Association between maladaptive sleep hygiene behaviors and sleep quality in the general population

Prevalence of sleep problems has grown globally in recent years and sleep hygiene recommendations have shown inconsistent results. This study aims to analyze the quality of sleep in a non-clinical population and its association with maladaptive sleep hygiene. A total of 465 participants, with median age of 35 years (Interquartile range – IQR = 28–44), completed the Sleep Hygiene Practices Scale (SHPS) and the Pittsburgh Sleep Quality Index (PSQI). Sample was divided into good quality sleepers (GQS; 52.7%, n = 245) and poor quality sleepers (PQS; 47.3%, n = 220). Comparison tests showed PQS had significant higher scores on SHPS (M = 61; IQR = 55–68, p < .01) compared with GQS (M = 68; IQR = 62–74). A logistic regression model indicated that only cognitive-arousal behaviors and inconsistent bedtimes were significant to classify poor sleep (R2 = .35; p < .01). In conclusion, poor sleep quality is common among healthy individuals and strongly associated with pre-sleep cognitive activity. This suggests that interventions aiming to improve sleep quality should consider strategies that would retract attention from concerns and worries at bedtime.


Method Participants
As shown in Figure 1, a total of 674 Spaniards participated in the study, out of which 31% (n = 209) were excluded since they represented a clinical sample according to the following exclusion criteria: 1) to be diagnosed or receive medical/psychological treatment for any sleep or psychological disorder (10.3%, n = 69); and 2) to score over 10 in the Insomnia Severity Index (ISI; Bastien, Vallières, & Morin, 2001) as this is considered a clinical outcome (21%, n = 140) (Morin, Belleville, Bélanger, & Ivers, 2011). The final sample included 465 participants with median age of 35 years (IQR = 28-44) ranging from 18 and 75 years. This sample size was sufficient as the minimum sample size required for an expected rate of 38% of sleep problems in the Spanish population (Madrid-Valero et al., 2017) was 255 participants (95% confidence interval, ±5 margin error).
The majority of participants were women 70.3% (n = 327), had a higher education level (65.4%; n = 304), were full-time or part-time employees (70.5%, n = 328), and were married or in a stable relationship (50.5%, n = 235). Likewise, one third of the sample (n = 142) were people working night shifts (n = 47) or taking care of people during night (e.g., babies, elderly, or ill people; n = 95). See Table 1.

Variables and Measurements
We assessed general sociodemographic variables (i.e., age, sex, marital status, level of education, employment situation, working night shifts and taking care of people during night) and also: Insomnia criteria. We used the self-reported questionnaire Insomnia Severity Index (ISI; Bastien et al., 2001) to identify people that could be diagnosed with insomnia using a cut-off point of 10 (Morin et al., 2011). The ISI provides information about insomnia severity, sleeping problems, level of satisfaction, and the impact on life quality. The 7 items of the questionnaire are rated on a 5-point Likert scale and the total scores range from 0 to 28, where higher values represent more severe insomnia. A study with the Spanish version in the general population showed adequate psychometric properties (Fernandez-Mendoza et al., 2012). Data from this study suggested acceptable reliability of the ISI with values of Cronbach's alpha and omega of α = .65 and ɷ = .75.
Sleep quality. The Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989) measured sleep quality within the past month through seven sleep components: 1) number of hours of sleep, 2) sleep latency or time it takes to fall asleep, 3) sleep efficiency which refers to the percentage of time spent asleep while in bed, 4) night disturbances as nightmares, awakenings, snoring, etc., 5) use of hypnotic medication for sleep problems, 6) daytime dysfunction or sleepiness, and 7) subjective quality of sleep. The global score of the 19-items PSQI ranges from 0 to 21, where scores over 5 indicate poor quality of sleep. The Spanish version showed good internal consistency with Cronbach's α = .81, and sound validity, with an 88.63% sensitivity and a 74.19% specificity (Royuela & Macías Fernández, 1997). Alpha and omega PSQI values in this study were α = .70 and ɷ = .75.
Sleep hygiene. In order to examine bedtime habits in the general population we selected the practices included in the Sleep Hygiene Practice Scale (SHPS; Yang, Lin, Hsu, & Cheng, 2010). This scale assesses how often participants followed 30 maladaptive sleep guidelines with a 5-point Likert scale scored form 1 (never) to 5 (always). The global score ranges from 30 to 150 with higher scores indicating worse sleep hygiene. The SHPS classifies maladaptive practices into 4 subscales: 1) Arousal-related behaviors; 2) Sleep scheduling and timing; 3) Eating and drinking behaviors; and 4) Sleep environment.
The SHPS was translated and adapted into Spanish by a forward-translation procedure. Before using this version, a pilot study was performed to examine the general functioning of the measure. The Spanish SHPS showed good internal consistency with data collected in this study with values of Cronbach's alpha and omega of α = .70 and ɷ = .73.

Procedure
An online recruitment method was performed to conduct the study using Survio®. The online survey included all the measures of this study and information about participants' data protection and privacy. Likewise, through this survey, we asked the participants for informed consent before completing it.
In order to disseminate the survey via a 'snowball' sampling technique, we selected the first wave of participants that acted as precursors for a chain dissemination of survey. Seed-participants were selected based on diverse sociodemographic characteristics (age, gender, level of education, etc.) from the authors' social context. We contacted them to ask for their collaboration in this study that would include forwarding the survey to multiple people and we informed them about different dissemination paths such as via instant messaging or posts on social networks. Likewise, we asked them to request subsequent participants to also disseminate the link in order to increase the number of referrals.

Statistical Analysis
We performed descriptive analyses (frequencies, means, standard deviations, medians and interquartile ranges) and bivariate analyses. Chi-square test (χ 2 ) was used to compare non-continuous variables and Mann-Whitney U non-parametric test (Z) to compare continuous variables due to violation of normality assumption, which was tested with Kolmogorov-Smirnov test. Likewise, Bonferroni adjustment was used for multiple comparisons to control the familywise error rate by dividing the critical value (α = .05) by the number of tests performed (.05/30 practices = .0017). Likewise, we calculated Rosenthal r effect size with the following thresholds of interpretation: .1 for small effect size, .2 PSIHOLOGIJA, 2020, Vol. 53(1), 87-100 for moderate, and .5 for large (Rosenthal, 1994). Finally, we performed a binary logistic regression to analyze which sleep hygiene guidelines (SHPS) show stronger association with the quality of sleep (PSQI) by entering simultaneously only the sleep hygiene guidelines that were significant in the intergroup comparison analysis. Bonferroni adjustment was also applied for this regression analysis (.05/8 practices = .0063). 95% confidence of level was used to interpret data results.

Sleep Quality and Differences between GQS and PQS
As shown in Table 1, participants stated to sleep an average of 6.87 (SD = 1.03) hours per night, of which 37.4% (n = 174) did not achieve the minimum recommendation of 7 hours of sleep. Around a third of the sample (n = 138) indicated having trouble falling asleep the first 30 minutes, while sleep latency mean average was about 20 (SD = 16.2) minutes. Moreover, 20.6% (n = 199) of participants had difficulties maintaining sleep, 11.4% (n = 53) reported taking hypnotic medication and 7.3% (n = 34) experienced sleepiness at least 3 days per week.
Sample's average PSQI score was 5.72 (SD = 2.5) whereas the percentage of healthy individuals with poor sleep quality was 47.3% (n = 220). By contrast, only 11.6% (n = 54) stated to experience poor quality of sleep.

Sleep Hygiene Practices and Differences between GQS and PQS
In order to compare the median of each SHPS behavior between GQSs and PQSs, Bonferroni adjustment was made considering the 30 SHPS guidelines (critical value of α = .0017). PQSs had significant higher scores than GQSs in 8 of the 30 sleep hygiene practices, of which five showed a medium effect size (r ≥ .

Power of Association of Sleep Hygiene Practices on Sleep Quality
In order to study the strength of association between sleep hygiene guidelines and the quality of sleep, we performed a logistic regression analysis introducing simultaneously the sleep hygiene practices in which groups' scores showed significant differences (p < .0017). The regression model was statistically significant predicting poor quality of sleep (χ 2 = 139.914; p < .01) with a Nagelkerke R 2 of .347 and a 73.8% of correct cases classified. As Table  3 shows, of the 8 practices introduced in the equation, 6 were statistically significant (p < .05), of which 4 remained significant after Bonferroni adjustment (.05/8 practices = .

Discussion
Approximately 50% of participants reported poor quality of sleep according to PSQI scores. This percentage is slightly higher than that observed in previous studies performed in the Spanish population (38.2%; Madrid-Valero et al., 2017), which supports the hypothesis about the increase in sleep problems (Léger et al., 2008). Although nearly half of the sample reported poor sleep quality, only 11.6% rated their overall sleep as bad, which could suggest that perception of poor quality of sleep is undervalued or underestimated.
Considering recommendations about the duration of sleep needed to preserve health, the average number of hours of sleep in the sample was insufficient (Buysse, 2014). Likewise, difficulties in initiating or maintaining sleep were slightly higher compared to other non-clinical populations (Madrid-Valero et al., 2017). In accordance with other studies, these findings indicate that a large percentage of healthy individuals experience inadequate sleep, which supports the hypothesis that sleep problems are emerging as a public health issue (Adams et al., 2017;Ford et al., 2015).
Results of this study also suggested that having inadequate sleep is associated with maladaptive sleep hygiene. Participants that more frequently perform these bedtime behaviors showed significant higher PSQI scores than good sleepers. These findings concur with previous studies with non-clinical population where participants with inappropriate sleep hygiene had more night awakenings, took longer to fall asleep and showed greater sleepiness during daytime (Chen et al., 2010;Morita et al., 2012).
Certain maladaptive bedtime habits yielded stronger association with poor sleep. Intergroup comparisons between GQSs and PQSs showed major differences in arousal-related behaviors prior to sleep in comparison with other comportments. This could indicate that healthy individuals that have more thoughts, worries and activity prior to sleep could be prompting sleep problems. Similarly, having an irregular bedtime schedule showed strong association with poor sleep, as seen in previous studies where people that more frequently had irregular sleep schedule reported sleeping less and having longer sleep latency (Härmä et al., 2018;Kang & Chen, 2009). In addition, significant mean differences were also found in other sleep hygiene behaviors between PQSs and GQSs, but the effect sizes were small (r < .2). These behaviors, such as keeping an appropriate bedroom temperature or using the bed to sleep only, need to also be taken into account in order to improve sleep quality as recommended in other studies (Irish et al., 2015).
In accordance with these results, regression analysis also indicated that people who more frequently perform behaviors that increase cognitive arousal level before sleep or have irregular bedtimes seem to be more likely to manifest poor sleep than people that don't perform those behaviors or perform them less often. These findings concur with results of other studies where participants with higher stress levels, higher cognitive activity prior to sleep, and more variable sleep schedules experienced more sleep problems (Gunn, Troxel, Hall, & Buysse, 2014;Härmä et al., 2018;Nota, Sharkey, & Coles, 2015). Sleep worries and preoccupations during bedtime have been shown to impair sleep quality and to maintain insomnia (Lancee, Eisma, van Zanten, & Topper, 2017;Takano, Iijima, & Tanno, 2012). Therefore, based on the results of this study it is worth considering potential behavioral strategies such as refocusing-retracting attention from intrusive thoughts (Gellis, Arigo, & Elliott, 2013), or solving stressful problems (Pech & O'Kearney, 2013) that could reduce night concerns, in order to improve treatments' efficacy to reduce sleep disturbances and prevent sleep disorders.
Several limitations should be considered. As this is a cross-sectional study, it is not possible to determine causal relationships between variables However, regression analysis produced a well-fitting model classifying poor sleepers with few maladaptive sleep hygiene practices. Furthermore, the use of self-reported measures can have bias associated, such as central tendency responses due to scales format. These bias were minimized using different questionnaires that assess similar sleep features and selecting a user-friendly survey layout.
In conclusion, aspects such as arousal-related behaviors and excess of concerns during bedtime could disturb the quality of sleep, as well as inconsistent bedtimes. In this sense, it seems necessary to improve sleep quality in the general population in order to prevent sleep disorders and related diseases and this can be done by addressing cognitive activity prior to sleep. Future longitudinal and experimental studies should be performed to corroborate the findings of this study and provide effective sleep hygiene programs.