Helping Clinicians Conceptualise Behavioural Insomnia in Children: Development of the Kids Insomnia Problems Scale (KIPS)

doi:10.21203/rs.3.rs-3145072/v1

Download PDF

Research Article

Helping Clinicians Conceptualise Behavioural Insomnia in Children: Development of the Kids Insomnia Problems Scale (KIPS)

https://doi.org/10.21203/rs.3.rs-3145072/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 05 Oct, 2023

Read the published version in Child Psychiatry & Human Development →

You are reading this latest preprint version

This paper outlines the development and psychometric evaluation of the Kids Insomnia Problems Scale (KIPS), an instrument intended to assess factors underpinning child behavioural insomnia. Study 1 comprised an exploratory factor analysis (EFA; n = 328 parents of children aged 3–12 years), with items found to load highly onto 6 factors; Sleep Maintenance Problems, Co-Sleeping Behaviours, Bedtime Routines, Bedtime Resistance, Bedtime Worries and Bedtime Fears. Study 2 comprised a confirmatory factor analysis (CFA) and tests of convergent validity (n = 313), with results confirming the factor structure and providing evidence for convergent validity through correlations in expected directions between KIPS scores and other sleep, anxiety and behaviour measures. Study 3 tested the test-retest reliability of the KIPS (n = 53), and found support for the temporal stability of the KIPS over a 2-week period. Overall, the results provide strong preliminary evidence for the validity of the KIPS total score and its subscales, although the Bedtime Routines subscale may be less useful.

Child

Sleep

Assessment

Measure

Insomnia

sleep problems

paediatric

Sleep problems in childhood are qualitatively different to those experienced in adolescence and adulthood. Only a minority of children experience biologically driven sleep problems such as respiratory disorders (e.g., sleep apnoea) and parasomnias (e.g., nightmares, night terrors, sleep walking, sleep paralysis, and confusional arousals). Instead, the vast majority of child sleep problems are behavioural and include difficulty falling asleep or staying asleep, bedtime resistance, and / or having difficulty sleeping without a parent being present or without parental support (Hoyniak et al., 2020). For this reason, the International Classification for Sleep Disorders, 3rd Edition (ICSD-3; American Academy of Sleep Medicine, 2014) lists ‘Behavioural Insomnia of Childhood’ as a specific subtype of insomnia for paediatric populations. Behavioural insomnia afflicts 10–30% of children (Trosman & Ivanenko, 2021), is unlikely to remit if left untreated (Falch-Madsen et al., 2020), and is associated with numerous problematic consequences both in the short- and long-term. Indeed, it has been linked cross sectionally and longitudinally to impaired academic performance, reduced cognitive functioning, anxiety related disorders, depressive disorders, schizophrenia spectrum and bipolar related disorders, behavioural disturbances, and obesity, as well as maternal depression and parental and family related stress (Gregory & Sadeh, 2016; Meltzer & Mindell, 2007, 2014).

Given the high prevalence and deleterious outcomes of behavioural insomnia in children, early intervention is vital. However, to successfully treat behavioural insomnia, clinicians must first a) obtain specific information around the child’s sleep patterns and problems and b) conceptualise the child’s difficulties by determining factors underpinning and contributing to a child’s particular sleep problem(s). With respect to specific information around a child’s sleep patterns and problems, information regarding sleep and wake times, sleep onset latency (the time it takes a child to fall asleep after being put to bed), sleep duration, number and frequency of daytime naps, and the number and frequency of night-time awakenings, is required. Such information allows the clinician to determine the type of behavioural sleep problem a child demonstrates (i.e., problems with sleep onset, sleep duration, sleep maintenance, and / or developmentally inappropriate sleep and wake times). In addition, information pertaining to the existence of parasomnias or respiratory problems is essential, as such difficulties require a treatment approach that is different to that taken for behavioural sleep problems.

In terms of conceptualising a child’s behavioural sleep problem(s), clinicians require information on a range of factors that may underly and / or contribute to, the child’s particular sleep difficulty. The pathophysiology of sleep related problems can be complex – especially among paediatric populations, with a number of potential child and parent factors at play. Parent factors include poor implementation of bedtime routines, allowance of poor sleep hygiene, and engagement in co-sleeping. Bedtime routines implemented by parents can inadvertently contribute to child sleep problems if implemented inconsistently (e.g., varied timing of pre-bedtime activities), incorrectly (e.g., placing a child to bed too early or late), or not at all (Paine & Gradisar, 2011). In particular, a poor bedtime routine disrupts sleep onset and therefore reduces sleep duration, as the parent struggles to get the child to bed at the desired time. Similarly, inadequate sleep hygiene behaviours such as engaging in alerting pre-bedtime activities, child consumption of caffeinated food and drinks, and non-sleep conducive environments, have all been linked with sleep impairment in childhood by making it physiologically difficult for a child to sleep (Gregory & Sadeh, 2016; Mindell et al., 2009). Finally, when parents and children co-sleep, the child becomes dependent on the parent to feel safe at night and to initiate and maintain sleep, disallowing the opportunity for the child to learn to fall asleep alone (Paine & Gradisar, 2011; Thompson-Hollands et al., 2014).

With respect to child factors that may contribute to behavioural sleep problems, oppositional behaviour at bedtime, worry at bedtime, bedtime fears, and an inability to return to sleep unaided, are all difficulties that may underlie or contribute to, a child’s sleep problem. Both oppositional behaviour and anxiety have shown strong associations with sleep problems in children (Gregory et al., 2004; Gregory & O'Connor, 2002; Hatzinger et al., 2013). Oppositional behaviour at bedtime is also referred to as bedtime resistance and includes a range of behaviours such as crying, tantruming, refusal to bathe and put on pyjamas, refusal to get into bed and stay in bed, and running away from parents. Anxiety and sleep problems have a similarly strong association in children, manifesting as worry at bedtime (e.g., about upcoming or past events and interactions) and / or specific bedtime fears (such as separation concerns, fear of the dark, monsters, burglars etc). Both anxiety and bedtime resistance serve to physiologically and cognitively arouse the child and / or delay them getting into bed, thus delaying sleep onset and reducing sleep duration (Meltzer & Mindell, 2006). Finally, inability to return to sleep unaided may also underpin sleep problems in children. All people, including children, ‘wake’ during the night, but most can put themselves back to sleep immediately, often without realising they have woken (Moore et al., 2007; Sadeh, 1994). However, some children exhibit difficulty putting themselves back to sleep (commonly referred to as sleep maintenance problems), which contributes to an increase in the duration of night awakenings and a reduction in overall sleep duration (Moore et al., 2007; Sadeh, 1994).

It is clear from the above discussion that the same sleep patterns or problems (e.g., difficulty with sleep onset, maintenance, or duration) may be the result of different underlying or contributing factors (co-sleeping, bedtime resistance, sleep hygiene, bedtime fears or worries, problems with sleep maintenance, and / or poor bedtime routines), each of which require different cognitive behavioural treatment strategies. The development of a comprehensive, multidimensional measure that assesses factors underpinning and contributing to behavioural insomnia in childhood, would therefore be of significant value to clinicians as it would assist with conceptualisation and treatment planning. To date, although numerous scales in the literature purport to measure child sleep problems, they are limited by poor psychometric properties, lack of psychometric evaluation, and/or reduced assessment scope, Indeed, none of the childhood sleep scales currently available provide a comprehensive and valid assessment of the factors underpinning and contributing to, child behavioural sleep problems.

Existing Measures of Paediatric Sleep Problems

An initial review by Spruyt and Gozal (2011) of scales assessing paediatric sleep problems, found that only two scales (the Sleep Disorders Inventory for Students- Child (Bruni et al., 1996) and the Sleep Disturbance Scale for Children (Shahid et al., 2012)) met all appropriate methodological and psychometric scale development criteria. An examination of the items comprising these scales however, reveals that they assess the physiological and medical aspects of sleep problems in children (e.g., excessive daytime tiredness, breathing difficulties, sleep related movement disorders and parasomnias) rather than the underpinning and contributing factors of behavioural insomnia that are targeted in cognitive behavioural treatment programs. Further, although the Sleep Disturbance Scale for Children includes items assessing issues such as bedtime resistance and anxiety, they are represented by a single item only (e.g., ‘the child goes to bed reluctantly’, ‘the child feels anxious or afraid when falling asleep’), and together comprise a larger factor measuring overall problems with sleep initiation and maintenance (Bruni et al., 1996). Although these scales are useful for the identification of paediatric sleep problems, they are less useful for providing a comprehensive assessment of the potential factors underpinning such problems and informing targets for treatment.

A recent updated review conducted by Sen and Spruyt (2020) reported on an additional 27 novel paediatric sleep tools developed since the initial review. Importantly, only two of the additional new scales met the outlined criteria for adequate development, with neither scale purporting to assess the underpinnings and contributing factors of behavioural paediatric insomnia. Specifically, the SNAKE questionnaire (Blankenburg et al., 2013) evaluates paediatric sleep issues and conditions associated with severe psychomotor impairment, whilst the Narcolepsy Quality of Life-21 (NARQoL-21; Chaplin et al., 2017) assesses the quality of life of children with narcolepsy. Thus, within the literature there appears to be a lack of well validated psychometric tools developed for the specific purpose of providing a multidimensional assessment of the potential factors underpinning behavioural insomnia in children.

Currently, the most popular measure of child behavioural sleep problems is the Child Sleep Habits Questionnaire (CSHQ; Owens et al., 2000). The CSHQ assesses sleep problems and their aetiology via eight domains: bedtime resistance, sleep onset delay, sleep duration, sleep anxiety, night waking, parasomnias, sleep disordered breathing and daytime sleepiness. However, the CSHQ is not without limitations. For example, the bedtime resistance subscale contains items that appear to measure resistance (e.g., ‘struggles at bedtime’), fear (e.g., ‘afraid of sleeping alone’), routine (e.g., ‘goes to bed at the same time’), and co-sleeping (‘needs a parent in the room to sleep’). While it is reasonable to assume that each of these problems could result in, or cause, resistance at bedtime, the extent of resistance is not actually assessed, and the reasons for resistance are not differentiated. Further, while issues such as co-sleeping, bedtime fears, and lack of a bedtime routine constitute important avenues for psychological intervention, a one-item assessment does not allow for the assessment of problem severity, meaning that primary and secondary issues are more difficult to determine, and treatment response is more difficult to assess. Most importantly perhaps, the psychometric properties of the CSHQ have recently come into question. In the review by Spruyt and Gozal (2011), it was noted that the questionnaire lacked a number of key methodological and psychometric criteria (i.e., pilot testing, item analyses, factor analyses, confirmatory factor analyses and norm generation). Moreover, in the paper reporting the scale’s development, only one subscale (bedtime resistance) was shown to demonstrate good internal consistency (i.e., Cronbach’s alpha > .70; (Owens et al., 2000). Thus, despite the popularity of the CSHQ, the brevity and limited psychometric testing of this measure place a ceiling on its clinical and empirical usefulness.

It is clear from the above discussion that a comprehensive, clinically useful, well operationalised and psychometrically validitated measure of the factors known to underlie behavioural sleep problems in childhood is currently lacking. The overarching aim of the current research therefore, was to develop and psychometrically evaluate across a series of three studies, the Kids Insomnia Problems Scale (KIPS). Study 1 documents the development of the KIPS items and the exploratory factor analysis conducted on the items produced. Study 2 reports on the confirmatory factor analysis and subsequent testing of the KIPS’ convergent validity. Finally, Study 3 assesses the KIPS in terms of its 2-week test-retest reliability.

The aim of Study 1 was to develop the KIPS, a novel multidimensional parent-report measure of the important domains contributing to behavioural insomnia in children aged 3–12 years. As noted above, it is important for clinicians to both obtain specific information around the child’s sleep patterns and problems and to conceptualise the child’s sleep problem(s) by determining factors underpinning and contributing to them. The KIPS therefore comprises two sections, 1) a more general sleep and bedtime information section and 2) a psychometric measure of six theoretically derived factors that underlie and contribute to, child sleep problems. In this way, the KIPS is similar to other measures developed for both clinical and research purposes such as the Child Behaviour Checklist (CBCL; Achenbach, 1991) and the Eating Disorder Inventory (EDI; Garner, 2004; Garner et al., 1983).

Section 1: Specific Sleep Information. Section 1 included three sub-sections: sleep diary information, sleep hygiene behaviours, and parasomnias / respiratory problems. Although important for clinicians to assess, sleep diary information (e.g., sleep and wake times, naps, wakings during the night etc) was not possible (or appropriate) to include in Section 2 (the psychometric questionnaire), and therefore was included in Section 1. Similarly, sleep hygiene information is critical for clinicians to gather, yet the behaviours are very specific, do not tend to co-occur, and therefore do not ‘hang together’ as a subscale. As such, sleep hygiene items were included in Section 1 rather than Section 2. Finally, given that parasomnias and respiratory difficulties require different psychological interventions to those considered standard for behavioural insomnia, and/or indeed may require medical intervention, the presence of parasomnias and respiratory issues was also screened for in Section 1.

Section 2: Psychometric Measure. Section 2 consisted of the psychometric measure that is the focus of this paper. It included 6 factors that, from a cognitive-behavioural perspective, are thought to underly and / or contribute to, sleep problems in children: Bedtime Routines, Bedtime Fears, Bedtime Worries, Bedtime Resistance, Sleep Maintenance Problems, and Co-Sleeping Behaviours. It was hypothesised that the exploratory factor analysis (EFA) of these items would produce 6 factors corresponding to the 6 constructs.

Study 1 Method

Participants

The participants were 328 men and women aged between 18 and 56 years (M = 36.47, SD = 5.85), who reported being either the mother (95.4%), father (2.7%), grandparent (0.3%) or caregiver (1.5%) of a child aged between 3 and 12 years. Another 34 participants began the questionnaire but were excluded due to obviously erroneous data entry, failure to consent, or having children outside the selected age range. Supplementary Tables 1 and 2 report detailed demographic information for parents and children respectively. Of the participants, 10.7% were university students, 37.2% reported a bachelor degree as their highest level of education, 46% reported a household income between $100,001 and $200,000, 78.3% were employed full time or part time, and 89.9% were Australian Caucasian. Of the participants in the sample, 55.2% reported having a child aged 3–5 years. Most participants (97.9%) reported having a child without any formal mental health, sleep or developmental diagnosis. Of the sample, 30.2%, 8.2% and 6% of the sample believed that their child had a mild, moderate and severe sleep problem respectively.

Measures

Caregiver Demographics. Participants were asked a series of single item demographic questions relating to their gender, age, level of education, marital status, household income, ethnicity, and relationship to the child.

Child Demographics. Participants were asked a series of demographic questions relating to the child’s age, ethnicity, family structure and caregiver arrangements, number of siblings, and the presence of any formal diagnoses.

Self-Reported Sleep Problems. Participants were asked to rate (irrespective of any formal diagnosis) whether they felt their child suffered with a sleep related problem. Participants indicated their answer on a four-point Likert-type scale, where 0 = no problem, 1 = mild problem, 2 = moderate problem, and 3 = severe problem.

The KIPS Measure.Section 1: Specific Sleep Information. As noted above, Section 1 of the KIPS included 3 sections assessing sleep diary information, sleep hygiene, and the presence of parasomnias / respiratory issues. With respect to sleep diary information, Section 1 required parents to consider the past week, and to indicate their child’s usual wake time, bed-time, and time they fall asleep on both weekdays and weekends. It also required them to report on the frequency and duration of night awakenings, and the frequency and duration of daytime naps. With respect to sleep hygiene information, parents were asked to consider the past week, and to indicate how true each of 8 items (assessing use of screens, hunger / fullness before bed, use of bed for play, rough and tumble play before bed, consistent bed time / wake time, caffeinated food and drink in the late afternoon / evening), were for their child on a 6-point scale from 0 (never true) to 5 (always true). In terms of screening questions for parasomnias and respiratory problems, parents were asked to consider their child’s sleep over the past week, and indicate how true they thought each of 6 statements (my child wakes in the night with panic or fear from a nightmare/night terror; my child has nightmares; my child wets the bed; my child snores loudly; my child stops breathing/snorts/gasps in their sleep; my child sleepwalks) were for their child on a six-point scale from 0 (never true) to 5 (always true).

Section 2: Psychometric Questionnaire. Items for Section 2 of the KIPS were generated from a comprehensive review of the paediatric sleep literature as well as consultation with experts in child sleep and anxiety (clinical and research experts), and a critical review of existing scales. A scale blueprint (i.e., the hypothesized factor structure) was created and served as a framework for item creation (Rust & Golombok, 2014). Items were then created specifically to tap each content area (i.e., factor). An initial 44 items were developed to address six key content areas (i.e., Bedtime Routines [5 items], Bedtime Fears [8 items], Bedtime Worries [5 items], Bedtime Resistance and/ or Oppositional Bedtime Behaviour [12 items], Sleep Maintenance Problems [7 items] and Co-Sleeping Behaviour [7 items]).

Items (for both sections of the KIPS) were written to avoid double-barrelled questions and complex wording, and included a mix of positively and negatively worded items. Insurance against ambiguity of items and indecisiveness, acquiescence and social desirability were tackled at the item development and expert review stages. The expert panel, consisting of 7 researchers from the USA and Australia, who had published scales or other research in paediatric mental health, were consulted on the six content areas and the appropriateness of items generated for each content area, including item phrasing. Clark and Watson (2019) suggest erring on the side of over-inclusiveness when generating initial items, and to rely on the subsequent psychometric analysis to identify weak or unrelated items. For this reason, items that were unanimously identified as being problematic, were deleted at the expert review stage, and other problematic items were flagged for review in the psychometric stages.

The instructions for the scale were as follows; “Below is a series of statements that describe a range of bedtime and sleep related behaviours your child might demonstrate. We would like you to think about your child and their behaviour over the pastweekwhen responding to the questions below. If there was a reason that the last week was unusual (such as your child was unwell or there was a holiday period), respond to the questions based on a typical week. Please think about the following statements in relation toyour child and household, and rate how true each of the following statements are, using the following scale:” The six-point scale ranged from 0 (never true), to 5 (always true), and subscale items were summed so that higher scores reflected greater sleep related difficulties. Thus, the asterisked items displayed in Table 1 are reverse scored before summing. A total score was obtained by summing the KIPS subscale scores.

Procedure

Approval for the study was granted by the BLINDED FOR REVIEW University Human Ethics Review Committee (HREC: 2019/785). All student participants were recruited through the psychology student subject pool, and all non-students were recruited through the university email call for research volunteers, and via social networking sites (e.g., Facebook). Recruitment material informed potential participants of eligibility criteria for participation (i.e., a primary caregiver of a child aged between 3 and 12 years) and provided a web link that directed them to the online survey hosted on Qualtrics. After clicking on the link, individuals were directed to a downloadable information sheet and consent form that outlined the purpose of the study, participation requirements, and confidentiality. The information sheet informed participants that the research was being conducted to develop a new measure of child sleep related problems, and that they would be asked to answer a series of questions related to child sleep, family life, and personal experiences as a parent. Participants were then instructed to indicate, via radio buttons, that they had read the information and consent forms and consented to participate in the research. Only those who provided informed consent went on to complete the questionnaire battery. Following completion of the questionnaire, participants were invited to enter their name into a draw to win one of ten $50 gift vouchers (non-students) or gain course credit (students) for their participation.

Study 1 Results

Preliminary Analyses

Barlett’s test of sphericity was significant (χ2 = 6053.34, df = 378, p < .001) and the Kaiser–Meyer–Olkin value was .90, indicating that the initial 44 KIPS items were appropriate for factor analysis. Additionally, all measures of sampling adequacy taken from the diagonal of the anti-image correlation table were = > .80.

Exploratory Factor Analysis

Prior to exploratory factor analysis (EFA), items were removed if they met two or more of the following criteria: 1) item redundancy or insufficient correlations with other items (i.e., inter-item correlations of r > .8 or < .2 respectively), 2) poor item statistics (i.e., if all response options were not utilized), and 3) age bias (i.e., if a singular item correlated (r > .35) with the reported age of the parent (Clark & Watson, 1995; Rust & Golombok, 2014). As a result, 11 items were excluded from further analyses, leaving 33 items for the EFA.

The first EFA resulted in the extraction of six factors with eigenvalues greater than 1 (i.e., 11.32, 3.33, 2.98, 2.63, 1.59, and 1.42 respectively). Parallel analysis revealed 15 eigenvalues greater than 1, the first six of which (i.e., 1.65, 1.56, 1.49, 1.44, 1.39, and 1.35 respectively) were smaller than those extracted through EFA (O’Connor, 2000). Inspection of the scree plot revealed an inflection point between 6 and 7 factors. Thus, results converged on a 6-factor structure. Inspection of the pattern matrix revealed that all factors aligned with the hypothesised blueprint.

Items loading on the six factors were evaluated for deletion against the following criteria; 1) poor factor loadings (i.e., loadings < .40) or small communalities (i.e., < .40), 2) cross-loadings on two or more factors (i.e., loadings > .3 on the second factor), 3) a lack of conceptual/face validity (i.e., if the loading of an item on a factor did not align with theory or the designed blueprint), and 4) constitution of part of a non-robust factor (i.e., a factor with < 3 items; Clark & Watson, 1995; Comrey, 1988; Floyd & Widaman, 1995; Guttman, 1954; Rust & Golombok, 2014). Subsequently, 8 items were removed, resulting in a final set of 25 items.

In a final EFA of the 25 items (see Table 1), six factors had eigenvalues greater than 1 and explained 73.4% of the variance in the items. The final items, factor loadings, and scale statistics are presented in Table 3. The factors were labelled; Sleep Maintenance Problems (4 items), Co-Sleeping Behaviours (4 items), Bedtime Routines (5 items), Bedtime Resistance (5 items), Bedtime Worries (3 items) and Bedtime Fears (4 items). Factor 1, Sleep Maintenance Problems, had an eigenvalue of 8.16 and accounted for 32.65% of the variance in the items. The four items loading highly onto this factor reflected the extent to which children have difficulty putting themselves back to sleep after waking and had loadings that ranged from .83 to .51. Factor 2, Co-Sleeping Behaviours, contained four items reflecting the extent to which parents and children engage in co-sleeping at night, with loadings ranging from .95 to .72. The five items loading onto Factor 3, Bedtime Routines, ranged from .85 to .55 and reflected the extent to which families consistently engage in a bedtime routine. Factor 4, Bedtime Resistance, contained five items reflecting the extent to which children exhibit oppositional behaviour at bedtime and resist the bedtime process, with item loadings ranging from .84 to .69. The three items loading onto Factor 5, Bedtime Worries, reflected the extent to which children’s worries interfere with sleep, with loadings ranging from .87 to .69. Finally, Factor 6, Bedtime Fears, contained four items reflecting the extent to which children demonstrate night-time related fears, with loadings ranging from .86 to .61. All factors were significantly correlated with each other (r’s ranged from .11 to .52). Cronbach’s alphas were acceptable to high for all subscales (α’s of .88, .93, .82, .88, .85, and .86 respectively for Factors 1–6) and Cronbach’s alpha for the total composite score was high (α = .91).

The aims of Study 2 were to confirm the factor structure of the 25-item KIPS developed in Study 1, investigate the possibility of a higher order factor structure, and assess convergent validity through correlations with existing measures of behavioural sleep problems, anxiety and externalising behaviours. It was hypothesised that: 1) the factor structure of the KIPS would be confirmed; 2) that there would be positive associations between the KIPS Bedtime Fears subscale, the KIPS Bedtime Worries subscale, and measures of child anxiety, sleep anxiety, bedtime resistance and night waking; 3) that there would be positive associations between the KIPS Co-Sleeping Behaviours subscale and measures of child anxiety and sleep anxiety; 4) that there would be positive associations between the KIPS Bedtime Resistance subscale and measures of child anxiety, sleep anxiety, bedtime resistance and externalizing behaviour and; 5) that there would be positive associations between the KIPS Bedtime Routine subscale, the KIPS Sleep Maintenance Problems subscale, and a measure of night waking.

Table 1

Study 1 EFA and Study 2 CFA Factor Loadings for the KIPS Items
		Study 1: EFA Factor Loadings						Study 2: Standardised Factor Loadings
	Mean (SD)	SM	CS	BRo	BRe	BW	BF	SM	CS	BRo	BRe	BW	BF
1. My child sleeps through the whole night*	2.8 (1.7)	.83						.83
2. My child wakes up during the night and wakes another family member	2.8 (1.6)	.75						.87
3. After falling asleep, my child wakes and calls out	2.2 (1.4)	.73						.75
4. My child repeatedly gets out of their bed at night time	2.2 (1.4)	.51						.69
5. At night, my child sleeps in the same bed as me, or another family member	2.6 (1.8)		.95						.85
6. My child sleeps alone in their bed throughout the night*	2.7 (1.9)		.89						.93
7. My child refuses to sleep in their own room by themselves	2.5 (1.8)		.82						.77
8. My child falls asleep, by themselves, in their own bed*	2.9 (2.0)		.72						.72
9. In our household, there is a set order of activities before bed*	2.2 (1.2)			.85						.86
10. In our household, all caregivers follow the same bedtime routine with my child*	2.2 (1.2)			.71						.75
11. In our household, the activities before my child’s bedtime are the same each night*	2.2 (1.0)			.69						.85
12. My child knows the activities they need to do before bed*	1.8 (1.0)			.66						.84
13. I attempt to put my child to bed at the same time each night (within 15 minutes)*	1.9 (1.0)			.55						.67
14. My child does things to delay going to bed	3.4 (1.4)				.84						.87
15. My child does not follow instructions bedtime	2.4 (1.2)				.82						.73
16. My child tantrums when asked to do things at bedtime	2.2 (1.2)				.75						.66
17. My child does not want to go to bed	3.2 (1.4)				.71						.80
18. At bedtime, my child makes repeated requests (e.g., for a drink, for food, for a cuddle)	2.8 (1.4)				.69						.77
19. My child worries about many different things when in bed	2.0 (1.2)					.87						.87
20. My child lies awake at night worrying	1.8 (1.0)					.80						.92
21. My child finds it difficult to sleep because they can't stop thinking	2.7 (1.5)					.69						.78
22. My child is scared of monsters, witches, or other scary things at night time	2.2 (1.3)						.86						.83
23. My child gets scared at bed / night time	2.1 (1.2)						.73						.89
24. My child is frightened of the dark	2.8 (1.6)						.72						.68
25. My child needs someone to tell them it's OK at night (e.g., about the dark, being alone, safety, monsters)	2.5 (1.5)						.61						.78
Eigenvalues		8.16	2.85	2.59	2.15	1.38	1.23	-	-	-	-	-	-
Item variance explained, %		32.65	11.38	10.35	8.60	5.52	4.91	-	-	-	-	-	-
Cronbach’s α		.88	.93	.82	.88	.85	.86	.86	.88	.92	.88	.89	.89
Mean (Standard deviation)		6.01 (5.23)	6.68 (6.75)	5.28 (4.19)	9.00 (5.54)	3.58 (3.31)	5.60 (4.74)	6.54 (4.97)	6.91 (6.14)	5.62 (5.12)	10.11 (5.54)	4.26 (3.89)	5.80 (4.77)
Note in study 1 EFA, all factor loadings below .20 are suppressed. CFA is based on MLR estimation. See text for explanations of analyses used in Study 1 and Study 2. Asterisked items are reverse scored.

Study 2 Method

Participants

The participants were 313 men (4.2%) and women (94.9%) aged between 21 and 55 years (M = 36.22 SD = 5.40), who reported being either the mother (93%), father (3.5%), grandparent (.6%), relative (1.9%) or other primary caregiver (1%) of a child aged between 3 and 12 years old. Another 99 participants began the questionnaire but were excluded because they did not indicate consent to their data being used for the study, or did not go on to begin the questionnaire after signing up. Detailed demographic data for the sample is provided in Supplementary Tables 1 and 2. Of the participants in the sample, 14.4% were university students from various campuses within Queensland Australia, 31.3% (majority) reported a bachelor's degree as their highest level of education, 41.9% reported a household income of between $100,000 - $2000,000 a year, 43.5% were employed casually or part time, and 86.6% were Australian Caucasian. Of the participants in the sample, 57.2% reported having a child aged between 3–5 years. Most participants (93.3%) reported having a child without any formal mental health, sleep or developmental diagnosis. Of the sample, 33.5%, 16% and 2% of the sample believed that their child had a mild, moderate and severe sleep problem respectively.

Measures

Caregiver Demographics, Child Demographics and Self-Reported Sleep Problems. Child and parent demographic items were identical to those used in Study 1.

Child Sleep Habits Questionnaire (CSHQ; Owens et al., 2000). The CSHQ is a 33-item, parent-report measure designed to assess common sleep behaviours in children aged 4 to 12 years. Respondents are required to rate the frequency with which each item has occurred in the last week on a three-point Likert scale from 1 (rarely; 0–1 night per week) through 2 (sometimes; 2–4 nights per week) to 3 (usually; 5–7 nights per week). Eight subscales relating to Bedtime Resistance, Sleep Onset Delay (1 item), Sleep Duration, Sleep Anxiety, Night Wakings, Parasomnias, Daytime Sleepiness and Sleep Disordered Breathing, may be derived. In addition to the total score, the current study utilised the Bedtime Resistance, Sleep Anxiety and Night Waking subscales. The scale has been used with parent samples of children aged 2–12 years (Boergers et al., 2007), it meets the minimal levels for acceptable reliability in community samples (α = .68), and it has demonstrated adequate reliability in clinical sleep disordered samples (α = .78; Owens et al., 2000). The internal consistency for the total composite score in the present study was good (α = .84). The internal consistencies of the bedtime resistance, sleep anxiety and night waking subscales were variable in the current study, with α = .77, α = .64, and α = .71 respectively.

Anxiety. Two age-appropriate anxiety measures were used: The Preschool Anxiety Scale (PAS; Spence et al., 2001) and the Spence Children’s Anxiety Scale- Parent (SCAS-P; Nauta et al., 2004). The PAS is a 28-item parent rated scale designed to assess anxiety in children aged 3–6 years and was completed by participants with a child aged 3–6 years. Respondents are required to rate on a 5-point scale from 0 (not at all true) to 4 (very often true), the frequency with which each item is true for their child. Items are summed to produce a total score that may range from 0–28, with higher scores reflecting higher anxiety. The PAS has demonstrated strong psychometric properties and excellent internal consistency in prior studies (Spence et al., 2001). The internal consistency of the total SCAS composite in the present study was excellent (α = .92).

The SCAS-P is a 38-item parent report scale developed to assess anxiety symptoms in children aged 7–18 years, and was completed by participants with a child aged 7–12 years. Respondents are required to rate the frequency with which each item applies to their child on a scale from 0 (never) to 3 (always). Items are summed to produce a total score that may range from 0-114, with higher scores reflecting higher levels of anxiety. The SCAS total score has demonstrated high internal consistency in previous studies (α = .89; Nauta et al., 2004) and excellent internal consistency in the present study (α = .92).

Conduct Problems subscale of the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997). The Conduct subscale of the SDQ is a 5-item, parent-rated behavioural screening questionnaire for young people aged 2–17 years. It consists of two versions, one for children aged 2–4 years, and one for children aged 5–17 years. The two versions are consistent, although the wording on several items differs to ensure age appropriateness (e.g., often argumentative with adults [young child] versus often lies or cheats [child]). Items are scored from 0 (not true), through 1 (somewhat true), to 2 (certainly true), with subscale scores therefore ranging from 0–10, and higher scores indicating greater behaviour problems. The SDQ has displayed good psychometric properties in previous research (Goodman et al., 2010). In the current sample, the conduct subscale showed good internal consistency across both younger (α = .72) and older (α = .68) child samples.

Procedure

The procedure of Study 2 was identical to that of Study 1.

Overview of Study 2 Data Analyses. AMOS v25 (Arbuckle, 2006) was used to conduct a confirmatory factor analysis (CFA) using maximum likelihood estimation. Model fit was determined using χ², root mean square error of association (RMSEA), the standardized root-mean-square residual (SRMR), the comparative fit index (CFI) and the Tucker–Lewis Index (TLI). Guidelines suggest that a non-significant χ² is indicative of good model fit. However, this statistic is known to be sensitive to sample size, meaning that even trivial deviations from a perfect model are often statistically significant in samples as large as that used in this study. Bollen (1989) therefore recommends dividing the χ² by the degrees of freedom, with ratios of 2–3 representing good fit. RMSEA values below .05 are considered good, values between .05 and .08 are considered indicative of fair fit, and values between .08 and .10 are considered an indication of mediocre fit (Hu & Bentler, 1999; Kaplan, 2008). SRMR values of < .08 indicate good model fit (Bentler, 1990). CFI and TLI values > 0.90 indicate acceptable model fit, and values > 0.95 indicate good model fit (Kaplan, 2008). Internal consistency was assessed using Cronbach’s α. Convergent and discriminant validity were tested using bivariate correlations between the KIPS, the CSHQ subscales, the SDQ, the PAS and the SCAS-P.

Study 2 Results

Prior to analyses, descriptive statistics were checked for skew and outliers. The results revealed 10 univariate outliers greater than 3 standard deviations from the mean. These participants were excluded from further analyses, leaving a final sample of 303. The CFA was performed with all items allowed to load only onto their respective factors, and factors allowed to covary as per the EFA results and a-priori theory. Although the CFA produced a significant χ² (260, N = 303) = 635.53 p < .001, the ratio of χ² to df was 2.4 indicating a good fit of the model to the data (Bollen, 1989). Other fit indices indicated that the CFA had an acceptable to good fit to the data (CFI = 0.92, IFI = 0.92, TLI = 0.91, RMSEA = 0.06, SRMR = 0.05; (Hooper et al., 2008; Hu & Bentler, 1999; Kaplan, 2008). Table 1 presents the standardized confirmatory factor loadings for each item, as well as the Cronbach’s α for each subscale. As shown in Table 2, the correlations between each of the KIPS subscales ranged from weak to moderate (r = .09 − .55).

In accordance with apriori theory, a second higher order model was tested, with the results also revealing good model fit (CFI = 0.91, IFI = 0.91, TLI = 0.90, RMSEA = 0.07, SRMR = 0.07. The loadings on the second order ‘sleep problems’ factor were Bedtime Resistance (.57), Co-Sleeping Behaviours (.53) Bedtime Fears (.69), Bedtime Routines (.20), Bedtime Worries (.54) and Sleep Maintenance Problems (.73). In addition, a general factor model was fit, whereby all 25 items were allowed to load onto a single sleep problems factor. This model had a poor fit to the data, χ²(275, N = 303) = 3435.26, p < .001. RMSEA = 0.19, CFI = 0.34, TLI = 0.28, IFI = 0.35, SRMR = 0.16. Item loadings were mostly adequate, ranging from .15-.61.

Convergent validity. Table 2 reports the bivariate correlations between the KIPS total score and subscale scores, and the convergent validity variables (i.e., the CSHQ-Total, CSHQ- Bedtime Resistance, CSHQ-Sleep Duration, CSHQ-Sleep Anxiety, CSHQ-Night Wakings, SCAS, PAS, and the SDQ). The majority of predicted correlations were significant, in the predicted directions, and were of moderate to high strength. The exception to this more general rule was the Bedtime Routines subscale, that was not found to correlate with a measure of night waking (and was not predicted to do so).

Table 2

Study 2 Correlations between the KIPS Subscales, KIPS Total Score, and Convergent Validity Measures
	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	Mean	SD
1. KIPS Total	1															40.27	19.48
2. KIPS BRe	.57**	1														2.05	0.69
3. KIPS CoS	.66**	.14*	1													1.73	1.53
4. KIPS BF	.71**	.36**	.32**	1												1.37	1.14
5. KIPS BW	.60**	.41**	.11**	.55**	1											1.43	1.29
6. KIPS SM	.72**	.35**	.42**	.42**	.37**	1										1.54	1.13
7. KIPS BRo	.36**	− .06	.20**	− .02	− .01	.09	1									1.12	1.03
8. CSHQ Total	.79**	.43**	.60**	.45**	.46**	.67**	.22**	1								47.00	8.83
9. CSHQ BR	.67**	.24**	.84**	.36**	.19**	.41**	.22**	.70**	1							9.06	3.08
10. CSHQ SA	.69**	.26**	.68**	.59**	.34**	.50**	.04	.71**	.80**	1						6.27	2.16
11. CSHQ NW	.57**	.25**	.46**	.30**	.21**	.81**	− .02	.62**	.41**	.48**	1					4.62	1.80
12. SCAS	.62**	.36**	.28**	.58**	.66**	.36**	.13	.50**	.34**	.44**	.24**	1				33.86	20.86
13. PAS	.56**	.33**	.31**	.61**	.60**	.34**	.11	.39*	.39**	.57**	.27*	-	1			20.00	15.19
14. SDQ_C_YC	.36**	.40**	.16	.22*	.27**	.33**	.05	.43**	.27*	.27**	.34*	-	.13	1		2.28	1.87
15. SDQ_C	.31**	.42**	.11	.09	.21**	.23**	.08	.38**	.24**	.17*	.15*	.26**	-	-	1	2.92	1.35
Note. * = p < .05, **= p < .01. KIPS = Kids Inventory for Problematic Sleep, Total = composite score, BRe = bedtime resistance, CoS = co-sleeping, BF = bedtime fears, BW = bedtime worries, SM = sleep maintenance, Bro = bedtime routines, CSHQ = Child Sleep Habits Questionnaire, BR = bedtime resistance, SD = sleep duration, SA = sleep anxiety, NW = night waking, SCAS = Spence Childhood Anxiety Scale, PAS = Preschool Anxiety Scale, - = NA due to different age sample used, SD = standard deviation.

The aim of Study 3 was to investigate the temporal stability of the KIPS over a 2-week period.

Study 3 Method

Participants

The participants were 53 mothers aged between 24 and 46 years (M = 36.77, SD = 4.45), of a child aged between 3 and 12 years. Of the participants in this sample, 84.9% were employed (45.3% part-time, 39.6% fulltime), 41.5% reported a bachelor degree as their highest level of education, 60.4% reported a household income of between $100,001 and $200,000, 73.6% were married, and 96.2% were Caucasian Australian. Of the participants in the sample, 56.6% reported having a child aged 3–5 years, 34.0% believed that their child had mild sleep problems, and 13.2% believed that their child had moderate or severe sleep problems.

Measures

Caregiver Demographics, Child Demographics and Self-Reported Sleep Problems. Parent and child demographic questions were identical to those used in Studies 1 and 2.

Child Insomnia Problems. The Kids Insomnia Problems Scale (KIPS) was used.

Procedure

The same procedure used in Studies 1 and 2 was used in Study 3, with some minor exceptions. At the end of the Study 2 survey, participants were given the option to consent (via radio buttons) to participate in a short follow up survey in exchange for further course credit, or an extra nomination into the prize draw. The 100 participants who consented were instructed to create a personal code (consisting of a colour and animal e.g., rainbow otter) and enter it into a text box. They were then directed to a new survey site where they re-entered their code and email address so that their data could remain anonymous while being linked across the two time points. In the lead up to the follow-up assessment, participants were reminded (via email) several times to again complete the KIPS, and were sent a link to complete the survey within the allocated time frame (i.e., 48hrs +/- 2 weeks from study 2 completion). In the email body, participants were reminded of their unique code and instructed to enter it at the beginning of the Study 3 survey. Of the 100 participants who consented, 53 completed the follow up survey on time. Only participants who completed the repeated assessment in the two-week retest period were included in the analysis.

At Time 1, Cronbach's α ranged from .88 to .91 for the 6 subscales of the KIPS and was .91 for the composite KIPS score. At Time 2, Cronbach's α ranged from .85 to .91 for the 6 subscales of the KIPS and was .91 for the composite KIPS score. All 2-week test-retest reliability coefficients were strong, with r's ranging from a low of .84 (p < 0.01) for the KIPS Bedtime Resistance subscale to a high of .95 (p < 0.01) for the KIPS Co-Sleeping Behaviours subscale.

The goal of this series of studies was to develop and test the psychometric properties of a comprehensive parent-report measure of factors underpinning behavioural insomnia in children; the Kids Insomnia Problems Scale (KIPS). The KIPS was designed to assess six theoretically derived domains of behavioural insomnia in children: Bedtime Routines, Bedtime Fears, Bedtime Worries, Bedtime Resistance, Sleep Maintenance Problems, and Co-Sleeping Behaviours. From a CBT perspective, popular scales purporting to assess childhood sleep problems suffer conceptual drawbacks, including reliance on singular items to assess behavioural sleep issues (such as bedtime routines, and co-sleeping behaviour) or affective issues (such as night-time anxiety), or a predominant focus on medically related sleep problems (such as disordered breathing and parasomnias). Many of these scales also suffer from limited psychometric testing or display poor item statistics), limiting the usefulness of such measures for both research and clinical purposes (for a review, see Sen & Spruyt, 2020; Spruyt & Gozal, 2011). The KIPS was designed to address these gaps in the literature, through the development of a theory derived multidimensional measure of childhood behavioural insomnia problems, the items of which assess a range of parent and child factors that may underlie behavioural insomnia in children aged 3–12 years.

With minor exceptions, findings from the 3 component studies were consistent with hypotheses. The results suggested that the 25 component items of the KIPS loaded highly onto the six hypothesised factors (Bedtime Routine, Bedtime Fears, Bedtime Worries, Bedtime Resistance, Sleep Maintenance Problems, and Co-Sleeping Behaviours), that the reliabilities of the subscales and total score were high, that the total score and subscales correlated with associated measures in ways that supported convergent validity, and that the temporal stability of the instrument over a two-week period was high. Together, the results suggest that (with the exception of the Bedtime Routines subscale that is discussed in detail below), the KIPS subscales provide valid assessments of important parent and child factors that may underlie behavioural insomnia in childhood, and that the KIPS total score may have some utility as an indicator of overall child sleep problems. These results are first summarised and then discussed further in the paragraphs below.

Studies 1 and 2 respectively established and confirmed the factor structure of the KIPS, revealing six distinct and mostly correlated factors that aligned with theory to assess a variety of domains that contribute to behavioural insomnia in children. The first factor, Sleep Maintenance Problems, assessed the extent to which children have problems returning to sleep after waking through the night. The second factor, Co-Sleeping Behaviours, assessed the of child and parent co-sleeping behaviour. The third factor, Bedtime Routines, assessed the extent to which there is an established and consistently utilised bedtime routine within the household. The fourth factor, Bedtime Resistance, assessed the level of oppositional behaviour at bedtime, or behaviour designed to resist or delay bed and/or sleep time. The fifth factor, Bedtime Worries, assessed the extent to which children experience worry at night that interferes with sleep. The sixth factor, Bedtime Fears, assessed the degree to which night-time related fears disrupt sleep. Each of the KIPS subscales demonstrated positive associations with one another in Studies 1 and 2, with the exception of Bedtime Routines, which correlated only with the Co-Sleeping Behaviours subscale in Study 2. All subscales were found to correlate with the total score, and all scores including the total score, demonstrated strong internal consistencies. Finally, all KIPS subscales and the total score were found to predict child sleep problems (i.e., the CSHQ- total score). Together, these results provide strong preliminary evidence for the validity of the KIPS subscale scores as indicators of factors underpinning insomnia problems in children. Importantly, the results are consistent with the definition of Behavioural Insomnia in Childhood listed by the International Classification for Sleep Disorders (ISCD-3), which stresses the importance of considering factors pertaining to both parent (e.g., limit setting through routine, or the creation of negative sleep associations such as co-sleeping) and child (e.g., resistant behaviour, sleep onset/maintenance problems due to anxiety, or problematic sleep associations such as co-sleeping), in the assessment of behavioural insomnia in childhood (American Academy of Sleep Medicine, 2014).

While the abovementioned findings support the overall validity of the KIPS subscales, there are some important limiting features to consider and acknowledge. Importantly, the results suggest that the KIPS Bedtime Routines subscale may be less useful as an indicator of sleep difficulties in children compared to the other KIPS subscales. In particular, the results of Study 2 found that the Bedtime Routines subscale did not correlate with any of the other KIPS subscales except for Co-Sleeping Behaviours, and while the Bedtime Routines subscale was found to predict sleep problems, the association was only weak. These are unexpected findings given extant literature demonstrating the importance of bedtime routines for optimising sleep (Owens & Mindell, 2011). One explanation may lie in the wording of the subscale items. The KIPS items assess presence of a well implemented bedtime routine (e.g., ‘In our household, there is a set order of activities before bed’) and are then reverse scored to indicate potential problems. Previous literature in scale development has found that reverse-scored items are not always indicative of the opposite construct (Rodebaugh et al., 2007), and in the interest of measuring sleep difficulties, it may be that direct assessment of ‘problems’ with bedtime routine would improve representation of this construct. Future research should test this hypothesis.

A further aim of Study 2 was to establish the construct validity of the KIPS subscales. The pattern of correlations observed between the majority of KIPS subscales and the constructs they were hypothesised to relate to, were theoretically and intuitively consistent. Extant literature suggests that anxiety in paediatric populations can detrimentally affect sleep quality (Owens & Mindell, 2011; Price et al., 2019), and CBT theory and research suggests that paediatric anxiety is often associated with bedtime resistant behaviour and parental accommodation behaviour such as co-sleeping (Owens & Mindell, 2011; Ravid et al., 2021; Thompson-Hollands et al., 2014). In keeping with this prior research, the KIPS subscales of Bedtime Fears, Bedtime Worries, Co-Sleeping Behaviours and Bedtime Resistance were all associated with higher levels of child anxiety (as measured by the PAS and SCAS) and CSHQ sleep anxiety. The KIPS Bedtime Fears and KIPS Bedtime Worries scales also predicted higher CSHQ bedtime resistance and CSHQ night waking, while KIPS Bedtime Resistance was associated with CSHQ bedtime resistance and externalising behaviour (as measured by the SDQ). Finally, while the KIPS sleep Maintenance Problems scale was positively associated with CSHQ night waking, the KIPS Bedtime Routine subscale was not. This finding is contrary to considerable existing research indicating that behavioural interventions such as bedtime routines can improve overall sleep quality and reduce night awakenings (Meltzer & Mindell, 2014; Staples et al., 2015), and provides further evidence that the Bedtime Routines subscale has limitations that need to be addressed. However, the Bedtime Routines subscale aside, the results of Studies 1 and 2 highlight that the KIPS subscale scores correlate with each other, and with theoretically relevant constructs in ways that suggest they are distinct and valid domains of the parent-child factors underlying behavioral sleep problems in children.

Finally, given the research that sleep problems in childhood are unlikely to remit without intervention (Falch-Madsen et al., 2020), KIPS scores were expected to demonstrate test-retest reliability, with moderate temporal stability over a 2-week period. The results from Study 3 supported this hypothesis, suggesting that the KIPS scores are consistent over time.

Limitations and Directions for Future Research

The findings surrounding the Bedtime Routines subscale points to a potential limitation in the operationalization of this domain that should be addressed in future research. Additionally, the sensitivity and specificity of the KIPS was not tested in this series of studies, and therefore future research should ascertain the ability of the KIPS to discriminate between those with sleep problems and those without. Finally, the sample used in the current research was relatively homogenous. Future research with the KIPS would benefit from ensuring the recruitment of families from more diverse ethnic and socio-demographic backgrounds, as well as the recruitment of more fathers.

The collective findings of this research support the supposition that subscale scores on the KIPS constitute valid indicators of the various parent and child related factors that may underpin behavioural insomnia in children. Filling an important gap in the literature, the KIPS delivers both a theoretically derived, and psychometrically evaluated multidimensional assessment of six distinct domains: Sleep Maintenance Problems, Co-sleeping Behaviours, Bedtime Resistance, Bedtime Worries, Bedtime Fears, and Bedtime Routines. Strong support for the construct and content validity of scores on the first five factors was garnered over 3 different studies, with results offering partial support for the validity of scores on the Bedtime Routine factor and a total score. To our knowledge, there are no existing measures that provide both a comprehensive and valid assessment of the factors underlying behavioural sleep problems in paediatric populations, making the KIPS the only assessment of its kind. While further adjustments and validation research is required, preliminary results point to the usefulness of the KIPS in identifying behavioural insomnia problems among children and the mechanisms that may contribute to and / or maintain these issues. The KIPS is therefore likely to have significant empirical and clinical value.

Ethical Approval: Ethics approval for all three studies was sought and obtained from the BLINDED FOR REVIEW Human Ethics Committee (XXXX approval number 2019/785).

Competing Interests: The authors declare that they have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper.

Authors Contributions: Caroline Donovan: conceptualisation, project administration, original draft writing, review and editing Laura Uhlmann: data analysis, original draft writing, review and editing Amy Shiels: data curation, project administration.

Funding: Funding was received from Griffith Health, Griffith University, Brisbane, Australia

Availability of data and materials: Not applicable.

Conflict of Interest: The authors declare that they have no conflict of interest.

Achenbach, T. M. (1991). Manual for the child behavior checklist/4-18 and 1991 profile. Dept. of Psychiatry, University of Vermont.
American Academy of Sleep Medicine. (2014). International Classification of Sleep Disorders (3 ed.). American Academy of Sleep Medicine.
Arbuckle, J. L. (2006). Amos. In (Version 25) [Computer Program]. SPSS.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psych Bulletin, 107(2), 238.
Blankenburg, M., Tietze, A. L., Hechler, T., Hirschfeld, G., Michel, E., Koh, M., & Zernikow, B. (2013). Snake: the development and validation of a questionnaire on sleep disturbances in children with severe psychomotor impairment. Sleep Medicine, 14(4), 339-351. https://doi.org/10.1016/j.sleep.2012.12.008
Boergers, J., Hart, C., Owens, J. A., Streisand, R., & Spirito, A. (2007). Child sleep disorders: Associations with parental sleep duration and daytime sleepiness. Journal of Family Psychology, 21(1), 88. https://doi.org/10.1037/0893-3200.21.1.88
Bollen, K. A. (1989). Structural equations with latent variables (Vol. 210). John Wiley & Sons.
Bruni, O., Ottaviano, S., Guidetti, V., Romoli, M., Innocenzi, M., Cortesi, F., & Giannotti, F. (1996). The Sleep Disturbance Scale for Children (SDSC). Construction and validation of an instrument to evaluate sleep disturbances in childhood and adolescence. Journal of Sleep Research, 5(4), 251-261. https://doi.org/10.1111/j.1365-2869.1996.00251.x
Chaplin, J. E., Szakács, A., Hallböök, T., & Darin, N. (2017). The development of a health-related quality-of-life instrument for young people with narcolepsy: NARQoL-21. Health and Quality of Life Outcomes, 15(1), 135. https://doi.org/10.1186/s12955-017-0707-8
Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psych Assessment, 7(3), 309-319. https://doi.org/10.1037/1040-3590.7.3.309
Clark, L. A., & Watson, D. (2019). Constructing validity: New developments in creating objective measuring instruments. Psych Assessment, 31(12), 1412-1427. https://doi.org/10.1037/pas0000626
Comrey, A. L. (1988). Factor-analytic methods of scale development in personality and clinical psychology. Journal of Consulting and Clinical Psychology, 56(5), 754.
Falch-Madsen, J., Wichstrøm, L., Pallesen, S., & Steinsbekk, S. (2020). Prevalence and stability of insomnia from preschool to early adolescence: A prospective cohort study in Norway. BMJ Paediatrics Open, 4(1). https://doi.org/10.1136/bmjpo-2020-000660
Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286. https://doi.org/10.1037/1040-3590.7.3.286
Garner, D. (2004). Eating disorder inventory-3 (EDI-3) Professional Manual. (Vol. 35). Psychological Assessment Resources.
Garner, D. M., Olmstead, M. P., & Polivy, J. (1983). Development and validation of a multidimensional eating disorder inventory for anorexia nervosa and bulimia. International Journal of Eating Disorders, 2(2), 15-34.
Goodman, A., Lamping, D. L., & Ploubidis, G. B. (2010). When to use broader internalising and externalising subscales instead of the hypothesised five subscales on the Strengths and Difficulties Questionnaire (SDQ): Data from British parents, teachers and children. Journal of Abnormal Child Psychology, 38, 1179-1191. https://doi.org/10.1007/s10802-010-9434-x
Goodman, R. (1997). The Strengths and Difficulties Questionnaire: A research note. JCCP, 38(5), 581-586. https://doi.org/10.1111/j.1469-7610.1997.tb01545.x
Gregory, A. M., Eley, T. C., O’Connor, T. G., & Plomin, R. (2004). Etiologies of associations between childhood sleep and behavioral problems in a large twin sample. Journal of the American Academy of Child & Adolescent Psychiatry, 43(6), 744-751. https://doi.org/10.1097/01.chi/0000122798.47863.a5
Gregory, A. M., & O'Connor, T. G. (2002). Sleep problems in childhood: A longitudinal study of developmental change and association with behavioral problems. Journal of the American Academy of Child & Adolescent Psychiatry, 41(8), 964-971. https://doi.org/10.1097/00004583-200208000-00015
Gregory, A. M., & Sadeh, A. (2016). Annual Research Review: Sleep problems in childhood psychiatric disorders - a review of the latest science. Journal of Child Psychology and Psychiatry, 57(3), 296-317. https://doi.org/10.1111/jcpp.12469
Guttman, L. (1954). Some necessary conditions for common-factor analysis. Psychometrika, 19(2), 149-161.
Hatzinger, M., Brand, S., Perren, S., Von Wyl, A., Stadelmann, S., von Klitzing, K., & Holsboer-Trachsler, E. (2013). In pre-school children, sleep objectively assessed via sleep-EEGs remains stable over 12 months and is related to psychological functioning, but not to cortisol secretion. Journal of Psychiatric Research, 47(11), 1809-1814. https://doi.org/10.1016/j.jpsychires.2013.08.007
Henderson, J. A., & Jordan, S. S. (2010). Development and preliminary evaluation of the bedtime routines questionnaire. Journal of Psychopathology and Behavioral Assessment, 32, 271-280. https://doi.org/10.1007/s10862-009-9143-3
Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53-60.
Hoyniak, C. P., Bates, J. E., McQuillan, M. E., Staples, A. D., Petersen, I. T., Rudasill, K. M., & Molfese, V. J. (2020). Sleep across early childhood: implications for internalizing and externalizing problems, socioemotional skills, and cognitive and academic abilities in preschool. Journal of Child Psychology and Psychiatry. https://doi.org/10.1111/jcpp.13225
Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
Kaplan, D. (2008). Structural equation modeling: Foundations and extensions (Vol. 10). SAGE publications.
Meltzer, L. J., & Mindell, J. A. (2006). Sleep and sleep disorders in children and adolescents. Psychiatr Clin North Am, 29(4), 1059-1076; https://doi.org/10.1016/j.psc.2006.08.004
Meltzer, L. J., & Mindell, J. A. (2007). Relationship between child sleep disturbances and maternal sleep, mood, and parenting stress: A pilot study. Journal of Family Psychology, 21(1), 67. https://doi.org/10.1037/0893-3200.21.1.67
Meltzer, L. J., & Mindell, J. A. (2014). Systematic review and meta-analysis of behavioral interventions for pediatric insomnia. Journal of Pediatric Psychology, 39(8), 932-948. https://doi.org/10.1093/jpepsy/jsu041
Mindell, J. A., Meltzer, L. J., Carskadon, M. A., & Chervin, R. D. (2009). Developmental aspects of sleep hygiene: Findings from the 2004 National Sleep Foundation Sleep in America Poll. Sleep Medicine, 10(7), 771-779. https://doi.org/10.1016/j.sleep.2008.07.016
Moore, M., Meltzer, L. J., & Mindell, J. A. (2007). Bedtime problems and night wakings in children. Sleep Medicine Clinics, 2, 377-385. https://doi.org/10.1016/j.pop.2008.06.002
Nauta, M. H., Scholing, A., Rapee, R. M., Abbott, M., Spence, S. H., & Waters, A. (2004). A parent-report measure of children’s anxiety: Psychometric properties and comparison with child-report in a clinic and normal sample. Behaviour Research and Therapy, 42(7), 813-839. https://doi.org/10.1016/S0005-7967(03)00200-6
O’Connor, B. P. (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior research methods, instruments, & computers, 32(3), 396-402.
Owens, J. A., & Mindell, J. A. (2011). Pediatric insomnia. Pediatric Clinics of North America, 58(3), 555-569. https://doi.org/10.1016/j.pcl.2011.03.011
Owens, J. A., Spirito, A., & McGuinn, M. (2000). The Children's Sleep Habits Questionnaire (CSHQ): Psychometric properties of a survey instrument for school-aged children. Sleep, 23(8), 1043-1052.
Paine, S., & Gradisar, M. (2011). A randomised controlled trial of cognitive-behaviour therapy for behavioural insomnia of childhood in school-aged children. Behavior Research and Therapy, 49(6-7), 379-388. https://doi.org/10.1016/j.brat.2011.03.008
Price, T. E., Farrell, L. J., Donovan, C. L., & Waters, A. M. (2019). Behavioral Sleep-Related Problems in Clinically Anxious Children: A Parent-Report Diary Study. Child Psychiatry & Human Development, 50(5), 746-755. https://doi.org/10.1007/s10578-019-00878-5
Ravid,A., Lagbas,E., Johnson,M., & Osborne,T. (2021). Targeting co-sleeping in children with anxiety disorders using a modified bedtime pass intervention: A case series using a changing criterion design. Behav Therapy, 52(2), 298-312. https://doi.org/10.1016/j.beth.2020.03.004
Rodebaugh, T. L., Woods, C. M., & Heimberg, R. G. (2007). The reverse of social anxiety is not always the opposite: The reverse-scored items of the Social Interaction Anxiety Scale do not belong. Behavior Therapy, 38(2), 192-206. https://doi.org/10.1016/j.beth.2006.08.001
Rust, J., & Golombok, S. (2014). Modern psychometrics : The science of psychological assessment (3rd ed.). Routledge, Taylor and Francis.
Sadeh, A. (1994). Assessment of intervention for infant night waking: Parental reports and activity-based home monitoring. JCCP, 62(1), 63-68. https://doi.org/10.1037//0022-006x.62.1.63
Sen, T., & Spruyt, K. (2020). Pediatric sleep tools: An updated literature review. Front Psychiatry, 11, 317. https://doi.org/10.3389/fpsyt.2020.00317
Shahid, A., Wilkinson, K., Marcu, S., & Shapiro, C. M. (2012). STOP, THAT and one hundred other sleep scales. Springer Science & Business Media.
Spence, S. H., Rapee, R., McDonald, C., & Ingram, M. (2001). The structure of anxiety symptoms among preschoolers. BRAT, 39(11), 1293-1316. https://core.ac.uk/download/14980881.pdf
Spruyt, K., & Gozal, D. (2011). Pediatric sleep questionnaires as diagnostic or epidemiological tools: A review of currently available instruments. Sleep Medicine Review, 15(1), 19-32. https://doi.org/10.1016/j.smrv.2010.07.005
Staples, A. D., Bates, J. E., & Petersen, I. T. (2015). Bedtime routines in early childhood: Prevalence, consistency, and associations with nighttime sleep. Monographs of the Society for Research in Child Development, 80(1), 141-159. https://doi.org/10.1111/mono.12149
Thompson-Hollands, J., Kerns, C. E., Pincus, D. B., & Comer, J. S. (2014). Parental accommodation of child anxiety and related symptoms: Range, impact, and correlates. Journal of Anxiety Disorders, 28(8), 765-773. https://doi.org/10.1016/j.janxdis.2014.09.007
Trosman, I., & Ivanenko, A. (2021). Classification and epidemiology of sleep disorders in children and adolescents. Child and Adolescent Psychiatric Clinics of North America, 30(1), 47-64. https://doi.org/10.1016/j.chc.2020.08.002

No competing interests reported.

SUPPLEMENTARYTABLESDonovanetal.docx

Download PDF

Journal Publication

published 05 Oct, 2023

Read the published version in Child Psychiatry & Human Development →

Editorial decision: Major revision
26 Aug, 2023
Reviews received at journal
23 Aug, 2023
Reviewers agreed at journal
29 Jul, 2023
Reviewers invited by journal
22 Jul, 2023
Editor assigned by journal
22 Jul, 2023
Submission checks completed at journal
10 Jul, 2023
First submitted to journal
06 Jul, 2023

You are reading this latest preprint version

Helping Clinicians Conceptualise Behavioural Insomnia in Children: Development of the Kids Insomnia Problems Scale (KIPS)

Status:

Journal Publication

Version 1

Abstract

Introduction

Existing Measures of Paediatric Sleep Problems

Study 1

Study 1 Method

Participants

Measures

Procedure

Study 1 Results

Preliminary Analyses

Exploratory Factor Analysis

Study 2

Study 2 Method

Participants

Measures

Procedure

Study 2 Results

Study 3

Study 3 Method

Participants

Measures

Procedure

Results

Discussion

Limitations and Directions for Future Research

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1