Disclaimer: This literature review has been written by a student and is not an example of our professional work, which you can see examples of here.

Any opinions, findings, conclusions, or recommendations expressed in this literature review are those of the authors and do not necessarily reflect the views of UKDiss.com.

Literature Review on Chronic Back Pain and Depression

Info: 15372 words (61 pages) Example Literature Review
Published: 19th Apr 2021

Reference this

Tagged: PhysiologyMental HealthMedicine

Table of Contents



Literature search

Review procedure


Prevalence of LBP among young females

Females are at a greater risk of depression

What is the association between CLBP/chronic pain and depression in the youth?

Adolescents with pain are more likely to have depression

Activity levels and fear avoidance model

Predisposing and protective factors for comorbid depression in young with pain

Chronic pain and depression have common risk factors

Sleep disturbance, chronic pain and depression

Pattern of pain prescriptions among youth with chronic pain




Table of Figures

Figure 1 Review Process of the Literature

Figure 2 Source: AIHW analysis of ABS Microdata: National Health Survey, 2014–15

Figure 3 Prevalence of mental disorders across age groups

Figure 4 Original version of fear avoidance model

Figure 5 Modified Fear avoidance model predicting depression in paediatric population

Figure 6 Fear avoidance model predicting disability in paediatric population

Figure 7 Psychological factors impacting the Fear Avoidance Model


Table 1 Search Statement

Table 2 Studies demonstrating an association between pain and depression

Table 3 Studies examination activity levels and biomechanical factors

Table 4 Studies exploring the psychosocial variables associated with pain

Table 5 Studies examining the association of sleep disturbance with pain and depression


Young Australian females have the greatest prevalence of psychological distress when compared across all age groups (1). Between 2011-12 and 2014-15, young females in the 18-24 age group were the only age group in Australia to have reported an increase in the prevalence of psychological distress (increasing from 13% to 20%) (1). What is concerning is whether this reduced mental wellbeing in young females will lead to a reciprocal rise in the incidence of low back pain (LBP[1]), as such pain often co-exists with depression leading to greater disability[2], reduced quality of life and increased healthcare visits among adolescents with chronic pain (2, 3). Furthermore, studies have demonstrated females are more likely to suffer from LBP than males (4, 5), and report greater stress levels from school that is associated with more health complaints, such as “musculoskeletal pain, fatigue, sleep disturbances, sadness and anxiety” (6). Adolescence and young adulthood is an opportunity for intervention to modify ?outcome as the onset of LBP frequently occurs in the 16-34 age group (7) as depicted in Figure 2 (prevalence 13.4% males, 14% females) (7). Since LBP that develops during adolescence is likely to persist into adulthood (8), along with the immense cost chronic LBP (CLBP) places on the Australian healthcare system ($1.2 billion per annum) (9), it is important to prevent or improve the management of LBP in this age group.

The majority of the research investigating the association between CLBP and depression is conducted in the older population (>40yrs). In contrast , research in the younger population explores chronic pain,[3] rather than CLBP specifically. Most of this research is conducted in countries outside of Australia as depicted in Table 2Table 5 (United States (10-13), Norway (14, 15), Sweden (16), Netherlands (17-19)), with only two studies conducted in young Australian adolescents and adults (3, 20). The existing chronic pain research involves children (8-12yrs) and younger adolescents (8-15yrs), and few young adults (18-25yrs). Therefore, to address this gap in the literature, this review aims to address the following primary research question: what is the association between CLBP and depression in young females aged 16-25yrs old?  The aims to address this question by exploring the topics outlined in the table of contents above.


Literature search

Three databases (PubMed, PsycINFO, Cinahl) were searched in February 2017 using the following Medical Subject Headings (MeSH) terms, titles and Boolean term as shown in Table 1.


Table 1 Search Statement

  MeSH* Titles
OR Low back pain


Chronic pain

Low back pain


Chronic pain

OR Depression



Mental health




Mental health

*Medical Subject Headings

Database filters were applied for all three searches as shown below:

  • Age was restricted to adolescents (13-18yrs old) and young adults (19-24yrs old)
  • Females
  • Humans
  • Last 10 years
  • English language

Review procedure

Figure 1 Review Process of the Literature

*Most studies relating to childhood adversities and alexithymia comprised mainly older adults (40-50yrs old).

**Not all articles were included in the table


Prevalence of LBP among young females

Four studies (3, 4, 11, 20) from Australia, United States and Greece have reported the prevalence of LBP in community-dwelling adolescents and young adults to range between 15.2%-41%. Only two Australian studies compared the prevalence of LBP between females and males. While Beales et al stated significantly more females reported a “lifetime experience of LBP” compared to males (55.8% vs 41.8%) (3), Rees et al stated significantly more females reported comorbid back and neck pain compared to males (17.6% vs 9.1%, p<0.001), but there was no significant sex differences in the prevalence of back pain (males 17.3% vs females 12.9%) (20).

Females are more affected by LBP. The study by Beales et al demonstrated females reported lower quality of life in both physical and mental components compared to males (p<0.001), and were more impacted by LBP in terms of schooling/work, activity limitation, exercise and medication (p<0.001 to p=0.046) (3). Similarly, a study conducted in 15-19yr old adolescents stated females are more likely to report higher “pain intensity, pain frequency, physical consultations, and school interference” (4).

Females are at a greater risk of depression

According to Australia Bureau of Statistics, mental health disorders is most prevalent in the 16-24yr old age group and it decreases with age as depicted in Figure 3, with 76% of mental disorders developing before the age of 25 (21). In 2007, more females than males (30% vs 23%) in the 16-24 age group were symptomatic for a mental disorder, with anxiety (20% vs 12%) being the most common followed by mood disorders (8% vs 4%) (21), which often coexist together. Poorer mental wellbeing in females is also replicated in two other cross sectional studies in Greece and Sweden with a significantly greater proportion of females reporting persistent stress (22% vs 7%, p=0.0001), depressed mood (6% vs 2%, p=0.0055), persistent nervousness (15% vs 7%, p=0.036), persistent fatigue (19% vs 7%, p=0.0001) (4), sadness (p=0.000), and school-related stress (p=0.000) (6).

What is the association between CLBP/chronic pain and depression in the youth?

Adolescents with pain are more likely to have depression

Depression and poor emotional wellbeing are more prevalent in children and adolescents with chronic pain (12, 20). A study involving college students (18-30yrs) demonstrated that LBP is significantly associated with greater depression scores (13). However, limitations of this study include no specification of pain duration and the possibility of selection bias, as all participants were recruited from the New York Institute of Technology where sedentary lifestyle may act as a confounding factor. Nevertheless, the results reported are consistent with two other cross sectional studies involving community-dwelling adolescents. Beales et al revealed adolescent females with LBP are more likely to suffer from depression/anxiety compared to males (84.1% vs 15.9%, p<0.001) (3). Furthermore, Rees et al revealed adolescent females reported higher scores for somatic complaints, anxious/depressed mood and withdrawn behaviour, which are associated with a greater risk of neck/back pain (MOR[4]=1.86, p<0.001) (20).

Pain and depression is a comorbidity with worse outcomes. The first study to explore the impact of comorbidities on LBP in 17yr old adolescents revealed anxiety/depression are significant comorbidities associated with LBP leading to reduced quality of life (3). Results from another study that investigated the impact of psychological and lifestyle factors on chronic pain revealed depressive/anxiety symptoms have the strongest association with chronic pain, more so than lifestyle factors (15). Akin to adult studies, a few studies in the youth with pain demonstrated higher depression scores are associated with (13, 15) or a significant predictor (ß=0.36, p=0.04) (17) of self-reported disability[5] (11, 17). Therefore, depression and chronic pain commonly co-exist leading to greater disability, which is no surprise since they share common neurobiological pathways (22). Hence, it is important to address these two most commonly occurring conditions early in life to prevent long term disability.

Activity levels and fear avoidance model

There is an inter-related relationship between activity levels, pain severity[6] and depression partly driven by pain catastrophizing[7]. Fear avoidance model (FAM) in Figure 4 (23) demonstrated pain catastrophizing drives pain related fear resulting in avoidance of activities, which reduces the pain threshold (24). This in turn leads to increased pain severity and further avoidance of activities, which results in a viscous cycle of deconditioning. A study by Long et al supported the FAM as it demonstrated a reciprocal relationship between activity levels and pain frequency (-0.66 < r < -0.45, p<0.01), and between mean activity levels (actigraphy) and pain intensity (r=0.31, p=0.05) (12). However, another study by Stommen et al reported no significant association between activity levels and pain intensity/disability (17), which appears to contend the FAM. This inconsistency may be due to Stommen et al using a questionnaire (SQUASH) that relied on participants to self-report the amount of time (minutes per a day) and intensity at which they spend on activities, which may be affected by recall bias. In contrast activity levels measured by an actigraphy over a 7-day period in the study by Long et al reduced the impact of recall bias.

Evidence to support the association between activity levels and depression in the younger population is equivocal. The FAM produced by Vlaeyen & Linton 2000 in adults with CLBP also predicted depression as an outcome Figure 4 (25), which is supported by Long et al where higher activity levels were inversely correlated with less depressive symptoms (-0.39 < r < -0.36, p<0.02) in adolescents (12-17yrs), moreover, reduced sedentary lifestyle was moderately associated with less depressive symptoms (r=0.33, p=0.04) (12). However, application of FAM in a group of 8-17yr olds revealed additions of direct links from pain catastrophizing and pain related fear to depression were required for the model to be predictive of depression. This modification reduced the existing association between avoidance behaviour and depression, which suggest pain beliefs may contribute more to depression compared to activity levels. Based on the current evidence that adolescents with chronic pain have reduced activity levels compared to their peers (12), and the higher risk of depression among young females, it is necessary to explore the application of the FAM in young females with LBP to help identify appropriate management strategies.

Predisposing and protective factors for comorbid depression in young with pain

Studies in adolescents have suggested that pain beliefs may be more important than pain severity in determining the risk for depression. A study conducted in adolescents and young adults demonstrated depression accounted for the frustration of not being able to achieve desired goals in personal values (p = 0.02), social acceptance (p < 0.01), self-acceptance (p < 0.01) and health (p < 0.01) (18). Parallels can be drawn with a study conducted largely in adults (only 12.2% were aged between 18-30yrs) that demonstrated helplessness mediated the effects of pain intensity on depression (26). Over time activity limitations due to chronic pain may result in increased frustration where the mind focuses on what pain has prevented one from achieving. In the long term, this predisposes to helplessness and low self-esteem, which increases the risk of depression. Pain acceptance encourages the mind to shift its focus away from the pain itself, and learn to achieve desired goals in the presence of pain (27). This helps the individual regain a sense of control and confidence over their life, thereby improving self-efficacy. This is further supported by a study involving adolescents with chronic pain that demonstrated pain acceptance significantly predicted the variance in pain related fear (∆R2=0.34, p<0.001), developmental functioning (∆R2=0.21, p<0.001), social functioning (∆R2=0.18, p<0.001), depression (∆R2=0.17, p<0.001), general anxiety (∆R2=0.12, p<0.001), physical functioning (∆R2=0.10, p<0.001) and family relationships (∆R2=0.076, p<0.01) (28). According to the FAM, reducing negative pain cognitions via pain acceptance may lead to increased activity levels thereby reducing the risk of depression and disability (23). A study in adolescents determined acceptance and commitment therapy resulted in better outcomes for both depression and disability (29). Moreover, a study in adults demonstrated changes in pain acceptance post treatment resulted in decreased levels of catastrophizing and depression (30). Therefore, pain acceptance appears to be a promising intervention for young females with LBP to reduce the risk of depression and improve general wellbeing.

The association between pain severity and depression is equivocal depending on the study design used. Two cross sectional studies have exhibited severity[8] did not differ according to depression, disability and LBP status (11, 13). Instead, one of the studies demonstrated a significant association between the grade of depression and “pain interference” (F=3.50, p<0.05) and “emotional burden” (F=36.42, p<0.001) (11). In contrast to the results reported in cross sectional studies that involved community samples, the longitudinal study by Holley et al involving a clinical sample revealed pain intensity and depressive symptoms were significantly associated with each other over a 12month period. Changes in pain intensity had a greater impact on depressive symptoms (ß=1.16, p<0.001) than vice versa (ß=0.026, p<0.05) (10). A major strength of this study was semi-structured interviews were conducted at baseline, 6 and 12month follow ups in addition to the completion of CES-D by participants, which made the assessment of depressive symptoms more accurate and reliable. Whereas other studies relied solely on questionnaires to assess depressive symptoms where the impact of social desirability[9] would be high among adolescents. The different results reported between cross sectional and longitudinal studies above emphasise the need for more longitudinal studies as pain and depression exist in a dynamic biopsychosocial model that changes with time. Pain intensity in cross sectional studies were merely a snapshot of the participant’s momentary subjective pain experience. Whereas in longitudinal studies, changes in pain intensity can be monitored over time, which is probably more reflective of the factors that influence pain intensity or perception over time, namely, pain catastrophizing and pain related fear (23, 31, 32). These cognitive factors have been shown to influence pain perception and depression in the FAM and PCS[10]. But these are yet to be explored in young females with LBP.

Thus far one study has speculated pain related beliefs may contribute to comorbid depression/anxiety in adolescents with LBP. This study identified four distinct LBP subgroups. Although group 2 had a higher likelihood for LBP diagnosis compared to group 3, group 3 but not group 2 exhibited an increased likelihood for comorbid anxiety/depression, sleep disturbance and eating disorders (3), as well as a significantly lower quality of life. The protective and risk factors for comorbid depression/anxiety in group 2 and 3 were not assessed in this study. Nevertheless the author suggested physical factors, (spinal curvature and back endurance (13)), lifestyle factors (sedentary activity (15), obesity (15), school bags (33), smoking (15)) and alterations in nociceptive processing may play an important role in group 2. Whereas “pain related beliefs, self-efficacy and locus of control” may play a more important in group 3. The validation of the FAM in the paediatric population above has demonstrated negative pain beliefs, such as catastrophizing, pain related fear play an important role towards the development of depression (23).

On the other hand, family cohesion and control beliefs act as protective factors against depression (11, 34). Good family cohesion protected emotional wellbeing from the negative impacts of disability associated with chronic pain (34). Similarly, another study revealed peer support is fundamental to “independence, emotional adjustment and identity formation” (35), which all contribute to a well-balanced mental health. Therefore, pain related cognitions should be routinely screened and targeted in treatment to reduce the risk of depression and disability.

Currently two studies have incorporated cognitive factors into screening tools to risk stratify adolescents with chronic pain into subgroups. The most promising tool was the BAPQ that correctly risk stratified 95% of participants (34), while the PPST correctly allocated 71-79% of participants on a 4month follow up (36). However, both of these tools have been validated in samples recruited from secondary or tertiary pain clinics and are yet to be validated in the general community where they will be most useful, as primary care is often the first point of contact where early intervention can be implemented. Nevertheless, these two studies have demonstrated depressive symptoms, catastrophizing, disability, pain related fear, anxiety and sleep disturbance have some prognostic value for disability in children and adolescents with chronic pain.

Negative pain related cognitions may persist into adulthood leading to reduced resilience. A study by Ruehlman et al demonstrated depressed young adults with chronic pain shared similar pain beliefs (PCP:EA[11]) with “non-resilient” adults (11). Clinically depressed adolescents and “non-resilient” adults had similar pain related fear (M=8.46 vs 9.49) and control belief (M=17.14 vs 17.28) scores. Meanwhile, catastrophizing (M=7.69 vs 8.83) and perceived disability (M=4.65 vs 11.59) was higher in “non-resilient” adults (11), which suggest catastrophizing is a dynamic factor that should be targeted early in the phase of chronic pain to prevent long term disability associated with reduced self-efficacy and depression. However, compliance rates are lower for psychological treatments (73%) compared to medication (94%) and physical treatments (92%) (36). In addition, adolescents who were classified as high risk based on PPST were more likely to be non-compliant with psychological treatments at 4month follow up (36). Therefore, factors that influence engagement with healthcare services and treatment programs need to be explored to improve outcomes for young females with LBP and depression.

Longitudinal studies offer greater insight into the bidirectional relationship between pain and depression. Aforementioned results reported by Holley et al demonstrated pain may have a stronger impact on depression than vice versa. This is supported by another 12month longitudinal study that reported depressive symptoms predicted both the number of pain sites and multiple frequent pain sites at 1-year follow up (14). Although this finding is statistically significant, depressive symptoms only explained 11% of variance in pain outcomes (14), which suggest pain may have a stronger influence over depression. However, a multinational study conducted in adults reported contradicting results whereby early onset of mental disorder (<21yrs) increased the risk of chronic back/neck pain in adulthood (37). Therefore, the onset of pain conditions and depression is fundamental to understanding the factors that impact on this comorbidity, which can only be analysed in prospective longitudinal studies that is currently lacking in both the older and younger populations.

Chronic pain and depression have common risk factors

Childhood adversities (CAs) are a risk factor for chronic pain in a “dose-dependent” manner (38-40) and depression (41). A multinational (37) and smaller cross sectional study in Japan (40) revealed physical and sexual abuse are significant risk factors for chronic back pain in adults. While a longitudinal study conducted in adolescents also revealed parental divorce during the 1-year of follow up is associated with frequent back pain co-existing with other pain sites (14). In the multinational study conducted in adults, the risk of chronic back/neck pain increased with the number of CAs: one CA (HR=1.13, p<0.015), two CAs (HR=1.34, p<0.05), three or more CAs (HR=1.59, p<0.05) (37). This is consistent with the allostatic stress hypothesis that suggest accumulation of biopsychosocial stressors over time wear out the body’s homeostatic system resulting in an increased risk of chronic pain. Similarly, the same concept can be applied to depression, aversive parenting styles along with childhood adversities over a sustained period of time can disrupt emotional development resulting in emotional dysregulation, such as alexithymia (42, 43) which predisposes to mental disorders such as depression (43). The World Mental Health Survey Initiative conducted by WHO demonstrated the risk for commonly diagnosed mental disorders, such as depression, was greatly increased by CAs and “maladaptive family functioning” (41). Furthermore, the increased risk for mental disorders was consistent across all age groups for all types of CAs. For example physical abuse significantly increased the risk of mental disorders in children, adolescents, young adults and adults (ORs 1.7-2.0, p<0.05) (41). Therefore it may be relevant to consider screening for CAs in young females with LBP to provide appropriate management plans that reduce the risk of chronicity for pain and depression (41).

CAs also predisposes to alexithymia[12] (42, 43) which is often associated with chronic pain (39, 44). A Finland study exhibited a correlation between the prevalence of alexithymia and pain status: no pain 4%, acute pain 6.6%, chronic pain 10.9% (39). Moreover, “difficulty identifying feelings” measured on the TAS-20[13] scale is significantly correlated with chronic pain in the general Japanese community (39). A study conducted in a health centre of United States also revealed alexithymic scores was significantly higher in adult females with intractable CLBP compared to controls (45). All these findings suggest difficulties with recognition of aversive emotions within oneself may lead to expression of these unrecognised emotions as somatic complaints such as pain (46). Therefore alexithymia may be a perpetuating factor for chronic pain.

The association between alexithymia and pain/depression may lead to greater disability among adults with chronic pain. A Finland study conducted in adults demonstrated the negative impact of alexithymia on pain intensity and disability was mediated by depression (44). This study also stated there was a moderate association between depression and specific components of alexithymia related to emotional regulation (difficulty identifying feelings: r=0.450, p≤0.01, difficulty describing feelings: r=0.464, p≤0.01). Most importantly, alexithymic score was also associated to with reduced life satisfaction[14] in Japanese adults with chronic pain (39). Given that alexithymia may reduce the quality of life in patients with chronic pain via its association with depression, poorer social support (47) and pain intensity, alexithymia is a promising target for intervention. A 6-month longitudinal study in adults demonstrated a decrease in the TAS-20 score is accompanied by a decrease in depression scores at follow up (48). The importance of emotional competence should not be under-estimated, as it is required for the identification and manipulation of unpleasant emotions to handle psychosocial challenges upon entering young adulthood (43). It is known that disruptions to emotional development and poor mental health (37) greatly contribute to pain conditions since pain perception consist of sensory, emotional and cognitive components (31). Therefore, alexithymia appears to be an intervention worth exploring in young females who are faced with many emotional challenges as they transition from adolescence to adulthood.

Sleep disturbance, chronic pain and depression

It is known that sleep disturbance[15] is more prevalent among adolescents and young adults with chronic pain (49, 50), and a significant mediator between pain intensity and disability (p≤0.01) (16). More specifically, a longitudinal study demonstrated adolescents with chronic pain reported poorer sleep quality[16] and a higher prevalence of insomnia symptoms compared to healthy adolescents, whereas total sleep time was comparable across both groups (49). Studies have shown sleep disturbance is a significant contributor to reduced quality of life (p<0.05) (2), number of healthcare visits (p=0.055) (2), fatigue (p<0.05) (51) and disability (p≤0.01) (16). Sleep quality is also associated with subjectively reported stress levels, general health and self-esteem (50). Beyond the variables addressed in the FAM, sleep is also an important contributor to greater disability and depression in adolescents with chronic pain, which will be discussed in more detail below.

Sleep disturbance negatively impacts on pain in young adults with chronic pain. A cross sectional study in young adults revealed a significant and robust correlation between the severity of pain and sleep quality after controlling for demographic and psychological factors (ß=0.26, p<0.01) (50), which is further supported by research in adults that have reported sleep deprivation reduces pain tolerance (52). At 3 year follow up of a longitudinal study in young adults, participants who experienced all 5 types of sleep disturbances on the NHS sleep scale had an increased risk of chronic pain (OR=3.8) and increased severity of musculoskeletal pain[17] (OR=1.3) compared to those with no sleep disturbances at baseline (19). Notably, this prognostic effect of sleep disturbance was stronger in females than males. However, this same study revealed chronic pain and musculoskeletal pain severity had no significant effect on sleep disturbance. Meanwhile, another longitudinal study in adolescents demonstrated chronic pain was the strongest predictor for sleep disturbance (coefficient=1.52, 95% CI [0.90, 0.21], p<0.001) compared to other factors[18] (2). This suggest there may be a bidirectional relationship between sleep and pain depending on the population studied, as Bonvanie et al was conducted in young adults from the community whereas Palermo et al was conducted in adolescents recruited from tertiary pain clinics.

Depression is known to be associated with sleep disturbance in adolescents and young adults with chronic pain. A cross sectional study by Graham et al reported an reciprocal association between depressive symptoms and sleep quality in young adults with chronic pain (r=0.39, p<0.001) (50). Similarly, another cross sectional study conducted in a 10-18yr old sample demonstrated insomnia also mediated the relationship between pain intensity and depression (p≤0.01) (16). These results appear to support the hypothesis that treatment of insomnia may have a beneficial impact on depression in adolescents with chronic pain.

Depression also impacts on sleep. A longitudinal study in adolescents demonstrated depressive symptoms are a significant risk factor for the persistence of insomnia over a 12month period (coefficient=0.05, p=0.031) (2). This is further supported by a study that reported depressive symptoms (ß=-0.32, p=0.07) and pre-sleep worry (ß=-0.43, p=0.02) were significant predictors for self-reported sleep quality (2). Although a longitudinal study conducted in adolescents revealed fatigue and not depressive symptoms mediated the predictive effect of sleep disturbance on chronic pain and musculoskeletal pain severity (19), another study revealed sleep disturbance mediated the effect of depression on fatigue (51). Therefore, sleep disturbance is not merely a symptom of depression, but also an important contributor to the association between pain and depression via fatigue.

Herein modifiable risk factors for insomnia could be potential targets for intervention. A study in young adults reported higher stress levels is significantly associated with reduced sleep quality (r=0.36, p<0.001) (50).Hence young females with LBP may be more at risk of reduced sleep quality, as a study reported greater stress levels are perceived by adolescents with chronic pain compared to healthy control (50), moreover, girls were 1.65 times more likely to report greater pressure and demands from school compared to boys (63.6% vs 38.5%) (6). Meanwhile pre-sleep arousal, such as racing thoughts are significantly associated with depressive symptoms (r=0.76, p<0.001) (49). On a background of increasing levels of psychological stress among young Australian females (1) this may lead to greater pre-sleep arousal, reduced sleep quality and predisposition or exacerbation of depressive symptoms. A longitudinal study in adolescents with chronic pain has also demonstrated depressive symptoms (coefficient=0.05, 95% CI [0.01, 0.10], p=0.031) and sleep hygiene (coefficient=-0.98, 95% CI [-1.62, -0.34], p=0.003) were both significant risk factors for the persistence of insomnia symptoms (2). Therefore, in addition to the treatment of depression, the impact of stress management strategies, such as meditation and sleep hygiene therapy are important interventions to explore in young females with LBP.

Sleep among young adults with chronic pain are more vulnerable to unhealthy lifestyle behaviours. A study in young college adults revealed health behaviours (alcohol, caffeine, exercise, typical diet, pain medication) are significant predictors of sleep quality among those with chronic pain only (∆R2=0.16, p<0.01) and not those with acute pain and no pain (50). Furthermore, despite similar alcohol consumptions across all three groups, alcohol was only predictive of sleep quality in the chronic pain group (ß=0.29, p<0.01). This is not surprising since a study has demonstrated sleep disturbance, pain and depression may be inter-related via the hypothalamic-pituitary-adrenal axis (53). Therefore, screening for perpetuating yet modifiable factors of insomnia could encourage the establishment of healthy lifestyle behaviours and potentially prevent the long term disability associated with insomnia.

Pattern of pain prescriptions among youth with chronic pain

Based on three studies it seems adolescents and young adults with chronic pain are more likely to be prescribed pain medications. Among young adults from the community, having chronic pain increases the likelihood of having taken prescribed analgesia and over the counter (OTC) herbal preparations (50). Meanwhile a longitudinal study revealed 75% of adolescents with chronic pain were prescribed ≥1 of anti-depressants, anti convulsants or opioids for pain control, whereas none of healthy controls had been prescribed any of the mediations above (p<0.001) (2). Another study in United States revealed the risk of receiving chronic opioid vs no opioid was dramatically increased by 2.4 times by pre-existing mental disorder diagnoses (OR=2.36, 95% CI [1.73, 3.23]) 13-24yrs olds with chronic pain (54). This study also reported MDD13 and anxiety disorders were the most prevalent mental disorders among chronic opioid receivers. Therefore, comorbidities commonly associated with chronic pain, namely, increased stress levels, mental disorders and sleep disturbance further increase the likelihood of receiving prescribed analgesia, which may lead to increased medication reliance/abuse and subsequent side effects in the long term. The long term consequences of prescribed analgesia among young females with LBP are yet to be explored in prospective longitudinal studies. However, based on these negative consequences associated with chronic medication use in adults (55-57), it may be worth exploring the effectiveness of psychological therapies, such as, stress management, pain acceptance and sleep therapy in young females with LBP, especially when higher stress levels and greater predictive effect of sleep disturbance on pain are more prevalent in young females.


In summary, LBP/chronic pain and depression are common comorbidities in the younger population associated with reduced quality of life (3). Current literature has demonstrated young females are more vulnerable to this comorbidity and its associated consequences on a background of declining mental wellbeing over the past 6 years (1). Evidence strongly suggest mental health and pain co-exist in a bidirectional relationship within a biopsychosocial matrix (53). The fear avoidance model has demonstrated how activity levels and psychological factors (pain catastrophizing, pain related fear) contribute to depression and disability in children and adolescents with chronic pain (23). Meanwhile pain acceptance, sense of control, social support and good family cohesion are protective against depression. Childhood adversities, alexithymia and sleep disturbance appear to act as predisposing and perpetuating factors for this comorbidity but prospective studies are required to validate this.

Young Australian females are still an under-researched group and there is a great need to conduct more longitudinal studies in this population to determine the risk factors associated with this comorbidity. It will also be interesting to conduct a cross sectional survey to gain a deeper understanding of how lifestyle and healthcare factors may influence their engagement with health services.

Word count: 5229

Table 2 Studies demonstrating an association between pain and depression

Association Study design  Inclusion criteria Sample  Measured variables Adjustment Aims 
Holley et al (10)


United States

Longitudinal with follow up at 6 and 12 months


No control group – chronic pain vs depression group

Chronic pain


  • Pain for ≥3month
  • Pain frequency for ≥3days/week
  • 12-18yrs old
  • Initial evaluation at pain clinic
  • Pain is unrelated to chronic disease


  • Diagnosis of MDD[19], dysthymia or depression NOS[20]
  • CES-D[21] cut off 16 for men and 20 for women
  • No history of schizophrenia, bipolar or psychosis
  • No serious chronic medical condition
  • No evidence of developmental disability
  • N=95 (chronic pain n=55, n=40 depression)
  • Clinical samples
  • Mean age 15.24yrs
  • 69% female
  • 7.3% had comorbid MDD and chronic pain


  • changes in pain intensity (NRS)[22]
  • changes in depressive symptoms (CES-D)


  • level of pain intensity (NRS)
  • level of depressive symptoms (CES-D)
  • Age
  • Gender
  • Race
  • Baseline pain intensity
  • Baseline depressive symptoms
Aim was to determine whether changes in pain intensity lead to changes in depressive symptoms and vice versa
Larsson et al (14)



1-year longitudinal study with two time points (baseline and follow up after 1 year)
  • Age range 12-15yrs
  • Attending one the 22 schools in two counties of Norway
  • Was able to participate in both baseline and follow up measures


  • N=2465
  • Mean age 13.7yrs
  • Females 50.8%
  • Non clinical sample recruited from 22 schools
  • 4.6% was lost with follow up[23]
  • Social factors (parental divorce, number of friends, school absence, leisure time)
  • Pain frequency
  • Duration of episode
  • Numbers of pain (headache, back, limb, stomach)
  • Stressors
  • Emotional and behavioural problems (YSR)
  • Depression (MFQ)[24]
  • Age
  • Sex
Examine the association between psychosocial factors and pain characteristics (number of pain, frequency, duration) other than pain type/location


Assess whether psychological factors are predictive of number of coexisting frequency pains at 1yr follow up

Beales et al (3)



Cross sectional
  • Age 17yrs old
  • Part of Raine study cohort
  • N=1391
  • Females 52.8%
  • Caucasian 93%
  • Self-reported medical conditions and health complaints
  • SF-36
  • Lifetime experience of LBP
  • LBP impact (medications, school or work absence/interference)
  • Sex
Explore the impact of common comorbidities on LBP in 17yr old adolescents


Results showed there was 4 distinct clusters with different SF-36 scores and LBP impacts

Korovessis et al (4)



Cross sectional


No control group

  • High school student with an age range 15-17yrs
  • Experienced non-specific LBP in the previous 6months
  • No known neurological disease
  • No previous spinal or pelvic surgery
  • N=350
  • General population (high school)
  • Mean age 16yrs
  • 51% females
  • LBP prevalence was 36% and 45% for boys and girls respectively
Pain variables


  • Pain intensity (VAS)[26]
  • Pain coping behaviour


  • Spinal curvatures
  • BMI
  • Athletic time
  • Daily walking time
  • Backpack weight
  • Method of carrying backpack
  • Daily backpack carrying duration


  • Stress
  • Depressed mood
  • Nervousness
  • Fatigue


  • Relationship with parents
  • Smoking
  • Screen time
  • Studying time
  • Leisure reading time
Gender Revealed gender differences in the biophysical and psychosocial factors associated with LBP in a non-clinical sample


Self-constructed questionnaire yet to be validated

Rees et al (20)



Cross sectional


Control group: no back or neck pain

Not provided
  • N=1580
  • Community sample
  • Mean age 14.1yrs
  • 49% female
Independent variable (YSR of CBCL[27])


  • Internalising (anxiety/depression, withdrawal, somatic complaints scales)
  • Externalising (rule breaking and aggressive behaviour)

Dependent variable

  • No back or neck pain in the last month
  • Neck pain only in the last month
  • Back pain only in the last month
  • Neck and back pain in the last month
Sex Revealed significant associations between internalising and externalising behaviours with back pain


Significantly higher correlation between withdrawn scale and back pain was found in the females compared to males

Hoftun et al (15)



Cross sectional
  • Age range 13-18yrs
  • Attending school
  • Participated in the HUNT[28] study
  • N=7373
  • Mean age 15.8yrs
  • Females 50.8%
  • Non clinical sample
Outcome measure: chronic pain ≥3months


  • Non specific
  • Multisite
  • Disabling

Exposure measure:

  • Physical activity (adopted from WHO[29])
  • Screen time
  • Smoking
  • Alcohol intoxication
  • BMI
  • Anxiety and depressive symptoms (SCL-5[30])
  • Age
  • SES
Aim was to explore the association between chronic pain, and lifestyle and psychological factors in a large cohort of adolescents from the community
Ruehlman et al (11)


United States

Cross sectional
  • Age range 17-24yrs
  • Enrolled in undergraduate introductory psychological classes
Part 1


  • N=2475
  • Mean age 18.9yrs
  • Female 53%
  • Non clinical sample

Part 2

  • N=275 chronic pain
  • Mean age 18.90yrs
  • Female 52%
  • 20% chronic back pain
  • PCP:S
  • PCP:EA
  • CES-D (depression)
Not mentioned Part 1


To validate the utility of PCP:S/EA as a screening tool for pain in young adults from the general population.

Part 2

To explore differences in pain attitudes and pain beliefs (using PCP:EA) in adolescents with chronic pain according to severity of depressive symptoms

Wiklund et al (6) Cross sectional
  • Age range 16-18yrs
  • Recruited from 3 different schools
  • N=1027
  • Female 60.7%
  • Non clinical
  • Subjective health complaints (16-item symptoms checklist)
  • HADS (Hospital Anxiety Depression Scale)
  • Perceived stress and sleep (Stress instrument)
  • General self-rated health
  • Medication
  Girls reported significantly higher amounts of somatic symptoms and poor mental health, which may be related to perceived stress from school

Table 3 Studies examination activity levels and biomechanical factors

Physical activity Study design  Inclusion criteria Sample  Measured variables Adjustment Aims 
Handrakis et al (13)


United States

Cross sectional


Control group: no or minimal LBP

  • Age range 18-30
  • No previous history of systemic disease, spinal surgery, spinal or pelvic fracture, hypertension, coronary artery disease or neuromuscular disease
  • Attending the New York Institute of Technology
  • N=84
  • Mean age 24.4yrs
  • 59.5% females
  • Community sample
Control variables


  • Pain intensity VAS
  • Oswestry Disability Index (ODI)

Subjective outcome measures

  • Baecke Physical Activity Questionnaire
  • DASS-21[31]

Objective outcome measures

  • Hamstring and hip flexor range of movement
  • Lower back extensor endurance
  • Abdominal strength and endurance
  • Spinal curvatures
No significance difference between groups for age, BMI, blood pressure and heart rate hence no adjustments were made To explore the difference between groups with LBP and no/minimal LBP in terms factors commonly associated with LBP and disability
Long et al (12)


United States

Cross sectional


Control group: healthy adolescents (n=20)

Chronic pain group (n=20)

  • Age range 12-18yrs
  • Attending MDT[32] pain clinic
  • Duration ≥3months
  • Frequency ≥3 days/week
  • At least of moderate pain intensity
  • No serious chronic medical conditions or developmental disabilities
  • N=40
  • Mean age 14.65 (controls), 15.05 (chronic pain)
  • 72.5% female
  • Clinical sample
  • 95% Caucasian
Self-reported measures


  • Pain intensity (11 NRS)
  • Activity limitations (CALI[33])
  • Depression (RCADS[34])

Physical activity (actigraphy over 7 days)

  • mean activity levels
  • peak activity levels
  • time spent in moderate and sedentary activity
No significance difference in age, gender, ethnicity between the two groups hence no adjustments were made Compare physical activity levels between adolescents with chronic pain and healthy adolescents


Investigate the relationship between actigraphy and subjective measures of activity limitation

Stommen et al (17)



Cross sectional case control


Control: healthy adolescents (n=42)

Non-specific MSK[35] pain (n=42)

  • Age range 12-21yrs
  • Duration ≥3months
  • Not diagnosed with specific somatic disorders
  • N=84
  • Mean age 17.1yrs (MSK pain), 16.6 (control)
  • Female 98% (MSK pain), 83% (control)
  • Clinical sample
  • Physical activity (SQUASH[36])
  • Disability (FDI)
  • Pain catastrophizing (PCS-C)
  • Pain intensity (VAS)
  • Depressive symptoms (CDI)
Not mentioned To compared physical activity levels between young adults with chronic pain and healthy participants

Table 4 Studies exploring the psychosocial variables associated with pain

Psychosocial Study design  Inclusion criteria Sample  Measured variables Adjustment



Simons et al (23)


United States

Cross sectional


No control group

  • Age range 8-17yrs
  • Attending MDT pain clinic
  • N=350
  • Mean age 13.7yrs
  • Females 80.6%
  • 14.1% back/neck pain
  • Pain duration 1-260months
  • Pain intensity (11 NRS)
  • Pain catastrophizing (PCS-C)
  • Pain related fear and avoidance (FOPQ-C)
  • Disability (FDI)
  • Depressive symptoms (CDI)
Duration of pain Aim was to validate the fear avoidance model (FAM) in the paediatric population
Hulsebusch et al (26)



Cross sectional
  • Age range 18-70yrs
  • First episode of thoracic or lumbar pain for <90days
  • No circumcised spinal diseases (neoplasm, fractures, herniated discs)
  • No comorbid psychiatric diagnosis (active psychosis, mania, acute suicidal risk, substance misuse)
  • N=164
  • Mean age ~40s
  • Females 50.6%
  • Clinical sample
  • Acute and subacute back pain (<90 days)
  • Depression (Beck Depression Inventory)
  • Pain intensity (11 NRS)
  • Pain catastrophizing (Kiel Pain Inventory)
  • Disability (Pain Disability Index)
Not mentioned Test the cognitive mediation hypothesis in a sample of participants with acute/subacute pain
Wallace et al (58)


United States

Cross sectional
  • Age range 10-19
  • Attended pain clinic
  • N=109
  • Mean age 15.2 yrs
  • 85% females
  • clinical sample
  • 58% back pain


  • Activity engagement
  • Pain willingness

Pain characteristics

  • Pain intensity 11 NRS
  • Pain duration
  • Pain frequency


  • Functional disability inventory


  • CED-S


Pain self-efficacy

Not mentioned Validate the CPAQ-A in adolescents with chronic pain
Weiss et al (30)


United States

Cross sectional


No control group

  • Age range 11-18yrs
  • Attended pain clinic
  • Able to attend a 3-week outpatient rehab program
  • had to be struggling with chronic pain (≥3months)
  • medical work up was complete
  • chronic pain was interfering with functioning
  • completed CPAQ-A
  • N=112
  • Mean age 15.47
  • 76% female
  • Clinical sample
  • 8% back pain
  • pain duration 3-144 months
  • CPAQ-A
  • CES-D (cut off 26)
  • PCS-C
  • FDI
  • Age
  • Pain intensity
Examine the impact of changes in pain acceptance on pain catastrophizing, depression and disability
Forgeron et al (59)



Cross sectional


Control group: healthy adolescents (n=62)

Chronic pain group (n=45)

  • Age range 13-18yrs
  • Attended pain clinic
  • Experiencing significant pain during treatment
  • No cognitive impairment
  • No chronic illness including recurrent pain for the healthy adolescents
  • N=107
  • Mean age 15.40yrs (chronic pain), 14.96yrs (control)
  • 79% female
  • Clinical samples recruited across 3 different hospitals
  • back pain (n=1)
  • Social information processing (SIP) – Vignette questionnaire
  • Pain intensity
  • Pain frequency
  • Pain location
  • Social disability (PedMIDAS[39])
  • Social anxiety (SAS-A)
  • Loneliness scale
  • Rosenberg self-esteem scale
  • Depression CES-D
  • Age
  • Sex
  • Depression
  • Loneliness
  • Social anxiety
  • Self-esteem
Compare social information processing between adolescents with and without chronic pain
Eccleston et al (35)


United Kingdom

Cross sectional


No control group

  • Age range 11-18yrs
  • Attending MDT pain clinic
  • Chronic pain ≥3months
  • N=110
  • Mean age 15.1yrs
  • 72.7% female
  • Clinical samples
  • LBP 6.4%
  • Pain intensity (VAS)
  • Disability (FDI)
  • Depression (CDI-S)
  • Anxiety (SCAS)
  • Social function (CASAFS[40])
  • Family function (CASAFS)
  • BATH adolescent pain questionnaire (developmental subscale)
  • Age
  • Gender
  • Pain intensity
  • Pain duration
Aim is to compared subjective views of social development among adolescents with and without chronic pain
Saariaho et al (44)



Cross sectional


Control: non alexithymic

  • Age range 18-64
  • First visit to one of the 6 pain clinics
  • Suffering from daily chronic pain for ≥3months
  • No psychotic disorders
  • No malignant disease
  • N=271
  • Mean age 47.4yrs
  • Female 53.1%
  • Clinical sample
  • Pain location
  • Pain duration
  • Pain intensity (VAS)
  • Pain disability (PDI)
  • Depression (BDI-II)
  • Alexithymia (TAS-20)
 Not mentioned Aim was to examine differences in pain disability and depression in chronic pain patients with and without alexithymia
Shibata et al (39)



Cross sectional


Control group: no pain

Acute pain group

Chronic pain group

  • Part of the Hisayama Study
  • Age range >40yrs
  • Chronic pain ≥6months
  • Acute pain <6months
  • N=927
  • Mean age 61yrs
  • Female 64.8%
  • Japanese community
  • LBP 30.1%
  • Alexithymia (TAS-20)
  • Pain intensity (VAS)
  • Disability (VAS)
  • Negative affect (SCL-90 R)
  • Life satisfaction (VAS)
Demographic variables


  • Age
  • Sex
  • Marital status
  • Educational level
  • SES
Aim was to evaluate the association of alexithymia with pain intensity, disability, distress and life satisfaction in a non-clinical sample
Stickley et al (40)



Cross sectional
  • Participated in the World Mental Health Survey, Japan (age ≥20yrs)
  • N=1740
  • Mean age 51.2yrs
  • Female
  • Non-clinical sample
  • Chronic back/neck problems 25.7%
  • Face to face interviews
  • Childhood adversities <18yrs
  • Chronic pain condition >21yrs
  • Current age
  • Sex
  • Education level
  • Early mental disorders
  • Number of CAs
Investigate the association between childhood adversities (CAs) and chronic pain
Scott et al (37)


United States

Multinational cross sectional survey involving 10 countries
  • ≥18yrs of age
  • N=18 303
  • Non clinical sample
Face to face interviews


  • Anxiety and mood disorders (DSM-IV)
  • Childhood family adversities
  • Chronic physical conditions including chronic spinal pain (back/neck)
  • Current age
  • Sex
  • Country
  • Current mental health disorder
  • Non response
  • Differential sampling
Examine the association between chronic physical conditions, and childhood adversities and early onset mental health disorders <21yrs) independently in a diverse population

Table 5 Studies examining the association of sleep disturbance with pain and depression

Sleep Study design  Inclusion criteria Sample  Measured variables Adjustment Aims 
Kanstrup et al (16)



Cross sectional


No control group

  • Age range 10-18yrs
  • Referred to clinic due to long-standing and/or recurrent pain
  • Pain duration of ≥3months
  • N=154
  • Mean age 14.6yrs
  • Female 75.3%
  • Clinical sample
  • Insomnia Severity Index (ISI)
  • Pain intensity (11 NRS)
  • Depression (CES-DC)
  • Disability (FDI)
  • Age
  • Sex
  • Pain duration
Investigate the association between sleep, pain and depression
Graham et al


United States

Cross sectional


Control group

Chronic pain group ≥3-6 months

  • College student ≥18yrs
  • Completed online survey
  • N=362
  • Mean age 20.58yrs
  • Female 73.2%
  • 81.8% white
  • Non clinical sample
Biological factors


  • Pittsburgh Sleep Quality Index (PSQI)
  • BMI
  • Pain severity scale

Psychosocial factors

  • Depression (CES-D)
  • Perceived Stress Scale (PSS)
  • State of Self Esteem Scale (SSES)
  • General health (SF-36)

Behavioural factors

  • Diet (4 rating scale)
  • Exercise
  • Caffeine intake
  • Alcohol intake
  • CAM[41] for pain
  • Sex
  • BMI
  • SES
Explore the bio-behavioural factors influencing sleep in young adults with chronic pain
Palermo et al (2007) (49)


United States

Cross sectional


Control group (n=20)

Controls were sex and age matched within 6months

Chronic pain (n=20)

  • Age range 12-18yrs
  • Currently receiving care from chronic pain clinic
  • Pain ≥3months
  • Pain frequency ≥3days a week of moderate intensity (≥5/10)
  • Pain not related to chronic disease
  • No diagnosis of developmental disabilities
  • N=40
  • Mean age
  • Female 72.5%
  • Clinical sample
  • Sleep patterns (actigraphy over 7days)
  • Sleep quality (ASWS)
  • Insomnia symptoms (ASWS)
  • Sleep hygiene (ASHS)
  • Arousal and worry at bedtime (PSAS)
  • Depressive symptoms (RCADS)
  • Pain perception (location, frequency, intensity)
Not mentioned Compare sleep among adolescents with and without chronic pain using objective and subjective measures
Palermo et al (2012) (2)


United States

1-year Longitudinal study


Control group (n=61): no serious chronic illness

Chronic pain group (n=60)

  • Age range 12-18yrs
  • Pain ≥3months
  • Pain ≥3days per week
  • Pain intensity ≥midpoint on VAS
  • No known diagnosis of developmental disability
  • N=121
  • Mean age 15yrs
  • Females 72%
  • Caucasian 83%
  • Clinical sample recruited from MDT pain clinic
  • Adolescent Sleep Wake Scale (ASWS)
  • Adolescent Sleep Hygiene Scale (ASHS)
  • Pre Sleep Arousal Scale (PSAS)
  • Pain intensity (11 NRS)
  • Depression (CES-D)
  • Pubertal Developmental Scale
  • Child Activity Limitations Interview (CALI-21)
  • Health related QOL (PedsQL)
  • Healthcare utilisation
  • Age
  • Sex
  • Race
  • Income
Assess differences in insomnia symptoms and risk factors for insomnia among adolescents with and without chronic pain
Bonvanie et al (19)



3-year Longitudinal study


Cross sectional (baseline)


  • MSK pain (legs, arm, back, neck, shoulders)
  • Headache/migraine
  • Abdominal pain
  • Age group 18-25yrs
  • Part of Tracking Adolescents’ Individual Lives Survey (TRAILS), a Dutch Population based cohort
  • No mental or physical handicap preventing participation


  • N=1688
  • Mean age 19yrs

Follow up

  • N=1501
  • Mean age 22.3yrs

Non clinical sample

  • Sleep scale of Nottingham Health Profile
  • Pain duration ≥3months
  • Pain frequency
  • Pain severity
  • Pain interference
  • Pain medication
  • Anxiety/depression (ASR[42])
  • Fatigue (ASR)
  • Physical inactivity
  • Sex
  • Baseline pain and sleep disturbance for longitudinal analysis
Explore the factors that mediate the relationship between pain and sleep disturbance
Tham et al (51)


United States

1-year Longitudinal study


Control group (n=60)

Chronic pain group (n=61)

Depressive group (n=51)



  • Age range 12-18yrs
  • No developmental delay, comorbid medical conditions, psychosis or active suicidal ideation
  • Able to ambulate independently

Chronic pain

  • Pain unrelated to chronic disease
  • Pain present for ≥3days a week for ≥3months
  • Clinical sample from MDT pain clinic

Depressive group

  • Dx of MDD, dysthymia, depression based on K-SADS
  • CES-D score ≥16 for males, ≥20 for females
  • Clinical sample

Healthy group

  • Absence of current chronic pain
  • Absence of comorbid medical conditions
  • Did not meet the criteria for depressive disorder on the K-SADS
  • Community
  • N=172
  • Mean age 15.1yrs
  • Female 68%
  • Caucasian 82.4%
  • Clinical sample
  • LBP 31.1%
  • Pain intensity (NRS)
  • Fatigue (PedsQL-MFS)
  • Sleep quality (ASWS)
  • Pre Sleep Arousal Scale
  • Depression (CES-D)
Not mentioned Investigate what contributes to fatigue in chronic pain adolescents

Figure 2 Source: AIHW analysis of ABS Microdata: National Health Survey, 2014–15


Figure 3 Prevalence of mental disorders across age groups

Taken from Australian Bureau of Statistics webpage


Figure 4 Original version of fear avoidance model

Ownership Vlaeyen & Linton 2000 (25)

Taken from Simons et al 2012 (23)


Figure 5 Modified Fear avoidance model predicting depression in paediatric population

Taken from Simons et al 2012 (23)


Figure 6 Fear avoidance model predicting disability in paediatric population

Taken from Simons et al 2012 (23)

Figure 7 Psychological factors impacting the Fear Avoidance Model  (reproduced from Vlaeyen & Linton, 2000)(25)

Coloured boxes are author’s addition whereby red represents a risk factor, green is a protective factor, blue are consequences


1. National Health Survey: First Results, 2014-15 Canberra Australian Bureau of Statistics; 2015 [updated 22/03/2016. Available from: http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by Subject/4364.0.55.001~2014-15~Main Features~Psychological distress~16.

2. Palermo TM, Law E, Churchill SS, Walker A. Longitudinal course and impact of insomnia symptoms in adolescents with and without chronic pain. The journal of pain : official journal of the American Pain Society. 2012;13(11):1099-106.

3. Beales DJ, Smith AJ, O’Sullivan PB, Straker LM. Low back pain and comorbidity clusters at 17 years of age: a cross-sectional examination of health-related quality of life and specific low back pain impacts. The Journal Of Adolescent Health: Official Publication Of The Society For Adolescent Medicine. 2012;50(5):509-16.

4. Korovessis P, Repantis T, Baikousis A. Factors affecting low back pain in adolescents. Journal of spinal disorders & techniques. 2010;23(8):513-20.

5. Taloyan M, Lofvander M. Depression and gender differences among younger immigrant patients on sick leave due to chronic back pain: a primary care study. Primary health care research & development. 2014;15(1):5-14.

6. Wiklund M, Malmgren-Olsson E-B, Öhman A, Bergström E, Fjellman-Wiklund A. Subjective health complaints in older adolescents are related to perceived stress, anxiety and gender–a cross-sectional school study in Northern Sweden. BMC public health. 2012;12(1):993.

7. Who gets back problems? : Australian Institute of Health and Welfare; 2016 [Available from: http://www.aihw.gov.au/back-problems/prevalence/.

8. Brattberg G. Do pain problems in young school children persist into early adulthood? A 13-year follow-up. European journal of pain (London, England). 2004;8(3):187-99.

9. Back pain and problems: Australian Institute of Health and Welfare 2016 [Available from: http://www.aihw.gov.au/back-problems/.

10. Holley A, Law E, Zhou C, Murphy L, Clarke G, Palermo T. Reciprocal longitudinal associations between pain and depressive symptoms in adolescents. European Journal of Pain. 2013;17(7):1058-67.

11. Ruehlman LS, Karoly P, Pugliese J. Psychosocial correlates of chronic pain and depression in young adults: further evidence of the utility of the Profile of Chronic Pain: Screen (PCP: S) and the Profile of Chronic Pain: Extended Assessment (PCP: EA) battery. Pain medicine (Malden, Mass). 2010;11(10):1546-53.

12. Long AC, Palermo TM, Manees AM. Brief report: using actigraphy to compare physical activity levels in adolescents with chronic pain and healthy adolescents. Journal of pediatric psychology. 2008;33(6):660-5.

13. Handrakis JP, Friel K, Hoeffner F, Akinkunle O, Genova V, Isakov E, et al. Key Characteristics of Low Back Pain and Disability in College-Aged Adults: A Pilot Study. Archives of Physical Medicine & Rehabilitation. 2012;93(7):1217-24.

14. Larsson B, Sund AM. Emotional/behavioural, social correlates and one-year predictors of frequent pains among early adolescents: Influences of pain characteristics. European Journal of Pain. 2007;11:57-65.

15. Hoftun GB, Romundstad PR, Rygg M. Factors associated with adolescent chronic non-specific pain, chronic multisite pain, and chronic pain with high disability: the Young-HUNT Study 2008. The journal of pain : official journal of the American Pain Society. 2012;13(9):874-83.

16. Kanstrup M, Holmstrom L, Ringstrom R, Wicksell RK. Insomnia in paediatric chronic pain and its impact on depression and functional disability. European journal of pain (London, England). 2014;18(8):1094-102.

17. Stommen NC, Verbunt JA, Gorter SL, Goossens ME. Physical activity and disability among adolescents and young adults with non-specific musculoskeletal pain. Disability and rehabilitation. 2012;34(17):1438-43.

18. Stommen NC, Verbunt JA, Goossens ME. Future goals of adolescents and young adults with chronic musculoskeletal pain. European journal of pain (London, England). 2016;20(4):564-72.

19. Bonvanie IJ, Oldehinkel AJ, Rosmalen JG, Janssens KA. Sleep problems and pain: a longitudinal cohort study in emerging adults. Pain. 2016;157(4):957-63.

20. Rees CS, Smith AJ, O’Sullivan PB, Kendall GE, Straker LM. Back and neck pain are related to mental health problems in adolescence. BMC public health. 2011;11:382.

21. Statistics ABo. Mental Health Canberra2013 [Available from: http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/4125.0main+features3150Jan 2013.

22. Simons LE, Elman I, Borsook D. Psychological processing in chronic pain: a neural systems approach. Neuroscience & Biobehavioral Reviews. 2014;39:61-78.

23. Simons LE, Kaczynski KJ. The Fear Avoidance model of chronic pain: examination for pediatric application. The journal of pain : official journal of the American Pain Society. 2012;13(9):827-35.

24. Dr Michael Nicholas DAM, Lois Tonkin, Lee Beeston. Manage your pain. 3rd ed. Australia Harper Collins Publishers; 2011. 256 p.

25. Vlaeyen JWS, Linton SJ. Fear-avoidance and its consequences in chronic musculoskeletal pain: a state of the art. Pain. 2000;85(3):317-32.

26. Hulsebusch J, Hasenbring MI, Rusu AC. Understanding pain and depression in back pain: The role of catastrophizing, help-/hopelessness, and thought suppression as potential mediators. International journal of behavioral medicine. 2016;23(3):251-9.

27. Hayes SC, Luoma JB, Bond FW, Masuda A, Lillis J. Acceptance and commitment therapy: model, processes and outcomes. Behaviour research and therapy. 2006(1):1.

28. McCracken LM, Gauntlett‐Gilbert J, Eccleston C. Acceptance of pain in adolescents with chronic pain: Validation of an adapted assessment instrument and preliminary correlation analyses. European Journal of Pain. 2010;14(3):316-20.

29. Wicksell RK, Olsson GL, Hayes SC. Mediators of change in Acceptance and Commitment Therapy for pediatric chronic pain. Pain. 2011;152:2792-801.

30. Weiss KE, Hahn A, Wallace DP, Biggs B, Bruce BK, Harrison TE. Acceptance of pain: associations with depression, catastrophizing, and functional disability among children and adolescents in an interdisciplinary chronic pain rehabilitation program. Journal of pediatric psychology. 2013;38(7):756-65.

31. Serge M, Djéa S, Isabelle G. Mental health and Pain: Somatic and Psychiatric Components of Pain in Mental Health Paris Springer; 2014. 307 p.

32. Sullivan MJL, Bishop SR, Pivik J. The Pain Catastrophizing Scale: Development and validation. Psychological Assessment. 1995;7(4):524-32.

33. Macedo RB, Coelho-e-Silva MJ, Sousa NF, Valente-dos-Santos J, Machado-Rodrigues AM, Cumming SP, et al. Quality of life, school backpack weight, and nonspecific low back pain in children and adolescents. Jornal de pediatria. 2015;91(3):263-9.

34. Vowles KE, Jordan A, Eccleston C. Toward a taxonomy of adolescents with chronic pain: exploratory cluster and discriminant analyses of the bath adolescent pain questionnaire. European journal of pain (London, England). 2010;14(2):214-21.

35. Eccleston C, Wastell S, Crombez G, Jordan A. Adolescent social development and chronic pain. European journal of pain (London, England). 2008;12(6):765-74.

36. Simons LE, Smith A, Ibagon C, Coakley R, Logan DE, Schechter N, et al. Pediatric Pain Screening Tool: rapid identification of risk in youth with pain complaints. Pain. 2015;156(8):1511-8.

37. Scott KM, Korff MV, Angermeyer MC, Benjet C, Bruffaerts R, de Girolamo G, et al. Association of childhood adversities and early-onset mental disorders with adult-onset chronic physical conditions. Archives of General Psychiatry. 2011(7):838.

38. Goldberg RT, Pachas WN, Keith D. Relationship between traumatic events in childhood and chronic pain. Disability and rehabilitation. 1999;21(1):23-30.

39. Shibata M, Ninomiya T, Jensen MP, Anno K, Yonemoto K, Makino S, et al. Alexithymia is associated with greater risk of chronic pain and negative affect and with lower life satisfaction in a general population: the Hisayama Study. PloS one. 2014;9(3):e90984.

40. Stickley A, Koyanagi A, Kawakami N. Childhood adversities and adult-onset chronic pain: Results from the World Mental Health Survey, Japan. European journal of pain (London, England). 2015;19(10):1418-27.

41. Kessler RC, McLaughlin KA, Green JG, Gruber MJ, Sampson NA, Zaslavsky AM, et al. Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. The British Journal Of Psychiatry: The Journal Of Mental Science. 2010;197(5):378-85.

42. Kooiman CG, van Rees Vellinga S, Spinhoven P, Draijer N, Trijsburg RW, Rooijmans HGM. Childhood adversities as risk factors for alexithymia and other aspects of affect dysregulation in adulthood. Psychotherapy and psychosomatics. 2004;73(2):107-16.

43. Goleman D. Emotional Intelligence. London: Bloomsbury; 1996. 352 p.

44. Saariaho AS, Saariaho TH, Mattila AK, Karukivi MR, Joukamaa MI. Alexithymia and depression in a chronic pain patient sample. General hospital psychiatry. 2013;35(3):239-45.

45. Pecukonis EV. Physical self-efficacy and alexithymia in women with chronic intractable back pain. Pain Management Nursing: Official Journal Of The American Society Of Pain Management Nurses. 2009;10(3):116-23.

46. Association AP. Diagnostic and statistical manual of mental disorders: DSM-5 / American Psychiatric Association, task force chair David J. Kupfer. 5th ed2013. 947 p.

47. Zeng F, Sun X, Yang B, Fu X. Life events, anxiety, social support, personality, and alexithymia in female patients with chronic pain: A path analysis. Asia-Pacific psychiatry : official journal of the Pacific Rim College of Psychiatrists. 2016;8(1):44-50.

48. Honkalampi K, Hintikka J, Saarinen P, Lehtonen J, Viinamäki H. Is alexithymia a permanent feature in depressed patients? Results from a 6-month follow-up study. Psychotherapy and psychosomatics. 2000;69(6):303-8.

49. Palermo TM, Toliver-Sokol M, Fonareva I, Koh JL. Objective and subjective assessment of sleep in adolescents with chronic pain compared to healthy adolescents. The Clinical journal of pain. 2007;23(9):812-20.

50. Graham JE, Streitel KL. Sleep quality and acute pain severity among young adults with and without chronic pain: the role of biobehavioral factors. Journal of behavioral medicine. 2010;33(5):335-45.

51. Tham SW, Holley AL, Zhou C, Clarke GN, Palermo TM. Longitudinal course and risk factors for fatigue in adolescents: the mediating role of sleep disturbances. Journal of pediatric psychology. 2013;38(10):1070-80.

52. Lautenbacher S, Kundermann B, Krieg J-C. Sleep deprivation and pain perception. Sleep Medicine Reviews. 2006;10(5):357-69.

53. Gatchel RJ, Peng YB, Peters ML, Fuchs PN, Turk DC. The Biopsychosocial Approach to Chronic Pain: Scientific Advances and Future Directions. Psychological Bulletin. 2007;133(4):581-624.

54. Richardson LP, Russo JE, Katon W, McCarty CA, DeVries A, Edlund MJ, et al. Mental health disorders and long-term opioid use among adolescents and young adults with chronic pain. The Journal of adolescent health : official publication of the Society for Adolescent Medicine. 2012;50(6):553-8.

55. Moore JT, Kelz MB. Opiates, Sleep, and PainThe Adenosinergic Link. The Journal of the American Society of Anesthesiologists. 2009;111(6):1175-6.

56. Morasco BJ, O’Hearn D, Turk DC, Dobscha SK. Associations Between Prescription Opioid Use and Sleep Impairment among Veterans with Chronic Pain. Pain Medicine. 2014;15(11):1902-10.

57. Robertson J, Purple R, Cole P, Zaiwalla Z, Wulff K, Pattinson K. Sleep disturbance in patients taking opioid medication for chronic back pain. Anaesthesia. 2016;71(11):1296-307.

58. Wallace DP, Harbeck-Weber C, Whiteside SP, Harrison TE. Adolescent acceptance of pain: confirmatory factor analysis and further validation of the chronic pain acceptance questionnaire, adolescent version. The journal of pain : official journal of the American Pain Society. 2011;12(5):591-9.

59. Forgeron PA, McGrath P, Stevens B, Evans J, Dick B, Finley GA, et al. Social information processing in adolescents with chronic pain: my friends don’t really understand me. Pain. 2011;152(12):2773-80.


[1] LBP is defined as pain in the lower back region, pain into the buttock region and/or pain radiating down the back of the leg

[2] Disability is used in the review encompasses both activity limitations and participation restriction with regards to school, home, social life, leisure activities (WHO)

[3] Chronic pain is defined as any pain regardless of site that is persisting beyond 3-6months. Some studies have used 3 months as the cut off for chronic pain, while others have used 6 months

[4] MOR Multimodal Odds Ratio

[5] Disability is used in the review encompasses both activity limitations and participation restriction due to pain in physical (daily activities, exercise) and social (school, work, leisure) domains of life

[6] Pain severity includes pain intensity and pain frequency

[7] Catastrophizing is currently defined as: “an exaggerated negative mental set brought to bear during actual or anticipated painful experience” (Sullivan et al., 2001)

[8] pain severity in this review will refer to pain intensity and frequency

[9] “Social desirability” may lead to under reporting of psychological distress among the children and adolescents, because children and adolescents tend to down-play their psychological symptoms as it is seen as a more favourable response by others (Logan et al 2008)

[10] The Pain Catastrophizing Scale assesses three components of catastrophizing, namely, rumination (“I can’t stop thinking about how much it hurts”), magnification (“I worry that something serious may happen”), and helplessness (“It’s awful and I feel that it overwhelms me”) – Sullivan et al 1995

[11] PCP:EA Profile of Chronic Pain: Extended Assessment contains 13 multi-item subscales addressing aspects of coping, positive and negative social responses, catastrophizing, and pain attitudes and beliefs (Ruehlman et al)

[12] Alexithymia is characterised by “difficulties in identifying and describing feelings, externally oriented thinking, and lack of imagination and fantasies” (Saariaho et al)

[13] TAS-20 Toronto Alexithymia Scale contains 3 subscales “difficulty identifying feelings”, “difficulty describing feelings” and “externally orientated thinking” (Shibata et al)

[14] Life satisfaction was assessed with a 100mm VAS rather than a valid questionnaire

[15] Sleep disturbance is the presence of insomnia symptoms and/or reduced sleep quality

[16] Sleep quality: includes “subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction”

[17] Musculoskeletal pain includes back, neck, shoulder, arms, legs

[18] pubertal development, depressive symptoms, sleep hygiene, cognitive and somatic pre sleep arousal, and pain intensity

[19] MDD Major depressive disorder

[20] NOS Not otherwise specified

[21] CES-D Centre for Epidemiologic Studies Depression Scale

[22] NRS Numerical Rating Scale

[23] Non-participants at T2 were characterised by having higher levels of depressive symptom level and more often had a non-Norwegian background

[24] MFQ Moods and Feelings Questionnaire

[25] SES socioeconomic status

[26] VAS visual analogue scale

[27] CBCL Child Behaviour Checklist

[28] HUNT The Nord-Trondelag Health Study

[29] WHO World Health Organisation

[30] SCL-5 5-item version of Symptom Checklist

[31] DASS-21 Depression, Anxiety and Stress Scale

[32] MDT Multidisciplinary Team

[33] CALI Child Activity Limitations Interview

[34] RCADS Revised Child Anxiety and Depression Scale

[35] MSK Musculoskeletal

[36] SQUASH Short Questionnaire to Assess Health-enhancing physical activity

[37] SCAS Spence Children’s Anxiety scale

[38] CSES Children’s self-efficacy scale

[39] PedMIDAS Paediatric Migraine Disability Assessment Scale

[40] CASAFS Child and Adolescent Social and Adaptive Functioning Scale

[41] CAM Complimentary Alternative Medicine

[42] ASR Adult Self Report (Anxious/Depressed scale)

Cite This Work

To export a reference to this article please select a referencing stye below:

Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.

Related Services

View all

Related Content

All Tags

Content relating to: "Medicine"

The area of Medicine focuses on the healing of patients, including diagnosing and treating them, as well as the prevention of disease. Medicine is an essential science, looking to combat health issues and improve overall well-being.

Related Articles

DMCA / Removal Request

If you are the original writer of this literature review and no longer wish to have your work published on the UKDiss.com website then please: