
> Correspondence to:
Jitse P. van Dijk
Department of Social Medicine
University Medical Center Groningen
University of Groningen
Ant. Deusinglaan 1
9713 AV Groningen, Netherlands
[email protected]
Aim To assess changes in the mental and physical health of adolescents
between the ages of 15 and 19.
Methods The study included a four-year follow-up of 844 students
from 31 secondary schools located in Košice, Slovakia (response rate
45.6%). The 36-item short form (SF-36) scales were used to assess vitality and mental health, self-rated health, long-term well-being, longstanding illness, and the number of perceived health complaints at the
age of 15 and four years later.
Results Both boys and girls reported significant deterioration in vitality (mean difference boys 5.3; girls 3.3; P = 0.001) and mental health
(mean difference boys 7.7; girls 5.7; P = 0.001), while only boys reported deterioration in self-rated health (P = 0.047). The proportion
of boys who reported an improvement ranged from 8%-40%, while the
proportion of girls who reported an improvement ranged from 8%45%. Significantly more girls than boys reported an improvement in
mental health (27% of boys vs 34% of girls) and vitality (32% of boys
vs 39% of girls), while more boys than girls reported a deterioration in
vitality(55% of boys vs 48% of girls)). These differences were trivial according to the effect size (Cohen’s H<0.20).
Conclusion Although significant deterioration in mental health and
vitality was detected among both genders, with boys deteriorating more
substantially in self-rated health than girls, the differences between the
proportion of those with improved and those with deteriorated status
were trivial in size.
> Received: April 17, 2007
> Accepted: November 16, 2007
> Croat Med J. 2008;49:66-74
> doi: 10.3325/cmj.2008.1.66
66
www.cmj.hr
Salonna et al: Improvement of Adolescents’ Health
It is of interest to study change in health during the period of adolescence because it has a
psychological and physical impact on adolescents’ further development. In general, health
status of subjects during this period is assumed
to deteriorate (1-3). Several studies have
shown that girls reported worse health than
boys (4-7). These gender differences remain
stable over time, as was shown in a longitudinal study of Finnish adults (4).
The fact that physical and psychological
health deteriorates in the period preceding
adulthood is shown in many studies (1,8-11).
Most of these results were found by crosssectional studies. Both in the cross-sectional study by Wade et al (10) among Americans and Canadians aged from 11 to 21 years,
and the longitudinal study by Mechanic (12)
among Americans aged 12 to 17, no change
in self-reported health was found. A crosssectional study by Waters et al (13) on Australians aged from 11 to 18 found different effects of age on self-reported health. However,
the cross-sectional studies by Hidalgo (2) on
the Spanish respondents aged from 14 to 20
and by Simeoni (14) on French adolescents
aged 11 to 17 reported worsening of psychological well-being. Furthermore, Currie et al
(8) reported worsening of self-reported health
with advancing age in a study that investigated the health status of children and adolescents aged 11, 13, and 15 years in 35 countries
and regions of the United States and Europe.
Wade et al (15) in a longitudinal study reported a substantial worsening of self-reported
health and depressive symptoms in children
from age 11 to age 15, followed by a plateau
(stable period) from age 15 to age 19 and an
improvement in health after the 19th year.
However, in contrast with these outcomes,
the results of Hankin et al (16) on clinical depression showed a plateau in children from
age 11 to age 15, worsening between age 15
and age 18 year, and again a plateau from age
18 to age 21. Furthermore, Wight et al (11)
found that the prevalence of depressive symptoms increased from the age 12 to 20, with a
plateau between the age of 15 and 17. Thus,
the results of both cross-sectional and longitudinal studies on changes in health status
are consistent, since there was, on average,
no improvement between the ages of 11 and
19. The results of these studies on perceived
health status among adolescents suggest that
health seems to be set to deteriorate or remain
stable during certain phases. This may lead to
a bias that distracts public health researchers
and professionals from the hypothesis that in
a given population it is also relevant to detect
those who improved, even though the majority deteriorates or remains stable. Therefore,
the current longitudinal study was performed
to contribute to the clarification of the direction and magnitude of changes in health status in a cohort of 15-year-old adolescents who
were followed-up to the age of 19.
Participants and methods
Participants
The sample was stratified according to the type
of secondary school. After leaving elementary school (9 years of attendance), Slovak adolescents aged around 15 enter one of the following four types of secondary schools: 1)
four-year general secondary school providing
brode education and preparation for university study; 2) four-year specialized secondary
school providing usually technical education,
after which it is also possible to study at university; 3) four-year apprentice school providing education for manual occupations; 4)
three or two-year apprentice school providing
only basic education for manual occupations.
A computer program generating random
numbers was used to randomly select numbered schools per stratum. After inclusion, no
school dropped out.
67
Croat Med J 2008;49:66-74
The sample consisted of 1850 first grade
students from 31 secondary schools (7 general secondary schools, 13 specialized schools,
11 apprentice schools 4 four-year, and 7 threeyear apprentice schools) located in Košice,
Slovakia. Based on official statistical data from
the Institute of Information and Prognosis of
Education, Bratislava, we ensured by means of
quota sampling that the proportions of male
and female students and their educational levels represented their proportions in Slovakia.
Participants completed the baseline questionnaire in their classrooms, under the guidance
of field workers. Four years later, respondents
received a self-administered questionnaire
by mail together with a stamped return envelope. A single reminder was sent to those who
did not reply. We received 844 questionnaires
that served the purpose of analysis, representing the response rate of 45.6%.
Outcome measures
According to Hammarström and Janlert (17),
the most common way of examining health
problems among young people is through selfreported symptoms. Six subjective health indicators assessing the health status of respondents were used in this study.
Self-rated health is widely used in health
studies because it is generally accepted as a
good predictor of mortality and morbidity
(18). Respondents assessed their health using the five-point Likert scale from “excellent” to “bad.” For this analysis, excellent and
very good health ratings were considered as
one group; while good, fairly good, and bad
ratings were, according to the findings of
Geckova (19), considered as a second group.
Vitality and mental health are two scales
in the 36-item RAND questionnaire (20).
The vitality scale consists of four items focusing on energy and fatigue. Mental health scale
is a five-item scale focusing on psychological distress and well-being. For both indica-
68
tors, respondents were asked to evaluate their
feelings during the previous four weeks using
five-point Likert scales. Sum scores were then
transformed into scales with a possible range
from 0 (worst) to 100 (best).
Prevalence of a long-standing illness was
assessed by the following question: “Do you
have any long-standing illness (lasting for
more than three months)?” with the response
options “yes” and “no” (21).
Long-term well-being was measured on
a seven-point scale consisting of stylized faces, with “1” representing the highest degree of
well-being and “7” the lowest. Respondents
rated their feelings about their life over the past
year. The scale was used to assess socio-emotional health, in addition to global and physical health measured by other indicators. This
simple scale provides a better representation of
respondent’s feelings than similar verbal scales,
with a sufficient test-retest reliability and a median validity coefficient of 0.82 (22).
Information on self-reported health complaints was collected by the Netherlands
Health Interview Survey (VOEG) (23-25).
It comprises thirteen dichotomous questions
on complaints related to general fatigue, the
stomach, musculoskeletal system, and cardiovascular system. Internal scale reliability
proved to be good (Cronbach’s α = 0.86) and
test-retest reliability was satisfactory (Pearson
r = 0.76) (26). Possible scores on the VOEG
scale ranged from 0 to 13, with a higher score
indicating more health complaints.
Estimation of longitudinal changes
Outcomes of statistical testing for average difference scores between independent samples
or paired observations may result in a mean
difference score, indicating deterioration
due to the fact that a majority of these difference scores indicate deterioration after subtraction of two mean scores. However, this
does not mean that positive (improvement)
Salonna et al: Improvement of Adolescents’ Health
or zero scores (remaining stable) do not exist
in the distribution. Using the respondents as
their own “controls” allows for comparisons
between those who improve, remain stable,
or deteriorate in health. Detection of those
who reported an improvement, remained stable, or reported deterioration was performed
in two steps. In the first step, we differentiated a change found by sample fluctuation from
a significant change in perceived health between the ages of 15 and 19 and estimated the
magnitude of the difference with Cohen’s effect size “d” (27) for continuous scales when
the change was significant. For individualized effect size calculation, we used the pooled
standard deviation as the standardizing unit
of mean difference score over time, so as to
avoid overestimation of effects (28). According to the thresholds of Cohen, health status
was classified as deteriorated with an effect
size ≤-0.20, as stable with an effect size between -0.19 and +0.19, and as improved with
an effect size ≥+0.20, only in cases when the
mean difference was not due to random error (P<0.05). For χ2 differences Cohen’s effect
size “w” was used (29). Thresholds of effect
size “w” for appraisal of “small,” “medium,”
and “large” differences between proportions
were 0.10, 0.30, and 0.50, respectively.
In the second step, we used the individualized effect size to detect proportions of those
who reported improvement (positive effect
size), remained stable (trivial effect size), or reported deterioration (negative effect size), and
tested the significance of differences in proportions (30) and estimated the magnitude of the
difference between proportions with Cohen’s
effect size “h” (31). Thresholds of effect size
“h” for appraisal of “small,” “medium,” and
“large” differences between proportions were
0.20, 0.50, and 0.80, respectively. For effect
size interpretation, Cohen (27) used the term
trivial, which we prefer to the term “insignifi-
cant,” since the term “insignificant” carries the
relationship to statistical significance.
Statistical analysis
Analyses were performed using the Statistical
Package for the Social Sciences, version 12.0.1
(SPSS Inc. Chicago, IL, USA) and for all tests
P-values of <0.05 were considered significant.
Differences between the means were not normally distributed (Shapiro Wilk, P<0.05) and,
therefore, paired testing was done using a nonparametric test. Longitudinal change between
the ages of 15 and 19 years was analyzed with
Wilcoxon matched-pairs signed ranks test for
continuous variables and McNemar test for
dichotomized data. We calculated 95% confidence intervals (95% CI) for the differences in
proportions (30). Discrete variables were compared with the χ2 (Fisher exact test when appropriate).
results
The sample consisted of 844 adolescents who
participated in the study at the age of 15 and
19. At baseline, 1850 students participated and were invited to fill out the questionnaire at the age of 19. The response rate was
45.6%. At baseline boys and girls did not differ in the six health indicators used in this
study (Table 1). Girls were over-represented
in the responder group, in comparison with
the non-response group (Table 1). More general secondary school students and fewer apprentice students participated in the second
stage of the study. Students who participated in the second stage of the study had at the
age of 15 a significantly worse mental health,
vitality, a higher number of physical complaints, a better long-term well-being, and a
lower prevalence of long standing illness than
those who did not participate in the second
stage. However, according to Cohen’s thresh-
69
Croat Med J 2008;49:66-74
Table 1. Characteristics of student responders and non-responders at baseline
Parameter
Sex*:
female
male
Type of school*:
general
specialized
apprentice
Short-Form-36 (SF-36) self-rated health*:
excellent/very good
good/fairly good/bad
Long-standing illness >3 mo*:
yes
no
SF-36 vitality║
SF-36 mental health║
Number of self-rated health complaints
(VOEG)║
Long-term well-being║
Non-responders (n = 1006)
Responders (n = 844)
P
Effect size
468 (46.5)
538 (53.5)
483 (57.2)
361 (42.8)
0.001†
0.21‡
193 (19.2)
420 (41.7)
393 (39.1)
247 (29.3)
382 (45.3)
215 (25.5)
6.2-14.0§
-10.2-8.0§
-9.3-17.7§
0.356†
0.09‡
518 (61.4)
325 (38.6)
636 (63.5)
637 (36.5)
0.043†
0.12‡
83 (9.8)
761 (90.2)
983 (0.63±0.17)
983 (0.69±0.16)
1003 (2.12±2.44)
72 (7.2)
933 (92.8)
838 (0.60±0.17)
838 (0.67±0.16)
844 (2.47±2.39)
0.003¶
0.005¶
0.016¶
0.18 (0.08-0.27)**
0.13 (0.03-0.22)**
0.14 (0.05-0.24)**
983 (1.58±0.49)
838 (1.55±0.50)
0.027†
0.06 (0.03-0.15)**
*No. (%).
†Fisher exact test.
‡Cohen’s H
§95% confidence interval for difference of proportions.
║No.; mean (standard deviation).
¶t test.
**Cohen’s d - pooled effect size (95% confidence interval for effect size ) (27).
††Mann-Whitney U-Wilcoxon-W test.
olds these significant differences were trivial
in size (Table 1) (27).
Longitudinal changes in mental and physical
health among boys and girls
Boys and girls reported a significant deterioration (P<0.05 for both) in vitality and mental
health between the ages of 15 and 19. Among
girls the longitudinal change in vitality was
trivial in size (although significant), but the
change in mental health in both genders exceeded the criterion of effect size ≥0.20. Boys
and girls reported a significant deterioration
in long-term well-being with moderate effect sizes. No significant differences between
boys and girls aged from 15 to 19 were found
in the number of self-reported physical complaints assessed with the VOEG and in the
prevalence of a long-standing illness. Only
in boys, self-rated health deteriorated significantly from excellent or very good at the age
of 15 to good, fairly good, or bad at the age of
19. According to Cohen’s thresholds for the
effect size “w,” this change was found to be
70
small since it exceeded the criterion of effect
size ≥0.10.
We showed that, on average, boys and girls
experienced a deterioration in their self-perceived health, which confirms the general trend
in measuring health in this important stage of
life (Table 2). However, this average outcome
does not imply that there are no subjects who
improved in health or remained stable.
Although young adolescents deteriorated
in 6 domains of health status (6-60% of boys;
6-56% of girls), but relevant proportions of
boys and girls improved (8-40% of boys; 845% of girls) or remained stable (13-86% of
boys; 10-86% of girls) between the age of 15
and 19 (Table 3).
The proportions of girls who reported an
improvement, remained stable, and reported a
deterioration in long-term well-being, health
complaints, and long-standing illness were
not significant in comparison with boys. The
differences in proportions between boys and
girls who remained stable and who reported a
deterioration in self-rated health and mental
health were not significant. Also, the differ-
Salonna et al: Improvement of Adolescents’ Health
Table 2. Change in mental and physical health status between boys and girls aged 15 and 19
Boys (n = 359)
Scale
15 y*
19 y*
effect size
†
SF-36 vitality
63.8±16.6
SF-36 mental health
71.2±14.8
Long-term well-being
2.4±0.9
Number of self-rated health complaints (VOEG) 2.0±2.2
Long-standing illness >3 mo (%)
7.9
SF-36 self-rated health
Excellent/very
good 19 y
Good/ fairly
good/bad 19 y
Excellent/very good at 15 y
Good/fairly good/bad at 15 y
68
64
181
46
Girls (n = 479)
P (Z)
58.5±17.1
63.5±15.8
2.8±1.3
1.8±2.3
7.2
0.001
0.001†
0.001†
0.532†
0.942‡
0.047‡
§
-0.32
-0.52§
0.54§
0.1║
15 y*
57.4±17.6
64.6±15.7
2.4±0.9
2.8±2.4
8.7
19 y*
effect size§
P (Z)
54.1±17.6
58.9±17.9
2.9±1.3
2.8±2.6
8.7
Excellent/very Good/fairly
good 19 y
good/bad
19 y
192
76
93
120
†
0.001
0.001†
0.001†
0.849†
0.368†
-0.18
-0.36
0.71
0.218†
*Mean±standard deviation.
†Wilcoxon matched pairs signed rank test.
‡McNemar test.
§Cohen’s d.
║Cohen’s W
Table 3. Proportions of boys and girls who reported improvement, remained stable, and reported deterioration in six health measures and the differences between boys and girls*
Boys (%)
Scale
Self-rated health
Vitality
Mental health
Long-term well-being
Health complaints
Long-standing illness
13
32
27
40
38
8
68
13
13
36
29
86
Difference in proportions (boys vs girls; 95% confidence interval)
Girls (%)
stable
improvement period deterioration
19
55
60
24
33
6
stable
improvement period deterioration
19
39
34
45
44
8
65
13
10
34
18
86
16
48
56
21
38
6
improvement
stable
period
deterioration
0.01-0.11
0.04-13.6
0.01-12.8
-0.13-0.01
-0.04-0.04
–
-0.04-0.09
-0.04-0.05
-0.01-0.07
-0.04-0.09
0.05-0.17
–
-0.02-0.08
0.01-0.15
-0.03-0.11
-0.03-0.09
-0.12-0.01
–
P
effect size/
Cohen’s H
0.031i
0.164
0.033i/0.024d 0.146i/0.140d
i
0.041
0.152
NA
NA
–
NA
*Abbreviations: i – improvement; d – deterioration.
ence between stable boys and girls on vitality
was not significant. However, the proportion
of girls who reported an improvement in perceived self-rated health (19%) differed significantly from the proportion of boys who reported an improvement (P = 0.031; 95% CI,
-0.01 to -0.11). The proportion of girls who
reported an improvement in vitality between
the age of 15 and 19 (39%) differed significantly from the proportion of boys (32%)
(P = 0.033; 95% CI, 0.04-13.6). Furthermore,
the difference in the proportion of boys and
girls who reported a deterioration in vitality
(55% vs 48%) was significant (P = 0.024; 95%
CI, 0.01-0.15). The proportion of girls who
reported an improvement in mental health
(34%) differed significantly from that of boys
(27%) (P = 0.041; 95% CI 0.01- 12.8). However, although significant, these differences
were, according to the thresholds of Cohen’s
“h” effect size, trivial in size.
Discussion
In the current study, boys reported a small deterioration in self-rated health. Both boys and
girls reported a deterioration in vitality and
mental health. However, the change in vitality was small for boys and trivial in size for
girls. Furthermore, the extent of deterioration
in mental health in boys was moderate, compared with the small extent of deterioration
in girls. Both boys and girls reported a moderate deterioration in long-term well-being
according to the thresholds of Cohen’s effect
size. Thus, in the three domains of self-reported health, boys reported more deterioration
than girls.
Contrary to the general trend of deterioration in health status in adolescence observed
in the literature, we detected substantial proportions of boys and girls who reported an
improvement in health. For the health indica-
71
Croat Med J 2008;49:66-74
tors used in this study, the proportions of adolescents who reported an improvement ranged
from 8% to 40% in boys and from 8% to 45%
in girls. Four out of 18 comparisons between
boys and girls who reported an improvement
were, although significant, trivial in size.
Most of 19-year-old adolescents refused to
participate in the research dealing with questions on personal health, psychological wellbeing, and risky health-related behavior. Furthermore, at the age of 19 many changed the
place of residence to go to study or start a professional career, which resulted in the return of
a substantial number of mailed questionnaires,
with the annotation “address unknown.” Nevertheless, 844 (46%) subjects filled out a questionnaire that was identical to the questionnaire they filled out at the age of 15. Female
adolescents were more likely to participate as
they were general secondary school students,
who are presumed to have a better health status. Responders had worse health status according to SF-36 and VOEG scales. Still, these
differences were, according to Cohen’s thresholds, trivial in size.
The main purpose of this study was to perform a longitudinal comparison of self-rated health status of adolescents from age 15 to
age 19. Subjects were their own controls in a
repeated measurement. The study also focused
on analyzing gender differences and identifying proportions of male and female adolescents who reported an improvement, remained stable, and reported a deterioration.
Both boys and girls reported deterioration in
vitality and mental health between the age of
15 and 19, while only boys reported a deterioration in self-rated health. The prevalence of
perceived health complaints and long-standing illness at 19 remained unchanged since
baseline.
In comparison with boys, girls reported
having worse health in five health indicators
both at the age of 15 and at the age of 19,
72
which is in line with several previous studies
(2-4,32-35). However, in this study, differences in health indicators between boys and
girls were not significant between the baseline and follow-up. According to the literature, it could be assumed that there would
be a general lifelong trend of deterioration
of health with increasing age. This general
trend is disturbed by some further deterioration in the periods of major life transitions
(2,8,11,12,14,15). Worse health in adolescents and adult females seems to be a general finding. However, although it is widely accepted, this belief should not be generalized
for all health indicators. This study shows
that for both sexes, scores on mental health
measures (eg, vitality, mental health, longterm well-being) deteriorated, while the
scores on physical health measures (number of physical health complaints and longstanding illness) did not change between
the baseline (age 15) and follow-up (age 19).
Only boys reported a significant deterioration in self-rated health. The period of life
investigated in this study is a period of important life transition associated with numerous stressful events, ie, preparing for
end-of-school exams, going to university, or
looking for a job. Studies covering health in
adolescence mostly reported either stability
or worsening of health status in the period
between the 15th and 19th year (10,12,14).
Furthermore, some studies reported alternating periods of worsening, as well as plateaus,
in health status (11,15,16).
To our knowledge, no studies have detected substantial improvement in self-reported health during this phase of adolescence.
However, our study has shown that the
health status of some subgroups of adolescents improved with increasing age. Adolescence is a time in which life-style and healthrelated behaviors are being established. A
substantial part of research efforts are aimed
Salonna et al: Improvement of Adolescents’ Health
at studying young adolescents at risk of getting involved in smoking, drug, and alcohol use, which may negatively affect health.
However, improvement in health in the current study may be related to a health-protective lifestyle.
Friis et al (36) found in a 4-5-year-long longitudinal study that absence of stressful school
and family events was related to improvement
in depressive disorders in respondents aged 1424 years at baseline.
With regard to the statistical conclusion
validity, the most relevant strength of this
study is its follow-up nature, where each participant serves as his or her own control. Due
to high costs and complex management, longitudinal studies are not very common, especially studies focusing on young people. Most
information about health of this age group is
obtained by cross-sectional studies, whereas
less data are obtained by longitudinal studies.
The main limitation of this study is the low response rate at follow-up. This is common in
longitudinal studies among school-attending
young adolescents, since a large proportion
move to study or work elsewhere. Although
differences in gender and education between
response and non-response groups did not occur due to sampling error, they were small according to standardized indices of differences between groups (effect sizes). Since in large
samples, small or trivial differences are likely to
become significant, we have come to the conclusion that the external validity is not hampered by unacceptably large differences.
Another strength of this study is the sample size. The sample was randomly selected
from each type of secondary schools in Slovakia. The sample represents the school population of school-attending adolescents in eastern part of Slovakia. Differences between the
ages of 15 and 19, due to sample fluctuation or
chance, were not used to estimate the change
with effect sizes.
The importance of this study is that we
identified not only deterioration, but also
improvement and stability in self-reported
health among boys and girls between the ages
of 15 and 19. More longitudinal studies, with
shorter time intervals, should be designed to
determine factors that may explain changing
mental and physical health and their (causal) paths with structural equation modeling.
Outcomes of such studies should provide support for a well-tailored and evidence-based
health policy for the adolescent population
and relevant strata.
Acknowledgment
The study was supported by internal funding of the Safarik University Košice, Slovakia and the University Medical Center of the Groningen University in the Netherlands.
references
1
Currie C, Hurrelmann K, Settertobulte W, Smith R,
Todd J. Health and health behaviour among young people.
Copenhagen: WHO Regional Office for Europe; 2000.
2
Hidalgo I, Garrido G, Hernandez M. Health status and
risk behavior of adolescents in the north of Madrid, Spain.
J Adolesc Health. 2000;27:351-60. Medline:11044708
doi:10.1016/S1054-139X(00)00100-2
3
Sleskova M, Salonna F, Madarasova Geckova A, van Dijk
JP, Groothoff JW. Health status among young people
in Slovakia: comparisons on the basis of age, gender and
education. Soc Sci Med. 2005;61:2521-7. Medline:15950348
doi:10.1016/j.socscimed.2005.04.039
4
Lahelma E, Martikainen P, Rahkonen O, Silventoinen
K. Gender differences in illhealth in Finland: patterns,
magnitude and change. Soc Sci Med. 1999;48:7-19.
Medline:10048834 doi:10.1016/S0277-9536(98)00285-8
5
Schraedley PK, Gotlib IH, Hayward C. Gender differences
in correlates of depressive symptoms in adolescents. J Adolesc
Health. 1999;25:98-108. Medline:10447037 doi:10.1016/
S1054-139X(99)00038-5
6
Settertobulte W, Kolip P. Gender-specific factors in
the utilization of medical services during adolescence. J
Adolesc. 1997;20:121-32. Medline:9063779 doi:10.1006/
jado.1996.0068
7
Wyke S, Hunt K, Ford G. Gender differences in consulting a
general practitioner for common symptoms of minor illness.
Soc Sci Med. 1998;46:901-6. Medline:9541075 doi:10.1016/
S0277-9536(97)00217-7
8
Currie C, Roberts C, Morgan A, Smith R, Settertobulte W,
Samdal O, et al, editors. Young people’s health in context:
international report from the HBSC 2001/02 survey.
Copenhagen: WHO Regional Office for Europe; 2004.
9
King A, Wold B, Tudor-Smith C, Harel Y. The health of
youth: a cross-national survey. Copenhagen: WHO Regional
Office for Europe; 1996.
10
Wade TJ, Pevalin DJ, Vingilis E. Revisiting student
73
Croat Med J 2008;49:66-74
self-rated physical health. J Adolesc. 2000;23:785-91.
Medline:11161339 doi:10.1006/jado.2000.0359
11
Wight RG, Sepulveda JE, Aneshensel CS. Depressive
symptoms: how do adolescents compare with adults? J
Adolesc Health. 2004;34:314-23. Medline:15041001
12
Mechanic D, Hansell S. Adolescent competence,
psychological well-being, and self-assessed physical health.
J Health Soc Behav. 1987;28:364-74. Medline:3429806
doi:10.2307/2136790
13
Waters E, Wake M, Toumbourou J, Wright M, Salmon
L. Prevalence of emotional and physical health concerns
amongst young people in Victoria. J Paediatr Child Health.
1999;35:28-33. Medline:10234631 doi:10.1046/j.14401754.1999.00338.x
14
Hartgers C, Van den Hoek JA, Coutinho RA, Van der Pligt
J. Psychopathology, stress and HIV-risk injecting behaviour
among drug users. Br J Addict. 1992;87:857-65. Med
line:1525529 doi:10.1111/j.1360-0443.1992.tb01980.x
25
Martens MF, Nijhuis FJ, Van Boxtel MP, Knottnerus JA.
Flexible work schedules and mental and physical health. A
study of a working population with non-traditional working
hours. Journal of Organizational Behavior. 1999;20:35-46.
doi:10.1002/(SICI)1099-1379(199901)20:1<35::AIDJOB879>3.0.CO;2-Z
26
van der Velden J, Abrahamse HP, Donker G, van der Steen J,
van Sonsbeek JL, van den Bos GA. What do health interview
surveys tell us about the prevalences of somatic chronic
diseases? A study into concurrent validity. Eur J Public
Health. 1998;8:52-8. doi:10.1093/eurpub/8.1.52
27
Cohen J. The t test for means. In: Cohen J. Statistical power
analysis for the behavioural sciences. 2nd ed. Hillsdale (NJ):
Lawrence Erlbaum Associates; 1988. p. 19-74.
28
Middel B, van Sonderen E. Statistical significant change versus
relevant or important change in (quasi) experimental design:
some conceptual and methodological problems in estimating
magnitude of intervention-related change in health services
research. Int J Integr Care. 2002;2:e15. Medline:16896390
15
Wade TJ, Cairney J, Pevalin DJ. Emergence of gender
differences in depression during adolescence: national
panel results from three countries. J Am Acad Child
Adolesc Psychiatry. 2002;41:190-8. Medline:11837409
doi:10.1097/00004583-200202000-00013
16
Hankin BL, Abramson LY, Moffitt TE, Silva PA, McGee R,
Angell KE. Development of depression from preadolescence
to young adulthood: emerging gender differences in a 10-year
longitudinal study. J Abnorm Psychol. 1998;107:128-40.
Medline:9505045 doi:10.1037/0021-843X.107.1.128
29
Cohen J. Chi-Square tests for goodness of fit and
contingency tables. In: Cohen J. Statistical power analysis for
the behavioural sciences. 2nd ed. Hillsdale (NJ): Lawrence
Erlbaum Associates; 1988. p. 215-71.
30
17
Hammarstrom A, Janlert U. Nervous and depressive
symptoms in a longitudinal study of youth unemployment
– selection or exposure? J Adolesc. 1997;20:293-305.
Medline:9208348 doi:10.1006/jado.1997.0086
Newcombe RG, Altman DG. Proportions and their
differences. In: Altman DG, Machin D, Bryant TN, Gardner
MJ, editors. Statistics with confidence. 2nd ed. Bristol:
British Medical Journal Books; 2000. p. 45-56.
31
18
Sadava SW, O’Connor R, McCreary DR. Employment
status and health in young adults: economic and behavioural
mediators? J Health Psychol. 2000;5:549-60.
Cohen J. Differences between proportions. In: Cohen
J. Statistical power analysis for the behavioural sciences.
Hillsdale (NJ): Lawrence Erlbaum Associates; 1988. p. 179213.
19
Geckova A, Tuinstra J, Pudelsky M, Kovarova M, van Dijk JP,
Groothoff JW, et al. Self-reported health problems of Slovak
adolescents. J Adolesc. 2001;24:635-45. Medline:11676510
doi:10.1006/jado.2001.0422
32
20
Ware JE Jr, Sherbourne CD. The MOS 36-item short-form
health survey (SF-36). I. Conceptual framework and item
selection. Med Care. 1992;30:473-83. Medline:1593914
doi:10.1097/00005650-199206000-00002
Cullen KW, Koehly LM, Anderson C, Baranowski T,
Prokhorov A, Basen-Engquist K, et al. Gender differences in
chronic disease risk behaviors through the transition out of
high school. Am J Prev Med. 1999;17:1-7. Medline:10429746
doi:10.1016/S0749-3797(99)00038-0
33
Glendinning A, Love JG, Hendry LB, Shucksmith J.
Adolescence and health inequalities: extensions to Macintyre
and West. Soc Sci Med. 1992;35:679-87. Medline:1439918
doi:10.1016/0277-9536(92)90006-C
Madarasova Geckova A, van Dijk JP, Honcariv R, Groothoff
JW, Post D. Influence of health risk behavior and socioeconomic status on health of Slovak adolescents. Croat Med
J. 2003;44:41-9. Medline:12590428
34
Andrews FM. Psychological well-being: four single-item
indicators of well-being. In: McDowell I, Newell C, editors.
Measuring health. A guide to rating scales and questionnaires.
2nd ed. New York & Oxford: Oxford University Press; 1996.
p. 194-8.
Marcell AV, Klein JD, Fischer I, Allan MJ, Kokotailo PK.
Male adolescent use of health care services: where are the
boys? J Adolesc Health. 2002;30:35-43. Medline:11755799
doi:10.1016/S1054-139X(01)00319-6
35
Ustun TB. Cross-national epidemiology of depression
and gender. J Gend Specif Med. 2000;3:54-8. Medline:11
253247
36
Friis RH, Wittchen HU, Pfister H, Lieb R. Life events
and changes in the course of depression in young adults.
Eur Psychiatry. 2002;17:241-53. Medline:12381493
doi:10.1016/S0924-9338(02)00682-X
21
22
23
74
Simeoni MC, Sapin C, Antoniotti S, Auquier P. Healthrelated quality of life reported by French adolescents: a
predictive approach of health status? J Adolesc Health.
2001;28:288-94. Medline:11287246 doi:10.1016/S1054139X(00)00198-1
24
Jansen ME, Sikkel D. Shortened version of the statistical
report on long-standing illnesses in the Dutch population
in 1991 and 1992 [in Dutch]. Voorburg (The Netherlands):
Dutch Central Office for Statistics; 1994.