PEDIATRICS Vol. 121 No. 3 March 2008, pp. e449-e457 (doi:10.1542/peds.2007-1093)
ARTICLE |
Predictors of Persistent and New-onset Fatigue in Adolescent Girls
a Laboratory of Psychoneuroimmunology, University Medical Center Utrecht, Utrecht, Netherlands
b Department of Health Psychology, Utrecht University, Utrecht, Netherlands
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ABSTRACT |
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OBJECTIVE. The purpose of this study was to investigate the stability of fatigue in adolescents and to explore whether psychological, somatic, and lifestyle factors are involved in the onset and persistence of fatigue during adolescence.
METHODS. In this longitudinal study, a total of 653 adolescent girls (aged 14.40 ± 1.45 years) who previously participated in an epidemiological study filled out questionnaires 6 (T2) and 12 (T3) months after the initial assessment (T1). Fatigue severity, depression, anxiety, and chronic fatigue syndrome–related symptoms were assessed. We determined the prevalence of severely fatigued cases at T2 and T3 and evaluated whether persistently fatigued participants initially differed from nonfatigued participants and participants with transient fatigue. We examined which factors predicted the development of new-onset fatigue and investigated whether changes in fatigue covaried with changes in other complaints and changes in lifestyle.
RESULTS. Of all participants who were severely fatigued at T1, 25.7% were persistently fatigued throughout the study. Persistently fatigued participants had higher levels of depression and anxiety at the beginning of the study, were less physically active, and slept shorter. New-onset fatigue was predicted by depression, less physical activity, and more nightlife activities. Interestingly, new onset was not predicted by initial levels of fatigue. Persistently fatigued participants did not differ in initial fatigue severity from short-term fatigued patients. A decrease in fatigue severity was associated with a decrease in depression, anxiety, and chronic fatigue syndrome–related symptoms and, to a lesser extent, with an increase in physical activity and sleep duration.
CONCLUSIONS. The stability of severe fatigue among adolescents is substantial. The involvement in the onset and persistence of fatigue suggests that both preventive and therapeutic strategies with respect to fatigue treatment in adolescents should concentrate on emotional well-being. Moreover, adolescents at risk should be stimulated to spend more time on physical activities and to sleep longer.
Abbreviations: CFS—chronic fatigue syndrome • CIS—Checklist Individual Strength • BDI—Beck Depression Inventory • STAIC—State/Trait Anxiety Inventory for Children
Fatigue is a common complaint among adolescents and is often attributed to hormonal changes during puberty, psychological struggles, and new educational and social demands. In a recent epidemiologic study in 3454 adolescents, we showed that >20% of adolescent girls and 6% of the boys reported high levels of fatigue. In both genders, fatigue was associated with symptoms of depression and anxiety and with chronic fatigue syndrome (CFS)-related symptoms such as headaches, myalgia, unrefreshing sleep, and cognitive disturbances.1 Duration of fatigue was positively related to severity of fatigue and its comorbidities; that is, participants with fatigue duration of 1 to 3 months were more depressed and anxious and reported increased fatigue severity and more CFS-related symptoms than participants who were fatigued only transiently.1 We also found that fatigue was associated with increased sleep duration and reduced physical activity in combination with high rates of school absenteeism; however, in our epidemiologic study, we assessed only the participants cross-sectionally, which limited the identification of potential causal factors and, thereby, possible threats for cognitive and social development.
Fatigue is a symptom with high long-term stability. In adult populations, fatigue severity was shown to be a significant predictor of future fatigue and CFS development later.2–5 In an adult primary care sample, Hickie et al6 showed that 58% of patients with a diagnosis of prolonged fatigue with or without psychological distress still reported fatigue 12 months later. In adolescents, fatigue is a stable complaint as well,7 and symptoms often co-occur with other mental or physical complaints.8,9 Instead of focusing on fatigue as a single symptom, most long-term studies on complaints in adolescents examined a constellation of medically unexplained symptoms, as in somatization and somatoform disorders, in which fatigue is 1 aspect of a symptom complex.10,11 Overall, high stability of medically unexplained physical symptoms and psychological problems was observed and the experience of psychological difficulties (ie, depression) was found to be a risk factor for poor outcome and worsening of symptoms.12,13
In our current longitudinal study in female adolescents, with assessments in spring (T1), autumn (T2), and the successive spring (T3), we examined (1) whether participants with persistent fatigue (fatigued at T1, T2, and T3) initially differed from participants with transient fatigue complaints and (2) whether premorbid lifestyle characteristics and emotional status or CFS-related complaints were related to new-onset fatigue (not fatigued at T1 and T2 but fatigued at T3). We also investigated to what extent changes in fatigue severity covaried with changes in lifestyle and changes in depression, anxiety, and CFS-related symptoms.
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Participants
Of the 1747 female participants in an epidemiologic study on fatigue among adolescents, 934 also participated after 0.59 ± 0.08 years at T2 and 931 participants took part after 1.11 ± 0.06 years at T3. A total of 653 participants participated at all 3 time points and were included in this study. Data were collected at 6 Dutch secondary schools in the proximity of Utrecht University Medical Center (radius 30 km). All students in the first year of high school to students in the pregraduation year were asked to participate. Students and their parents were informed in writing. Data were collected in 3 waves (March and April 2002 to March and April 2003, n = 166; March and April 2003 to March and April 2004, n = 171; February, March, and April 2004 to February, March, and April 2005, n = 316), and all participants were assessed at 3 time points: spring (T1), autumn (T2), and the successive spring (T3). This study was approved by the Medical Ethical Committee of the University Medical Center Utrecht.
Measures
Paper-and-pencil questionnaires were distributed to the students by instructed tutors who monitored completion of the questionnaires. Self-reported fatigue was measured with the Checklist Individual Strength (CIS) questionnaire, which consists of the following 4 subscales together composing a multidimensional total fatigue score: (1): severity of fatigue, (2) concentration, (3) motivation, and (4) physical activity.14 The response to each of the 20 statements was scored on a 7-point Likert scale (1 = yes, that is true, to 7 = no, that is not true). Participants were instructed to indicate how they felt during the past 2 weeks. The CIS was originally developed to measure fatigue in the adult population. On the basis of our prevalence study, 1 item was excluded from the subscale "activity" to adjust the questionnaire to the adolescent population.1 Prevalence of severe fatigue was determined using a cutoff point of 40 on the "severity of fatigue" subscale, according to an adolescent CFS study by Stulemeijer et al.15
Depressive symptoms were measured using the Beck Depression Inventory (BDI), which is often used for adolescents.16 The BDI item concerning fatigability was excluded to avoid overlap between the CIS and the BDI. Trait anxiety was assessed with the Dutch version of the State/Trait Anxiety Inventory for Children (STAIC).17,18 The scale contains 20 items. Responses are scored on a 3-point scale (1 = almost never, 2 = sometimes, 3 = often). Self-reports of the CFS-related symptoms unrefreshing sleep, muscle pain, joint pain, headaches, tender lymph nodes, and memory and concentration problems in the past 2 weeks were recorded using a dichotomous scale (yes/no).19 For determination of time spent on extracurricular activities, participants were asked to report how many hours weekly they spent on homework, sports (at school and extracurricular), leisure time activities and hobbies, and friends and nightlife (bars, cinemas, parties) and whether they had an additional job. Sleep characteristics were measured by self-reports of bedtimes, time it takes to fall asleep (sleep-onset latency), and rise times during school days and weekends. BMI was calculated as self-reported body weight divided by the square of self-reported body height (kg/m2). Fatigue- and illness-related absenteeism in the past month (0 classes, 1–5 classes, 6–10 classes, 11–20 classes, >20 classes) was recorded as well. Participants were asked to report medication use and use of oral contraceptives and the experience of menarche.
Statistics
All analyses were performed with SPSS 12.0 (SPSS, Chicago, IL). Before analysis, all variables were tested for normality, log-transformation was applied when necessary, and extreme values (>3 SD) were excluded. Untransformed data are displayed in the figures and tables. Group differences in normally distributed data sets between responders and nonresponders and among nonfatigued, temporarily fatigued, and persistently fatigued participants were assessed by Student's t test or analysis of variance (with Bonferroni posthoc test), and 
2 test or Fisher's exact test was used for noncontinuous variables. Logistic regression analysis was performed to identify which past symptoms and lifestyle characteristics (sleep, extracurricular activities) at T1 and T2 were related to new-onset fatigue. No fatigue at any of the time points and new onset of high levels of fatigue at T3 served as the dependent variable. Multiple regression analysis was conducted to determine the contribution of predictor variables to fatigue severity. All 
scores (T1–T2 or T1–T3) of independent variables were entered at once, which is the most conservative method (fewer type 1 errors). The significance level for all analyses was set at P < .05.
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RESULTS |
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Participant Characteristics and Selection
Figure 1A presents the CIS total fatigue scores of all available participants at T1 (n = 1747), T2 (n = 934), and T3 (n = 931), and Fig 1B depicts CIS total fatigue scores for participants who took part in all 3 time points (n = 653). Group comparisons between participants who filled out the questionnaire at all 3 time points (responders) and participants who participated only at T1 or at T1 and 1 subsequent time point and T2 or T3 (partial responders, hereafter referred to as nonresponders) showed that nonresponders and responders did not differ at T1 in fatigue severity, depression, anxiety, and CFS-related symptoms and did not differ in BMI, medication use, and use of oral contraceptives. Also, no differences were observed with respect to sleep-onset latency and time spent on physical activities and homework. Equal proportions of responders and nonresponders had an additional job (nonresponders: 41.1%; responders: 39.5%;
2 = 6.10, P = .19); however, some selection bias was observed with respect to demographics and lifestyle characteristics. The nonresponders were slightly older than the responders (nonresponders: 14.79 ± 1.35; responders: 14.42 ± 1.45; t = 5.26, P < .001). In line with this, a somewhat larger proportion of nonresponders had experienced their menarche before T1 (nonresponders: 83.0%; responders: 75.9%; 2 = 13.07, P < .001). Nonresponders reported shorter total nocturnal sleep during the week, and on weekends, they spent more hours on nightlife activities, hobbies, and activities with friends. A larger proportion of nonresponders smoked (nonresponders: 7.4%; responders: 4.9%; 2 = 13.07, P < .001) or used alcohol (nonresponders: 44.4%; responders: 35.7%; 2 = 12.68, P < .001) compared with responders, whereas groups did not differ in drug use (nonresponders: 2.5%; responders: 1.5%; 2 = 1.75, P = .12). After correction for age, differences between groups disappeared, except that nonresponders spent more hours with friends. Table 1 presents the characteristics of responders and nonresponders.
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Persistent Fatigue
Prevalence of Severe Fatigue at T2 and T3
"Severe fatigue" was defined as a score of
40 on the severity of fatigue subscale of the CIS.1,15 Of all participants, 20.5% were severely fatigued at T1,1 and 17.0% and 15.1% of the girls were severely fatigued at T2 and T3, respectively. Of all severely fatigued participants at T1, 42.1% were still severely fatigued at T2 and 38.8% were still fatigued at T3. A total of 25.7% of the severely fatigued participants were severely fatigued at T2 and T3.
Characteristics of Participants With Persistent Fatigue
To investigate whether persistent fatigue depended on characteristics at T1, we compared 4 groups of participants classified on fatigue severity and duration. To increase the reliability of our findings, we enlarged the group of participants with persistently high levels of fatigue by using a minimal fatigue severity score of 35 instead of 40. Using this criterion, we were able to increase the various groups of fatigued individuals. Using the cutoff of 35, we defined 4 groups: (1) nonfatigued: participants with levels of fatigue <35 at all 3 time points (n = 348); (2) fatigued at T1: participants with a high level of fatigue (35) only at T1 (n = 57); (3) short-term fatigued: participants who reported fatigue 35 at T1 and T2 or at T1 and T3 (n = 72); and (4) persistently fatigued: participants with high levels of fatigue at all 3 time points (n = 83).
Symptoms and lifestyle characteristics of the groups at T1 are presented in Table 2. The girls in the nonfatigued group were younger than the girls in the other groups (F3,559 = 10.06, P < .001) and had a lower BMI (F3,539 = 6.13, P < .001) at T1 than participants with short-term fatigue and persistent fatigue. BMI did not differ between nonfatigued girls and girls who were fatigued at T1. In line with this, a smaller proportion of nonfatigued participants had experienced their menarche (2 = 27.12, P < .001) and used oral contraceptives (2 = 18.04, P < .001) at T1. Daily life activities at T1 did not differ between groups except for the time spent on physical activities and sleep duration. The girls in the nonfatigued group were significantly more active (F3,551 = 8.94, P < .001) and also had longer total nocturnal sleep (F3,542 = 13.16, P < .001) than participants with short-term fatigue and persistent fatigue. Sleep-onset latency during both weekdays and weekends at T1 was lower in the nonfatigued girls compared with the girls with persistent fatigue (respectively F3,539 = 5.68, P < .001; F3,532 = 4.47, P < .01). Obviously, girls with fatigue at T1, short-term fatigue, and persistent fatigue had higher scores of fatigue at T1 than the nonfatigued girls. Also, higher levels of depression and anxiety and more CFS-related symptoms were reported by the girls with fatigue at T1, short-term fatigue, and persistent fatigue compared with the nonfatigued girls. After exclusion of the nonfatigued girls, the girls with persistent fatigue had significantly higher levels of depression and anxiety at T1 than participants with fatigue at T1 and short-term fatigue (respectively F2,211 = 9.57, P < .001; F2,211 = 13.64, P < .001; Fig 2). Initial fatigue severity and reported CFS-related symptoms at T1 did not differ among these 3 groups. At all time points measured, girls with persistent fatigue consistently reported highest school absenteeism rates compared with the other groups. The proportion of participants using medication did not differ among groups. Correcting for age in all the analyses did not alter the results. To conclude, persistent fatigue was not related to increased fatigue severity or a higher number of CFS-related complaints at T1 as compared with the 2 temporarily fatigued subgroups. Persistent fatigue, however, was associated with higher levels of depression and anxiety and different sleep and physical activity patterns and was related to reduced school attendance throughout the study.
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Characteristics of New-Onset Fatigue
Of the girls without fatigue at T1 and T2 (fatigue severity <35), 28 (9.3%) developed high levels of fatigue (fatigue severity
35) at T3. Logistic regression analysis of comorbidities and lifestyle characteristics at T1 and T2 was performed to investigate whether previous emotional and CFS-related symptoms and lifestyle features predicted whether participants would develop high levels of fatigue. Depressive symptoms at T1 and T2 significantly predicted the development of high levels of fatigue at T3 in participants who were not fatigued at T1 and T2 (Wald = 6.17, P < .05; and Wald = 6.16, P < .05, respectively). Less physical activity and more nightlife activities at T1 also predicted new-onset fatigue (Wald = 4.02, P < .05; and Wald = 4.04, P < .05, respectively). In addition, shorter sleep duration at T1 tended to be related to fatigue development (Wald = 3.19, P = .07). Fatigue score at T1 or T2 did not predict new-onset fatigue at T3 (Wald = 0.001, P = .97; and Wald = 3.51, P = .06, respectively) and neither did age (Wald = 0.03, P = .86). Medication use did not predict the onset of fatigue. School absenteeism rates did not differ at any of the time points between nonfatigued participants and participants with new-onset fatigue. In conclusion, new-onset fatigue was preceded by depressive symptoms, and some lifestyle features of the past played a role in the onset of fatigue.
Do Changes in Fatigue Severity Covary With Changes in Other Complaints and in Daily Life Activities?
Multiple regression analysis was performed to examine whether changes in emotional comorbidity and lifestyle characteristics between T1 and T2 (n = 631) or between T1 and T3 (n = 645) predicted changes in fatigue in the whole group (Table 3). A decrease in fatigue severity between T1 and T2 was associated with a decrease in depression, anxiety, and CFS-related symptoms, and these changes explained 21.7% of the variance. The same was observed for changes in these variables between T1 and T3. Moreover, an increase in time spent on physical activities as well as an increase in sleep duration was associated significantly with a decrease in fatigue severity between T1 and T3. Explained variance in the T1 to T3 model was 27.2%. The contribution of lifestyle predictors for the changes in fatigue severity was minor, as can be observed in Table 3. In conclusion, the main predictors of changes in fatigue were changes in depression, anxiety, and CFS-related symptoms. In addition, and changes in lifestyle characteristics played a modest role.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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In this study, we aimed at gaining more insight into factors that are involved in the persistence and onset of fatigue and in factors that are associated with changes in fatigue severity in adolescent girls. We showed that compared with nonfatigued girls, transiently and persistently fatigued girls were less physically active and had longer sleep-onset latency and reduced sleep duration at the beginning of the study. It is interesting that persistently fatigued participants reported much higher initial levels of depression and anxiety than transiently fatigued and nonfatigued participants and were consistently more absent from school throughout the study. New-onset fatigue was associated with higher levels of depression, less physical activity, and more nightlife activities before fatigue onset. Sleep characteristics played a minor role in new-onset fatigue. In contrast to the literature on adults, new-onset fatigue was not preceded by increased fatigue severity, and fatigue severity at T1 in persistently fatigued participants was not higher than that in girls with short-term fatigue. Longitudinally, a decrease in fatigue severity was related to a decrease in depressive symptoms, anxiety, and CFS-related symptoms and also, but to a lesser extent, related to an increase in physical activity and sleep duration.
We are the first to investigate fatigue in a healthy adolescent population in a longitudinal design for a longer period and with 2 follow-up assessments. Previously, we showed that 20.5% of all girls included in our initial study were severely fatigued.1 Our longitudinal stability rate was 25.7%, which was lower than the rate that Rimes et al7 reported (53% after 4–6 months). Longer term recovery may explain why in our study a lower number of adolescents remained fatigued. Indeed, in our study, stability of fatigue after 6 months was 42.1%, which is more comparable to the rate observed by Rimes et al7. Our stability rate was also lower than in a study regarding adolescent fatigue-related disorders, which was reevaluated with a 42-month interval between measurements.13 Possibly, fatigue in healthy individuals has a more fluctuating character and depends more often on situation-specific features than fatigue in diseased individuals.
In our previous epidemiologic study,1 we concluded that fatigue in adolescents is highly related to symptoms of depression and anxiety. This longitudinal study adds to these conclusions because our new results give more insight in the direction of these relations. Participants who were persistently fatigued throughout the whole year of the study had higher initial levels of depressive symptoms and anxiety than nonfatigued participants and participants with transient fatigue. In addition, participants with new-onset fatigue had higher levels of premorbid depression and anxiety than participants who did not develop fatigue. Our results are in contrast to findings in adults by Hickie et al,6 who reported that the risk for development of prolonged fatigue was not related to initial levels of psychological distress, a construct highly related to depression and anxiety. Our results suggest that depression and anxiety are risk factors for adolescent fatigue in a healthy population, as was recently reported by Rimes et al.7 Because most epidemiologic studies on fatigue in adolescents investigated symptoms only cross-sectionally, causal relations between fatigue and other symptoms remained obscured.9,20–22 It is known, however, that mental health is 1 of the most important risk factors for the development of unexplained somatic symptoms in adolescents23 and, the other way around, that the presence of unexplained somatic symptoms during childhood or adolescence increases the risk for emotional disorders in adulthood.24,25 The strong association between fatigue and anxiety and depressive and CFS-related symptoms reported in our previous article and also reported in other studies1,20,26–28 suggests that these symptoms should be approached as a cluster. Severe fatigue rarely comes alone; however, our results suggest that development of symptoms seems to occur in a certain order (ie, high levels of depressive symptoms preceded the onset of fatigue), which suggests that therapeutic strategies should initially be focused on emotional problems in adolescents.
A body of evidence obtained from studies in adult populations showed that the level of fatigue is a significant predictor for the development of severe fatigue and CFS later2–5; however, data presented here show that in our group of adolescent girls, premorbid fatigue scores were associated neither with persistence of fatigue nor with new-onset fatigue within 1 year after the initial assessment. We were also surprised by the finding that the number of CFS-related symptoms was not 1 of the factors predicting fatigue persistence or onset because changes in CFS-related symptoms covaried with changes in fatigue severity. Our data warrant a follow-up study to investigate whether (persistence of) fatigue and CFS-related symptoms during adolescence, which is considered to be a crucial period of life, are predictors for the development of fatigue-related illnesses in later life. Regardless, these results show that although fatigue forms a cluster with depression, anxiety, and CFS-related symptoms, mood disturbances seem to be more important than fatigue per se.
The role of lifestyle factors in fatigue in adolescents has not been studied before in an adolescent population using a longitudinal design. Although influences of lifestyle in fatigue development were relatively small, both persistent fatigue and new-onset fatigue were related to low levels of physical activity. In an adult population, it has also been described that physical activity was negatively related to fatigue, but this study did not address the question of whether reduced physical activity was a cause or a consequence of fatigue.29 Our results support the idea that lower levels of physical activity may cause higher levels of fatigue. This notion is supported by the finding that higher levels of exercise in childhood lowered the risk for the development of CFS later in life.30 Moreover, higher levels of physical exercise have been associated with a reduction of depression and anxiety31 and thus maybe of influence on fatigue as a correlate. In most cases, the easiest way to increase exercise is to promote "lifestyle activity," such as walking and cycling to school; however, we cannot rule out the possibility that some adolescents refrain from physical activity because of fear of getting even more tired or feeling more pain. In these cases, graded exercise therapy, as in treatment of CFS,32 may be an advisable approach.
As we stated in the beginning of this article, in our previous cross-sectional study, we observed that participants who were more fatigued slept longer than participants who were less fatigued.1 In addition, within-subject analysis of our longitudinal data showed that shorter sleep preceded persistent fatigue and tended to precede new-onset fatigue. The latter results are not contradictory to the ones described in our cross-sectional study but reveal the effects of sleep duration when studied in a comparison between individuals or as a process within individuals. The direction of the longitudinal relation between fatigue and sleep was as logical as could be expected: initial shorter nocturnal sleep was related to persistent and new-onset fatigue. In addition, persistent fatigue was related to longer sleep-onset latency, which possibly is associated with the higher levels of emotional symptoms.33 In line with previous reports that depressed adolescents had longer sleep-onset latency,33 we observed positive correlations between sleep-onset latency and depressive symptoms (weekdays: between r = 0.18 at T1 and r = 0.30 at T2; weekends: r = 0.19 at T3 and r = 0.20 at T1 and T2; all P < .001). Both long-term changes in physical activity and changes in sleep duration covaried with changes in fatigue. These observations suggest not only that symptom worsening is associated with activity and sleep but also that reduction of fatigue severity may be obtained by increasing physical activity and night rest. With respect to promotion of night rest, it is important to make parents, teachers, and pediatricians aware of the consequences of reduced nocturnal sleep duration.33 Research has shown that watching television, computer gaming, and use of the Internet during the evening are significantly related to shorter sleep and daytime tiredness,34 suggesting that these stimulating events in the late evening should be avoided.
Of all measured extracurricular activities, the only relation observed was between new-onset fatigue and a larger amount of time spent on nightlife activities at preceding time points. Although this seems to be a plausible relation, it was unexpected because we did not observe a relation between fatigue and extracurricular activities, other than physical activity and not having an additional job, in our previous cross-sectional analysis.
A limitation of the study was the selection bias, which may be a disadvantage for the generalizability of the results; however, the bias was limited to differences in lifestyle features and age-dependent characteristics. Responders reported comparable symptom severity as nonresponders did. Another limitation was that we investigated only girls in this study. We chose to focus on girls because fatigue and fatigue-related syndromes are especially present in female individuals.1,20,35,36 Nevertheless, it would be interesting to investigate whether the same factors are involved in fatigue development and persistence in boys as in girls. Finally, we used self-reports to investigate the severity of depression and anxiety and CFS-related symptoms. Clinical diagnosis to detect CFS or anxiety disorder or major depressive disorder was not an aim of the study; therefore, we cannot rule out that some participants fulfilled the Centers for Disease Control and Prevention criteria for CFS37 or Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for major depression or anxiety disorder or completely exclude the possibility that fatigue was a result of an infectious disease. However, because we are dealing with a normal school population and not with a patient group, we believe that the relative contribution of diseased participants will be small. In addition, on the basis of the Dutch prevalence rate of CFS in adolescents, 10 to 20 per 100000,38 we expect that this rate is too low to have influenced the results.
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CONCLUSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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Severe fatigue in adolescent girls is fairly stable over time: in >25% of severely fatigued adolescent girls, fatigue persisted for at least 1 year. Symptoms of depression and anxiety are involved in the persistence of fatigue, and depressive symptoms are related to new-onset fatigue in adolescents. Although to a minor extent, other risk factors for adolescent fatigue were reduced physical activity and unhealthy sleep patterns (shorter nocturnal sleep and longer sleep-onset latency). Depression, anxiety, CFS-related symptoms, physical activity, and sleep characteristics covaried with fatigue over time. Our results suggest that the therapeutic strategies with respect to treatment of fatigue in adolescents should focus on psychological functioning. Also, because presence of depressive symptoms was the most important predictor of new-onset fatigue, prevention of fatigue also should concentrate on emotional well-being. Moreover, adolescents should be motivated to get more physically active and to change their sleep characteristics.
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ACKNOWLEDGMENTS |
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We are greatly indebted to C.D.J. Tersteeg-Kamperman, M. Donker, and M. Maas for contribution to the data collection and processing.
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FOOTNOTES |
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Accepted Jul 20, 2007.
Address correspondence to Cobi J. Heijnen, PhD, Department of Psychoneuroimmunology, University Medical Center Utrecht, Room KC03.068.0, PO Box 85090, 3508 AB Utrecht, Netherlands. E-mail: c.heijnen{at}umcutrecht.nl
The authors have indicated they have no financial relationships relevant to this article to disclose.
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PEDIATRICS (ISSN 1098-4275). ©2008 by the American Academy of Pediatrics
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