The scientific motivation behind the study stems from a fundamental shift in how researchers think about physical activity, sedentary behaviour, and sleep. For decades, epidemiologists examined each of these behaviours in isolation, asking, for example, whether more exercise lowers the risk of heart disease or whether prolonged sitting raises the risk of type 2 diabetes. The evidence from such studies is clear: higher physical activity, less sedentary time, and adequate sleep are each associated with lower risks of cardiovascular disease, type 2 diabetes, obesity, several cancers, anxiety, depression, and premature mortality. But there is a hidden flaw in treating these behaviours separately. Time is finite. Every additional minute spent sitting is a minute not spent standing, stepping, or sleeping. The three behaviours are co-dependent components of a single twenty-four-hour whole, and analysing them independently distorts their true relationships with health.

This realisation has driven what researchers call the 24-hour movement paradigm, a framework that treats physical activity, sedentary behaviour, and sleep as inseparable parts of a daily time-use composition. The paradigm has already reshaped public health policy: several countries, including Canada, Australia, Thailand, South Africa, Saudi Arabia, and Egypt, along with the World Health Organization, have issued integrated 24-hour movement guidelines. Yet the first generation of these guidelines was built largely on studies that examined single behaviours in isolation, because rigorous evidence on their combined effects simply did not exist. The authors of the Canadian 24-hour movement guidelines for adults explicitly called for research with stronger designs, including longitudinal follow-up, device-measured behaviours, and attention to dimensions such as domain-specific activity, sleep consistency, napping, and daytime alertness. The Slovenian team designed the GIB study to answer exactly these calls.

The recruitment strategy leverages an existing national infrastructure. Every four years, the Statistical Office of Slovenia draws a nationally representative sample of 17,500 residents aged 18 to 74 from the Central Population Register, using stratified simple random sampling with region and settlement type as strata. These individuals are invited by post to complete the National Health-related Lifestyle Survey, conducted by the National Institute of Public Health, which historically achieves a response rate of around 60 percent. From the roughly 10,500 survey responders, the GIB team expects about 5 percent to accept an additional invitation to the device-based study, yielding approximately 525 participants per recruitment wave. The first baseline data collection took place in 2024, with subsequent waves planned for 2028, 2032, and beyond, creating a rolling cohort intended to span more than a decade.

At the heart of the measurement strategy sits the activPAL4micro, a small tri-axial accelerometer measuring just 4 by 2 by 0.4 centimetres and weighing 9 grams, which is attached to the front of the thigh. Unlike wrist-worn devices, thigh placement allows the monitor to distinguish posture with high precision: sitting, standing, lying, and stepping can be classified directly from body position rather than inferred from wrist movement. Participants wear the device for seven consecutive days, twenty-four hours per day, including during sleep, and simultaneously keep a diary recording bedtimes, wake times, naps, night-time awakenings, and, for employed participants, working hours. Sleep onset and offset are then determined by combining the algorithmic output with diary entries, with adjustments applied when the device records upright activity near the reported sleep window. The result is a complete, posture-based map of each participant’s entire week.

From these raw data, the researchers will construct two complementary time-use compositions. The first is posture-based, comprising stepping, standing, sitting, lying while awake, and sleeping. The second is movement-based, comprising moderate-to-vigorous physical activity, light-intensity physical activity, sedentary behaviour, and sleep. For employed participants, a third, domain-specific composition will separate occupational from non-occupational behaviour, allowing the team to ask whether physical activity at work carries the same health value as leisure-time exercise, a question with major implications for millions of workers in physically demanding jobs. Non-wear time will be proportionally reallocated to wake-time behaviours, daytime naps will be added to sleep time, and validated algorithms will process the event files in the R programming environment.

The device data will be complemented by an extensive battery of questionnaires. A novel ten-item instrument, the GIB24-Q, developed specifically for Slovenian population surveillance, asks about domain-specific moderate-to-vigorous activity, muscle-strengthening and balance exercise, walking, sedentary behaviour, recreational screen time, and sleep. The widely validated Global Physical Activity Questionnaire provides an international benchmark. The 46-item Healthy Built Environment Questionnaire captures perceptions of neighbourhood, home, and workplace environments, along with time spent outdoors and in nature. Each participant’s home address will also be linked to the Walk Score index, an open-access measure of neighbourhood walkability ranging from 0 to 100, and to environmental indicators including air quality and the number of days with high temperatures, enabling the team to test whether the places people live shape the way they move.

Well-being and health will be assessed through eight short validated instruments: the WHO-5 Well-being Index for subjective mental well-being, the Need for Recovery Scale for work-related fatigue, the International Fitness Scale for perceived fitness, the Epworth Sleepiness Scale for daytime sleepiness, the Fatigue Assessment Scale for chronic fatigue symptoms, the Satisfaction With Life Scale, the Perceived Time Poverty Scale, which measures the feeling of lacking freely disposable time, and the Nordic Musculoskeletal Questionnaire for pain across nine body regions. In parallel, each participant’s data will be linked to the National Health-related Lifestyle Survey, which covers demographics, diet, smoking, alcohol, self-rated health, diagnosed conditions, medication use, stress, social support, body mass index, and waist circumference. From 2028 onward, with additional informed consent, the team will link records to national registers covering healthcare utilisation, hospitalisations, drug prescriptions, sickness absence, retirement, disease incidence, and causes of death, all under strict data protection law and GDPR compliance.

The statistical approach is as innovative as the data collection. Because the components of a 24-hour composition are co-dependent, conventional regression is inappropriate; the team will instead apply compositional data analysis, expressing time-use as sets of isometric log-ratio coordinates before entering regression models, handling zeros with a log-ratio expectation-maximisation algorithm, and applying survey weights to preserve national representativeness. An a priori power analysis determined that the expected sample of roughly 472 participants per wave providing valid accelerometer data is sufficient to detect a minimum effect size of 0.2 with 80 percent power. For significant findings, the researchers will map what they call the Goldilocks Zone: the range of 24-hour movement compositions, estimated at ten-minute granularity, associated with the best 5 percent of predicted health outcomes, and will search for compositions that fall in the optimal zone across multiple health outcomes simultaneously.

The potential payoff is considerable. The GIB study will deliver the first device-measured estimates of 24-hour movement behaviours in a national sample of Slovenian adults, identify the socio-demographic and environmental factors that shape healthy and unhealthy time use, and clarify the relative importance of occupational versus leisure activity, sleep regularity, and specific postures for long-term health. As Slovenia develops its own 24-hour movement guidelines, the findings will provide directly relevant, population-specific evidence, and the team anticipates contributing data to international consortia pooling thigh-worn accelerometer records worldwide. If the study succeeds in defining Goldilocks Zones for daily time use, the humble question of how a nation spends its twenty-four hours could yield some of the most actionable health guidance of the coming decade.

Subject of Research: A longitudinal population-based study of 24-hour movement behaviours, their correlates, and health associations in Slovenian adults

Article Title: Prevalence, correlates, and health associations of 24-hour movement behaviours in Slovenian adults: a protocol for a longitudinal population-based study

Article References: Kastelic, K., Knific, T., & Šarabon, N. (2025). Prevalence, correlates, and health associations of 24-hour movement behaviours in Slovenian adults: a protocol for a longitudinal population-based study. Journal of Activity, Sedentary and Sleep Behaviors, 4(1), Article 3. https://doi.org/10.1186/s44167-025-00073-z

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00073-z

Keywords: 24-hour movement behaviours, physical activity, sedentary behaviour, sleep, compositional data analysis, accelerometry, longitudinal study, population health, built environment, well-being, Slovenia, movement guidelines

The review, led by Nicholas Kuzik of the Healthy Active Living and Obesity Research Group at the Children’s Hospital of Eastern Ontario Research Institute, together with Markus J. Duncan, Natalie Beshara, Matthew MacDonald, Diego Augusto Santos Silva and Mark S. Tremblay, examined studies applying compositional data analysis, or CoDA, to 24-hour movement behaviours in school-aged children aged 5 to 17.9 years. Unlike conventional analyses that treat sleep, sedentary time, light physical activity and moderate to vigorous physical activity as independent variables, CoDA respects the zero-sum reality of the day. It treats time-use data as relative information, typically through isometric log-ratio transformations, so that the effect of any single behaviour is always interpreted in the context of all the others. Since Chastin and colleagues first applied the technique to movement behaviours in 2015, the field has grown rapidly, and this review is the first attempt to pool its results quantitatively across health domains.

The team registered the review with PROSPERO and followed PRISMA guidelines, searching MEDLINE, EMBASE, PsycINFO, CINAHL and SPORTDiscus up to May 24, 2024, and restricting inclusion to peer-reviewed English-language studies published since January 2014. From 1,217 identified records, 26 studies survived full-text screening. Sample sizes ranged from 88 to 5,828 participants with a median of 387, and mean ages spanned 8.0 to 16.4 years. Twenty-three studies were cross-sectional, two reported both cross-sectional and longitudinal results, and one was purely longitudinal. Study quality, appraised with the Joanna Briggs Institute checklist, was high for most groupings, with only four categories rated moderate.

The 26 studies reported their compositional results in four distinct ways. Sixteen used regression parameters, typically pivot coordinates that isolate the influence of one behaviour relative to the rest of the composition. Twelve reported substitution effects, estimating what happens when a fixed slice of time is swapped from one behaviour to another. Three identified optimal compositions, the so-called Goldilocks Days, and one compared clusters of movement behaviours. Because reporting practices varied so widely, the authors standardized substitution effects to 10-minute increments and converted them to standardized mean differences, pooling them with random-effects models that anticipated substantial heterogeneity across the many health outcomes involved.

The descriptive picture that emerged is itself a public health warning. Across the 51 samples contributing data, the weighted compositional means were approximately 9.1 hours of sleep, 8.9 hours of sedentary behaviour, 5.1 hours of light physical activity and just 0.8 hours, about 49.8 minutes, of moderate to vigorous physical activity per day. That figure sits below the 60-minute daily recommendation, a shortfall echoed globally: the Global Matrix 4.0 report card across 57 countries graded children a D for overall physical activity, with only 27 to 33 percent meeting the guideline, and a D-plus for sedentary behaviour, with 34 to 39 percent keeping recreational screen time under two hours.

The pooled regression results were largely null, but telling patterns surfaced within specific outcome categories. Every one of the ten associations between moderate to vigorous physical activity and adiposity indicators was favourable, as were nine of eleven associations with cardiometabolic biomarkers. Light physical activity, by contrast, was unfavourable in eight of ten adiposity findings and five of seven cognitive findings, while sedentary behaviour was unfavourable in seven of ten adiposity results. In other words, when the whole day is held constant, the intensity of movement matters: the modest minutes children spend truly moving appear to do disproportionate work, while the long hours of gentle activity and sitting lean the other way.

The meta-analyses of substitutions delivered the review’s most striking quantitative message. Replacing 10 minutes of sedentary behaviour, sleep or light activity with 10 minutes of moderate to vigorous physical activity was associated with a 0.1 standardized mean difference improvement in overall health and well-being. The reverse trade was far more damaging: surrendering 10 minutes of that vigorous activity to any of the other three behaviours produced a 0.2 standardized mean difference decline. As the authors put it, the risk of losing vigorous activity is double the magnitude of the benefit of gaining it. One illustrative study found that middle school students who exchanged 10 minutes of sleep or sitting for vigorous movement saw a 0.1 drop in BMI z-score. The practical implication is urgent: beyond promoting more exercise, public health strategy must actively protect the limited vigorous activity children already accumulate, since once lost, it is disproportionately hard to win back.

Longitudinal substitutions, drawn from only two studies, hinted that sleep’s benefits may grow over time, with a 10-minute swap of sleep for vigorous activity associated with a small unfavourable change while the sedentary-for-vigorous swap remained favourable, though effect sizes were tiny and the evidence preliminary. The Goldilocks Day analyses, meanwhile, offered a glimpse of what an optimized day might look like. Across two studies of adiposity, the weighted ideal comprised 9.8 hours of sleep, 10.1 hours of sedentary behaviour, 2.5 hours of light activity and 1.6 hours of moderate to vigorous physical activity. For broader health spanning mental, cognitive and physical domains, one study pointed to 10.4 hours of sleep, 9.7 hours of sedentary time, 2.4 hours of light activity and 1.5 hours of vigorous activity. Yet even here, methodological fragility loomed large: two analyses of the same bone health dataset diverged by more than an hour in their recommended vigorous activity simply because one weighted accelerometer data to account for weekends and the other did not.

That sensitivity underscores the review’s methodological critique. Only nine of the 26 studies reported dispersion metrics for movement behaviours, leaving uncertainty about how much children’s time use actually varies. Most studies reported only the first pivot coordinate rather than full model parameters, limiting replication and meta-analysis. And the handling of accelerometer non-wear time emerged as a hidden elephant in the room: normalizing geometric means to 1,440 minutes implicitly imputes unmeasured time in the same ratios as measured time, which can push a child recording 7 hours of sleep and 45 minutes of vigorous activity into apparent compliance with both guidelines. The authors argue for epoch-by-epoch imputation techniques, consensus on accelerometer processing, a DELPHI-derived reporting checklist for observational CoDA studies, and routine reporting of arithmetic means alongside geometric ones.

The review’s limitations are acknowledged candidly: heterogeneity across outcomes forced broad category groupings, the a priori questions about optimal distributions and covariates could not be fully answered with available data, and the substitution effects depend on baseline compositions that varied between studies, sometimes by more than the 10-minute increments being modelled. Still, the core conclusions align with earlier reviews, including a 2025 meta-analysis of adiposity outcomes, while adding a sharper edge. The messages of moving more, sitting less and sleeping well survive the compositional lens, but the day’s arithmetic gives them new weight. In a world where the average child logs under 50 minutes of vigorous activity, every one of those minutes is an asset whose loss costs twice what its gain delivers, and the field’s next task is to move from more-or-less messaging toward the precise, personalized balances that a constrained 24-hour day demands.

Subject of Research: Compositional data analysis of 24-hour movement behaviours and health outcomes in school-aged children

Article Title: A systematic review and meta-analysis of the first decade of compositional data analyses of 24-hour movement behaviours, health, and well-being in school-aged children

Article References: Kuzik, N., Duncan, M. J., Beshara, N., MacDonald, M., Silva, D. A. S., & Tremblay, M. S. (2025). A systematic review and meta-analysis of the first decade of compositional data analyses of 24-hour movement behaviours, health, and well-being in school-aged children. Journal of Activity, Sedentary and Sleep Behaviors, 4(1), Article 4. https://doi.org/10.1186/s44167-025-00076-w

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00076-w

Keywords: compositional data analysis, 24-hour movement behaviours, physical activity, sedentary behaviour, sleep, children, adolescents, meta-analysis, systematic review, MVPA, adiposity, health guidelines

The research team screened 21,418 references drawn from six major databases, including PubMed/MEDLINE, Scopus, Web of Science, SPORTDiscus, PsycINFO and Open Dissertations. From this vast pool, only 40 papers met the stringent inclusion criteria, which required studies to report total, direct or indirect monetary costs associated with at least one of the three movement behaviours in the general adult population. That small yield is itself revealing. Despite growing scientific consensus that physical activity, sedentary behaviour and sleep should be understood as a continuous, integrated 24-hour cycle of time use, the economic evidence base remains remarkably thin, fragmented and geographically skewed. Fully 77.5 percent of the included studies came from high-income countries, and an equally striking 77.5 percent addressed the costs of physical activity alone, leaving sedentary behaviour and sleep largely neglected in economic terms.

The methodological foundation of the review deserves attention because cost-of-illness studies vary enormously in how they count the money. Most of the included research, some 90 percent, relied on self-reported movement-behaviour data rather than device-based measurements, a choice that introduces well-documented recall and social desirability biases. People systematically overestimate how much they move and underestimate how long they sit. Many of the studies also employed the population attributable fraction approach, a technique borrowed from epidemiology that estimates what proportion of disease burden and associated costs could be avoided if exposure to a risk factor, such as insufficient exercise, were eliminated from the population. When applied to national data, PAF-based studies estimated the total annual cost of insufficient physical activity at between 1.94 and 9.78 billion US dollars, while the cost of excessive sedentary behaviour ranged from 1.82 to 1.97 billion dollars.

Sleep, the third pillar of the movement-behaviour triad, fared worst in terms of research attention. Only a single study in the review used the population attributable fraction approach to estimate the economic cost of inadequate sleep duration, placing Canada’s national bill at 0.44 billion US dollars per year. That figure, while substantial in absolute terms, is dwarfed by the estimates for physical inactivity, and the authors caution that it rests on a solitary data point rather than a robust, replicated body of evidence. The scarcity of sleep-cost studies is especially notable given the accelerating public health interest in sleep as a modifiable risk factor for cardiometabolic disease, mental illness, workplace accidents and lost productivity.

Perhaps the most consequential finding of the review is the relative ranking of the three behaviours. Across the included studies, the economic cost of insufficient physical activity was approximately two to four times higher than the cost of excessive sedentary behaviour and roughly sixteen times higher than the cost of inadequate sleep duration. On the basis of this cost hierarchy, the authors suggest that public health initiatives should focus primarily on promoting physical activity, while continuing to address sitting time and sleep within a broader 24-hour framework. The conclusion carries practical weight for policymakers forced to allocate finite prevention budgets: if the goal is to maximise the economic return on public health investment, getting populations moving appears to deliver the largest financial dividend.

The direct and indirect cost categories underlying these figures illuminate why unhealthy movement behaviours drain national economies so severely. Direct costs encompass healthcare expenditure, including hospital admissions, physician visits, medications and treatment for conditions attributable to inactivity, prolonged sitting or poor sleep, such as cardiovascular disease, type 2 diabetes, several cancers, depression and musculoskeletal disorders. Indirect costs capture productivity losses from absenteeism, presenteeism, premature mortality and unpaid informal care. Because movement behaviours influence such a wide array of chronic diseases, even modest shifts in population-level behaviour can translate into enormous aggregate expenditure changes. A behaviour that raises the risk of multiple conditions simultaneously multiplies its economic footprint across every disease pathway it touches.

The review’s global picture, however, remains frustratingly incomplete. The authors emphasise that while billions of dollars are cumulatively spent each year on the adverse consequences of unhealthy movement behaviours worldwide, the exact global cost could not be estimated because evidence exists only for a limited number of mostly high-income countries. This gap matters enormously. Low- and middle-income countries bear a growing share of the global burden of non-communicable disease, driven by rapid urbanisation, motorised transport, desk-based employment and changing dietary and sleep patterns, yet virtually no economic cost estimates exist for these settings. Without local cost data, governments in these countries lack the financial arguments needed to justify investment in physical activity infrastructure, workplace interventions or sleep health programmes.

The study also highlights a deeper conceptual challenge within the field. Public health research is increasingly shifting toward an integrative, compositional view of daily time use, in which physical activity, sedentary behaviour and sleep are treated as interdependent components constrained by the finite 24-hour day. Time spent in one behaviour necessarily displaces time in another, so the health and economic effects of any single behaviour depend on what it replaces. Yet the economic literature reviewed here remains overwhelmingly siloed, with most studies costing one behaviour in isolation and almost none examining the economic consequences of failing to meet the overall 24-hour movement guidelines that now appear in national and international recommendations. The authors explicitly call for more research exploring the costs of non-compliance with these integrated guidelines.

Looking forward, the research agenda outlined by the review is clear. Future studies should extend cost estimation to low- and middle-income countries, replace self-reported behaviour data with device-based measurements from accelerometers and other research-grade movement sensors, and address the glaring underrepresentation of sedentary behaviour and sleep in economic analyses. Until such work is done, the 9.2 billion dollar Canadian figure and the multi-billion dollar estimates for physical inactivity should be read as conservative, incomplete accounting of a problem whose true global scale remains hidden. What the review makes unambiguous is that unhealthy movement is not merely a personal health risk but a macroeconomic liability, and that the price of collective inactivity compounds year after year on national balance sheets.

Subject of Research: Systematic review of the economic costs of insufficient physical activity, excessive sedentary behaviour and inadequate sleep duration in adults

Article Title: Economic cost of movement behaviours: a systematic review

Article References: Chen, S., Matolic, T., Memon, A. R., Rachele, J. N., Grgic, J., Espinoza, M. A., & Pedisic, Z. (2026). Economic cost of movement behaviours: a systematic review. Journal of Activity, Sedentary and Sleep Behaviors. https://doi.org/10.1186/s44167-026-00108-z

Image Credits: AI Generated

DOI: 10.1186/s44167-026-00108-z

Keywords: physical activity, sedentary behaviour, sleep, economic cost, systematic review, public health, cost of illness, 24-hour movement behaviours, population attributable fraction, health economics, physical inactivity, chronic disease

The intervention, called Happy Homework 2.0, is a digital application designed to weave movement-based activities into the routines children already follow at home. Rather than adding another demand to crowded school timetables, the programme exploits a slot that already exists in every child’s evening. The concept builds on a growing body of evidence that school-based interventions, while scalable, often lose their impact once children leave the school gates. Homework, the researchers reasoned, could act as a bridge, extending the reach of classroom health messaging into the living room, the garden and the bedroom, where most sedentary time and sleep actually occur.

To test whether the idea could work in practice, the team conducted an eight-week pilot cluster randomised controlled trial across four primary schools in the West of Scotland. In a cluster randomised design, entire classes rather than individual children were allocated to either the intervention or the control condition, a method that reduces the risk of contamination between participants who see each other every day. A total of 82 children aged between 8 and 12 years took part, representing 60 percent of those invited, and 87 percent of them were still providing data at follow-up. Those retention figures, the researchers report, indicate good feasibility for a trial of this kind, which is precisely what a pilot study is designed to establish before larger, fully powered trials are attempted.

The evaluation went beyond simple attendance numbers. Feasibility, usability and acceptability were assessed through basic app-usage analytics and questionnaires completed by three separate constituencies: the children themselves, their parents, and their teachers. Gathering perspectives from all three groups matters because a digital health intervention for children sits at the intersection of competing interests. Children must find the app engaging enough to open it voluntarily, parents must be willing to accommodate it in the evening routine, and teachers must see enough value to integrate it into their homework expectations without it becoming a burden.

The study also collected objective data on the outcomes that matter most. Children wore activPAL devices, small sensors attached to the thigh that distinguish between sitting, standing and stepping based on posture rather than relying on self-report. This technology provided multiple posture- and movement-based metrics, giving the researchers a far more reliable picture of sedentary behaviour than questionnaires alone could offer. Sleep was measured through self-report questionnaires, and children’s motivation was assessed using instruments based on basic psychological need satisfaction, a framework rooted in self-determination theory, which holds that motivation flourishes when people feel autonomous, competent and connected to others.

The statistical analysis used linear mixed-effects models, a technique well suited to this kind of trial because it accounts for two sources of dependency in the data: the clustering of children within schools, and the fact that each child was measured repeatedly over time. By modelling group-by-time interactions, the researchers could ask whether children in the intervention arm changed differently from those in the control arm, rather than simply comparing average values at the end of the study. This approach is now standard in behavioural trials, but its careful application in a small pilot is notable, because it demonstrates that the study design can detect genuine signals even before scaling up.

What did those signals show? The most striking finding concerned sedentary behaviour. The activPAL data revealed a significant group-by-time difference, with sedentary time increasing more in the intervention group than in the control group, a difference of 66.2 minutes per day that reached statistical significance. Self-reported sleep also showed a significant interaction, with smaller increases in reported sleep duration among children using the app relative to controls. No other secondary outcomes, including measures of physical activity, showed significant group-by-time differences. Taken at face value, these results are not the triumphant headline one might hope for from a movement intervention: the app did not reduce sitting or boost activity in the intended direction during this pilot period.

The researchers are candid about the most likely explanation: engagement. The app-use analytics showed repeated engagement among participants, but overall use was modest, defined by declining frequency and duration of interactions over the eight weeks. In other words, children tried the app, returned to it for a while, and then gradually drifted away, a pattern familiar to anyone who has downloaded a fitness app with good intentions in January and abandoned it by March. When the dose of an intervention falls, its effects tend to attenuate with it. The team concludes that Happy Homework 2.0 was feasible and acceptable as a homework-based health intervention, but that engagement levels likely limited its effectiveness, and the unexpected shifts in sedentary time and sleep may reflect this weak implementation rather than any inherent failure of the concept.

That interpretation is where the real scientific value of the study lies. Pilot trials are not meant to deliver definitive answers; they are meant to expose the practical friction points that would otherwise sabotage a large trial. Here, the friction is clear: sustaining children’s voluntary engagement with a digital health tool over weeks, not days, remains the central challenge of mHealth interventions for young people. The authors emphasise the need to strengthen implementation strategies, sustain engagement, and enhance the involvement of parents and teachers, the two adult groups whose encouragement could counteract the natural decay of novelty. The study was retrospectively registered as NCT07631754, funded through a University of the West of Scotland Vice-Chancellor’s Studentship Scheme, and published open access in the Journal of Activity, Sedentary and Sleep Behaviors.

The broader lesson extends well beyond one Scottish app. Digital interventions promise scale and personalisation that classroom programmes cannot match, but they also compete for attention in an ecosystem saturated with far more compelling screen content. The paradox is sharp: an app designed to pull children away from screens must first win a battle for screen time. Future iterations of Happy Homework, and similar tools now in development through co-design studies with children and families, will need to treat engagement not as an afterthought but as the primary design target, using gamification, family involvement and curriculum integration to keep the dose high enough for biology to respond. The 24-hour movement behaviours of children remain a modifiable target, and the homework slot remains an underexploited opportunity. What this pilot establishes is that the pipeline from idea to evidence works; what it also establishes is that the hardest variable to move is not the child’s body, but the child’s attention.

Subject of Research: A pilot cluster randomised controlled trial testing the feasibility, acceptability and usability of a digital homework app targeting physical activity, sedentary behaviour and sleep in primary school children.

Article Title: Happy Homework 2.0: effects on 24-hour movement behaviours in children—findings from a pilot cluster randomised controlled trial

Article References: Forrest, A., Buchan, D. S., Sculthorpe, N., & Robinson, S. (2026). Happy Homework 2.0: effects on 24-hour movement behaviours in children—findings from a pilot cluster randomised controlled trial. Journal of Activity, Sedentary and Sleep Behaviors. https://doi.org/10.1186/s44167-026-00111-4

Image Credits: AI Generated

DOI: 10.1186/s44167-026-00111-4

Keywords: physical activity, sedentary behaviour, sleep, children, homework, digital intervention, mHealth, cluster randomised controlled trial, 24-hour movement behaviours, app development, school-based intervention, activPAL