ns were conducted for each sleep outcome, entering gender (coded as 0=male, 1=female) and age as predictors to determine whether gender predicted insomnia symptom severity, sleep quality, and sleep characteristics when controlling for age.
To examine whether gender predicted declines in ISI and PSQI from pretreatment to posttreatment, we conducted hierarchical linear mixed models using SPSS (version 25; IBM Corp) with restricted maximum likelihood estimation. This modelling approach handles missing data by incorporating all available data from each participant into the analysis. Data from the pretreatment and posttreatment time points were grouped by participant. Participant was specified as a random factor, and time, gender, and age were specified as fixed factors. The outcome variables were ISI and PSQI at both time points, with gender as the predictor. Time was coded as 0 for pre and 1 for post, and gender was coded as 0 for male and 1 for female participants. We specified two sets of multilevel models for each outcome variable. In the first model we entered time, gender, and age as predictors, and in the second model we added the two-way interactions between time and gender, time and age, and age and gender. For all models, we specified a random intercept, which allows participants’ mean levels of each outcome to vary. Intraclass correlations (ICCs) were calculated for ISI and PSQI based on intercept-only models. ICC values indicate the amount of variance accounted for by within-person variability. Convention suggests that variables with ICC values greater than 0.10 show sufficient dependency to be analyzed with multilevel modelling . ICCs were 0.42 for ISI and 0.81 for PSQI.
Gender Differences in Baseline Symptoms
Baseline score comparisons are presented in. Boys and girls did not significantly differ in age or city residence; however, more girls than boys were currently using medication and receiving mental health treatment. Girls had significantly higher ISI scores at baseline (t47=−2.13, P=.04; Cohen d=0.60), suggesting significantly greater symptom severity compared to boys. Differences in PSQI scores did not reach significance (t47=−1.90, P=.07; d=0.57), suggesting negligible differences between girls and boys in sleep quality. Girls reported significantly greater WASO and TWT and significantly reduced TST and sleep efficiency compared to boys (t44=−2.72, P=.01, d=0.54; t45=−2.12, P=.04, d=0.24; t45=2.34, P=.02, d=0.68; t45=2.28, P=.03, d=0.30, respectively) but no difference in SOL or NWAK (P=.21 and P=.16, respectively).
Post hoc linear regressions found that when controlling for age, gender predicted WASO (t44=2.07, P=.04; f2=0.09), TWT (t45=2.39, P=.02; f2=0.13), and SE (t45=−2.18, P=.03; f2=0.11). In contrast, when controlling for age, gender did not predict baseline ISI (t47=1.42, P=.16; f2=0.04), PSQI (t47=1.31, P=.20’ f2=0.04), SOL (t45=−0.57, P=.23; f2=0.04), or NWAK (t45=0.88, P=.39; f2=0.02) or TST (t45=1.45, P=.15; f2=0.04). Notably, two variables identified as showing gender differences in the t tests, ISI and TST, were not significant predictors in the linear regressions, suggesting baseline gender differences in these variables are accounted for by boys being marginally younger in age.
Of relevance to the current study, there were no differences between boys and girls in the number of Sleep Ninja lessons completed (P=.42). Information regarding uptake and adherence to the intervention can be found in Werner-Seidler et al .
|Age (years), mean (SD)||13.70 (1.04)||14.47 (1.51)||.07|
|Reside in city, n (%)||13 (81)||30 (91)||.38|
|MHa treatment,b n (%)||0 (0)||13 (39)||.004|
|Medication use,c n (%)||1 (6)||13 (39)||.02|
|ISI,d mean (SD)||7.90 (4.63)||9.87 (5.00)||.04|
|Global PSQI,e mean (SD)||7.40 (3.78)||7.91 (3.90)||.07|
|SOL,f,g mean (SD)||0.82 (0.75)||0.73 (0.54)||.21|
|NWAK,f,h mean (SD)||1.50 (2.31)||0.65 (0.69)||.16|
|WASO,f,i mean (SD)||0.12 (0.18)||0.24 (0.26)||.01|
|TWT,f,j mean (SD)||1.13 (0.88)||1.40 (1.32)||.04|
|TST,f,k mean (SD)||8.74 (0.65)||8.14 (1.07)||.02|
|SEl (%), mean (SD)||88.