During early and mid-adolescence,greater mental toughness is related to increased sleep quality and quality of life

Abstract

The aim of this study was to explore the association between mental toughness, subjective sleep, physical activity, and quality of life during early and mid-adolescence. A total of 1475 participants (mean age = 13.4 years; range: 11–16 years) took part in the study. They completed questionnaires related to mental toughness, physical activity, subjective sleep, and quality of life. Greater mental toughness was related to more favorable quality of life and increased subjective sleep. Mental toughness was not related to physical activity. Increased mental toughness, favorable quality of life, and sleep are related during early and mid-adolescence. Against our expectations, mental toughness was not related to physical activity.

Keywords

early and mid-adolescence mental toughness physical activity quality of life subjective sleep

Introduction

Adolescence is marked by a vast array of social, emotional, cognitive, and behavioral changes, with conceptually distinct physical changes and neural networks marking puberty and maturation (Paus et al., 2008; Pinyerd and Zipf, 2005; Spear, 2000). Adolescents have to face new challenges and assume responsibility for issues such as their academic and vocational careers; peer and intimate relationships; increased physical, emotional, and financial independence from parents and siblings; use of psychoactive substances; extra-curricular employments; and leisure-time activities such as sports participation and music (cf. Spear, 2000). Dealing with these issues is potentially stressful, and accordingly, it is assumed that adolescents with better coping skills will deal more successfully with these challenges (Grant et al., 2004).

A psychological construct related to favorable stress management is mental toughness (MT). MT is a relatively new area of academic research (Gucciardi and Gordon, 2011) and a cognitive strength variable known to be associated with good performance both in elite sport (Crust and Azadi, 2010) and, more recently, in non-elite sport (Gerber et al., 2012, 2013a, 2013b). MT has been conceptualized in various ways in the scientific literature (see Jones and Parker, 2013, for review). In this study, we used the 4C model of MT¹ defined as performing well in Challenging situations, Commitment, Control (emotional control and life control), and Confidence (interpersonal confidence and confidence in ability; Clough et al., 2002; see Table 1 for typical items).

Table 1.

Dimensions of mental toughness and typical items (Mental Toughness Questionnaire–48 (MTQ-48); cf. Clough et al., 2002).

Dimension	Typical item
Challenge	“Challenges usually bring out the best in me”
Commitment	“I don’t usually give up under pressure”
Control, emotional control	“Even when under pressure I usually remain calm”
Control, life control	“I generally feel in control”
Confidence, interpersonal confidence	“I usually take charge of a situation when I feel it is appropriate”
Confidence, in ability	“I am generally confident in my own abilities”

Emotional control and life control are aggregated to Control; interpersonal confidence and confidence in ability are aggregated to Confidence.

In previous studies (Gerber et al., 2012, 2013a, 2013b), we have been able to validate the German version of the Mental Toughness Questionnaire–48 (MTQ-48; Clough et al., 2002) and to show, in a large sample of adolescents and young adults, (1) that the construct of MT is not limited to high performing elite athletes (Gerber et al., 2012, 2013a, 2013b); (2) that MT is associated with increased stress resilience (Gerber et al., 2012, 2013a, 2013b); (3) that MT remains relatively stable over time (Gerber et al., 2013a); (4) that MT is associated with higher physical activity (PA) levels (Gerber et al., 2012, 2013b); (5) that relative to males, females reported lower MT; and that greater MT was associated both with favorable (6) subjective (Brand et al., 2014a) and (7) objective sleep (Brand et al., 2014b), suggesting therefore that MT is related to successful stress management, psychological well-being, favorable sleep, and increased PA.

However, for young adolescents, research on this topic does not exist so far. The aim of this study was therefore to investigate the association between MT, subjective sleep (sS), quality of life (QoL), and PA in adolescents aged 11–16 years. Based on previous research (Brand, et al., 2014a, 2014b; Gerber et al., 2012, 2013a, 2013b), we hypothesized that greater MT was associated with increased PA, decreased sleep disturbances,² and greater QoL. Also, we predicted more unfavorable values in female as compared to male participants. Moreover, we treated as exploratory the extent to which MT, PA, and sS might predict QoL as expressed by a global health-related QoL index.

Methods

Sample

A total of 1475 adolescents (mean age: 13.4 years; range: 11–16 years; 48.8% males) took part in the study. Adolescents were recruited from five middle schools in the Cantons Basel, Basel-Land, and Aargau, three districts in the northwestern of the German-speaking part of Switzerland. Participants and participants’ parents were informed about the purpose of the study and about the voluntary basis of their participation. They were also assured of the confidentiality of their responses, and written informed consent was obtained from both participants and parents. Data collection took place in spring 2013. Participants completed the questionnaire booklet during a school lesson; the booklet was completed within 20–35 minutes. During data collection in the classroom, professional staff members provided examples on how to complete the items in the questionnaire booklet.

The study protocol was carried out in accordance with the Declaration of Helsinki, and the local ethics committee approved the study.

Material

MT

Participants were asked to fill in the MTQ-48 (Clough et al., 2002; German version: Gerber et al., 2012, 2013a, 2013b). The questionnaire measures the following subcomponents (see also Table 1): challenge, commitment, emotional and life control, and interpersonal confidence and confidence in ability. Answers on the MTQ-48 are given on 5-point Likert-type scales ranging from 1 (= strongly disagree) to 5 (= strongly agree). Items were summed, with higher scores reflecting greater subcomponents of MT; moreover, all subcomponents were aggregated to a MTQ-48 overall score (Cronbach’s alpha = .91).

QoL

Participants completed the KIDSCREEN-52 (Ravens-Sieberer et al., 2008). The questionnaire consists of 52 items focusing on 10 different domains of children’s and adolescents’ social, physical, and QoL: physical functioning, psychological functioning, moods and emotions, self-perception, autonomy, parent relation and home life, financial resources, social support and peers, school environment, and social acceptance. Answers are given on 5-point Likert scales, with the anchor points 1 (= not at all) and 5 (= extremely/always). The 10 domains are aggregated to the following subscales: Physical well-being, psychological well-being, relationship to parents and autonomy, relationship to peers, school environment, and social acceptance. Moreover, a global health-related QoL index is calculated. Higher mean scores reflect a higher functioning in the respective domains (Cronbach’s alpha for the overall index = .92).

Moderate to vigorous PA

To assess PA, participants were asked on how many days per week they exercised or participated in (high intensity) activities and sports. The response categories ranged from 0 to 7 days. In addition, participants were asked to indicate the average duration (per day) for the days they engaged in these activities. Multiplication of frequency and duration scores resulted in an estimate of weekly hours invested in vigorous PA. In addition, participants were asked to indicate how many days per week they engaged in moderate PA. Again, an additional question asked about duration per day in order to estimate the weekly engagement (hours/week) in moderate PA. All items were taken from the International Physical Activity Questionnaire (IPAQ; Craig et al., 2003). Validity of such general items is considered acceptable in samples of adolescents (Hagströmer et al., 2008). Ottevaere et al. (2011) showed that the IPAQ is equally able to predict cardiorespiratory fitness among adolescents as data from accelerometers. Following the IPAQ guidelines (see http://www.ipaq.ki.se/scoring.pdf), daily PA values of 10 minutes or lower were set at 0 because it is assumed that daily PA values of 10 minutes or lower have no impact on health. Moreover, reports of daily PA higher than 180 minutes/day were limited to 180 minutes/day, leading to a maximum moderate or vigorous weekly PA of 21 hours.

sS/sleep disturbance

The Insomnia Severity Index (ISI; Bastien et al., 2001) is a 7-item screening measure for insomnia and an outcome measure for use in treatment research. The items, answered on 5-point rating scales (0 = not at all, 4 = very much), refer in part to Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition (DSM-IV) criteria for insomnia (American Psychiatric Association (APA), 2000) by measuring difficulty in falling asleep, difficulties remaining asleep, early morning awakenings, increased daytime sleepiness, impaired daytime sleepiness, impaired daytime performance, low satisfaction with sleep, and worrying about sleep. The higher the overall score, the more the respondent is assumed to suffer from sleep disturbances (Cronbach’s alpha = .92). Note that we used the terms sS and sleep disturbances interchangeably.

Statistical analysis

To calculate the association between age, MT, QoL, sS, and PA, correlational computations were performed. To compare MTQ-48 subcomponents between female and male participants, a series of t-tests was performed. Next, the MTQ-48 overall score was categorized into the variable MT group of four groups based on percentages of <25, 25–50, 50–75, and 75–100 percent. A series of analyses of covariances (ANCOVAs) was performed with gender and the variable MT group as independent factors and sS, PA, and QoL as dependent variables (with age as covariate). Post hoc analyses were calculated with the Bonferroni–Holm correction for p values. To explore to which extent a global health-related QoL is predicted by MT, PA, andsS, a multiple regression analysis (stepwise exclusion) was performed. The level of significance was set at alpha = .05. Statistics was performed with SPSS^® 20.0 (IMB Corporation, Armonk, NY, USA).

Results

Correlative associations between MT, PA, sS, and QoL

Table 2 provides the descriptive statistics and correlations (Pearson’s correlations) between the five MT scales and variables related to demographics (age, gender, body mass index (BMI)), PA, sS, and QoL.

Table 2.

Descriptive statistics and correlations (Pearson’s correlations) between the five MT scales and variables related to demographics (age, gender, BMI), physical activity (PA), sleep and quality of life.

N = 1475	Mental toughness				MTQ-48 overall score	Descriptive statistics, M (SD)
	Challenge	Commitment	Control	Confidence	MTQ-48 overall score	Descriptive statistics, M (SD)
Age (years)	.03	−.05	−.04	−.03	.01	13.37 (1.46)
Gender (0 = female, 1 = male)	.03	.09	.15***	.12***	.11**	n = 755/720; % = 51.8/48.8
BMI	−.02	−.05	−.03	−.05	−.01	19.07 (3.19)
Vigorous PA (minutes/week)	.02	.08	.06	.08	.03	411.86 (346.86)
Moderate PA (minutes/week)	−.07	.08	.06	.04	.03	247.86 (326.10)
Sleep disturbances	−.24***	−.28***	−.20***	−.34***	−.25***	6.67 (4.39)
Psychological functioning
Physical well-being	.27***	.34***	.21***	.39***	.27***	3.85 (0.77)
Psychological well-being	.35***	.37***	.26***	.46***	.38***	4.07 (0.64)
Relationship to parents and autonomy	.27***	.29***	.20***	.35***	.29***	4.11 (0.69)
Relationship to peers	.22***	.18***	.12***	.24***	.19***	4.12 (0.74)
School environment	.23***	.33***	.15***	.35***	.32***	3.87 (0.84)
Social acceptance	.17***	.13***	.11***	.18***	.17***	4.49 (0.80)
Global health-related quality of life index	.34***	.38***	.22***	.48***	.51***	3.96 (0.75)
Descriptive statistics, M (SD)	3.07 (0.87)	3.27 (0.64)	3.14 (0.56)	3.18 (0.84)	3.17 (0.72)

MT: mental toughness; BMI: body mass index; SD: standard deviation.

***

p < .001.

Greater MT (subcomponents and overall score) was significantly associated with male gender, lower sleep disturbances, and greater QoL (subcomponents and global health-related QoL index). MT (subcomponents and overall score) was not significantly associated with age, BMI, and moderate and vigorous PA.

Differences in MT scores (subcomponents and overall score) between female and male participants

Compared to male participants, female participants reported significantly lower scores in MTQ-48 subcomponents and in the MTQ overall score (challenge f: M = 2.95, standard deviation (SD) = 0.85; m: M = 3.10, SD = 0.88; t(1473) = 2.39, p < .001; commitment f: M = 3.12, SD = 0.63; m: M = 3.33, SD = 0.63; t(1473) = 3.48, p < .001; control f: M = 3.05, SD = 0.56; m: M = 3.22, SD = 0.55; t(1473) = 5.72, p < .001; confidence f: M = 3.02, SD = 0.69; m: M = 3.43, SD = 0.37; t(1473) = 4.98, p < .001; MTQ-48 overall score f: M = 3.11, SD = 0.49; m: M = 3.32, SD = 0.47; t(1473) = 4.79, p < .001).

Differences in PA, sS, and QoL as a function of gender and MT groups

Table 3 and Table 4 provide the descriptive and inferential statistical overview of PA (moderate and vigorous), sS, and QoL, separately for gender and MT groups.

Table 3.

Descriptive statistics of physical activity (PA), sleep, and psychological functioning (PF), separately by groups of mental toughness (MT) and gender.

Article 1.	MT
Article 1.	MT ≤ 25% (L)		25% < MT ≤ 50% (RL)		50% < MT ≤ 75% (RH)		MT > 75% (H)
Gender	F	M	F	M	F	M	F	M
N	200	168	180	189	210	159	130	239
Vigorous PA (minutes/week)	304.44 (378.14)	449.84 (443.21)	325.77 (357.71)	272.99 (431.64)	329.47 (342.74)	507.44 (621.09)	365.12 (304.41)	500.23 (428.54)
Moderate PA (minutes/week)	168.73 (221.09)	290.24 (492.76)	195.63 (311.75)	301.53 (407.42)	180.85 (213.27)	352.58 (628.44)	269.88 (358.71)	300.52 (479.15)
Sleep disturbances^a	8.88 (5.14)	7.25 (4.54)	7.33 (3.88)	6.15 (4.09)	5.76 (3.54)	6.40 (4.26)	5.74 (3.67)	4.70 (3.21)
Psychological functioning
Physical well-being	3.25 (0.76)	3.69 (0.80)	3.59 (0.71)	3.99 (0.63)	3.82 (0.72)	4.05 (0.69)	4.12 (0.67)	4.34 (0.60)
Psychological well-being	3.59 (0.69)	3.90 (0.58)	3.94 (0.58)	4.18 (0.49)	4.28 (0.54)	4.22 (0.46)	4.33 (0.57)	4.49 (0.41)
Relationship to parents and autonomy	3.68 (0.77)	3.93 (0.62)	4.01 (0.65)	4.23 (0.60)	4.22 (0.60)	4.26 (0.46)	4.38 (0.59)	4.39 (0.60)
Relationship to peers	3.91 (0.81)	3.86 (0.81)	4.17 (0.66)	4.08 (0.67)	4.22 (0.69)	4.02 (0.72)	4.38 (0.67)	4.35 80.60)
School environment	3.39 (0.84)	3.35 (0.93)	3.57 (0.69)	3.69 (0.67)	3.87 (0.72)	3.65 (0.72)	4.02 (0.79)	3.99 (0.81)
Social acceptance	4.30 (0.95)	4.40 (0.78)	4.95 (0.66)	4.45 (0.82)	4.75 (0.67)	4.31 (0.87)	4.64 (0.82)	4.65 (0.61)
Global health-related quality of life index	3.63 (0.58)	3.70 (0.60)	3.89 (0.47)	3.98 (0.45)	4.12 (0.49)	3.96 (0.48)	4.25 (0.51)	4.28 (0.43)

F: female; M: male; (L): low MT; (RL): rather low MT; (RH): rather high MT; (H): high MT.

The higher the scores, the higher the sleep disturbances.

Table 4.

Inferential statistics (ANCOVAs) of physical activity (PA), sleep, and psychological functioning (PF), separately by MT groups and gender.

Gender	Statistics
Gender	ANCOVA^a			Pairwise comparisons
	MT group	Gender	MT group × gender interaction	Pairwise comparisons
N
Total vigorous PA (minutes/week)	1.00	25.02***	0.07	M > F
Total moderate PA (minutes/week)	1.11	13.92***	1.09	M > F
Sleep disturbances	27.42***	5.17*	0.60	(L) > (RL) > (RH) > (H); F > M
Psychological functioning
Physical well-being	55.21***	32.45***	0.88	M > F; (L) < (RL) < (RH) < (H)
Psychological well-being	78.20***	14.70***	2.78*
Relationship to parents and autonomy	45.48***	7.20**	2.01	M > F; (L) < (RL) = (RH) < (H)
Relationship to peers	24.08***	2.98	0.40	(L) < (RL) = (RH) < (H)
School environment	36.57***	0.94	1.46	(L) < (RL) = (RH) < (H)
Social acceptance	7.16***	3.72	3.41*
Global health-related quality of life index	73.76***	0.00	1.50	(L) < (RL) = (RH) < (H)

ANCOVA: analysis of covariance; MT: mental toughness; (L): low MT; (RL): rather low MT; (RH): rather high MT; (H): high MT.

Degrees of freedom: MT Group; MT Group × Gender Interaction: F(3, 1471); Gender: F(1, 1473).

ANCOVA with age as covariate.

p < .05; ***p < .001.

To further investigate associations between MT, sS, and PA, subjects were also divided into quartile groups according to their MTQ-48 overall scores (from the lowest, quartile 1, to the highest, quartile 4). The MTQ-48 overall score was divided into four MT subgroups to study whether the sleep disturbance, PA, and QoL mean scores changed with the level of MT, or whether the mean scores of sleep disturbance, PA, and QoL were different only between high and low MT subgroups.

When PA, sS, and QoL are considered between gender and MT groups, compared to females, male participants reported significantly higher moderate and vigorous PA, lower sleep disturbances, and increased physical and psychological well-being and increased scores in relationships to parents and autonomy.

For MT groups, except for moderate and vigorous PA, where no significant MT group differences were observed, sleep disturbances decreased and QoL increased from “Low MT group” to “High MT group.”

Significant MT group × Gender interactions were found for sleep disturbances (Figure 1(a)), psychological well-being (Figure 1(b)), and social acceptance (Figure 1(c)), sleep disturbances decreased from “Low MT” to “High MT group”; females reported greater sleep disturbances, although sleep disturbances were lower in females of the “Rather high MT group,” compared to males of the “Rather high MT group.” Psychological well-being increased from “Low MT” to “High MT group”; compared to male participants, female participants reported a higher increase in psychological well-being from “Low MT” to “High MT group.” In females, social acceptance changed in an inverted U-shaped manner from “Low MT” to “High MT group”; in males, social acceptance increased from “Low MT” to “High MT group.” However, we note that effect sizes were small.

Figure 1.

(a) Sleep disturbances were statistically significantly decreased as a function of MT group and gender, (b) psychological well-being was statistically significantly increased as a function of MT group and gender, and (c) social acceptance was statistically significantly increased as a function of MT group and gender.

Predicting global health-related QoL

To predict global health-related QoL as the composite score of the dimensions of QoL questionnaire (KIDSCREEN-52), a multiple regression analysis was performed with global health-related QoL index as dependent variable, and MT, sS, and PA as independent variables. The global health-related QoL index was predicted (F(3, 1471) = 23.91, p < .000; R² = .31) by greater MT (MT Challenge: β = .185, p < .000; MT Commitment: β = .21, p < .001; MT Control, β = .07, p = .004) and lower sleep disturbances (β = −.21, p < .001), whereas PA (moderate; vigorous) and MT Confidence were excluded from the equation.

Discussion

The key findings of this study are that among 11- to 16-year-old adolescents, MT is related to male gender, to greater QoL, and to lower sleep disturbances. Against our expectations, MT is not associated with PA.

Based on previous research (Brand et al., 2014a, 2014b; Gerber et al., 2013a, 2013b), we hypothesized that greater MT was associated with increased PA, decreased sleep disturbances, and greater QoL; however, data did not fully support these assumptions. Greater MT was associated with greater QoL: This pattern of results fits very well with previous findings on research in older adolescents and young adults (Gerber et al., 2012, 2013a, 2013b). The present data therefore add to the current literature in that MT was assessed for the first time among early and mid-adolescents, and in that also among these adolescents, MT was associated with facets of QoL, as assessed via self-reports with the KIDSCREEN-52 (Ravens-Sieberer et al., 2008), a tool assessing a broad variety of adolescents’ concerns ranging from physical well-being, peer and parents relationships, to school environment. Moreover, results from the multiple regression analysis showed that the global health-related QoL index was best predicted by greater MT scores and low sleep disturbances.

Greater MT was associated with lower sleep disturbances: This pattern of results was also in accordance with previous research: We found that among late adolescents, greater MT was associated with both increased subjective (Brand et al., 2014a) and objective sleep (Brand et al., 2014b). How to explain this association? Research has established links between MT and hardiness, which has previously been found to be associated with stress resilience, and this observation is in accordance with the idea that resilience does not evolve from avoidance of adversity, but from successful dealing with negative stimuli (Rutter, 1993). In this respect, although highly speculative and not provable with the present data, we hypothesize that MT influences sleep positively via reduced stress (Gerber et al., 2012, 2013a, 2013b), reduced hyperarousal (Riemann et al., 2010), and reduced dysfunctional thoughts (Carney and Edinger, 2006; Harvey, 2000, 2002). Accordingly, it is highly plausible that dysfunctional thoughts and maladaptive behavior are incompatible with the dispositions toward appraisal of high control, challenge, and commitment that characterize a mentally tough person.

Next, we predicted more unfavorable MT scores in female as compared to male participants, and data did confirm this assumption. However, the study design does not allow an in-depth understanding of the underlying mechanisms as to why females, compared to males, report lower MT and QoL. We follow Hyde et al. (2008): The authors propose that, specifically, depressive disorders are more often observed in female as compared to male adolescents as a function of affective (emotional reactivity), biological (genetic vulnerability, pubertal hormones, pubertal timing, and development), and cognitive (cognitive style, objectified body consciousness, rumination) factors. Along with the interaction with negative life events, these affective, biological, and cognitive factors may confer to an increased risk of depressive symptoms. Accordingly, although highly speculative, we claim that these affective, biological, cognitive, and environmental factors lead to lower self-reported MT scores in female as compared to male adolescents.

Against expectations and therefore at odds with previous research (Gerber et al., 2012, 2013a, 2013b), MT was not associated with PA, and PA was also not a predictor of the global health-related QoL index. These findings do not mirror the wealth of studies showing a tight association between physical functioning, QoL, and PA (Josefsson et al., 2014; Silveira et al., 2013). We might suppose that the assessment tool (IPAQ) was inadequate to assess PA in this age group or that items were incorrectly completed; however, the tool is well established to assess adequately PA among adolescents and adults. Moreover, to complete the entire questionnaire, professional staff members were present in the classes and instructed thoroughly by means of examples on how to complete the IPAQ items. However, it remains possible that some participants over- and underestimated their weekly frequency and intensity of PA. We also note that SDs are high (see Table 3), suggesting therefore a very broad range of self-reported PA within and between the groups. Accordingly, significant mean differences were unlikely. Furthermore, perhaps one reason for the discrepant results from other studies is that either MT is a different construct in younger adolescents or at least that the MTQ-48 does not function equivalently in the younger and older adolescents. Finally, we claim that further latent, although unassessed, psychological dimensions might have blurred the association between PA, MT, and QoL.

Despite the clarity of the findings and the large sample size, several considerations warrant against overgeneralization. First, we fully relied on self-report and not on experts’ reports; accordingly, systematic rating biases are possible. Future research should also include experts’ ratings. Second, sleep was only subjectively assessed, and again, it is possible that the correlation between MT and sleep primarily reflects an association between youth who see themselves as mentally tough and a tendency to see themselves as good sleepers, rather than any real relationship between sleep and MT. Third, pubertal stage was not assessed, and, accordingly, underlying hormonal and neuroendocrine processes might have biased the present pattern of results. Fourth, objective PA analysis might have conferred to a more reliable assessment of PA. Fifth, effect sizes were small; therefore, statistically significant mean differences should not be overestimated. Sixth, the present pattern of results might have emerged due to a latent third variable causing the measured variables to change in the same direction. Finally, the cross-sectional design does not allow any conclusion as to the causal direction of the pattern of association.

Conclusion

In a larger sample of participants of early and mid-adolescence, we found that MT was associated with increased sleep quality and greater QoL. Against expectations, MT was not associated with PA, suggesting that in this age group, the association between PA, MT, and QoL might be more complex as generally assumed.

Footnotes

Acknowledgements

We thank Kathrin Christof, Judith Meyer, and Fabian Kosir for data collection and data entry. Moreover, we thank Nick Emler (University of Surrey, UK) for proofreading the manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

References

American Psychiatric Association (APA) (2000) Diagnostic and Statistical Manual of Mental Disorders (4th edn). Washington, DC: APA.

Bastien

Vallières

Morin

(2001) Validation of the Insomnia Severity Index (ISI) as an outcome measure for insomnia research. Sleep Medicine 2: 297–307.

Brand

Gerber

Kalak

. (2014a) In adolescence, greater mental toughness is related to better sleep schedules. Behavioral Sleep Medicine 12: 1–11.

Brand

Gerber

Kalak

. (2014b) Adolescents with greater mental toughness show higher sleep efficiency, more deep sleep and fewer awakenings after sleep onset. Journal of Adolescent Health 54: 109–113.

Carney

Edinger

(2006) Identifying critical beliefs about sleep in primary insomnia. Sleep 29: 444–553.

Cicchetti

(2010) Resilience under conditions of extreme stress: a multilevel perspective. World Psychiatry 9: 145–154.

Clough

Earle

Sewell

(2002) Mental toughness: The concept and its measurement. In: Cockerill

(ed.) Solutions in Sport Psychology. London: Thomson Learning, pp. 32–46.

Crust

Azadi

(2010) Mental toughness and athletes’ use of psychological strategies. European Journal of Sport Science 10: 43–51.

Craig

Marshall

Sjöström

. (2003) International physical activity questionnaire: 12-country reliability and validity. Medicine and Science in Sports and Exercise 35: 1381–1395.

10.

Dageid

Grønlie

(in press) The associations between resilience, social capital and self-rated health among HIV-positive South Africans. Journal of Health Psychology.

11.

Gerber

Brand

Feldmeth

. (2013a) Adolescents with high mental toughness adapt better to perceived stress: A longitudinal study with Swiss vocational students. Personality and Individual Differences 54: 808–814.

12.

Gerber

Kalak

Lemola

. (2012) Adolescents’ exercise and physical activity are associated with mental toughness. Mental Health and Physical Activity 5: 35–42.

13.

Gerber

Kalak

Lemola

. (2013b) Are adolescents with high mental toughness levels more resilient against stress? Stress and Health 29: 164–171.

14.

Grant

Compas

Thurm

. (2004) Stressors and child and adolescent psychopathology: Measurement issues and prospective effects. Journal of Clinical Child and Adolescent Psychology 33: 412–425.

15.

Gucciardi

Gordon

(2011) Mental Toughness in Sport: Developments in Theory and Research. London: Taylor & Francis.

16.

Hagströmer

Bergman

De Bourdeaudhuij

.; HELENA Study Group (2008) Concurrent validity of a modified version of the International Physical Activity Questionnaire (IPAQ-A) in European adolescents: The HELENA Study. International Journal of Obesity 32: 42–48.

17.

Harvey

(2000) Pre-sleep cognitive activity: A comparison of sleep-onset insomniacs and good sleepers. British Journal of Clinical Psychology 39: 275–286.

18.

Harvey

(2002) A cognitive model of insomnia. Behavior Research and Therapy 40: 869–894.

19.

Hyde

Mezulis

Abramson

(2008) The ABCs of depression: Integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psychological Review 115: 291–313.

20.

Jones

Parker

(2013) What is the size of the relationship between global mental toughness and youth experiences? Personality and Individual Differences 54: 519–523.

21.

Josefsson

Lindwall

Archer

(2014) Physical exercise intervention in depressive disorders: Meta-analysis and systematic review. Scandinavian Journal of Medicine & Science in Sports 24: 259–272.

22.

Luthar

Cicchetti

Becker

(2000) The construct of resilience: A critical evaluation and guidelines for future work. Child Development 71: 543–562.

23.

Masten

(2001) Ordinary magic: Resilience processes in development. American Psychologist 56: 227–238.

24.

Ottevaere

Huybrechts

De Bourdeaudhuij

. (2011) Comparison of the IPAQ-A and actigraph in relation to VO₂max among European adolescents: The HELENA study. Journal of Science and Medicine in Sport 14: 317–324.

25.

Paus

Keshavan

Giedd

(2008) Why do many psychiatric disorders emerge during adolescence? Nature Reviews Neuroscience 9: 947–957.

26.

Pinyerd

Zipf

(2005) Puberty: Timing is everything! Journal of Pediatric Nursing 20: 75–82.

27.

Ravens-Sieberer

Gosch

Rajmil

.; KIDSCREEN Group (2008) The KIDSCREEN-52 quality of life measure for children and adolescents: Psychometric results from a cross-cultural survey in 13 European countries. Value in Health 11: 645–658.

28.

Riemann

Spiegelhalder

Feige

. (2010) The hyperarousal model of insomnia: A review of the concept and its evidence. Sleep Medicine Reviews 14: 19–31.

29.

Rutter

(1993) Resilience: Some conceptual considerations. Journal of Adolescent Health 14: 626–631.

30.

Silveira

Moraes

Oliveira

(2013) Physical exercise and clinically depressed patients: A systematic review and meta-analysis. Neuropsychobiology 67: 61–68.

31.

Spear

(2000) The adolescent brain and age-related behavioral manifestations. Neuroscience and Biobehavioral Reviews 24: 417–763.

32.

Wolfson

Carskadon

Acebo

. (2003) Evidence for the validity of a sleep habits survey for adolescents. Sleep 26: 213–216.

33.

Yi-Frazier

Yaptangco

Semana

. (2013) The association of personal resilience with stress, coping, and diabetes outcomes in adolescents with type 1 diabetes: Variable- and person-focused approaches. Journal of Health Psychology. Epub ahead of print 21 November 2013. DOI: 10.1177/1359105313509846.