J Behav Med https://doi.org/10.1007/s10865-018-9918-7
BRIEF REPORT
Temporal relationship between daily pain and actigraphy sleep patterns in pediatric sickle cell disease Karin Fisher1 • Andrea M. Laikin2 • Katianne M. Howard Sharp3 Catherine A. Criddle2 • Tonya M. Palermo4 • Cynthia W. Karlson2
•
Received: September 6, 2017 / Accepted: March 6, 2018 Ó Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract Limited research is available on the relationship between objective sleep patterns and pain in children with SCD. Research in other chronic pain populations suggests that the effect of sleep disruption on pain may be stronger than the effect of pain on sleep that night. To examine the bi-directional relationship between objective sleep patterns and daily pain in a pediatric SCD sample. Participants were 30 African American children with SCD 8–18 years (13 ± 2.8 years; 66.7% female) with frequent pain. Children and parents completed questionnaires to assess pain, medications, and depression/anxiety. Over a 14-day period, children completed a pain diary and ambulatory actigraphy monitoring to assess nighttime sleep (duration, efficiency and WASO). Greater pain severity was associated with worse sleep efficiency and greater WASO that night, controlling for age, sex, opioid medication, and depression/ anxiety symptoms. Worse sleep efficiency was associated with the occurrence of pain and more severe pain the next day. There was no relationship between WASO and pain. Similarly, sleep duration did not influence pain. Results lend support for a bi-directional relationship between sleep parameters and daily pain in pediatric SCD, and identify
& Karin Fisher
[email protected] 1
University of Southern Mississippi, 118 College Drive, Box 5025, Hattiesburg, MS 39406, USA
2
Department of Pediatrics, Hematology/Oncology, University of Mississippi Medical Center, Jackson 39216 MS, USA
3
The Research Institute, Nationwide Children’s Hospital, Columbus 43205 OH, USA
4
Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle 98195 WA, USA
sleep as a potential target for future research and intervention. Keywords Children Adolescents Persistent pain Sleep Actigraphy Sickle cell disease
Introduction Pain is a hallmark symptom that occurs frequently in youth with sickle cell disease (SCD), often associated with psychosocial and physical impairment (Barakat et al., 2006). Applying a biobehavioral framework, both biological factors (e.g., profound hemolytic anemia, systemic inflammation) and behavioral factors (e.g., depression, anxiety and sleep disruption) may contribute to pain in SCD (Ameringer & Smith, 2011). Sleep disruption is also commonly endorsed by children diagnosed with SCD (Daniel et al., 2010), with youth reporting more severe pain also tending to report shorter sleep duration (Jacob et al., 2013). Lewin and Dahl (1999) postulated multiple links between sleep disruptions, increased pain, lower ability to cope with ache, anxiety, prolonged tissue healing, and perception of pain, with research in other pediatric chronic pain populations empirically supporting such a bi-directional relationship between sleep disruption and pain (Palermo & Kiska, 2005; Palermo et al., 2007; Rabbitts et al., 2014). Furthermore, experimental studies indicate that sleep disruptions are associated with increased pain sensitivity and impair individuals’ ability to efficiently modulate pain (for review see Finan et al., 2013). Thus, theoretical and empirical justification identifies sleep interventions as an important component of pediatric pain management (Lewin & Dahl, 1999). However, research in pediatric SCD is limited and previous studies examining
123
J Behav Med
the relation between pain and sleep in youth with SCD have relied exclusively on retrospective sleep questionnaires (Barakat et al., 2006; Daniel et al., 2010) or subjective sleep diaries to assess sleep parameters (Jacob et al., 2013; Valrie et al., 2007, 2008; Moscou-Jackson et al., 2015). One daily diary study to date has examined self-reported sleep and pain in 20 youth with SCD (Valrie et al., 2008). Youth completed daily diaries for 8 weeks and rated their sleep quality and average pain severity on a visual analogue scale (VAS), as well as their daily mood on the facial affective scale (FAS). Findings suggest that increased daily pain severity was associated with poorer subjective sleep quality that night, whereas poorer sleep quality was associated with increased pain severity the next day (Valrie et al., 2008). Research in pediatric SCD suggests that pain, sleep disruption and depression commonly co-occur and are interrelated (Palermo & Kiska, 2005). In the above described daily diary study, negative mood partially mediated the relationship between daytime pain and nighttime sleep disruption in youth with SCD (Valrie et al., 2008). Similarly, a retrospective questionnaire study in 86 adolescents with SCD and other chronic pain conditions found that symptoms of depression were associated with more severe sleep disturbance, and sleep disturbance was associated with both mood disturbance and reductions in daily functioning and quality of life (Palermo & Kiska, 2005). Negative mood is thus an important factor to measure and control for when examining the relationship between sleep and pain in youth with SCD. Although prior research suggests that sleep may be important to the experience of pain in SCD, subjective reports of sleep are not sufficient to capture accurate sleep parameters including wake time after sleep onset (WASO) or total sleep time (Tremaine et al., 2010), and are subject to cognitive biases and retrospective reporting errors (Tremaine et al., 2010; Alfano et al., 2015). Moreover, the sleep parameters measured by self-report tools and actigraphy are not clearly overlapping and are seen as providing complementary information (Tremaine et al., 2010; Alfano et al., 2015). Wrist-worn actigraphy represents a convenient method to capture objective sleep patterns in the home setting, is reliable for assessing sleep, and has been validated in studies with healthy adolescents and youth with chronic pain (Palermo et al., 2007). Actigraphy also provides reliable ecological assessment of sleep and behavioral sleep data over multiple days (Tremaine et al., 2010). To fill these gaps in the literature, the primary aim of this study was to examine the potential bi-directional relationship between objective nighttime sleep parameters and daily pain in youth with SCD who experienced frequent pain. Given the relation between negative mood and
123
pain, we controlled for negative mood to examine the unique contribution of objective nighttime sleep on daily reported pain, above the contribution of negative mood on pain (Palermo & Kiska, 2005; Valrie et al., 2008; Chorpita et al., 2000). We hypothesized that, controlling for negative mood: (1) the occurrence of daytime pain and more severe pain will be associated with worse objective nighttime sleep efficiency, shorter nighttime sleep duration, and greater wake after sleep onset (WASO) during that night, and (2) worse nighttime sleep parameters would be associated with the occurrence of pain and more severe pain the next day.
Methods Participants The study was approved by the Institutional Review Board. Parents provided consent and youth provided assent for study procedures. Youth were recruited at a tertiary care pediatric hematology clinic. Inclusion criteria were (a) 8–18 years of age, (b) SCD types hemoglobin SS, SC, Sb + thalassemia, or Sb0 Thalassemia, and (c) pain occurring at least once every 2 weeks (in order to provide adequate variability in daily pain and adequate occurrences of pain for statistical analyses) (Kashikar-Zuck et al., 2010; Tabachnick & Fidell, 2007). Exclusion criteria included significant developmental delay or cognitive impairment. Participation rate One hundred twenty-six African American children with SCD between the ages of 8 and 18 were screened for eligibility. Reasons for non-enrollment included: infrequent pain (n = 86), not interested (n = 1), parent not present (n = 1), child with cognitive impairment (n = 1), and medical non-compliance (n = 1). Thirty-six participants were enrolled but six participants were excluded from data analyses due to greater than 50% missing data. The final 30 participants included in analyses were 13 ± 2.8 years old, majority female (66.7%), and primarily diagnosed with SCD Hb SS genotype (77%). There was no significant difference in completers and non-completers in regard to age, sex, or SCD type (p’s [ 0.05). Procedures Parents and children completed questionnaires. Children were provided with a 14-day paper daily pain diary and a wrist-mounted actigraphy device. Research assistants called families each week to problem-solve concerns, remind children to complete the pain diary, and continue
J Behav Med
wearing the Actiwatch. Families received $30 compensation. Questionnaires Demographics—Data on child’s age, sex, grade in school, parent marital status, parent education, and family income were collected on a demographics questionnaire. Medication Use—Parents reported the prescribed and over-the-counter medications their children took at baseline (NIH 2017). Chart review confirmed parent report of physician prescribed medications. Medication types were coded into classes: Folic Acid, Hydroxyurea, Deferasirox, opioids, other prescription medication for pain, antidepressants, over-the-counter pain medication, allergy and asthma medications, other prescription medication, and multi-vitamin/supplement. Total number of prescribed medications (Rabbitts et al., 2014) and opioid medication prescription were examined as possible covariates. Daily medication use was not recorded. Negative Mood—Symptoms of depression and anxiety were measured at baseline using the Revised Child Anxiety and Depression Scale (RCADS; 15). The RCADS is a 47-item self-report measure of anxiety and depressive symptoms on a 4-point scale (0 ‘‘never,’’ 1 ‘‘sometimes,’’ 2 ‘‘often,’’ and 3 ‘‘always’’) (Chorpita et al., 2000). The raw scores for items within each subscale are summed to provide subscale scores. The five anxiety subscales scores (separation anxiety, generalized anxiety, panic, social phobia, obsessions/compulsions) and the major depressive disorder subscale score are then summed to provide the Total Internalizing Scale score. Raw score sums are converted to T-scores based on gender and school grade level. A T-score of 65–69 indicates borderline clinical threshold and a T-score of 70 or higher indicates clinical symptoms (Chorpita et al., 2015). The RCADS has good reliability (ranging from 0.65 to 0.80), internal consistency (a between 0.73 and 0.82), as well as convergent and discriminant validity in healthy children and adolescents (Chorpita et al., 2000). The Total Internalizing Scale score was used in analyses (a = .95). Daily pain diaries—Children were instructed to record pain occurrence and pain severity once a day at bedtime (Karlson et al., 2013; Connelly et al., 2006). Pain occurrence was rated as ‘‘yes’’ or ‘‘no.’ Daily pain severity was rated on a 6 cm visual analog scale ranging from 0 (no pain) to 6 (worst pain). Daily diaries are a well-validated method of capturing pediatric pain in the home setting (Rabbitts et al., 2014; Valrie et al., 2007, 2008). In the current study daily pain ratings correlated with baseline pain ratings on the Pain Questionnaire (Wilson & Palermo, 2012) (r’s = .25–.38, p’s \ 0.001).
Nighttime Sleep—Objective recordings of children’s daily nighttime sleep were collected using an Actiwatch 2 (Phillips Respironics, Bend, OR), which was worn on children’s non-dominant wrist for the duration of the 14-day study period. For this study, movement counts were stored on the device in 1-min epochs. Three actigraphic nighttime sleep variables were computed using the Actiware 5.59 software package: (1) sleep duration, calculated as sleep in minutes from sleep onset to sleep offset, (2) sleep efficiency expressed as a percentage, calculated as the ratio of total sleep time divided by total time spent in bed 9 100, with values closer to 100 meaning more efficient sleep, and (3) WASO computed as the sum of the number of minutes in which youth were awake from sleep onset to final awakening (Lewandowski et al., 2010). Statistical analyses Demographic characteristics of the final sample were summarized using descriptive statistics in SPSS 22.0 (Tabachnick & Fidell, 2007). Preliminary Pearson correlations were used to examine the associations between possible covariates (i.e., age, gender, depression/anxiety, pain medications) and nighttime sleep (sleep efficiency, sleep duration, WASO) and daily pain outcome variables (pain occurrence, pain severity). Between group differences (males vs. females) were examined using independent sample t tests for continuous data and Chi squared (v2) test for categorical data. Analyses of within-subject changes over time were conducted using maximum likelihood estimation multilevel modeling (MLM) in LISREL 8.71 for continuous repeated measure outcome variables (pain and sleep) (Goldstein, 1986). The date of diary entries was compared to and matched with objective actiwatch dates to maximize integrity of self-report data. Missing daily diary and actigraphy days (range 0–7 days; 3.6%) were handled in MLM analyses which uses full information maximum likelihood estimation to account for differences in the number of observations (i.e., full days) due to missing data (Goldstein, 1986; Longford, 1987). MLM analyses were modeled with 14 days nested within 30 participants. Level 1 variables were those measured on a repeated basis (pain occurrence, pain severity, sleep duration, sleep efficiency, WASO). Variables that were measured once (child age, child gender, opioid medication prescribed, and depression/anxiety) contained only between person variance and were modeled as Level 2 control variables. v2 assessed model fit and effect size (ES) was calculated as the square root of [t2/(df + t2)]. A significance of p \ 0.05 was used.
123
J Behav Med
ity (SD range 7.65–86.46 min). This mean is slightly lower than the mean WASO recorded for healthy norms of 61.65 min (Lewandowski et al., 2010).
Results Descriptive statistics Pain was primarily reported in the legs (27%), head (23%), and back (23%). The percentage of participants who reported or were prescribed medications at baseline included: Folic Acid (100%), Hydroxyurea (24%), Deferasirox (24%), opioid pain medication (83%; e.g., Tylenol III, Percocet, Oxycodone), other prescription medication for pain (20%; e.g., Neurontin, Norvasc), Amitriptyline (7%), over-the-counter pain medication (62%; e.g., Ibuprofen, Acetaminophen), allergy (20%, e.g., Zyrtec, Singulair) and asthma (10%; e.g., Advair, Albuterol) medications, other prescription medication (23%; e.g., Antibiotic, Prevacid), and multi-vitamin or supplement (13%). Clinically significant depression/anxiety symptoms were reported on the RCADS by 16.7% (n = 5) of children but not parents. Across all participants and diary days, mean sleep duration was 456.49 min (SD = 105.91; range 170–790). Participant’s sleep duration was less than 8 h on 57.6% of nights, between 8 and 9 h on 22.2% of nights, and greater than 9 h on 20.2% of nights. All participants had at least 2 nights of sleep less than 8 h duration (range 2–13 nights). Mean sleep efficiency fell within the normal range (M = 86.42%, SD = 7.00, range 34.88–97.66%) across all diary days but varied between children (range 77.74–92.49%) and within children (SD range 2.45–15.83%). Approximately one-third (31.3%) of all nights fell below the optimal level of 85% sleep efficiency and 86.67% (n = 26) of children experienced at least one night of low sleep efficiency below 85%. Mean amount of wake time after sleep onset (WASO) was 51.84 min (SD = 30.97; range 3–304 min), with individual variabil-
Covariate analyses Older age was correlated with increased daily pain severity (r = .10, p \ 0.049). Males were more likely to report experiencing pain during the study period (v2 = 12.64, p \ 0.001) and reported higher daily pain severity (t = 3.03, p = 0.003) than female participants. Increased depression/anxiety symptoms on the RCADS were correlated with more frequent daily pain (r = .14, p = 0.01) and increased daily pain severity (r = .13, p = 0.01). Increased total number of medications correlated with decreased WASO (r = - .10; p = 0.04). Being prescribed an opioid pain medication was correlated with increased daily pain severity (r = .13; p = 0.009) and marginally correlated with decreased WASO (r = -.10; p = 0.05). To provide a parsimonious covariate model, age, sex, depression/anxiety, and opioid medication prescription were controlled for in MLM analyses. Associations between daily pain and objective sleep A total of 394 days of diary and actigraphy data were used for analysis, with an average of 13 valid/usable days (SD = 1.5; range 7–14 days) per child. Children reported pain occurring on 43% of study days (range 0–14 days) and moderate pain severity (M = 3.8, SD = 1.5; 6 point scale). Regression results are shown in Table 1. Daily pain: Association with same-day sleep—Control variables included age, sex, opioid medication prescribed, and depression/anxiety. In line with hypotheses, more
Table 1 MLM Linear regressions examining sleep duration, sleep efficiency and WASO as associated with daily pain Sleep duration same-day
Sleep efficiency same-day
WASO same-day
b
SE
z
p
b
SE
Z
p
b
SE
z
p
1. Pain occurrence
8.45
11.50
.73
0.46
- 1.03
.77
- 1.34
0.18
5.57
3.40
1.64
0.10
2. Pain severity
0.40
2.78
.14
0.89
- .46
.19
- 2.49
0.01*
1.82
.82
2.22
0.03*
Pain occurrence next-day
Pain Severity next-day
b
SE
1. Sleep duration
- 0.00
0.00
- 1.16
0.25
- .00
.00
- .05
0.96
2. Sleep efficiency
- 0.01
.00
- 2.08
0.04*
- .03
.01
- 2.17
0.03*
0.00
.00
1.14
0.00
.00
1.50
3. WASO
z
p
0.25
b
SE
Z
p
0.13
Adjusted for age, gender, opioid medication prescribed, and RCADS child depression/anxiety. b values for pain severity represent the expected change in a unit of pain severity for a unit change in the predictor variable (sleep duration, sleep efficiency, WASO); b values for pain severity represent the expected change on a 0–6 scale for a unit change in the predictor variable * = p \ .05; ** = p \ .01
123
J Behav Med
severe pain during the day predicted worse sleep efficiency that night (z = - 2.49, p = 0.01), as well as increased WASO (z = 2.22, p = 0.03). Pain severity during the day did not predict sleep duration that night (z = .14, p = .89). The occurrence of pain during the day was not significantly associated with sleep duration (z = .73, p = .46), sleep efficiency (z = - .34, pz = .18) or WASO that night (z = 1.64, p = .10). Nighttime Sleep: Association with next-day pain— Controlling for age, sex, opioid medication prescribed, and depression/anxiety, as hypothesized, we found that worse sleep efficiency was associated with the occurrence of pain the next-day (z = - .08, p = 0.04) and more severe pain the next day (z = - .17, p = 0.03). However, contrary to hypotheses, WASO was not significantly associated with next-day pain (z = 1.14, p = 0.25) or pain severity the next day (z = 1.50, p = .13). Similarly sleep duration did not predict next-day pain occurrence (z = - .16, p = .25) or next-day pain severity z = - 0.05, p = .96).
Discussion In this study we examined the bi-directional relationship between daily objective actigraphic sleep patterns and selfreported pain in children with SCD who experience frequent pain. Overall, our pattern of findings supports a bidirectional relationship between pain and nighttime sleep disruption. Specifically, more severe daily pain predicted worse sleep efficiency that night and worse sleep efficiency during the night was associated with the occurrence of pain and increased pain severity the next day. Pain severity also predicted increased nighttime WASO. All models controlled for the effects of child age, sex, opioid medication prescribed, and child-reported symptoms of depression/ anxiety. Results are consistent with previous cross-sectional and retrospective research using self-reported sleep assessment (Jacob et al., 2013; Palermo & Kiska, 2005; Valrie et al., 2007, 2008, 2013) and identifying sleep as an important variable in the experience of daily pain for children with SCD. Study results suggest that a biopsychosocial feedback loop may exist between sleep disruption and pain, whereby poor sleep efficiency contributes to maintaining and amplifying pain in children with SCD and pain in turn predicts sleep disruption (lower sleep efficiency and higher WASO) the following night. Child-reported symptoms of depression/anxiety were correlated with daily pain but not objective sleep efficiency. This is in line with prior research in adolescents with chronic pain indicating depression and pre-sleep worries are not significantly related to objective sleep efficiency assessed by actigraphy (Palermo & Kiska, 2005).
Whereas depression and anxiety are well described as frequently co-occurring and being associated with chronic pain in pediatric populations (Palermo & Kiska, 2005; Palermo et al., 2007; Valrie et al., 2008, 2013), minimal research has examined the likely complex interactions between sleep, daily pain, and daily mood or the theoretical models underlying these associations (Chambers et al., 2008). The complex relationships between these variables are better defined in adult chronic pain populations suggesting that sleep problems may contribute toward the onset, precipitation, and maintenance of chronic pain in adults, and interact with daily mood to influence pain (Hamilton et al., 2012). Further study of these complex relationships in pediatric SCD is warranted. There are several strengths to this study, including the use of a repeated measures daily diary, objective actigraphy, and controlling for depression/anxiety and opioid medication prescribed in analyses (Chambers et al., 2008). However, there are also several limitations that warrant discussion. Foremost is that pain was recorded once at the end of the day using self-report paper diaries, which are subject to reporting bias and possible inaccurate data. Pain location was not recorded in daily diaries and thus we were unable to distinguish between different pain conditions such as headache, musculoskeletal pain, and vaso-occlusive pain that may co-occur in youth with SCD. The relatively short measurement period (14 days) may also have provided limited power and limited ability to fully capture complex relationships and potential interactions between nighttime sleep and pain in this population. In addition, 68% of children approached for this study were not eligible due to infrequent pain, which limits the generalizability of results to the broader pediatric SCD population. Finally, despite having a large number of data points and adequate power through the use of daily diary (n = 394), the small sample size (n = 30) and wide age range may further limit generalizability of study findings. Future studies would benefit from recording of pain location, longer measurement periods, use of electronic within-day repeated assessment, and examining potential daily interactions between objective sleep, mood, and pain. In conclusion, similar to research in other pediatric chronic pain populations (Valrie et al., 2013), our results suggest that nighttime sleep disruption may be an important factor contributing to the experience of pain in pediatric SCD. The relationship between pain and objective nighttime sleep in pediatric SCD appears to be bi-directional in nature. Sleep monitoring and treatment for sleep disruption should be incorporated into treatment plans for children with SCD who experience frequent pain (Valrie et al., 2013). Cognitive-behavioral therapy for pain management demonstrates efficacy for reducing pain and associated disability (Eccleston et al., 2014); however,
123
J Behav Med
cognitive-behavioral therapy for pain has been found to be insufficient for simultaneously improving sleep quality in patients experiencing chronic pain (Fales et al., 2015). Rather, sleep specific intervention strategies are needed such as cognitive-behavioral therapy for insomnia that includes sleep restriction and stimulus control (Blake 2017; Schlarb et al., 2016). Research examining efficacious psychological interventions targeting sleep in children and adolescents with sickle cell disease who experience frequent pain is needed. Acknowledgements This work was supported by a grant from the Society of Pediatric Psychology Diversity Research Grant awarded to Cynthia W. Karlson, Ph.D. Thank you to the families at the University of Mississippi Medical Center Sickle Cell Clinic for their participation. Compliance with ethical standards Conflict of interest The authors Karin Fisher, Andrea M. Laikin, Katianne M. Howard Sharp, Catherine A. Criddle, Tonya M. Palermo, and Cynthia W. Karlson declare that they have no conflict of interest. Human and animal rights and informed consent All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.
References Alfano, C. A., Patriquin, M. A., & De Los, Reyes A. (2015). Subjective–objective sleep comparisons and discrepancies among clinically-anxious and healthy children. Journal of Abnormal Child Psychology, 43, 1343–1353. Ameringer, S., & Smith, W. R. (2011). Emerging biobehavioral factors of fatigue in sickle cell disease. Journal of Nursing Scholarship, 43, 22–29. Barakat, L. P., Lash, L., Lutz, M. J., & Nicolaou, D. C. (2006). Psychosocial adaptation of children and adolescents with sickle cell disease. In R. T. Brown (Ed.), Comprehensive handbook of childhood cancer and sickle cell disease: A biopsychosocial approach (pp. 471–495). New York, NY: Oxford. Blake, M. J., Sheeber, L. B., Youssef, G. J., & Raniti, M. B., & Allen, N. B. (2017). Systematic review and meta-analysis of adolescent cognitive—Behavioral sleep interventions. Clinical Child and Family Psychology Review, 20, 227–249. Chambers, C. T., Corkum, P. V., & Rusak, B. (2008). Commentary: the importance of sleep in pediatric chronic pain—A wake-up call for pediatric psychologists. Journal of Pediatric Psychology, 33, 333–334. Chorpita, B. F., Ebesutani, C., Spence, S.H. (2015) Revised Children’s Anxiety and Depression Scale [Internet]. 2015 Jul. [cited 2018 Feb 17]. http://www.childforst.ucla.edu/ RCADSUersGuide20150701.pdf. Chorpita, B. F., Yim, L., Moffitt, C., & Umemoto, L. A. (2000). Assessment of symptoms of DSM-IV anxiety and depression in children: A revised child anxiety and depression scale. Behaviour Research and Therapy, 38, 835–855.
123
Connelly, M., Rapoff, M. A., Thompson, N., & Connelly, W. (2006). Headstrong: a pilot study of a CD-ROM intervention for recurrent pediatric headache. Journal of Pediatric Psychology, 31, 737–747. Daniel, L. C., Grant, M., Kothare, S. V., & Dampier, C. (2010). Sleep patterns in pediatric sickle cell disease. Pediatric Blood and Cancer, 55, 501–507. Eccleston, C., Palermo, T. M., Williams, A. C., et al. (2014). Psychological therapies for the management of chronic and recurrent pain in children and adolescents. The Cochrane Database of Systematic Reviews, 5, CD003968. Fales, J., Palermo, T. M., Law, E. F., & Wilson, A. C. (2015). Sleep outcomes in youth with chronic pain participating in a randomized controlled trial of online cognitive-behavioral therapy for pain management. Behavioral Sleep Medicine, 13, 107–123. Finan, P. H., Goodin, B. R., & Smith, M. T. (2013). The association of sleep and pain: an update and a path forward. The Journal of Pain, 14, 1539–1552. Goldstein, H. (1986). Multilevel mixed linear model analysis using iterative generalized least squares. Biometrika, 73, 43–56. Hamilton, N. A., Pressman, M., Lillis, T., et al. (2012). Evaluating evidence for the role of sleep in fibromyalgia: A test of the sleep and pain diathesis model. Cognitive Therapy and Research, 36, 806–814. Jacob, E., Duran, J., Stinson, J., & Lewis, M. A. (2013). Remote monitoring of pain and symptoms using wireless technology in children and adolescents with sickle cell disease. Journal of the American Association of Nurse Practitioners, 25, 42–54. Karlson, C. W., Litzenburg, C. C., Sampilo, M. L., et al. (2013). Relationship between daily mood and migraine in children. Headache, 53, 1624–1634. Kashikar-Zuck, S., Flowers, S. R., Verkamp, E., et al. (2010). Actigraphy-based physical activity monitoring in adolescents with Juvenile Primary Fibromyalgia Syndrome. The Journal of Pain, 11, 885–893. Lewandowski, A. S., Palermo, T. M., De la Motte, S., & Fu, R. (2010). Temporal daily associations between pain and sleep in adolescents with chronic pain versus healthy adolescents. Pain, 151, 220–225. Lewin, D. S., & Dahl, R. E. (1999). Importance of sleep in the management of pediatric pain. Journal of Developmental and Behavioral Pediatrics, 20, 244–252. Longford, N. T. (1987). A fast scoring algorithm for maximum likelihood estimation in unbalanced mixed models with nested random effects. Biometrika, 74, 817–827. Moscou-Jackson, G., Finan, P. H., Campbell, C. M., et al. (2015). The effect of sleep continuity on pain in adults with sickle cell disease. The Journal of Pain, 16, 587–593. NIH. (2017). The management of sickle cell disease provided by Division of Blood Diseases and Resources. http://www.nhlbi.nih. gov/files/docs/guidelines/sc_mngt.pdf. Accessibility verified December 1, 2017. Palermo, T. M., & Kiska, R. (2005). Subjective sleep disturbances in adolescents with chronic pain: Relationship to daily functioning and quality of life. The Journal of Pain, 6, 201–207. Palermo, T. M., Toliver-Sokol, M., Fonareva, I., & Koh, J. L. (2007). Objective and subjective assessment of sleep in adolescents with chronic pain compared to healthy adolescents. Clinical Journal of Pain, 23, 812–820. Rabbitts, J. A., Holley, A. L., Karlson, C. W., & Palermo, T. M. (2014). Bidirectional associations between pain and physical activity in adolescents. Clinical Journal of Pain, 30, 251–258. Schlarb, A. A., Bihlmaier, I., Velten-Schurian, K., Poets, C. F., Hautzinger, M. (2016). Short- and long-term effects of CBT-I in groups for school-age children suffering from chronic insomnia:
J Behav Med The KiSS-program. Behavioral Sleep Medicine https://doi.org/ 10.1080/15402002.2016.1228642. Tabachnick, B. G., & Fidell, L. S. (2007). using multivariate statistics (5th ed.). Boston, MA: Allyn and Bacon. Tremaine, R., Dorrian, J., & Blunden, S. (2010). Subjective and objective sleep in children and adolescents: Measurement, age, and gender differences. Sleep and Biological Rhythms, 8, 229–238. Valrie, C. R., Bromberg, M. H., Palermo, T., & Schanberg, L. E. (2013). A systematic review of sleep in pediatric pain populations. Journal of Developmental and Behavioral Pediatrics, 34, 120–128.
Valrie, C. R., Gil, K. M., Redding-Lallinger, R., & Daeschner, C. (2007). Brief report: Sleep in children with sickle cell disease: an analysis of daily diaries utilizing multilevel models. Journal of Pediatric Psychology, 32, 857–861. Valrie, C. R., Gil, K. M., Redding-Lallinger, R., & Daeschner, C. (2008). Brief report: Daily mood as a mediator or moderator of the pain-sleep relationship in children with sickle cell disease. Journal of Pediatric Psychology, 33, 317–322. Wilson, A. C., & Palermo, T. M. (2012). Physical activity and function in adolescents with chronic pain: a controlled study using actigraphy. The Journal of Pain, 13, 121–130.
123
