Sleep problems and self-harm in adolescence

Journal Reading
The British Journal of Psychiatry (2015)
207, 306–312. doi: 10.1192/bjp.bp.114.146514

Sleep problems and self-harm in adolescence
Mari Hysing, Børge Sivertsen, Kjell Morten Stormark and Rory C. O’Connor

Self-harm among adolescents is a major public health concern
with approximately 10% of adolescents having reported self-harm
at some stage in their lives.
Although there is growing consensus
that we need to look beyond psychiatric disorders to fully
appreciate the complexity of the antecedents of self-harm, it
remains difficult to predict with acceptable levels of sensitivity
and specificity which young people are at elevated risk of selfharm. As a result, there has been a growth in studies focusing
on more specific markers of risk.
Such research has identified
two main clusters of factors;
environmental influences (e.g.
exposure to self-harm) and negative life events on the one hand
and psychological factors (e.g. personality and mood) on the
other which interact to increase risk of psychological distress
and self-harm.
A fruitful strand of the more specific markers of risk research
has been the work on self-regulatory processes
4
including studies
on the regulation of sleep.
5
Attention directed at sleep is
unsurprising given the long-standing relationship between sleep
and adolescent development in general.
6,7
However, in recent
years there has been growing evidence that sleep problems are risk
factors for self-harm and suicidal behaviour and that this
relationship is independent of psychiatric disorder.
8–12
Despite
the accumulation of evidence confirming a relationship between
sleep problems and self-harm in adolescents, the utility of the
findings has been circumscribed because the measures of sleep
have tended to be brief. As a consequence, it is not clear whether
specific characteristics of sleep disturbance are more strongly
associated with risk of self-harm than others. If so, these markers
should be highlighted in risk assessment and targeted, if possible,
in intervention studies.
The aim of the present study, therefore, was to conduct a
detailed investigation of the relationship between sleep problems
and self-harm in a large sample of adolescents by employing a
more comprehensive assessment of sleep than has been done
previously. Given the established relationship between depression,
perfectionism and attention-deficit hyperactivity disorder
(ADHD) and self-harm,
1,13,14
we aimed to control for their effects
when testing the sleep problem–self-harm relationship.
Method
In this population-based study, we used data from the youth
hordaland-survey of adolescents in the county of Hordaland in
Western Norway. All adolescents born between 1993 and 1995
and all students attending secondary education during spring
2012 were invited to participate. The main aim of the survey
was to assess the prevalence of mental health problems and service
use in adolescents. Data were collected during spring 2012.
Adolescents in secondary education received information via
email, and time was allocated during regular school hours for
completion of the questionnaire. A teacher was present to organise
the data collection and to ensure confidentiality. Those not in
school received information by postal mail to their home address.
Survey staff were available by telephone to answer any queries
from both the adolescents and school personnel. The study was
approved by the Regional Committee for Medical and Health
Research Ethics in Western Norway.
Sample
A total of 19 430 adolescents were invited to participate, of which
10 220 agreed, yielding a participation rate of 53%. Sleep variables
were checked for the validity of their answers based on
preliminary data analysis, resulting in data from 374 adolescents
being excluded due to obvious invalid responses (e.g. negative
sleep duration or sleep efficiency). Thus, the total sample size in
the current study was 9875 with valid responses on sleep and
self-harm variables.
Instruments
Demographic information
All participants indicated their vocational status, with response
options being ‘high school student’, ‘vocational training’ or ‘not
in school’. Maternal and paternal education (highest level) was reported separately with three response options; ‘primary school’,
306
Sleep problems and self-harm in adolescence
Mari Hysing, Børge Sivertsen, Kjell Morten Stormark and Rory C. O’Connor
Background
Although self-harm and sleep problems are major public
health problems in adolescence, detailed epidemiological
assessment is essential to understand the nature of this
relationship.
Aims
To conduct a detailed assessment of the relationship
between sleep and self-harm in adolescence.
Method
A large population-based study in Norway surveyed 10 220
adolescents aged 16–19 years on mental health, including a
comprehensive assessment of sleep and self-harm.
Results
Adolescents with sleep problems were significantly more
likely to report self-harm than those without sleep problems.
Insomnia, short sleep duration, long sleep onset latency,
wake after sleep on set as well as large differences between
weekdays versus weekends, yielded higher odds of self-harm
consistent with a dose–response relationship. Depressive
symptoms accounted for some, but not all, of this
association.
Conclusions
The findings highlight a strong relationship between sleep
problems and self-harm. Interventions to reduce adolescent
self-harm ought to incorporate sleep problems as a
treatment target.
Declaration of interest
None.
Copyright and usage
BThe Royal College of Psychiatrists 2015.
The British Journal of Psychiatry(2015)
207, 306–312. doi: 10.1192/bjp.bp.114.146514
‘secondary school’ and ‘college or university’. Perceived family
economy (i.e. how well off they perceive their family to be)
was assessed by asking the adolescents how their family economy
is compared with most others. Response alternatives were 1 =
‘approximately like most others’, 2 = ‘better economy’ and
3 = ‘poorer economy’.
Self-harm
Self-harm was assessed using the following question which is taken
from the Child and Adolescent Self-harm in Europe (CASE)
Study:
15
‘Have you ever deliberately taken an overdose (e.g. of pills
or other medication) or tried to harm yourself in some other way
(such as cut yourself)?’ If a participant endorsed the ‘yes’
response, they were asked to complete the following item thinking
about the last time they self-harmed if they had self-harmed more
than once: ‘Describe what you did to yourself on that occasion.
Please give as much detail as you can – for example, the name
of the drug taken in an overdose’. Classification of self-harm was
done according to the CASE guidelines by two coders and in line
with the CASE definition of self-harm:
‘act with a non-fatal outcome in which an individual deliberately did one or more of
the following: initiated behaviour (e.g., self-cutting, jumping from a height), which they
intended to cause self-harm; ingested a substance in excess of the prescribed or
generally recognised therapeutic dose; ingested a recreational or illicit drug that
was an act the person regarded as self-harm; ingested a non-ingestible substance
or object’.
Frequency of self-harm was also recorded and coded as follows:
‘none’, ‘once’, ‘two or more times’.
A total of 1024 of the 10 220 young people completed the
open-ended question on self-harm. In 140 (1.2%) patients, the
information was not sufficient to code as self-harm, and for 38
(0.3%) the description did not meet criteria. This resulted in
846 (7.5%) of the total population meeting the criteria for selfharm. In the current sample, after deleting non-valid responses
on sleep, a total of 702 (7.2%) met the criteria for self-harm.
Sleep variables
Insomnia. Difficulties initiating and maintaining sleep (DIMS)
were rated on a 3-point Likert-type scale with response options
‘not true’, ‘somewhat true’ and ‘certainly true’. If a positive
response was endorsed (‘somewhat true’ or ‘certainly true’),
participants were then asked how many days per week they
experienced problems either initiating or maintaining sleep.
Duration of DIMS was rated in weeks (up to 3 weeks), months
(up to 12 months) and a last category over a year. A joint question
on tiredness/sleepiness was rated on a 3-point Likert-type scale
with response options ‘not true’, ‘somewhat true’ and ‘certainly
true’. If there was evidence of tiredness/sleepiness (‘somewhat true’
or ‘certainly true’) participants reported the number of days per
week they experienced sleepiness and tiredness respectively.
Insomnia was operationalised according to the DSM-5 criteria
for insomnia:
16
self-reported DIMS at least three times a week,
with a duration of 3 months or more, as well as tiredness or
sleepiness at least 3 days per week.
Other sleep variables. Self-reported bedtime and rise time were
indicated in hours and minutes using a scroll down menu with
5-minute intervals and they were reported separately for weekends
and weekdays. Time in bed (TIB) was calculated by subtracting
bedtime from rise time. Sleep onset latency (SOL) and wake after
sleep onset (WASO) were indicated in hours and minutes using a
scroll down menu with 5-minute intervals, and sleep duration was
defined as TIB – (SOL + WASO). For statistical analyses purposes
in the present study, sleep duration was categorised in two
different ways (a) 3 groups: ‘short sleep’ (51 s.d.: 4.85 h), ‘normal
sleep’ (4.85–8 h) and ‘long sleep’ (41 s.d.: 8 h); and (b) 6 groups:
‘54 h’, ‘4–5 h’, ‘5–6 h’, ‘6–7 h’, ‘7–8 h’, ‘8–9 h’, ‘9–10 h’ and ‘10+ h’.
Subjective sleep need was reported in hours and minutes, and sleep
deficiency was calculated separately for weekends and weekdays,
subtracting total sleep duration from subjective sleep need.
Daytime napping was also assessed using the following response
alternatives: ‘never’, ‘seldom’, ‘sometimes’, ‘mostly’ and ‘always’, with
the two latter alternatives coded as positive in a dichotomous variable.
Confounders
Symptoms of depression were assessed using the short version of
the Mood and Feelings Questionnaire (SMFQ).
17
The SMFQ
comprises 13 items assessing depressive symptoms rated on a
3-point Likert-type scale. The wordings of the response categories
in the Norwegian translation equates to the original categories of
‘not true’, ‘sometimes true’ and ‘true’. High internal consistency
between the items and a strong uni-dimensionality have been
shown in population-based studies,
18
and have been recently
confirmed in a study based on the sample included in the present
study.
19
For the purposes of the current study, depression was
definedasascoreabovethe90thpercentileoftheTotalSMFQ-score.
It should be noted that the term depression as used in the current
study does not imply existence of a clinical diagnosis, such as
major depressive disorder. Also, being a relatively brief self-report
questionnaire, the SFMQ does not differentiate between different
types of depressive disorders/ conditions. The Cronbach’s alpha of
the SMFQ in the current study was 0.91.
Perfectionism was assessed by the short version of the
Perfectionism subscale from the Eating Disorder Inventory
(EDI).
20
The scale was adapted to a 3-point scale from the
original 6-point scale for this study with the response options:
‘not true’, ‘somewhat true’ and ‘certainly true’, and a total score
was employed for the present study.
Symptoms of ADHD were assessed using the Adult ADHD
Self-Report Scale Screener (ASRS).
21
ASRS is an 18-item selfreport scale, comprising 9 items on a hyperactivity subscale and
9 items on an inattention subscale reflecting the DSM-IV diagnostic
symptom criteria. The response categories are a Likert-type scale
(‘never’, ‘rarely’, ‘sometimes’, ‘often’ and ‘very often’). The
questionnaire was originally constructed for use with adults, but
has recently been validated for use with adolescents.
22
Statistic
IBM SPSS Statistics 22 for Mac (SPSS Inc., Chicago, Illinois, USA)
was used for all analyses. Pearson’s chi-squared test and independent samplest-tests were used to examine differences in demographic, psychological and sleep variables between the
adolescents reporting self-harm versus no self-harm. Pearson’s
chi-squared tests were also used to examine differences in sleep
problems in method of self-harm (i.e. self-cutting and overdose)
and frequency of self-harm (none, once, two or more times). Logistic regression analyses were conducted to examine the predictive effect of the sleep variables (independent variables) on selfharm (dependent variable), using ‘no self-harm’ as the reference
category. Both crude and adjusted models were examined, the
latter adjusting for the following covariates entered in separate
blocks: (a) demographics (age, gender, parental education and
family economy), (b) demographics+depression (SMFQ total
score), (c) demographics+perfectionism (EDI total score), (d)
demographics+ADHD (ASRS Inattention and ASRS Hyperactivity/Impulsivity subscales, and (e) fully adjusted model (i.e.
including all covariates).
307
Sleep problems and self-harm in adolescence
Hysing et al
Results
Demographic characteristics of the sample
The mean age was 17.9 (s.d. = 0. years, and the sample included
more girls (53.3%) than boys (46.7%). The majority (98%) were
high-school students. A total of 5.3% of the sample was defined
as immigrants as they had both parents born outside Norway.
In terms of maternal education, 10.1% had been educated to
primary school level, 41.3% to secondary school level and
48.6% to university/college level. The corresponding percentages
for paternal education were 10.6%, 46.4% and 43.0% respectively.
A total of 67.4% reported having a family economy (income) ‘like
most others’, whereas 25.5% had ‘better’ and 7.1% had ‘worse
family economy’.
Self-harm
As detailed in Table 1, 7.2% of the population met the criteria for
self-harm, of which 55% reported self-harm on two times or more
occasions. There were significantly more girls (11%) than boys
(2.8%;P50.001) meeting the criteria. The most frequent method
used was self-cutting (n= 547) followed by overdose (n=115) and
other methods (n= 17). Self-harm was significantly associated with
lower parental education, poor family economy, as well as more
symptoms of depression, perfectionism and ADHD (allP50.001).
Self-harm and sleep
As depicted in Fig. 1 and detailed in Table 1, there was a
significant relationship between self-harm and sleep duration.
The average sleep duration among adolescents reporting self-harm
was 05.33 h, compared with 06.29 h among adolescents without no
self-harm. Figure 1 shows that a significantly larger proportion of
adolescents reporting self-harm slept less than 5 h compared with
no adolescents without self-harm.
Adolescents reporting self-harm also reported significantly
longer SOL, WASO and had larger sleep deficiency than their
non-self-harming peers (allP50.001). The differences between
weekdays and weekend bedtimes were also larger among those
adolescents who self-harmed (P= 0.023) and they also napped
more frequently during the day (P50.001; see Table 1 for details).
308
Table 1 Demographic and sleep variables in adolescents stratified by self-harm
No self-harm (n= 9139, 92.8%) Self-harm (n= 707, 7.2%) P
Demographic variables
Age, years: mean (s.d.) 17.9 (0. 17.8 (0. 0.004
Gender 50.001
Girls, % (n) 89.0 (4673) 11.0 (576)
Boys, % (n) 97.2 (4466) 2.8 (128)
Sleep variables
Sleep duration category, % (n) 50.001
Short sleeper (51 s.d.: 4.85 h) 13.2 (1147) 33.2 (232)
Normal sleeper 76.3 (6650) 60.7 (424)
Long sleeper (14s.d.: 8 h) 10.6 (922) 6.0 (42)
Sleep duration, h:min: mean (s.d.) 6:29 (1:36) 5:33 (1:56) 50.001
Insomnia (DSM-V), % (n) 16.5 (1456) 43.5 (307) 50.001
Sleep onset latency (SOL), h:min: mean (s.d.) 0:45 (0:56) 1:13 (1:05) 50.001
SOL430 min, % (n) 36.9 (3374) 61.0 (431) 50.001
Wake after sleep onset (WASO), h:min: mean (s.d.) 0:13 (0:38) 0:33 (0:54) 50.001
WASO430 min, % (n) 10.8 (984) 27.3 (193) 50.001
Sleep deficiency (42h), % (n) 45.2 (3247) 68.2 (375) 50.001
Bedtime diff (weekdays/weekends)42h, % (n) 48.7 (4276) 53.2 (374) 0.023
Daytime napping, % (n) 22.0 (2008) 35.8 (454) 50.001

No self-harm
Self-harm
Fig. 1 Self-harm and no self-harm among adolescents stratified by categories of sleep duration.
Error bars represent 95% confidence intervals. If confidence intervals do not overlap then the difference between the estimates is statistically significant atP50.001.
Sleep problems and self-harm in adolescence
The results from the series of logistic regression analyses
investigating the relationship between the different sleep variables
and self-harm are presented in Table 2. Reinforcing the findings
from Table 1, the crude analyses showed that all sleep variables,
except long sleep duration, were associated with significantly
increased odds of also reporting self-harm.
As detailed in Table 2, adjusting for potential confounders,
including sociodemographics, symptoms of depression,
perfectionism and ADHD symptoms, reduced several of the odds
ratios (ORs). Depression was the confounder that explained most
of the reductions in ORs; sociodemographic factors, perfectionism
and ADHD did not, or only slightly, attenuated the associations.
However, the effect on all sleep variables remained significant in
the fully adjusted analyses: short sleep duration (OR = 1.68, 95%
CI 1.38–2.04), insomnia (OR = 1.73, 95% CI 1.44–2.08), SOL
(OR = 1.36, 95% CI 1.14–1.63), WASO (OR = 1.50, 95% CI
1.23–1.84), sleep deficiency (OR = 1.46, 95% CI 1.17–1.79),
bedtime differences between weekdays and weekends (OR = 1.29,
95% CI 1.09–1.53) and daytime napping (OR = 1.23, 95% CI
1.02–1.47).
Method of self-harm and sleep
The prevalence of insomnia among adolescents reporting an
overdose (n= 115) was 47%, compared with 43.3% among those
reporting self-cutting (n= 547), and 16.6% of those reporting
no self-harm (w
2
(2) = 306.6, P50.001). Similarly, as depicted in
Fig. 2, nearly half of those reporting overdose tend to sleep less
than 4.85 h (1 s.d.), compared with 30.6% among those reporting
self-cutting and 13.3% of those reporting no self-harm
(w
2
(4) = 206.4,P50.001).
Frequency of self-harm and sleep
There were significant dose–response associations between sleep
problems and the frequency of self-harm. As depicted in Fig. 3,
the prevalence of insomnia was 48% among adolescents reporting
self-harm two times or more, compared with 37% among
adolescents reporting having engaged in self-harm once
(w
2
(2) = 423.2,P50.001). The same pattern was found for short
sleep duration (37% v. 29% [w
2
(4) = 302.2, P50.001]), SOL
(64%v.59% [w
2
(2) = 212.9, P50.001]) and WASO (30%v.24%
[w
2
(4) = 223.9,P50.001]).
Discussion
This population-based study of adolescents demonstrated a
consistent association between sleep and self-harm, presenting as
a dose–response relationship; the more sleep problems, the higher
frequency of self-harm. Self-harm was linked to a range of
different sleep parameters, including insomnia, short sleep
duration, long SOL and WASO, as well as large discrepancies
between weekdays versus weekend bedtimes. Whereas depression
did account for some of the association between sleep and selfharm, neither perfectionism nor symptoms of ADHD had any
impact on the sleep-self-harm association.
Previous studies have heightened our awareness of the
importance of sleep in relation to self-harm and suicidal
behaviour, but the measures assessing sleep have typically been
brief and non-specific, often using a single item to assess symptom
of insomnia. The current study extends this literature by assessing
a wide range of different sleep problems, including a full
operationalisation of the recent DSM-5 criteria of insomnia.
Further, no studies have previously examined the link between
sleep duration, in contrast to subjectively reported insomnia.
Whereas sleep duration and insomnia may indeed overlap, they
309
Table 2 Logistic regression analyses of sleep variables associatedwith self-harm among adolescents in the ung@hordaland study
Unadjusted analyses Adjusted for demographics
a
Adjusted for
demographics+depression
b
Adjusted for
demographics+perfectionism
c
Adjusted for
demographics+ADHD
d
Fully adjusted analyses
e
OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Sleep duration
Normal sleep 1.00 – 1.00 – 1.00 – 1.00 – 1.00 – –
Short sleep (51 s.d.: 4.85 h) 3.22 2.71–3.84 2.95 2.47–3.53 1.77 1.45–2.15 2.88 2.41–3.45 2.26 1.87–2.72 1.68 1.38–2.04
Long sleep (1> s.d.: 8 h) 0.72 0.52–0.99 0.70 0.50–0.97 0.84 0.60–1.19 0.73 0.22–1.01 0.83 0.59–1.16 0.88 0.62–1.24
Insomnia (DSM-V) 3.97 3.38–4.66 3.32 2.81–3.92 1.87 1.56–2.24 3.16 2.67–3.73 2.40 2.01–2.86 1.73 1.44–2.08
Sleep onset latency
(SOL)430 min 2.50 2.13–2.93 2.27 1.93–2.67 1.46 1.23–1.74 2.21 1.88–2.60 1.74 1.47–2.06 1.36 1.14–1.63
Wake after sleep onset
(WASO)430 min 3.06 2.56–3.67 2.67 2.22–3.21 1.58 1.29–1.93 2.53 2.10–3.05 2.04 1.67–2.47 1.50 1.23–1.84
Sleep deficiency (42h) 2.67 2.22–3.23 2.39 1.97–2.89 1.59 1.30–1.95 2.33 1.92–2.82 1.77 1.45–2.16 1.46 1.19–1.79
Bedtime difference
(weekdays/ends)42h 1.20 1.02–1.40 1.37 1.17–1.61 1.32 1.12–1.57 1.37 1.17–1.61 1.24 1.06–1.47 1.29 1.09–1.53
Daytime napping 1.92 1.63–2.27 1.61 1.36–1.91 1.30 1.09–1.56 1.61 1.36–1.91 1.30 1.09–1.55 1.23 1.02–1.47
a. Adjusted for age, gender, parental education, family economy.
b. Depression assessed by short version of the Mood and Feelings Questionnaire (SFMQ) total score.
c. Perfectionism assessed by Eating Disorder Inventory (EDI) total score.
d. Attention-deficit hyperactivity disorder (ADHD) assessed by the Adult ADHD Self-Report Scale Screener (ASRS) in attention hyperactivity/impulsivity subscales.
e. Adjusted for age, gender, parental education, family economy, SFMQ total score, EDI total score, and ASRS in attention hyperactivity/impulsivity subscales.
Statistically significant associations are highlighted in bold.
Hysing et al
are distinct sleep parameters, with differences in relation to both
risk factors and consequences such as school performance and
gender patterns.
23
It is therefore important to assess a wide range
of sleep parameters, as conclusions regarding one of them (e.g.
insomnia) cannot necessarily be generalised to the others (sleep
deficit). However, the results from the current study show that
the sleep–self-harm relationship is consistent across a wider range
of sleep measures. However, inspection of the overlap in
confidence intervals suggests that insomnia is a stronger risk
factor than some of the other sleep parameters, such as sleep
deficiency, SOL and weekday–weekend differences.
As we expected, adolescents who reported self-harm also had
higher rates of depression, perfectionism as well as ADHD
symptoms than those who did not report self-harm. Knowing
from past research that these factors have been linked to both
initiation and maintenance of sleep problems,
24–26
they may be
important factors in accounting for the overlap between self-harm
and sleep. As hypothesised, depression accounted for some of the
association between sleep and self-harm, but the latter association
remained significant even in the fully adjusted analyses, which is
consistent with previous studies.
5
Theoretically, emotional
regulation can serve as a useful framework for understanding this
relationship. Indeed, it has been suggested that the effect of
sleep problems on emotion regulation may be more marked in
adolescents than in adults. This was exemplified in an experimental
study comparing sleep deprivation on a catastrophising task in
three age groups, with adolescents showing a higher rate of
catastrophising when sleep deprived than adults.
27
Symptoms of
Short sleep (51 s.d.: 4.85 h) Normal sleep Long sleep (14s.d.: 8 h)
%
No self-harm
Self-cutting
Overdose
Fig. 2 Sleep duration stratified by type of self-harm.
Error bars represent 95% confidence intervals. If confidence intervals do not overlap then the difference between the estimates is statistically significant atP50.001.

Insomnia Short sleep SOL430 min WASO430 min
%
None
Once
Two times or more
Fig. 3 Self-harm and sleep problems, stratified by frequency of self-harm.
Error bars represent 95% confidence intervals. If confidence intervals do not overlap then the difference between the estimates is statistically significant atP50.001.
Sleep problems and self-harm in adolescence
ADHD have also been shown to be related to self-harm
28
and it
has been previously suggested that they may explain the link
between sleep and self-harm.
5
However, this was not supported
in the present study, with impulsivity, inattention and hyperactivity
not reducing the strength of the association between sleep and
self-harm.
The present study indicates that sleep problems and short
sleep duration are sensitive markers for self-harm. The findings
also suggest that the relationship between sleep and self-harm
varies as a function of method of self-harm. In future research,
it would be important to determine whether this relationship is
moderated by frequency and medical seriousness of self-harm.
The general effectiveness of sleep interventions in reducing
symptoms of both sleep and co-occurring symptoms suggest that
such interventions may play a role in the prevention and
treatment of self-harm. Incorporating sleep interventions transdiagnostically to improve self-regulation has been suggested, and
has shown promise in reducing symptoms of depression as well
as addressing sleep problems.
29
Recently, including healthy sleep
in the prevention of self-harm and suicide has been suggested as
one of five factors recommended for future interventions.
30
However, further studies are required to determine whether
including sleep interventions, as part of self-harm treatment or
prevention programmes, is effective.
Strengths and limitations
Although the study has many strengths, there are some potential
limitations worth discussing. A limitation of the present study,
consistent with other studies which rely on self-report, is that
the findings are subject to response biases and may have been
affected by demand characteristics. Nonetheless, as far as possible,
we have employed widely used questionnaire measures with
recognised reliability and validity. The present study is based on
a broad and detailed assessment of sleep. Although the definition
of insomnia was based on published quantitative criteria, it was
not based on a structured interview, which, of course, is difficult
to employ in a population-based study. However, the use of both
SOL and WASO to estimate exact sleep duration was a significant
strength of the current study, as most population-based studies on
sleep rarely provide such detailed measures. Although selfreported sleep parameters, including SOL and WASO typically
differ from those obtained from objective assessments,
31
recent
studies have shown that such self-report sleep assessments can
be recommended for the characterisation of sleep parameters in
both clinical and population-based research.
32
Also, the accuracy
of self-reported SOL and WASO are generally better among
adolescents than in older adults,
33
and a study of young
adolescents in Hong Kong found good agreement between
actigraphy measured and questionnaire reported sleep
durations.
34
The use of the Quantitative Research Criteria for
Insomnia
35
is also a major strength of the study, not limiting sleep
problems to self-reported single items of initiating and maintaining
sleep as has been used in previous studies.
36
Self-harm was
assessed without specifying the motivation(s) underpinning the
behaviour. However, such operationalisation is consistent with
clinical guidance
37
and is employed widely in adolescent studies
in Europe.
15
Many previous studies have also focused on self-harm
in relation to suicidal ideation or suicide attempts but the current
study was restricted to self-harm. It should also be noted that
our operationalisation of socioeconomic status included the
adolescents’ own perceived family economy, rather than objective
measures of household income. However, this index of socioeconomic status has been shown to align well with previous
studies in which family economy has been defined using more
traditional methods.
38
Also, the cross-sectional design restricts
causal attributions, and longitudinal studies are needed to assess
the temporal association between sleep, self-harm and depression.
Are the findings representative? We have previously
demonstrated that the prevalence of insomnia and short sleep
duration in the present study are at the higher end of the
prevalence estimates in the literature.
23
However, this can also
be seen as a result of the shorter sleep duration in recent years.
The prevalence estimates of self-harm were somewhat lower than
in previous studies. This may partly be due to missing data, as
some of the adolescents did not provide sufficiently specific
information needed to code the self-harm acts. The inclusion of
adolescents with incomplete information would yield prevalence
rates more in line with previous studies.
39
Also, depression was
assessed by a self-report instrument, the SMFQ. As no validated
cut-off exists for Norwegian adolescents, the 90th percentile on
the total SFMQ score was chosen as an operationalisation of
depression. Clearly, this does not imply the existence of a clinical
diagnosis, such as major depressive disorder, and the lack of a
clinical interview in confirming a clinical diagnosis of depression
is a limitation of the present study. This is in contrast to conventional depression rating scales which normally contain such items,
thereby preventing circularity and facilitating the unambiguous interpretation of associations between the symptoms of sleep and affective problems in the present study. Tiredness was included in
the SMFQ; however, the association with several sleep parameters
was not higher for this item than for other depressive symptoms.
Furthermore, although we did assess depression, perfectionism
and ADHD, which accounted for some of the link between sleep
and self-harm in the full model, there may be other covariates not
addressed in the current study that may explain parts of this
association, such as other mental health disorders (e.g. psychosis
or bipolar disorder) or physical illnesses. Although beyond the scope
of the present study, future research could usefully explore the
relationship between cognitive variables (e.g. rumination and
hopelessness), sleep problems and self-harm. Another limitation
comprises the inclusion of a relatively low number of adolescents
not in school compared with adolescents in school. It is worth
noting, however, that many of the previous European studies of
self-harm have excluded adolescents who are not in school. Finally,
the attrition from the study could affect generalisability, with a
response rate of about 53% and with adolescents in schools
overrepresented. Based on previous research from the former waves
of the Bergen Child Study, non-participants often have more
psychological problems than participants,
40
and it is therefore likely
that the prevalence of both self-harm, sleep problems and depression
may be underestimated in the current study.
Self-harm is related to sleep across a wide range of sleep
parameters and this relationship is partly accounted for by
depression. Addressing both sleep and depression in the
prevention and treatment of self-harm may be fruitful avenues
for new research.
Mari Hysing, PhD, PsyD, The Regional Centre for Child and Youth Mental Health and
Child Welfare, Uni Research Health, Bergen, Norway;Børge Sivertsen, PhD, PsyD,
The Regional Centre for Child and Youth Mental Health and Child Welfare, Uni
Research Health, Bergen, Norway, Division of Mental Health, Norwegian Institute of
Public Health, Bergen, and Department of Psychiatry, HelseFonna HF, Haugesund,
Norway;Kjell Morten Stormark, PhD, PsyD, The Regional Centre for Child
and Youth Mental Health and Child Welfare, Uni Research Health, Bergen, and
Department of Clinical Psychology, University of Bergen, Norway;Rory C. O’Connor,
PhD, CPsychol, FAcSS, Suicidal Behaviour Research Laboratory, Institute of Health
& Wellbeing, University of Glasgow, UK
Correspondence:Mari Hysing, Regional Centre for Child and Youth Mental
Health and Child Welfare, Postboks 7810, 5020 Bergen, Norway. Email:
mari.hysing@uni.no
First received 14 Feb 2014, final revision 25 Nov 2014, accepted 27 Nov 2014
311
Hysing et al
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10.1192/bjp.bp.114.146514 Access the most recent version at DOI:
2015, 207:306-312. BJP
Mari Hysing, Børge Sivertsen, Kjell Morten Stormark and Rory C. O'Connor
Sleep problems and self-harm in adolescence
References
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