Barriers and Facilitators to Physical Activity, Screen time and Sleep in 3- to 4-year-olds living in Scotland

doi:10.21203/rs.3.rs-4711675/v1

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Research Article

Barriers and Facilitators to Physical Activity, Screen time and Sleep in 3- to 4-year-olds living in Scotland

https://doi.org/10.21203/rs.3.rs-4711675/v1

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Background

This study evaluated the barriers and facilitators that families experience in adhering to the 24-Hour Movement behaviours guidelines as outlined by World Health Organisation (WHO).

Methods

Twenty-four families from low- and high-income families living in Scotland were recruited. This cross-sectional study used a mixed-methods approach which included: 1) an online questionnaire for parents, 2) objectively measured physical activity (PA), sedentary behaviour and sleep, 3) online focus groups with parents. For the quantitative part, children wore an Actigraph (GT3X+) accelerometer to measure physical activity, sedentary behaviour, and sleep. Parents/guardians kept an activity diary outlining when their child had to remove the device (i.e., showering, bathing, swimming) and record the child’s screen time each day. Once the data had been analysed, a unique activity profile chart was sent to each family illustrating their child’s 24-hour movement behaviours (i.e., time spent active, time spent sedentary and on screens, time spent sleeping). The activity profile provided a day-by-day output as well as a weekly average for each of the 24-hour movement behaviours. Qualitative data was collected using the Asynchronous Remote Communities method (ARC) via private groups on a social media platform.

Results

The results showed most of the children in this sample adhere to the sleep and MVPA guidelines (71% and 86% respectively). However, adherence to the total PA guideline and ST guideline is much lower (50% and 21% respectively). Qualitative results in this study provide insights into the experiences of low-income and high-income families when adhering to the 24hMB guidelines. The results have shown different sub-themes affecting family’s adherence to each of the guidelines both positively and negatively. Results did not appear to differ substantially between low-income and high-income families.

Conclusions

24-Hour Movement Behaviours

Physical Activity

Sleep

Screen Time

Sedentary Behaviour

Low-Income Families

The World Health Organisation (WHO) has identified childhood obesity prevention in children as one of the key priorities of the 21st century (1). Evidence has shown that physical activity, sedentary behaviours, and sleep all play an important role in the health and development of young children (2). This has led to the WHO releasing the first global guidelines on physical activity, sedentary behaviour, and sleep for children under five-years of age (also known as the 24-hour movement behaviour guidelines). The guidelines state that children aged 3- to 4-years should engage in at least 180-minutes of physical activity including 60-minutes of moderate-to-vigorous physical activity, spend no more than one-hour on a screen, and achieve between 10- to 13-hours of quality sleep (3). Following the release of the guidelines several studies from across the world have shown most young children are not meeting these guidelines (4–6). For example, a recent international cohort study, showed the only 14% of children met all three guidelines before the COVID-19 pandemic and this number decreased even further during the pandemic (11%) (7). It is evident that targeted interventions are required to empower families to build a better day for their children.

While there is an increasing interest in measuring adherence to the 24-hr movement guidelines, we must acknowledge that not enough is known about the factors influencing multiple health behaviours in the early years (8, 9). Previous research has highlighted a range of promising intervention settings, professionals, and components (i.e., the features that define an effective program). For example, recent systematic reviews identified that tailoring interventions that take into consideration the cultural and community needs facilitated improvements in levels of physical activity in children and young people whilst the use of educational strategies alone acted as a barrier and were not effective in positively impacting on the 24-hour Movement Behaviours (24hMBs) (5, 10). However, many of these studies have involved the participation of middle to high-income families (11). These studies may therefore not represent those most in need. In Scotland, for example, 13% of pre-school children in deprived families are at risk of obesity compared to 6% in the least deprived. For interventions to be effective to those most in need, it is crucial to gain a better understanding of their barriers and facilitators which may differ substantially from those of families in the least deprived areas. Gaining an understanding of the factors influencing these behaviours in deprived families would enable key stakeholders to introduce more effective strategies and promote a healthier lifestyle choice for children with behaviour-specific interventions (10).

Promoting 24hMBs adherence is a complex matter because the behaviours are individually, and collectively, influenced by a multitude of factors (9, 11–15). Bronfenbrenner’s socio-ecological model (16) can be used to examine the many factors that influence 24hMBs adherence. The socio-ecological model engages with four levels: individual characteristics (e.g., gender, age), microsystem (e.g., family, friends), mesosystem (e.g., neighbourhood, family make-up, pre-school), and exosystem (e.g., culture, finances, policies). The socio-ecological model is key when trying to understand the most effective ways on promoting 24hMBs (17, 18) and to promote adherence to the 24hMBs in children aged 3- to 4-years, our understanding of the barriers and facilitators families experience at each level of the socio-ecological model needs to be increased. Therefore, the aim of this study was to identify the barriers and facilitators that impact on the 24hMBs in children aged 3- to 4-years living in Scotland, using the socio-ecological model as a theoretical framework.

Design and recruitment

This cross-sectional study used a mixed methods approach which included: 1) an online questionnaire for parents, 2) objectively measured physical activity (PA), sedentary behaviour and sleep, 3) online focus groups with parents. The quantitative data collected via questionnaire and accelerometery was used to inform the qualitative phase. Data was collected between January and August 2023. Ethical approval has been obtained from the Department of Psychological Sciences and Health Ethics Committee at the University of Strathclyde and informed consent was obtained from all participants. A detailed description of the study protocol has been published previously (19).

Participants

Participants were recruited via social media platforms, and nurseries and local parent-toddler groups were targeted either online or face-to-face by the lead researcher. In total 24 families from both deprived and non-deprived areas were recruited, 9 from high-income and 15 families from low-income. Low-income families were defined as earning <£16,000 per annum (i.e., 60% of the median pay in Scotland in April 2022).

Protocol

Parent questionnaire

After consent was obtained, parents/guardians were asked to complete a brief online questionnaire (or a paper copy). The questionnaire included demographical questions (e.g. parent/child age, parent education) as well as questions about their child’s screen time (ST) on a typical day and whether their child had been restrained for more than one hour at a time (See Appendix 1). Questions were based on a previously used questionnaire (4).

Objectively measured physical activity, sedentary behaviour, and sleep

Children were asked to wear an activity monitor (Actigraph GTX3+) for seven consecutive days for 24-hours each day, in line with standardised protocols used in large studies globally (20). The Actigraph is a widely used activity monitor which has shown acceptable classification accuracy for sedentary behaviour, moderate-to-vigorous physical activity (MVPA), and sleep in this age group (21, 22). Parents/guardians were also asked to keep an activity diary outlining their child wake and bedtimes, daily ST, as well as indicating any time the monitor was removed.

Actigraph data was collected at 100Hz and converted to 15-second epochs for analysis. Parent/guardian completed wear time diaries which indicated when monitors were taken off and their child’s bed and wake times. Visual screening was used to identify non-wear periods in line with the wear time diaries and non-wear times were removed from the data. Sedentary behaviour, light physical activity and MVPA were calculated using < 200counts/15s, between 200–799 counts/15s and > 800 counts/15s respectively (23). Sleep time per day was calculated using the Sadeh algorithm ActiLife version 6.12.1 (Actigraph, Penscola, FL, USA) (24). This algorithm has previously been validated for use in young children (22). The time flags for sleep onset and sleep offset were determined based on the bed and waketimes reported in the wear time diary. Participants with at least 3-days of valid data were included in the analysis. A valid day is defined as having at least 10-hours per waking day of accelerometer data (25).

Qualitative data

Qualitative data was collected using the Asynchronous Remote Communities method (ARC). The ARC involves participants completing activities using an online closed Facebook group. This method is recommended for seldom heard and hard to reach populations as it removes barriers such as availability and difficulty of travel, often associated with face-to-face focus groups (26, 27). During recruitment consent was obtained from each participant outlining their role within the Facebook groups. The lead researcher set-up a University Facebook account and invited each participant to join the Private group they were assigned to. In total there were 3 different Facebook groups, each containing a combination of high and low-income families. Parents were asked to engage in group discussion tasks using the platform. An example of the posts can be seen in appendix 1. Activity posts were introduced onto the online platform for a period of 6-weeks where parents/guardians were encouraged to post comments and opinions related to each of the activities designed for this study. The activities aim was to gain an understanding of the barriers and facilitators parents/guardians face when building a better day and the settings and key people involved in promoting and supporting healthy behaviours in their children. Key weekly topics were: 1) thoughts and reflections on the 24-hour movement behaviours; 2) perceptions of their child’s actual 24-hour movement behaviours; 3) incorporating the 24-hour movement behaviours daily; 4) 24-hour movement behaviours and its impact on their child’s behaviour; 5) main barriers to achieving the WHO recommendations; 6) facilitators to achieving WHO recommendations; 7) key players in helping families build a better day. During the second week participants received individualised activity profiles based on the data collected from the accelerometer and diary data in the quantitative part of the study (example in Fig. 1). These profiles enabled parents to reflect in a more detailed discussion about their child’s 24-h day and aimed to increase engagement with the discussion tasks. Where parents/guardians are not interacting with the online discussion, personal reminders were sent by ‘tagging’ them into the post or by sending them an email reminder.

Analysis

The quantitative data obtained from the accelerometers and parent questionnaire were analysed and presented descriptively. Medians and ranges for the movement behaviour outcomes were reported, as well as the percentage of children meeting the movement behaviour guidelines.

Using Braun and Clarke’s reflexive approach, qualitative data was collated and analysed thematically (28). This process involved six phases including familiarisation of the data through completing and reading the transcripts, identifying then generating the initial codes, searching for themes through the data, reviewing initial codes generated during the second phase, defining then naming themes, and producing a final report. NVivo software (Version 1.7,2022) was used to thematically analyse the data collected in the Facebook focus groups and a final report was produced and sent to FM for validation. AD and FM agreed that the six phases had been completed accurately and provided a detailed account of the obtained data. Agreement was reached between the researchers by reflective discussion on interpretation (29, 30).

Quantitative

Descriptive statistics for this sample are described in Table 1. Briefly, 20 parents completed the questionnaire and 14 provided valid accelerometery data from their child. The median age of children who participated was 3.9 years (interquartile range = 1.2), with 9 boys and 11 girls included in the sample. Most parents were female (male n = 1) with a mean age of 34.8 years (interquartile range = 6.5).

Table 1

Descriptive characteristics (n = 20)
	Median or %	IQR
Child age (years)	3.9	0.9
Child sex (girls)	55.0
Parent age (years)	34.8	6.5
Parent sex (female)	95.0
Parent income level (low)	60.0
Parent report activity
Screen time (min/day) ^a	120	15
Total Physical Activity (min/day)	180	135
High intensity physical activity (min/day)	60	60
Sleep (hr/day)	11	0.5
Accelerometery recorded activity ^b
Sedentary behaviour (min/day)	605	67
Total Physical Activity (min/day)	184	52
High intensity physical activity (min/day)	85	26
Sleep (hr/day)	11	1
^a n = 19, ^b n = 14

The percentage of children meeting the guidelines has been displayed in Table 2. Based on accelerometery recorded data 50% of children met the total PA guideline, 86% met the MVPA guideline, and 71% met the sleep guideline. Parent reported ST indicated only 21% met the ST guideline whereas 75% met the restrained guideline.

Table 2

Percentage of children meeting the 24-hour movement behaviour guidelines
	% meeting the guidelines
Parent report activity
Screen time guideline (≤ 60 min/day) ^a	21
Restraint (≤ 60 min at one time)	75
Total Physical Activity (≥ 180 min/day)	75
Moderate-to-vigorous physical activity (≥ 60 min/day)	75
Sleep (10–13 hr/day)	85
Accelerometery recorded activity^b
Total Physical Activity (≥ 180 min/day)	50
Moderate-to-vigorous physical activity (≥ 60 min/day)	86
Sleep (10–13 hr/day)	71
^a n = 19, ^b n = 14

Qualitative

Sixteen families were included in the qualitative analysis. Using Bronfenbrenner’s socio-ecological model as a theoretical framework, results were organised to highlight the many factors that influence adherence of the 24hMBs. Results identified barriers and facilitators at each of the four levels (see Table 3).

Individual Characteristics: Age, Finances, and Personal health

Participants varied in personal circumstances in respect of age of their child, financial position, and personal health factors. Some participants found the age of their child was a limiting factor when trying to encourage appropriate levels of PA in their area.

“…she is yet too young for highland dancing and gymnastics.” (BD003, low income)

“Maybe more clubs and classes in the evenings for younger kids. “(BD018, low income)

Even when activities for 3- to 4-yeard-olds was available within the local community, many parents felt the cost of these activities was prohibitive.

“Although I don’t see cost/money as a direct barrier to activity in general, I do think that when you start introducing more variety/structure to a child’s activity, cost and timing and access can be barriers e.g., swimming lessons tend to be expensive and offered at times that are in direct conflict with working hours.” (BD007, high income)

“…in wet days it’s harder as there are few free activities that are indoors that we can take the kids to and soft play etc can be very expensive.” (BD022, low income)

In direct contrast, the cost of local activities for one parent was a facilitator when encouraging their children to be active, although they still acknowledged the need for costs to be appropriate.

“I think having activities local and at a reasonable cost is the main thing that can make a difference. I am lucky to have two midweek days off work where things like soft play are much cheaper.” (BD006, high income)

There were a few mentions of personal health factors as having an impact on the adherence to the 24hMBs guidelines.

“I’ll start by agreeing with BD008’s comments about the never-ending sickness – that is definitely a barrier that tends to agitate all 3 behaviours (in our family, sickness = more screen time, erratic sleep times, and reduced activity.” (BD007, high income)

This was not only from the child’s perspective but also from the personal health of the parent. For example, one parent indicated that the personal health of their partner makes it more difficult to encourage their child to be active.

“..but it can be hard as my husband has arthritis..” (BD005, low income)

Microsystem: Family dynamics, Parental influences, and Social environment

Most of the parents recognised the influence that family dynamics has on the adherence of the 24hMBs guidelines. Within these comments, there were positive and negative influences.

“So, on reflection my son’s older sister is paramount in keeping my son active.” (BD011, low income)

“Our kids not being able to sleep in their own bed is a barrier for us. We have tried so many things even had the sleep consultant health visitor for them both. We can be strict for a few nights but end up giving in just so we can at least get some sleep!” (BD003, low income)

“I think a big part of building a child’s best day is by participating in it as much as your time/capacity allows. This also means that the messaging is more positive and encouraging.”(BD007, high income)

In addition, many parents shared comments regarding how their parenting approach positively influences building a better day for their child.

“…us having an active lifestyle when have days off such as going walks and hill walking when we can.” (BD005, low income)

“Probably a big help is that my husband and I largely lead a lifestyle/live in an environment that makes the 24-hour movements guidelines achievable. My husband and I both play sport (and so my son is regularly exposed to sport and spends many weekends next to a sports field).” (BD007, high income)

“We are lucky as CBD022 has an older sister, we have a good network of local mums and dads, and we have a WhatsApp group and share information about what is on and arrange to meet up at the local park or go out on bikes etc together which helps to motivate the kids.” (BD022, low income)

In contrast, some of the parental influences were recognised as potential barriers to building a better day for their child(ren) though these tended to focus more on ST and not on sleep or PA levels.

“At this age parents have an essential role in this……so I need to become less reliant on the TV.” (BD006, high income)

“I also think that we are a tech heavy family which plays into the screen use.” (BD012, low income)

However, parents did comment that they recognised the link between their decisions and their child’s adherence to the 24hMBs guidelines and were considering readdressing their concerns.

“I think it highlighted our overuse of screen time. Particularly in the morning we do rely on the TV too much to get stuff done.” (BD006, high income)

“I agree all 3 areas are important. We try to ensure our child’s days are as physically active as possible. We also try to maintain a reasonably similar sleep pattern each day but are not overly strict with it. We have never had any issues with sleeping. We do try to limit screen time but have no issues with our child watching TV or playing on her tablet in the evening, providing she has been active the rest of the day.” (BD018, low income)

Additionally, we learned from participants how the social environment influences their child’s adherence to the 24hMBs, though the comments tended to focus more on PA and not in relation to sleep or ST.

“We also have a large communal space at our back door which is enclosed within all the houses so it’s very safe and the kids can play out there with the neighbour kids on bikes or scooters or just running around.” (BD022, low income)

“Our playgroup and childminder do lots of activities and when we meet with friends it’s often a physical activity (such as the park or soft play).” (BD008, high income)

Mesosystem: Time, Routine, and Location

We learned for many of the participants that the time available, the benefit of routines and structure, and the location of the family were all contributing factors in the adherence of the 24hMBs. For many parents the time pressure of working life and family life were factors influencing their child(ren)’s 24hMBs.

“The barriers we have is with work and studies, as we are a young family, we are trying everything to get a better future for them.” (BD005, low income)

“Busy work schedules mean we take the car a lot.” (BD018, low income)

Some participants did offer potential solutions to the negative impact of time.

“Most places ask that parent stay in the building for under 5s. If I could drop him off, then that would give me time for shopping/chores etc so that my time with him could be spent being more active and without screen time.” (BD022, low income)

“Getting the place at nursery really allowed me some time to get things done, think and I felt like my parenting and my mood (tolerance!) improved.” (BD009, low income)

“I think less demand/need for both parents to be working full or full and part time would allow us to live healthier lifestyle, more time for activities and meal preparation or planning instead of going with the quickest option after work.” (BD003, low income)

Time was not always viewed in a negative light and some families found time as a facilitator that helped them to build a better day for their child.

“I’m lucky that both my partner and I have some flexibility in our work.” (BD005, low income)

“I’m now a full-time PGR and, while it’s time consuming, I have the flexibility to work around my kids’ needs.” (BD012, low income)

The need of routines, especially around sleep behaviours, was a common factor in achieving the guidelines within the 24hMBs.

“A good bedtime routine is important to us as our kids aren’t great sleepers.” (BD022, low income)

“I think sleep is good possibly due to a good routine and full-on days.” (BD008, high income)

There was also acknowledgement from one participant recognising that daily demands on time influences sleep with reference to routines.

“Sleep wise, again less work/school may make for more family time and in my opinion better routine.” (BD003, low income)

Whilst routine was in connection with the sleep behaviour, many participants commented on the location where they stayed as a contributing factor when trying to encourage and/or maintain their child(ren)’s PA levels. Opinions and experiences were often linked to the availability of local amenities and opportunities to be active.

“We have a local park close by and plenty of beaches and forests.” (BD008, high income)

“When it’s wet, we tend to take her to either soft play or Silverburn (loving the new indoor kids play areas in Silverburn. Feel we need more of this in Scotland!).” (BD018, low income)

Whilst many participants viewed their location as a facilitator to achieving good levels of PA, there were others who identified their living environment as a barrier.

“I’ll be candid that when she is really active in the house it causes me so much anxiety because our space is so small, and we have stairs. I just constantly am afraid she will get hurt if she is too crazy in the house, so it makes it hard for her to be able to actively play inside on her own.” (BD012, low income)

“We live in a rural area and there isn’t as much to do as a city.” (BD003, low income)

Exosystem: Weather, Seasonal Changes and Guidelines

The weather and seasonal changes were noted as key factors in relation to the 24hMBs, with direct relation to PA and sleep.

“I know I’ve mentioned this before, but the daylight is definitely going to turn our (already bad) sleeper into a worse sleeper. Just last night my son mentioned that the sky was blue during dinner time.” (BD007, high income)

“I think it’s so much easier to get your child active when the weather is good.” (BD011, low income)

Participants provided a mixed view after being presented with the WHO 24hMBs guidelines as part of the ARC data collection method. Some indicated that they were aware of certain guidelines but not all 3.

“I didn’t know about these targets; I had heard of the sleep targets but not the others.” (BD022, low income)

“I’m not sure how much advice is about regarding the activity targets in question as I wasnt aware of them before.” (BD018, low income)

Other participants who had some knowledge of the guidelines felt that there was not enough advice around the guidelines and indicated that they would welcome ideas to help achieve them.

“I don’t think there is a lot of obvious advice or support regarding recommendations or the importance of movement behaviours unless you specifically look for it.” (BD008, high income)

“I’d welcome any ideas for being very active…” (BD022, low income)

In addition, those participants who had some knowledge of the guidelines, felt under pressure to achieve each of them.

“… at some times it can definitely feel like added pressure or judgement that maybe I’m not doing enough as a parent or I’m failing in a certain area…” (BD012, low income)

In relation to knowledge of the 24hMBs guidelines, participants indicated that being part of this study made them more conscious about building a better day for their child(ren).

“I was aware my child spent excessive time on screens, but the graph really emphasised this point and I will do my best to reduce my child’s screen time.” (BD009, low income)

“I always suspected we had too much screen time and too little daily activity. The study has given me the data to confirm my suspicions and the motivation to do something about it.” (BD018, low income)

Table 3

Barriers and facilitators by level of Bronfenbrenner’s socio-ecological model
SUB-THEMES	BARRIER	FACILITATOR
INDIVIDUAL CHARACTERISTICS
Finances Personal health Age	• Childcare costs are expensive. • Number of activities can make it expensive, especially if more than one child. • Constantly ill, upsets activity and sleep. • Child too young for some activities that are available.	• Costs of activities in area are reasonable. • Cheaper costs for activities.
MICROSYSTEM
Family dynamics Parental influences Teachers, friends, family	• More than one child – spreading parental support. • Sleeping arrangements – children must be in beside parents. • Single parent in FT education. • Parent fatigue – screen use is easy option.	• Parents are active and live a healthy lifestyle. • Only one child to support. • Playgroup/Childminder/Friends are all active. • Lessons learned from more experienced parents with older children. • Education and encouragement from nursery staff. • Sense of togetherness in the community.
MESOSYSTEM
Time Routine Location	• Demands from work limit time for other things. • Housework demands – screens used during this to keep child occupied. • Break in routine, upsets sleeping habits. • Rural area – not much to do. • Rental is quite small, indoor activity very hard to do. • Lack of safe indoor space and facilities.	• Close to many amenities. • Community focus on outdoor activity. • Safe and inviting indoor spaces. • Full on days – good sleep routine. • Clear boundaries from parents about bedtime. • Similar routine as parents. • Flexible working arrangements. • 4-day working week – more family time.
EXOSYSTEM
Weather Seasonal Changes Guidelines	• Light/dark nights make it difficult to convince children it is time for bed. • Rain and wind. • Lack of awareness of the guidelines. • Added pressure – feel like not doing enough as a parent.	• More aware of guidelines. • Unique profiles were helpful to highlight areas to work on, and what is working well. • Encouragement through emphasising benefits of the guidelines.

The results of the current study show most of the children in this sample adhere to the sleep and MVPA guidelines (71% and 86% respectively). However, adherence to the total PA guideline and ST guideline is much lower (50% and 21% respectively). While the quantitative findings in this study are based on a small non-representative sample, the findings are in line with previous research which has shown that in western countries, the majority of children meet the sleep guidelines but fail to meet the ST guidelines (31). In addition, approximately half of the sample did not meet the PA guidelines (i.e. both 60 min/day of MVPA and 180 min/day light PA and/or MVPA). These findings indicate there is a need for interventions to address these behaviours early on and to understand the reasons behind non-compliance with the guidelines.

Qualitative results in this study provide insights into the experiences of low-income and high-income families when adhering to the 24hMB guidelines. The results have shown different sub-themes affecting family’s adherence to each of the guidelines both positively and negatively. Results did not appear to differ substantially between low-income and high-income families.

Physical Activity

Finance was a key factor in families being able to adhere to the PA guidelines. Results seemed to indicate that both high-income and low-income families saw the high cost of organised activities as a barrier. Interestingly, feedback from the families tended to focus more on structured PA rather than free play which might provide an insight into how parents perceive what constitutes PA. Previous studies have shown the importance of involving, supporting, and educating parents about the importance of PA for their children in later life but perhaps further work in this area is merited (32). In addition, results from this study suggest that the age of the child can be both a barrier and facilitator to their child’s adherence to the PA recommendations. Some families noted that the age of their child can make adherence to the PA guideline realistic but that it does depend on the level of provision that is available within their community. Families from both low- and high-income backgrounds indicate that provision for children aged 3- to 4-years is adequate in their community whilst other families feel there is a lack of provision in their community. Once again, the provision of what constitutes PA may be a key factor. There is a wide range of research that has investigated the impact the physical environment has on PA levels in children (33–35) but perhaps greater understanding of what constitutes PA would allow more families to adhere with the guideline.

The personal health of families was also a key sub-theme reflected in our results. Many parents indicated that their child was consistently ill which affected their ability to be active, detrimentally influencing their PA guideline adherence. However, it is important to acknowledge that data was collected in Scotland during spells of inclement weather which may have impacted on results. Despite this, one family provided an interesting insight indicating that their own physical limitations (due to health-related issues) made it more difficult for them to encourage their child’s activity levels as they were unable to be active themselves. In contrast, some families felt that as both parents were active, this naturally encouraged their child to be active. Previous studies have shown the influence that parent’ self-efficacy can have on their child’s PA levels (36) and findings from this study support these previous findings.

The dynamics of the family also seemed to influence PA guidelines adherence. Whilst some families indicated that their child having a sibling helped achieve good levels of PA, other families felt it was more difficult as the parent-child time was spread thinly when supporting more than one child. In addition, one participant indicated that for single-parent families it is not always possible to adhere with the PA guideline especially as they are in full-time education and their time to be with their child is limited. Results from this study do seem to indicate that time is a limiting factor to children adhering with the PA guideline, and has been identified in previous research (37).

Sleep

In this study cohort, 71% of families were achieving the recommended sleep guidelines. Income levels did not seem to influence the adherence of sleep guidelines but there were some common barriers and facilitators amongst this study cohort. A recent study in 2022 indicated that a bed-time routine that is consistently maintained has a positive association with good sleep behaviours in infants (38). Results from participants within our study support these findings, although not all families were able to provide a bedtime routine consistently. For a few of the families, their child had had sleeping difficulties from birth and despite establishing a routine, there was no positive association between this and their child’s adherence with the sleep guidelines. In addition, family dynamics also seemed to contribute to children’s adherence to sleep guidelines. Whilst many families managed to achieve the guidelines, there were some families that indicated that their child(ren) had to sleep in beside them to get a good night’s sleep. This is an interesting insight as it throws a light on the importance of understanding not only if the guidelines are achievable but perhaps more importantly how they are being achieved. Further research could help shape future strategies and support for families with children who have sleeping difficulties. For example, a recent systematic review on sleep behaviours in infants has shown a positive association between behavioural strategies and improved sleep behaviours (39). Whilst establishing a good bedtime routine does seem to facilitate appropriate sleep behaviours, further understanding of sleep behaviour strategies may increase the number of families adhering with the guidelines potentially leading to an improvement in overall health outcomes. However, the strategies and support for family’s needs to also consider other barriers to sleep such as illness and poor health. In our study, illness and poor health were clearly cited by participants as a barrier to sleep guideline adherence. Similarly, a break in routine (i.e. later nights during holidays etc) was also cited as a barrier to sleep, though this is likely to be short-term once the routine is reestablished. What was clear from this study is that income did not influence sleep guidelines adherence.

Screen Time

Results from parent-reported ST indicated that only 21% of families managed to adhere with the ST guidelines. Of these families, facilitating ST guidelines adherence was influenced through a combination of setting strong parameters around screen use, the availability of alternative use of time (i.e., community groups and outdoor activities, garden space, amenities close by), and the education and lessons received from education and nursery staff. The most prominent barrier to adhering with the ST guidelines was an over-reliance on screens being used to occupy children when housework was to be done, including meal preparation. Many of the participants in this study indicated that they would often use ST as a means of keeping their child occupied or at rest, when they were making the family dinner or tidying up the house. Some family’s indicated that they viewed ST in a more positive light, as it could be used to connect with distant family members and at times were used for learning and education purposes also. These findings do suggest that although there are clear quantitative guidelines for ST in 3- to 4-year-old children, the quality of this interaction should be carefully considered. Previous research has shown a combination of positive and negative influences of ST use in young children but equally the importance of considering the purpose and use of this screen use (40). However, previous studies have identified that parent habits when using screens directly influences children’s ST (41). Within our study, there were families who relied heavily on screens during times when family and household chores were needing to be done, but for some families there was acknowledgement that the habits of the older siblings and the parents influenced their child’s ST and could be addressed.

24hMBs

Families who were aware of the guidelines felt they were both a barrier and facilitator to adherence. Some families indicated feeling motivated to achieve the recommendations and were prepared to make changes accordingly. In contrast, there were families who felt that knowledge of the guidelines increased the pressure on parents to do what is best for their child. These parents did not feel empowered by the guidelines but felt a sense of disappointment indicating that it made them feel as though they were not doing enough for their child when one or more behaviours was not within the recommended level. Parent opinions were common among both low-income and high-income families suggesting that financial status is not a primary factor in families adhering to each of the three behaviours. Whilst previous research has indicated lower adherence to the guidelines is common in lower developed countries, there is no current evidence indicating the impact of guidance awareness on low-, middle- or high-income families achieving one, two, or more of the recommendations (4, 6, 19)

Findings from this study indicate that each family’s adherence to the guidelines is different when considering each of the behaviours individually, than when combining two or more of these behaviours. For example, the family whose children have not been good sleepers from birth causes sleep deprivation in all the family and thus not having enough energy to adhere to the PA guidelines the following day. In addition, one family reported using ST in the morning to allow the parents to sleep a little more as their sleep was disturbed through the night. Results from this study demonstrate that the interrelationship between each of the three 24hMBs should be carefully considered to fully support and encourage guidelines adherence in children aged 3- to 4-years.

Within this study cohort, there does seem to be a consensus that when families are made more aware of their individual circumstances (i.e., to measure and monitor their child’s 24hMBs), they become more conscious of trying to adhere with the guidelines. It does appear as if raising better awareness of the guidelines and individualising this for each family could lead to more families adhering with these and lead to building a better day for their child. For example, during this project, when each family was provided with their own unique profile, the comments offered included the ease of its use, as well as how conscious they became of changes that were required from the family to adhere to one or more of the guidelines. This does suggest that further research into how the guidelines is conveyed to the public is required. This would have to involve key stakeholders and public health authorities to liaise more directly with families and in addition consider the influence that each of the four levels within Bronfenbrenner’s socio-ecological framework have on guideline adherence. Training suitable personnel within the public health domain, as well as pre-school and schools, could provide families with adequate support and guidance when trying to make changes in adhering to the 24hMB guidelines.

Strengths and Limitations

The strengths from this study included the use of objectively measured PA using the accelerometer Actigraph GTX3 + for seven consecutive days. This along with the parental diaries allowed us to accurately track the activity levels and sleep patterns. This data was then utilized to provide individualised visual graphs of the children’s adherence to the 24hMBs and formed part of the discussion during the qualitative phase which informed the parents well. In addition, the use of high- and low-income families provided an opportunity to compare any differences between these two population cohorts.

Limitations in this study included a lower number of low-income families (n = 15) than anticipated, though this was more than the number of high-income families involved in the study (n = 9). This is in keeping with other similar studies that have stated that it is hard to recruit low-income families in research. Amongst the parents there was only one male participant involved in the qualitative phase, and this may have influenced the data and perspectives offered from this study cohort. It prevented an opportunity to analyse if male and female perspectives on adhering to the 24hMBs differed in terms of barriers and facilitators. The dropout rate for the quantitative data was four participants, and the drop-out rate for the qualitative data was 8 participants. Parents who dropped out of the quantitative phase were generally due to their child not wanting to wear the device, or the device being returned with no data stored. The drop-out of four further participants during the 6-week qualitative phase was a combination of being too busy to participate in the 6-week data collection phase, or just a breakdown in communication despite encouraging their participation via email and social media.

This study has identified that there are numerous factors on all levels of the socio-ecological framework that need to be considered when promoting, supporting, and encouraging family’s adherence to the 24hMB guidelines. Whilst previous studies have indicated differences between low- and high-income families with respect to guideline adherence, this was not supported by this study. Nevertheless, family circumstances did appear to play a substantial role in guideline adherence and future intervention studies aiming to promote 24-hour movement behaviours should consider how these family difference can be accounted for.

WHO – World Health Organisation

MVPA – Moderate-to-Vigorous-Physical Activity

ST – Screen Time

PA – Physical Activity

24hMB – 24-hour Movement Behaviour

ARC – Asynchronous Remote Communities

PGR – Post-Graduate Researcher

Ethics approval and consent to participate

Ethical approval has been obtained from the Department of Psychological Sciences and Health Ethics Committee at the University of Strathclyde. Informed consent was obtained from all participants to participate in the study.

Consent for publication

Participant consent was obtained to allow anonymised data to be made available for publication.

Availability of data and materials

The de-identified data from this study will be made available as “open data” through a research data repository. Information such as name, address and email will not be included in the dataset uploaded. The database will remain there indefinitely. Any person who wants access to that data on the repository will need to submit a data request explaining why they want to use the data.

Competing Interests

There are no competing interests.

Funding

Funding was received from the QSR Early Career Grant.

Author’s contributions

AD made substantial contributions to the design and writing of this work. AD was responsible for conducting the research and investigation process, specifically coordinating the qualitative data collection and analysis. XJ conceptualised and acquired the funding for this work and made substantial contributions to the design of this study. XJ has full management, coordination, leadership, and oversight responsibilities for the research. FM was responsible to cross-check the coding and analysis of the qualitative data and contributed to edits of this manuscripts. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

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No competing interests reported.

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Barriers and Facilitators to Physical Activity, Screen time and Sleep in 3- to 4-year-olds living in Scotland

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Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Design and recruitment

Participants

Protocol

Parent questionnaire

Objectively measured physical activity, sedentary behaviour, and sleep

Qualitative data

Analysis

Results

Quantitative

Qualitative

Individual Characteristics: Age, Finances, and Personal health

Microsystem: Family dynamics, Parental influences, and Social environment

Mesosystem: Time, Routine, and Location

Exosystem: Weather, Seasonal Changes and Guidelines

Discussion

Physical Activity

Sleep

Screen Time

24hMBs

Strengths and Limitations

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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