The Journal of School Nursing2021, Vol. 37(4) 259–269© The Author(s) 2019 Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/1059840519865942journals.sagepub.com/home/jsn
The purpose of this cross-sectional, descriptive, pilot study was to examine the correlations in sleep between caregivers (≥18 years) and young (6–12 years) children with type 1 diabetes. Sleep was measured in both parent and child over 7 days using actigraphy and a sleep diary. Parents completed questionnaires on sleep, stress, depressive symptoms, and demographics. Children completed pediatric anxiety and fatigue questionnaires, and A1C (Hemoglobin A1c) was documented at clinic. Descriptive statistics and Pearson correlations were used to analyze data. Parents (N = 18, mean age: 39.3 ± 5.4 years, 100% Caucasian, 83% mothers) and children (N = 18, mean age: 9.6 ± 2.4 years, diagnosed for mean 3.0 ± 2.4 years, 66% female, mean A1C: 7.5 ± 0.8%) were recruited. Strong to moderate correlations were found for several measures including sleep measures based on actigraphy: mean sleep duration (hours; 7.6 ± 0.7 for parents and 8.8 ± 0.8 for children; r = .638, p = .004), mean sleep efficiency (r = .823, p < .001), and mean daily wake after sleep onset (minutes; r = .530, p = .024).
sleep, children, parents, caregiver, type 1 diabetes, school nurse
There are nearly 15,000 new cases of type 1 diabetes (T1D) diagnosed in children each year in the United States, with the incidence among children under 14 years of age estimated to increase by 3% annually worldwide (JDRF, 2019). It has been estimated that T1D accounts for nearly US$14.9 billion in health-care costs annually and ranks as one of the costliest chronic diseases in the United States (JDRF, 2019). The acute and long-term complications of T1D can be devastating, including severe hypoglycemia, hospitalizations for diabetic ketoacidosis, or, as adults, amputations, heart attacks, and blindness.
In part, what makes T1D so costly is the complexity of care and relentless nature of its progression (Harrington et al., 2017; Monaghan, Hilliard, Cogen, & Streisand, 2011). As more and more children are diagnosed and sent home with a complex management plan, more and more parents are finding that they must assume a role beyond parenting that includes being a nurse, nutritionist, pharmacist, exercise specialist, physical therapist, and case manager, among others (Muller-Godeffroy, Treichel, & Wagner, 2009; Sullivan-Bolyai, Sadler, Knafl, & Gilliss, 2004). This often introduces a new level of stress into the parental caregiver’s and child’s life, as they try to manage their child’s care.
Parents of children with T1D have reported elevated levels of stress and anxiety related to their caregiving duties and child’s future (Herbert et al., 2014; Kovacs et al., 1990). They are forced to adapt to the increased behavioral and medical demands that are inherent in the management of T1D in children. As a caregiver, parents must now check blood glucose levels, administer insulin injections appropriately, and monitor their child’s diet and activity patterns in order to avoid dangerous and costly complications. Especially for T1D where hypoglycemia is a 24-hr concern, caregiving does not simply end during the daytime hours (Monaghan, Herbert, Cogen, & Streisand, 2012; Van Name et al., 2018). Getting adequate and good quality sleep tends to become lower priority for some parents and may lead to chronic sleep deprivation as they struggle to balance the many responsibilities they face (Jaser et al., 2017; Monaghan et al., 2012; Monaghan, Hilliard, Cogen, & Streisand, 2009). Likewise, for children with T1D, obtaining adequate sleep may be a struggle. Previously, researchers have found that parental caregivers of children with T1D reported their children had increased bedtime resistance, elevated levels of stress leading up to bedtime, called their parents into their room more frequently during the night, had increased wake after sleep onset (WASO), co-slept with their parents more often, and reported fewer hours of sleep than an age-matched control group (Jaser et al., 2017; Jaser, Lord, Simmons, & Malow, 2016; Monaghan et al., 2012; Sullivan-Bolyai, Knafl, Deatrick, & Grey, 2003; Sullivan-Bolyai et al., 2004).
Sleep deprivation has a number of negative health consequences in adults, ranging from increased incidence of hypertension, cardiovascular disease, obesity, and heart disease, to decreased memory capacity and elevated feelings of daytime fatigue (Altena, van der Werf, Strijers, & van Someren, 2008; Cappuccio, Cooper, D’Elia, Strazzullo, & Miller, 2011; Patel et al., 2008). Poor sleep may also influence mood and affect in both caregiver and child, with previous research supporting a link between poor sleep and increased levels of stress, anxiety, and depressive symptoms (Chu & Richdale, 2009; Estrada, Danielson, Drum, & Lipton, 2012; Feeley et al., 2014; McEwan, 2006). Specifically, for children with T1D, poor sleep may have a relationship with glycemic control, with some investigators suggesting that clinicians recommend higher A1C levels in children who reported poorer quality of sleep and short sleep duration due to an increased susceptibility to overnight hypoglycemia (Happe, Treptau, Ziegler, & Harms, 2005; Perez et al., 2018; Villa et al., 2000). This suggests that obtaining adequate amounts of sleep is recognized as important for both the child and parental caregiver. However, while previous researchers have investigated sleep in family parental caregivers and children with T1D separately (Adler, Gavan, Tauman, Phillip, & Shalitin, 2017; Monaghan et al., 2012), few studies have examined sleep within the dyad of a child with T1D and their caregiver (Jaser et al., 2017).
In a cohort of healthy children, how the child slept was a significant predictor of how the parent slept (Meltzer & Mindell, 2007). This suggests that the child’s sleep plays an important role in the parent’s sleep. An important next step would be to examine sleep within the dyad, both the parental caregiver and the child with T1D, to explore whether relationships exist between nighttime sleep and daytime function. The overall purpose of this study was to explore associations between parent and child sleep in school-age children (aged 6–12 years) with T1D using questionnaires and actigraphy and describe sleep in the dyad. The study also examined the relationship between sleep and the symptoms of stress and depressive symptoms in parents and anxiety, fatigue, and A1C in children.
Lazarus and Folkman’s (1984) theory of stress, appraisal, and coping was used as a guiding framework for this study. Sleep influences stress and outcomes in caregivers and children (Feeley et al., 2014; Gallagher, Phillips, & Carroll, 2010) and may act as an antecedent to the parental caregiver’s or child’s appraisal of the situation. Sleep may influence how the parental caregiver or child perceives the demands of managing T1D (Feeley et al., 2019). Poor sleep may influence parental caregiver or child to report poorer outcomes (elevated stress, depressive symptoms, or anxiety in adults, and more anxiety or fatigue in children). Therefore, parents with poor sleep may view their interaction with the caregiving environment of living with a child with T1D as a threat rather than a challenge (whereas a challenge may have a more positive connotation; Lazarus & Folkman, 1984). The current study is focused on sleep in children with T1D and their parental caregivers, the association of sleep between the parent/child dyad, and the associations that sleep may have with symptoms (stress, depressive symptoms, and anxiety in adults, and anxiety and fatigue in children) in parent and child.
This was a descriptive, cross-sectional, pilot study that recruited a convenience sample of 18 parent caregiver and child dyads from an outpatient pediatric endocrinology clinic. Institutional review board approval was sought before data collection began. Informed consent and assent were obtained from parents and children before any data were collected. For the child to be included in the study, she or he had to be between the ages of 6 and 12 years, have been diagnosed with T1D for at least 2 years, and have no other major illnesses. For the parent to be included in the study, they had to be at least 18 years of age, be the self-identified primary caregiver of the child, have the child primarily live with them, and be able to read, write, and understand English. A parent and/or child was excluded if he or she had a diagnosed sleep disorder, were currently undergoing treatment for a diagnosed sleep disorder (restless leg syndrome, obstructive sleep apnea, and/or insomnia), or were taking any prescribed or over-the-counter medications for sleep.
Patient-Reported Outcomes Measures Information System (PROMIS) Pediatric Fatigue–Short Form (10a). The National Institutes of Health (NIH) developed PROMIS measures. The Pediatric Fatigue Short Form 10a and Parent Proxy Short Form 10a were used in this study to measure fatigue in the child with T1D. The instruments each consist of 10 questions measuring daytime fatigue, as designed and tested through the NIH PROMIS initiative. The Pediatric Fatigue Short Form has been shown to be reliable and valid in children 8 years and older, with the Parent Proxy Short Form used for children younger than 8 years (Lai et al., 2013). Items are rated on a 5-point scale (ranging from never = 0 to almost always = 4), with a higher score indicating greater fatigue. Scores (T-scores) can range from 30.3 to 84.0 (Lai et al., 2013).
PROMIS Pediatric Anxiety Short Form. PROMIS Pediatric Anxiety Short Form 8a was used to measure anxiety in the child with T1D. It was adapted and framed from the World Health Organization’s tripartite framework of physical, mental, and social health (Pilkonis et al., 2011). The PROMIS Anxiety Short Form 6a utilizes five response categories (never, rarely, sometimes, often, and always). Scores are converted to T-score metrics based on a representative calibration sample consisting of the U.S. general population and multiple disease populations. Similar to the PROMIS Pediatric Fatigue measures, a parent proxy form is available for children younger than 8. The PROMIS Pediatric Anxiety Short Form 8a has an item correlation with the original long-form version of the same questionnaire of 0.79 and a Cronbach’s α coefficient of .93. It was used in a sample of caregivers of patients with polytrauma and demonstrated good reliability. Scores (T-scores) can range from 32.3 to 82.8, with higher scores indicating higher levels of anxiety (Stevens et al., 2015).
Pittsburgh Sleep Quality Index (PSQI). The PSQI is a self-report measure of subjective sleep quality. It consists of 19 items measuring on a 4-point scale, with responses ranging from “not during the past month” to “3 or more times a week.” The instrument yields a global score derived from seven component scores (sleep quality, sleep latency, sleep duration, sleep efficiency [SE], sleep disturbances, sleep medications, and daytime dysfunction) that range in score from 0 to 3, with higher scores indicating a greater disturbance (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989; Meltzer & Mindell, 2006). The seven subscales are summed for a global sleep quality score, with a total range of 0–21, and a score greater than 5 indicating severe sleep difficulties (Buysse et al., 1989). The global score was used in this study to determine perceived sleep quality in the parental caregivers. The three factors proposed by Cole and colleagues (2006) were used for further analyses. These factors include (1) SE, (2) sleep quality, and (3) sleep disturbance (Cole et al., 2006).
PROMIS Sleep Disturbance Measure 8a. The PROMIS Sleep Disturbance Short Form 8a is an 8-item instrument developed by the NIH PROMIS consortium. This short form utilizes five response choices (never, rarely, sometimes, often, and always), and total summary scores are converted to T-score metrics based on a representative calibration sample consisting of the U.S. general population and multiple disease populations. A higher score indicates higher levels of sleep disturbance. PROMIS measures have been tested extensively in large diverse samples drawn from the general population and clinical groups, and validity has been demonstrated by correlation with well-standardized measures, in this case, with the PSQI (Yu et al., 2011). The correlation between PROMIS Sleep Disturbance 8a with the global PSQI was r = .85 (n = 2,252). This PROMIS measure has been used previously in a sample of caregivers of infants in the neonatal intensive care unit and had a Cronbach’s α of .90 (Busse, Stromgren, Thorngate, & Thomas, 2013).
Perceived Stress Scale (PSS). The PSS consists of 10 self-report questions on a 5-point Likert-type scale, with 6 of the items being negatively worded and the remaining 4 items being reverse scored and more positive. Scores range from 0 (never) to 4 (very often), with higher scores indicating elevated stress (Cohen, Kamarck, & Mermelstein, 1983). The PSS has been used previously with caregivers of children with allergies and had a reported Cronbach’s α of .84 (King, Knibb, & Hourihane, 2009).
Center for Epidemiological Studies Depression Scale (CES-D). The CES-D was designed to be used in a general population of healthy adults as a measures of depressive symptoms. It consists of 20 self-report items on a 4-point Likert-type scale (Radloff, 1977). The item scaling ranges from 0 (rarely or none of the time) to 3 (most or all of the time), and a higher score indicates greater incidence of depressive symptoms. A score greater than or equal to 16 has been found to be highly correlated with a clinical diagnosis of depression (Radloff, 1977).
Wrist actigraphy. Actigraphy was conducted for both parent and child for 7 consecutive days. Respironics Actiwatch® 2 actigraph (Phillips Respironics, Bend, OR) is a small, lightweight, and unobtrusive wristwatch style accelerometer worn on the nondominant arm. Physical activity, recorded in 1-min epochs, was used to derive objective, movementbased estimates of sleep. The Actiwatch has been shown to be highly valid and reliable for the differentiation of sleep from wakefulness, as well as recording total sleep time (TST), nighttime awakenings, and WASO when compared to home-based polysomnography (gold standard) in persons with insomnia (Sanchez-Ortuno, Edinger, Means, & Almirall, 2010). In this study, the Actiwatch was used to derive objective sleep parameter estimates for caregivers and children over 7 days. Wrist actigraphy has been used successfully in children as young as 3 years, with parents keeping a proxy sleep diary until the age of 6 (Meltzer, Walsh, Traylor, & Westin, 2012; Werner, Molinari, Guyer, & Jenni, 2008). Actigraph sleep measures for this study included TST (defined as the total amount of time a participant was scored as asleep), SE (defined as the ratio of the time a participant was scored as asleep to total period of time in bed), and WASO (defined as number of minutes awake after sleep onset). Sleep onset and offset were scored and supplemented with sleep diary data, which parent and child were instructed to keep while wearing the actigraph. Activity counts were scored using a medium threshold, with 40 activity counts per epoch for both parent and child. A medium threshold algorithm has high sensitivity to detect sleep and low specificity to detect wake when compared to polysomnography (Meltzer et al., 2012; Ward, Lentz, Kieckhefer, & Landis, 2012; Yuwen et al., 2016). Actigraphy data will only be included from participants with at least four nights of recorded data. Sleep parameters are based on the average of the data for the nights available.
Sleep diary. Both caregiver and child kept a sleep diary during the week they were wearing the actigraph. In the diary, participants were asked to fill in estimates of the previous night’s sleep, including when they went to sleep, when they woke up, how long it took them to fall asleep, total time in bed, and number of times they woke up at night and why.
Demographic characteristics and diabetes management questionnaire. Caregivers completed a questionnaire that gathered demographic information on both the caregiver and child, including age, sex, race/ethnicity, education, family makeup, and the child’s diabetes management routine (how child regularly received insulin, how child’s blood glucose was checked, although, of note, this study was conducted before continuous glucose monitoring was prevalent in this population). Information also included the child’s A1C at the clinic visit and whether the parent performs nighttime blood glucose checks.
Participants were recruited from an outpatient pediatric diabetes clinic. Patients were screened before clinic visit for age and time since diagnosis, and those who met the inclusion criteria were approached for further screening and interest in the study during their clinic visit. Upon completing the consent and assent process for children, both caregiver and child were given the questionnaire packets and actigraphs, as well as a postage-paid, addressed envelope. Actigraphs were placed on the participants’ wrists while they were in clinic, and they were given verbal and written instructions on their use and care. Participants were instructed to wear the actigraph and keep a sleep dairy for 7 days, then mailed the actigraph and questionnaires back to the PI in the selfaddressed, stamped envelopes. Upon receipt of the questionnaires and actigraph, both parent and child received reimbursement for their time.
Actigraph data were downloaded from the watches into the Actiware software (Phillips Respironics v. 6.0.9) package for cleaning and analyzing. Data were then exported into IBM® SPSS® Statistics (v25, IBM Corp, Armonk, NY), along with questionnaire and demographic data. Parent and child were given a linked identifier within the database. All variables were described using frequency distributions and summarized using appropriate measures of central tendency and dispersion given the level of measurement of the variable. Bivariate correlational analyses were performed and reported to examine associations of the sleep variables from the actigraph (TST, SE, WASO) and sleep questionnaires (PSQI, PROMIS sleep disturbance) (a) within the dyad of the parental caregiver with child with T1D and (b) with the PSS and CESD in adults and with the PROMIS fatigue and anxiety in children. Correlation coefficients were reported from theses analyses as effect sizes.
The sample consisted of 18 dyads of children with T1D and their parental caregiver. Twenty dyads were originally recruited, with 18 completing all data collection. Children were Caucasian, mostly female, and on average 9 years of age. Parental caregivers were Caucasian, primarily the child’s mother, currently married, at least high school educated, on average 39 years of age, and most did not have diabetes. Table 1 describes the sample characteristics of parent and child.
Almost one quarter (n = 4; 22%) of the children used an insulin pump, and most (n = 15; 83%) had their blood glucose checked at night by their parental caregiver. Most parents rated their child’s glucose control as a 4 (n = 13; 72.2%; median = 4.0, Interquartile Range [IQR] = 1.0), where 5 is the very best it could be. The children’s average A1C was 7.53 (SD = .75); however, A1C ranged from 6.50 to 9.50. There were no significant correlations between the age of child and A1C, nor the time since diagnosis and A1C. Fourteen (77.7%) dyads wore the actigraph and kept a sleep diary for the full 7 days. Three (16.6%) dyads wore the actigraph for 6 days, and 1 (5.5%) dyad had 5 nights of data (only five nights of data were available due to battery malfunction in the actigraph).
Table 2 describes parent and child sleep characteristics from actigraphy and the within-dyad correlations. Based on actigraphy, children recorded, on average, 8.82 hr (529.5 min) of TST with a range of 4.5–10.0 hr and parents recorded 7.6 hr (457.0 min) of TST with a range of 6.5 to 8.0 hr. Over half (56%) of the children had 8 or less hours of sleep per night (9–10 hr of sleep is considered normal for this age-group), and 72% of parents reported 7 or less hours of sleep per night.
For the parent’s objective and subjective sleep measures, mean daily SE (%) based on actigraphy was associated with PSQI global scores (r = −.584, p = .028) as well as the Perceived Sleep Quality Factor subscale (r = −.478, p = .045) and Sleep Efficiency Factor subscale (r = −.515, p = .049) scores. Moderate to large correlations were found between child’s and parent’s sleep based on actigraphy ranging from .638 (mean TST) to .823 (mean daily percentage SE). Parent’s self-reported sleep measures based on the PSQI and PROMIS were not correlated with child’s sleep based on actigraphy. There was no significant association between age and sleep measured by actigraphy in either parent or child, nor was there a significant association between how long the child had been diagnosed with T1D and parent or child sleep (actigraphy or questionnaire).
Tables 3 and 4 describe parent and child subjective measures. No significant associations were observed between child’s sleep parameters based on actigraphy and child’s outcomes (i.e., self-reported fatigue or anxiety levels) or parent’s outcomes (i.e., depressive symptom severity or perceived stress). There was a significant correlation between age of child and parent’s global PSQI (r = −.544, p = .044). A significant correlation was found between child’s A1C and parent’s TST as measured by actigraphy (r = −.500, p = .044), with children with worse glycemic control being correlated with parental caregivers who obtained shorter sleep duration.
Parent’s levels of depressive symptoms based on the CESD were positively associated with the PSQI global (r = .548, p = .043) and daytime Sleep Disturbance Factor subscale (r = .621, p = .008) scores. Perceived stress was negatively associated with mean daily SE (r = −.592, p = .010) based on actigraphy and positively associated with the PSQI global (r = .694, p = .006) and perceived Sleep Quality factor subscale (r = −.559, p = .016) scores. Parent’s sleep in terms of PSQI daytime Sleep Disturbance Factor subscale score was positively associated with the child’s level of anxiety (r = .726, p = .001).
This study is one of the first to examine sleep in the dyad of parent and child with T1D using questionnaires, actigraphy, and sleep diaries. TST, WASO, and SE as measured by actigraphy for both parent and child, while close, largely did not meet recommendations (except for parent SE). Child WASO was elevated compared to recommendations but was similar to other children with T1D and other chronic conditions where sleep was measured using actigraphy. Jaser and colleagues (2016) measured sleep using actigraphy in young children with T1D (3–5 years) and found a mean of 56.9 min of WASO. Likewise, Perfect and colleagues (2012) found a mean of 86.6 min of WASO in children 10–16 years with T1D. In a sample of children with juvenile idiopathic arthritis (JIA) where sleep was measured using actigraphy, children recorded a mean of 93 min of WASO (Yuwen et al., 2016). Elevated WASO in this population may be related to a number of things, such as nighttime glucose checks or trouble falling asleep after nighttime glucose checks. Other possibilities include co-sleeping or undiagnosed sleep disordered breathing (such as obstructive sleep apnea). While participants were excluded if they had a diagnosed sleep disorder, it is possible some children may have had an undiagnosed sleep disorder. Children between 6 and 12 years should sleep around 9–12 hr every night, and adults should sleep around 7–8 hr per night, SE should be greater than 85%, and WASO should be less than 30 min per night (Paruthi et al., 2016). These results are similar to other researchers who found parents and children with T1D often do not obtain the recommended hours of sleep for their age range. In a study of young children (2–5 years) with T1D and their parents using actigraphy, children reported a mean of 8 hr of sleep per night (recommended 10–13 hr) and parents reported a mean of 6.2 hr per night (Jaser & Ellis, 2016). Likewise, in a large survey study of children with T1D (n = 515) and their caregivers, children 5–12 years reported a mean of 9.5 hr of sleep and parents reported a mean of 6.5 hr (Jaser et al., 2017).
Overall, parent and child sleep parameters as measured by actigraphy (TST, SE, and WASO) were significantly correlated, and furthermore, a significant inverse correlation was found between parent’s TST (via actigraphy) and child’s A1C. Significant associations were also found among subjective measures for parents, including correlations between the PSS and PSQI, and CESD and PSQI. The child’s subjective measures (anxiety and fatigue) were not significantly associated with objective or subjective sleep parameters or outcomes.
Parents reported poor sleep quality via the PSQI global sleep score, which indicates a score of 5 or higher as suggestive of clinically disturbed sleep. Parents in this sample reported a mean PSQI global sleep score of 8.1, which is lower than caregivers of children on a ventilator (mean 10.07) and caregivers of children with developmental disabilities (mean: 9.9; Meltzer & Mindell, 2006). The sample in this study scored slightly higher than caregivers of children with bronchopulmonary dysplasia (mean: 7.6), higher than a large sample (n = 515) of parents of children with T1D (6.6), and higher than a national sample of healthy women (3.6; Feeley et al., 2014; Gallagher et al., 2010; Hall et al., 2009; Jaser et al., 2017). Caregiving may have a negative influence on sleep quality, for a number of reasons. Specifically, in parents of children with T1D, the fear of overnight hypoglycemia and overnight blood glucose checks may interfere with their ability to get adequate, good quality sleep (Van Name et al., 2018).
Parents in this sample reported elevated levels of stress with a mean of 19.1 on the PSS when compared to caregivers of children with bronchopulmonary dysplasia (mean: 18.3) and a national sample of adult, healthy women (mean: 16.1; Cohen et al., 1983; Feeley et al., 2014). This suggests that caregiving for a child with T1D may influence parent’s feelings of stress. However, parents in this sample reported lower stress than parents of children with a peanut allergy (mean: 25.1; King et al., 2009). This may, in part, be due to the timing of data collection. Parents of children with a peanut allergy may feel a marked increase in stress as their child enters school and begins making their own food choices away from home (King et al., 2009).
A mean of 13.2 was reported for the CESD by the parents in this sample. This is higher than a national sample (mean: 9.06) and parents of children without a chronic or special health-care need (mean: 9.28), indicating that caregiving for a child with T1D may negatively influence depressive symptoms (Makambi, Williams, Yalor, Rosenberg, & Adams-Campbell, 2009; Meltzer & Mindell, 2006). Furthermore, parents of newly diagnosed children with T1D reported a mean of 25.9 on the CESD, but the period of time before, during, and immediately after diagnosis is often marked with increased stress and uncertainty (Streisand et al., 2008). The children in this study had been diagnosed for at least 2 years, which may account for the lower depressive symptoms. In a different sample of parents and children with T1D who had been diagnosed for a mean of 3 years, parents reported a mean of 14.6 on the CESD, closer to the mean in this sample (Hood, 2009).
Children with T1D reported a mean T-score of 45.0 and 39.6 on the Pediatric PROMIS anxiety and fatigue measures, respectively. Children in this sample reported lower scores when compared to other samples of children with chronic illnesses (Wang et al., 2018). Wang et al. (2018) examined children with cancer, who reported a mean of 48.1 and 52.4 on the PROMIS pediatric anxiety and fatigue measures, respectively. Children and adolescents with sickle cell anemia reported a mean score of 45.0 for anxiety and 46.7 for fatigue on the PROMIS pediatric measures (Dampier et al., 2016). For ease of interpretation, PROMIS measures are transformed into a T-score metric (mean = 50, SD = 10). On this scale, 50 represents the mean score of the general population. This suggests that children in this sample are reporting relatively low levels of fatigue and anxiety; however, they are similar to other children with chronic conditions. A condition-specific questionnaire may have elicited more in-depth data (Lai et al., 2013). This may also be the case related to the lack of significant associations related to child’s reported sleep and reported anxiety and fatigue. The amount of sleep recorded via actigraphy was below recommendations; however, self-reported fatigue and anxiety were relatively low in this sample. A more sensitive measure of fatigue and anxiety may be necessary.
Significant moderate to large correlations were found between several measures. The PSQI was significantly correlated with parental SE via actigraphy, child’s age, and parent’s CESD and PSS. The PSS was also significantly correlated with parental SE via actigraphy. These correlations suggest interesting relationships among variables such that poor sleep quality was related to poor SE, having a younger child, higher depressive symptoms, and higher levels of stress. Elevated levels of stress were also related to poorer SE. These relationships are similar to previous studies that found poor sleep quality was associated with elevated stress and depressive symptoms in caregivers of children with T1D (Monaghan et al., 2012; Monaghan et al., 2009; Streisand & Monaghan, 2014) and children with other chronic conditions (Feeley et al., 2014; Meltzer & Mindell, 2006; Raina et al., 2005). The relationship between child’s age and parent’s PSQI has been reflected in previous literature examining young children with T1D and their parents. Managing T1D in a younger child may present unique challenges, especially related to communication (ability to verbalize hypo- or hyperglycemic symptoms) which may affect parent’s sleep (Monaghan et al., 2012).
There were significant correlations between parent and child sleep as measured by actigraphy, including TST, SE, and WASO. This, in part, supports previous findings in parents of children without a chronic condition or special healthcare need (Meltzer, Boroughs, & Downes, 2010; Meltzer & Mindell, 2007; Yuwen et al., 2016) that found that child’s sleep was a significant predictor of parent’s sleep. Similarly, Kouros and El-Sheikh (2017) examined 163 children and their parents using actigraphy over 7 days and found a significant relationship between child’s and mother’s sleep (total sleep minutes, SE, WASO, and wake time), but not father’s sleep. However, duration and quality of mother’s sleep were associated with both father and child on that same night (Kouros & El-Sheikh, 2017).
A relationship between sleep and aspects of sleep in the dyad is also supported in parent–child dyads with JIA, cancer, and autism (Goldman, Wang, & Fawkes, 2014; Matthews, Neu, Cook, & King, 2014; Yuwen et al., 2016). Yuwen and colleagues (2016) examined parent–child dyads of young children with newly diagnosed JIA using actigraphy and found an interrelationship between parent and child SE and WASO, but no relationship between parent and child sleep in typically developing children and parents. Likewise, Goldman, Wang, and Fawkes (2014) examined sleep in the parent–child dyads of children with (n = 11) and without (n = 6) autism using actigraphy over 14 nights and found significant associations based on whether the child was rated as a “good” or “poor” sleeper. In good-sleeper parent–child dyads, time in bed and TST were significantly associated. In poor-sleeper dyads SE, fragmentation, and WASO were found to be significantly correlated, and in the typically developing child–parent dyads, only TST was significantly correlated (Goldman et al., 2014). Matthews and colleagues (2014) examined dyads of children with and without acute lymphoblastic leukemia and their parents using actigraphy and found only TST to be significantly correlated in dyads with acute lymphoblastic leukemia, but not parent/child dyads without acute lymphoblastic leukemia. There is a somewhat small, but growing, body of literature that examines sleep using actigraphy in the dyad of parent and child. However, the relationships have been found to suggest that sleep is impacted by caring for a child with a chronic condition and that there is a significant relationship between how the child sleeps and how their parent or caregiver sleeps.
Limitations of the study include that this was a small pilot study and was not designed to formally test hypotheses and hence is a risk for Type I error and should to be replicated with a larger sample of parent and child dyads. The findings are also limited by a lack of diversity and cross-sectional design such that causality cannot be assessed. A convenience sample was used, which may introduce selection bias, as dyads had to volunteer to be in the study. The use of sleep medications was used as an exclusion criterion; however, the medication history of the dyad was not assessed and may have had an influence on sleep parameters. Child cosleeping with parents was not assessed, and while child and parent were excluded if they had a diagnosed sleep disorder (such as sleep apnea), a separate screening questionnaire was not administered for participants who may have an undiagnosed sleep disorder. Specific data on how parent and child tolerated the actigraph were not collected; however, over half of the study participants completed all elements of data collection, which may act as indicator of tolerance. Despite limitations, this study does add to the growing body of literature on sleep in dyads and highlights the needs for further studies examining this important relationship.
School nurses are in a unique position to assess, care for, manage, and provide support to children and families with T1D. Children and adolescents spend a significant amount of their time at school, where diabetes management is still necessary (Keough, Sullivan-Bolyai, Crawford, Schilling, & Dixon, 2011). School nurses are often called to aide children in checking their blood glucose, administering insulin, and assessing for complications (hypoglycemia and hyperglycemia), as well as providing and reinforcing diabetes education. Including education on the importance of sleep, sleep habits, and asking children how they are sleeping may be first steps in opening up a wider dialogue that also can include parents (Hamilton, Knudsen, Vaina, Smith, & Paul, 2017).
With mounting evidence on the importance of sleep on overall physical and mental health, school nurses are relied upon to be important, first-line sources of information and education for parents, children, and school faculty and staff (Jaser et al., 2017). Restricted sleep and poor sleep quality have been linked with elevated stress, depressive symptoms, and decreased attention and memory in both adults and children (Perfect et al., 2012; Philip et al., 2004). Specifically, in children with T1D, elevated levels of sleepiness and poor sleep habits were correlated with reduced quality of life as well as lower grades and lower state standardized reading scores (Perfect et al., 2012). This underscores the importance of sleep, especially related to the school setting, and highlights an important area for school nurses to provide education and support for families and school staff. School nurses could also provide important insights to faculty and staff when a child’s school performance is poor and may be related to restricted or poor quality sleep.
Beyond the school setting, these results would help to inform clinicians and researchers alike. This study adds to the burgeoning body of literature on sleep in parents and children with T1D, and specifically, that both parents and children are sleep deprived (Adler et al., 2017). Sleep has important implications for children with T1D as researchers have found a link between poor sleep and poor glycemic control and more self-regulatory failures (Perez et al., 2018). Furthermore, to highlight the importance of sleep in the dyad of child with T1D and parent, poor child sleep has been associated with poor overall well-being and quality of life in parents (Jaser et al., 2017). Many clinicians do not assess or ask about sleep, sleep routines, or sleep problems during clinic visits or provider interactions. Given the importance of sleep for diabetes management and overall quality of life for both parent and child, open, frank discussions about sleep routines and sleep problems are a starting point for providers and families. Research has found that establishing a bedtime routine (set, predictable activities that occur before bedtime, such as brushing teeth, reading a book, or listening to music) has a beneficial influence on sleep and sleep quality (Mindell, Telofski, Wiegand, & Kurtz, 2009; Mindell & Williamson, 2018). Helping and encouraging families to establish bedtime routines could be beneficial to their overall sleep, as well as discussing sleep hygiene measures, such as limiting light exposure, including light from device screens, before bed, not eating or drinking immediately before bed, and maintaining a regular wake time and bedtime (Mindell & Williamson, 2018). Also, health-care providers are in a unique and important position to reinforce the importance of sleep for a healthy lifestyle.
Christine Feeley, Susan Sereika, Eileen Chasens, Linda Siminerio, Denise Charron-Prochownik, and Radhika Muzumdar contributed to the conception of the manuscript, and the draft was prepared by Christine Feeley. Christine, Susan, Eileen, and Pushpa Viswanathan contributed to the data analysis and interpretation. All authors were involved in the critical revisions of the manuscript, gave final approval, and agree to be accountable for all aspects of work ensuring integrity and accuracy.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: C Feeley received funding from the American Nurses Foundation, the National Association of School Nurses, and the Center for Research and Evaluation Seed Fund at the University of Pittsburgh School of Nursing.
Christine A. Feeley, PhD, RN https://orcid.org/0000-0003-1938-684X
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Christine A. Feeley, PhD, RN, is an assistant professor at University to Pittsburgh, School of Nursing.
Susan M. Sereika, PhD, is a professor at University of Pittsburgh, School of Nursing.
Eileen R. Chasens, PhD, RN, FAAN, is a professor at University of Pittsburgh, School of Nursing.
Linda Siminerio, RN, PhD, CDE, is a professor at University of Pittsburgh, School of Medicine.
Denise Charron-Prochownik, PhD, RN, CPNP, FAAN, is a professor at University of Pittsburgh, School of Nursing.
Radhika H. Muzumdar, MD, is an associate professor at University of Pittsburgh, School of Medicine.
Pushpa Viswanathan, MD, is an associate professor at University of Pittsburgh, School of Medicine.
1 School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA
2 School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
3 UPMC Children’s Hospital of Pittsburgh, Pittsburgh, PA, USA
Corresponding Author:Christine A. Feeley, PhD, RN, School of Nursing, University of Pittsburgh, 3500 Victoria Street, 440 Victoria Building, Pittsburgh, PA 15213, USA.Email: caf117@pitt.edu
