Abstract
Background
Over the last decades, adolescents’ sleep has deteriorated, suggesting the need for effective healthy sleep interventions. To develop such interventions, it is important to first ...gather insight into the possible factors related to sleep. Moreover, previous research has indicated that chances of intervention effectivity could be increased by actively involving adolescents when developing such interventions. This study examined psychosocial factors related to sleep in adolescents and investigated adolescents’ willingness to participate in the development of a healthy sleep intervention.
Methods
Nine focus group interviews were conducted with seventy-two adolescents (63.9% girls, 14.8 (± 1.0) years) using a standardized interview guide. Interviews were audio-recorded and thematic content analysis was performed using Nvivo 11.
Results
Adolescents showed limited knowledge concerning sleep guidelines, sleep hygiene and the long-term consequences of sleep deficiency, but they demonstrated adequate knowledge of the short-term consequences. Positive attitudes towards sleep were outweighed by positive attitudes towards other behaviors such as screen time. In addition, adolescents reported leisure activities, the use of smartphones and television, high amounts of schoolwork, early school start time and excessive worrying as barriers for healthy sleep. Perceived behavioral control towards changing sleep was reported to be low and norms about sufficient sleep among peers were perceived as negative. Although some adolescents indicated that parental rules provoke feelings of frustration, others indicated these have a positive influence on their sleep. Finally, adolescents emphasized that it would be important to allow students to participate in the development process of healthy sleep interventions at school, although adult supervision would be necessary.
Conclusion
Future interventions promoting healthy sleep in adolescents could focus on enhancing knowledge of sleep guidelines, sleep hygiene and the consequences of sleep deficiency, and on enhancing perceived behavioral control towards changing sleep. Interventions could also focus on prioritizing positive sleep attitudes over positive attitudes towards screen time, finding solutions for barriers towards healthy sleep and creating a positive perceived norm regarding healthy sleep. Involving adolescents in intervention development could lead to intervention components that match their specific needs and are more attractive for them.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This study examines the mediating role of sleep duration and sleep onset difficulties in the association of school pressure, physical activity, and screen time with psychological symptoms in early ...adolescents. Data were retrieved from 49,403 children (13.7 ± 1.6 years old, 48.1% boys) from 12 countries participating in the World Health Organization (WHO) "Health Behaviour in School-aged Children" 2013/2014 study. A validated self-report questionnaire assessed psychological symptoms (feeling low, irritability or bad temper, feeling nervous), school pressure, physical activity (number of days/week 60 min moderate-to-vigorous), screen time, sleep duration on week- and weekend days, and perceived difficulties in getting asleep. Multilevel mediation analyses were conducted. School pressure and screen time were positively associated with psychological symptoms, whereas physical activity was negatively associated. With the exception of sleep duration in the association between physical activity and psychological symptoms, all associations were significantly mediated by sleep duration on week- and weekend days and sleep onset difficulties. Percentages mediated ranged from 0.66% to 34.13%. This study partly explains how school pressure, physical activity, and screen time are related to adolescents' psychological symptoms. Future interventions improving adolescents' mental well-being could target schoolwork, physical activity, and screen time, as these behaviours are directly and indirectly (through sleep) related to psychological symptoms.
BackgroundMutual learning and shared decision-making are key elements of Participatory Action Research (PAR), highlighting the important role of the facilitator to support this. This study aims to ...illustrate how a facilitator can contribute to successful PAR sessions based on the reflection of three PAR projects.MethodsParticipatory sessions took place with adolescents for 3–4 school years. After each session (n = 252 sessions across three projects), facilitators filled in a reflection form that assessed the group process and their facilitating role. Facilitators independently coded a selection of 135 reflection forms partly deductive and partly inductive based on core PAR principles derived from a pragmatic literature search.ResultsA well-prepared session – for example, including active and creative participatory methods and a clearly stated goal – contributed to efficiency and the necessary flexibility. Making agreements, making sure everyone is heard and taking 'fun-time' appeared important for creating and maintaining a safe, functional and positive atmosphere. Finally, facilitators needed to encourage co-researchers to take the lead and adapt to the group dynamics, to ensure ownership and shared decision-making.ConclusionIn-depth qualitative analyses of a standardized reflection form used in three different PAR projects resulted in various lessons to support facilitators in collaborating with co-researchers in PAR projects.
Adolescents' sleep deteriorated over the last decades, urging the need to develop effective interventions. Using participatory action research (PAR) is a promising and unique approach to target ...adolescents' sleep. This study aims to describe the process and results of combining PAR and intervention mapping (IM) to guide future researchers on developing and planning of the implementation and evaluation of interventions promoting healthy sleep in adolescents.
In each of three intervention schools (two with general and technical education and one with technical and vocational education), an action team including adolescents (age 13- 15 years, n=max. 12) and a researcher was composed to develop and plan the intervention. During weekly sessions (n=ranging from 23 to 34 per school), the action team went through the six steps of IM. A short PAR was performed with parents (n=7) to develop parental intervention components.
Combining PAR and IM resulted in interventions focusing on the importance of healthy sleep, regular sleep patterns and associated behaviors: screen behaviors, physical activity, dietary behavior and relaxation. Several differences in the participatory process (i.e. more guidance needed during brainstorms in the vocational/technical school) and developed intervention (i.e. less intrusive intervention components in the vocational/technical school) were observed between schools.
Combining PAR with IM resulted in more extensive interventions than other existing school-based sleep interventions. Future studies should investigate whether a participatory developed sleep intervention could be transferred to another setting using a shorter participatory process.
The measurement of automatic attitudes towards sleep, in addition to reflective self‐reports, might improve our ability to predict and explain sleep‐hindering practices. Two types of implicit ...association tests (IATs), a sleep‐related evaluations IAT and a sleep‐related self‐identity IAT, were developed to evaluate their efficacy for assessing automatic sleep‐related attitudes. In addition, a speeded self‐report measure of sleep evaluations was explored as a means to assess automatic sleep‐related attitudes. The study included 136 young adults (age = 21.70 ± 2.22, 43% female). At baseline, the two IATs, the speeded self‐report, and standard self‐reports of sleep determinants (reflective attitudes, self‐efficacy, intention and action planning for sleep‐promoting behaviour), sleep hygiene practices, sleep quality, and sleep duration were assessed. All variables except for the sleep determinants were assessed again at 2‐week follow‐up. The results demonstrated good reliability of the two IAT versions, but both IATs were unrelated to the speeded self‐report, the sleep determinants, sleep practices, sleep quality or sleep duration. The speeded self‐report correlated significantly with the standard self‐reports of sleep determinants. Baseline scores on the IATs or speeded self‐report did not predict sleep hygiene practices, sleep duration or sleep quality at follow‐up. The findings indicate that sleep‐related IATs might not be suited to assess automatic sleep‐related attitudes. Further investigation is needed to determine whether speeded self‐reports are valid measures of automatic attitudes. Moreover, more empirical research is required to clarify the role of automatic processes for sleep hygiene behaviours.
Purpose
While a multitude of studies focused on biological and behavioral determinants of adolescents’ sleep quality, a paucity of research examined the impact of social factors. The current study ...therefore examines the relationship between adolescents’ sleep quality and peer, family and school factors.
Methods
Data of Flemish participants in the 2017/2018 Health Behavior in School-aged Children survey (HBSC) were used, which is representative of the adolescent population (11–18 years) in Flanders. Adolescents’ sleep quality was linked to individual-level data on peer relationships (i.e., peer support), family relationships (i.e., family support, perceived family wealth, caregiving responsibilities) and school relationships (i.e., teacher support, school support, school pressure) and contextual-level data on the school culture. Three-level multilevel models were fitted to account for the clustering of individuals (
N
= 8153) within classes (
N
= 769) and classes within schools (
N
= 177).
Results
The individual-level results indicated that adolescents’ sleep quality was positively related to family support, teacher support, student support and perceived family wealth. In contrast, adolescents’ sleep quality was negatively related to caregiving responsibilities and school pressure. In addition, the contextual-level results pointed out that adolescents tended to report better sleep quality in less-demanding schools.
Conclusion
These findings highlight the need to consider social factors in promoting better sleep in adolescence.
Objectives
We examined changes in sleep-onset difficulties over time and associations with physical activity and screen time behavior among adolescents.
Methods
We used data from last four survey ...waves of the Health Behavior in School-Aged Children (HBSC) study (2002–2006–2010–2014). Multilevel logistic regression analyses were conducted to explore associations between regular sleeping difficulties, excessive screen time exposure and being insufficiently physically active (i.e., < 60 min daily) among 33 European and non-European countries.
Results
Findings indicate an increase in the prevalence of sleep-onset difficulties and in excessive screen time exposure and a small but significant increase in physical activity levels. Additionally, adolescents exceeding 2-h daily screen time had 20% higher odds of reporting sleep-onset difficulties, while no association was found for physical activity. The strength of the association between screen time and sleep-onset difficulties increased over time, which may reflect a change in type of screen time use (e.g., the increased use of easy accessible screens such as smartphones and tablets).
Conclusions
Effective strategies to reduce screen time are key to reverse the detrimental trend in sleep-onset difficulties among adolescents.
To date, it remains unknown which psychosocial determinants identified by several leading behavior change theories are associated with different sleep parameters among adolescents. Therefore, this ...study investigates whether changes in knowledge about healthy sleep, attitude toward healthy sleep and going to bed on time, self-efficacy to engage in healthy sleep behavior, perceived parental and peer norms, perceived barriers (e.g., worrying, fear of missing out), and perceived support (e.g., bedtime rules, encouragement) related to healthy sleep are associated with changes in adolescents’ sleep duration on school days and free days and sleep quality over a period of 1 year. Two-wave data of 1648 Flemish adolescents (mean age = 15.01, SD = 0.65, 46.3% female) were analyzed using linear models. Increased levels of parental social support, positive attitude towards and perceived advantages of healthy sleep, norm-knowledge, and perceived peer behavior were associated with sleep duration, with parental social support having the strongest association. Increased levels of perceived barriers were associated with decreased levels of sleep quality parameters, and increased levels of self-efficacy, positive attitude, and parental modeling were associated with improved sleep quality parameters, with perceived barriers having the strongest association. The current results indicate that behavior change theories are useful in the context of adolescent sleep behavior and suggest that perceived parental support (i.e., bedtime rules) and perceived barriers are most strongly associated with adolescents’ sleep duration and/or quality.
Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by ...researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption.
This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2.
A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0.
Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient ICC=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA.
This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.
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