From a false sense of safety to resilience under uncertainty.

Understanding and acting upon risk is notably challenging, and navigating complexity with understandings developed for stable environments may inadvertently build a false sense of safety. Neglecting the potential for non-linear change or "black swan" events - highly impactful but uncommon occurrences - may lead to naive optimisation under assumed stability, exposing systems to extreme risks. For instance, loss aversion is seen as a cognitive bias in stable environments, but it can be an evolutionarily advantageous heuristic when complete destruction is possible. This paper advocates for better accounting of non-linear change in decision-making by leveraging insights from complex systems and psychological sciences, which help to identify blindspots in conventional decision-making and to develop risk mitigation plans that are interpreted contextually. In particular, we propose a framework using attractor landscapes to visualize and interpret complex system dynamics. In this context, attractors are states toward which systems naturally evolve, while tipping points - critical thresholds between attractors - can lead to profound, unexpected changes impacting a system's resilience and well-being. We present four generic attractor landscape types that provide a novel lens for viewing risks and opportunities, and serve as decision-making contexts. The main practical contribution is clarifying when to emphasize particular strategies - optimisation, risk mitigation, exploration, or stabilization - within this framework. Context-appropriate decision making should enhance system resilience and mitigate extreme risks.

How do behavioral public policy experts see the role of complex systems perspectives? An expert interview study.

Amidst the global momentum of behavioral insights (BI), there has been a shift from mostly nudge-based BI applications to systemic approaches. This is particularly pressing in public health, where interacting issues regularly produce unanticipated consequences. Regardless, little is known about adopting complex systems approaches in behavioral public policy. This study aims to capture current practices of international BI experts on the definition, application, drivers, and hindering factors in adopting complex systems approaches in public policy. Semi-structured individual expert interviews (n = 12) of international BI experts with extensive experience in educating, cooperating with, and/or advising public servants were analyzed with inductive content analysis. While the working definition of BI aligned with published definitions, experts varied in their descriptions of complex systems approaches and its significance for public policy, including socioecological aspects, systematic BI use across policy stages, recognizing intertwined behavior, and lack of ready-made solutions. They emphasized the importance of systems approaches, identifying drivers (e.g. need for a broader focus) and hindrances (e.g. pressure for quick results). Embracing complex systems in behavioral public policy provides a holistic perspective, extending beyond simple nudges, sometimes presumed as universally applicable. While complexity perspectives would align with policymakers' worldview, applications require more work to tailor to local situations and to evaluate. Recognizing that, given their distinct expertise content, BI expertise can be quite different from complex systems expertise. The field would benefit from clear descriptions and specialized training for effective integration and advocacy for these approaches.

In recent years, the use of behavioral insights (BI) in public policy, including health policy, has been shifting from nudges to more comprehensive approaches. This study examines how international BI experts view the use of complex systems approaches in behavioral public policy. Through interviews with 12 experts advising public servants, we found that while BI definitions align with earlier published definitions, experts interpret and apply complex systems approaches differently. Some consider socioecological factors, advocate applying the systematic use of BI throughout the policy cycle, and for some using complex systems approaches means considering intertwined nature of behavioral phenomena and that there are no one-size-fits-all solutions. Experts stress the importance of a systems approach, identifying drivers (e.g. need for a broader focus, experience-based expertise) and hindering factors (e.g. advisory settings, pressure for quick results) in its implementation. This study presents BI's evolving role in public policy, highlighting the need for complex systems approaches to address multifaceted societal challenges.

Stable isotope analyses of carbon and nitrogen in hair keratin of suspected man-eating wolves from 1880s.

The so-called man-eating wolves of Turku, a pack of three wolves, reportedly killed 22 children in South-Western Finland in 1880-1881. Enormous efforts were carried out to eradicate them. In January 1882 the last remaining wolf was killed. Since then, there has been considerable debate regarding the validity and extent of the man-eating behaviour. This study aims to clarify whether man-eating behaviour can be observed from the remains of these wolves. One of the wolves was mounted in 1882 and is on display at St. Olaf's school in Turku, enabling us to collect hair keratin samples. Additionally, hair keratin was collected from two other suspected man-eaters. We analysed carbon (δ13C) and nitrogen (δ15N) stable isotope values to study the wolf's diet during the last months of its life. Samples from seven temporally concurrent wolves were used to construct reference values. Our analyses indicated that δ15N values of suspected man-eaters were relatively low compared to the reference sample. We could not detect clear trends in isotope ratios associated with potential man-eating behavior. We believe that this lack of distinctive patterns can be explained by the relatively minor role that man-eating played in their overall diet.

Museum specimens of a landlocked pinniped reveal recent loss of genetic diversity and unexpected population connections.

The Saimaa ringed seal (Pusa hispida saimensis) is endemic to Lake Saimaa in Finland. The subspecies is thought to have originated when parts of the ringed seal population of the Baltic region were trapped in lakes emerging due to postglacial bedrock rebound around 9000 years ago. During the 20th century, the population experienced a drastic human-induced bottleneck. Today encompassing a little over 400 seals with extremely low genetic diversity, it is classified as endangered. We sequenced sections of the mitochondrial control region from 60 up to 125-years-old museum specimens of the Saimaa ringed seal. The generated dataset was combined with publicly available sequences. We studied how genetic variation has changed through time in this subspecies and how it is phylogenetically related to other ringed seal populations from the Baltic Sea, Lake Ladoga, North America, Svalbard, and the White Sea. We observed temporal fluctuations in haplotype frequencies and loss of haplotypes accompanied by a recent reduction in female effective population size. In apparent contrast with the traditionally held view of the Baltic origin of the population, the Saimaa ringed seal mtDNA variation also shows affinities to North American ringed seals. Our results suggest that the Saimaa ringed seal has experienced recent genetic drift associated with small population size. The results further suggest that extant Baltic ringed seal is not representative of the ancestral population of the Saimaa ringed seal, which calls for re-evaluation of the deep history of this subspecies.

Attractor landscapes: a unifying conceptual model for understanding behaviour change across scales of observation.

Models and theories in behaviour change science are not in short supply, but they almost exclusively pertain to a particular facet of behaviour, such as automaticity or reasoned action, or to a single scale of observation such as individuals or communities. We present a highly generalisable conceptual model which is widely used in complex systems research from biology to physics, in an accessible form to behavioural scientists. The proposed model of attractor landscapes can be used to understand human behaviour change on different levels, from individuals to dyads, groups and societies. We use the model as a tool to present neglected ideas in contemporary behaviour change science, such as hysteresis and nonlinearity. The model of attractor landscapes can deepen understanding of well-known features of behaviour change (research), including short-livedness of intervention effects, problematicity of focusing on behavioural initiation while neglecting behavioural maintenance, continuum and stage models of behaviour change understood within a single accommodating framework, and the concept of resilience. We also demonstrate potential methods of analysis and outline avenues for future research.

White Paper: Open Digital Health - accelerating transparent and scalable health promotion and treatment.

In this White Paper, we outline recommendations from the perspective of health psychology and behavioural science, addressing three research gaps: (1) What methods in the health psychology research toolkit can be best used for developing and evaluating digital health tools? (2) What are the most feasible strategies to reuse digital health tools across populations and settings? (3) What are the main advantages and challenges of sharing (openly publishing) data, code, intervention content and design features of digital health tools? We provide actionable suggestions for researchers joining the continuously growing Open Digital Health movement, poised to revolutionise health psychology research and practice in the coming years. This White Paper is positioned in the current context of the COVID-19 pandemic, exploring how digital health tools have rapidly gained popularity in 2020-2022, when world-wide health promotion and treatment efforts rapidly shifted from face-to-face to remote delivery. This statement is written by the Directors of the not-for-profit Open Digital Health initiative (n = 6), Experts attending the European Health Psychology Society Synergy Expert Meeting (n = 17), and the initiative consultant, following a two-day meeting (19-20th August 2021).

Studying Behaviour Change Mechanisms under Complexity.

Understanding the mechanisms underlying the effects of behaviour change interventions is vital for accumulating valid scientific evidence, and useful to informing practice and policy-making across multiple domains. Traditional approaches to such evaluations have applied study designs and statistical models, which implicitly assume that change is linear, constant and caused by independent influences on behaviour (such as behaviour change techniques). This article illustrates limitations of these standard tools, and considers the benefits of adopting a complex adaptive systems approach to behaviour change research. It (1) outlines the complexity of behaviours and behaviour change interventions; (2) introduces readers to some key features of complex systems and how these relate to human behaviour change; and (3) provides suggestions for how researchers can better account for implications of complexity in analysing change mechanisms. We focus on three common features of complex systems (i.e., interconnectedness, non-ergodicity and non-linearity), and introduce Recurrence Analysis, a method for non-linear time series analysis which is able to quantify complex dynamics. The supplemental website provides exemplifying code and data for practical analysis applications. The complex adaptive systems approach can complement traditional investigations by opening up novel avenues for understanding and theorising about the dynamics of behaviour change.

Characterizing and predicting person-specific, day-to-day, fluctuations in walking behavior.

Despite the positive health effect of physical activity, one third of the world's population is estimated to be insufficiently active. Prior research has mainly investigated physical activity on an aggregate level over short periods of time, e.g., during 3 to 7 days at baseline and a few months later, post-intervention. To develop effective interventions, we need a better understanding of the temporal dynamics of physical activity. We proposed here an approach to studying walking behavior at "high-resolution" and by capturing the idiographic and day-to-day changes in walking behavior. We analyzed daily step count among 151 young adults with overweight or obesity who had worn an accelerometer for an average of 226 days (~25,000 observations). We then used a recursive partitioning algorithm to characterize patterns of change, here sudden behavioral gains and losses, over the course of the study. These behavioral gains or losses were defined as a 30% increase or reduction in steps relative to each participants' median level of steps lasting at least 7 days. After the identification of gains and losses, fluctuation intensity in steps from each participant's individual time series was computed with a dynamic complexity algorithm to identify potential early warning signals of sudden gains or losses. Results revealed that walking behavior change exhibits discontinuous changes that can be described as sudden gains and losses. On average, participants experienced six sudden gains or losses over the study. We also observed a significant and positive association between critical fluctuations in walking behavior, a form of early warning signals, and the subsequent occurrence of sudden behavioral losses in the next days. Altogether, this study suggests that walking behavior could be well understood under a dynamic paradigm. Results also provide support for the development of "just-in-time adaptive" behavioral interventions based on the detection of early warning signals for sudden behavioral losses.

Promoting scientific integrity through open science in health psychology: results of the Synergy Expert Meeting of the European health psychology society.

The article describes a position statement and recommendations for actions that need to be taken to develop best practices for promoting scientific integrity through open science in health psychology endorsed at a Synergy Expert Group Meeting. Sixteen Synergy Meeting participants developed a set of recommendations for researchers, gatekeepers, and research end-users. The group process followed a nominal group technique and voting system to elicit and decide on the most relevant and topical issues. Seventeen priority areas were listed and voted on, 15 of them were recommended by the group. Specifically, the following priority actions for health psychology were endorsed: (1) for researchers: advancing when and how to make data open and accessible at various research stages and understanding researchers' beliefs and attitudes regarding open data; (2) for educators: integrating open science in research curricula, e.g., through online open science training modules, promoting preregistration, transparent reporting, open data and applying open science as a learning tool; (3) for journal editors: providing an open science statement, and open data policies, including a minimal requirements submission checklist. Health psychology societies and journal editors should collaborate in order to develop a coordinated plan for research integrity and open science promotion across behavioural disciplines.

Moose genomes reveal past glacial demography and the origin of modern lineages.

BACKGROUND: Numerous megafauna species from northern latitudes went extinct during the Pleistocene/Holocene transition as a result of climate-induced habitat changes. However, several ungulate species managed to successfully track their habitats during this period to eventually flourish and recolonise the holarctic regions. So far, the genomic impacts of these climate fluctuations on ungulates from high latitudes have been little explored. Here, we assemble a de-novo genome for the European moose (Alces alces) and analyse it together with re-sequenced nuclear genomes and ancient and modern mitogenomes from across the moose range in Eurasia and North America. RESULTS: We found that moose demographic history was greatly influenced by glacial cycles, with demographic responses to the Pleistocene/Holocene transition similar to other temperate ungulates. Our results further support that modern moose lineages trace their origin back to populations that inhabited distinct glacial refugia during the Last Glacial Maximum (LGM). Finally, we found that present day moose in Europe and North America show low to moderate inbreeding levels resulting from post-glacial bottlenecks and founder effects, but no evidence for recent inbreeding resulting from human-induced population declines. CONCLUSIONS: Taken together, our results highlight the dynamic recent evolutionary history of the moose and provide an important resource for further genomic studies.

The compendium of self-enactable techniques to change and self-manage motivation and behaviour v.1.0.

Behaviour change techniques describe the content of behaviour change interventions, but do not adequately account for the actions that people must themselves undertake to successfully change or self-manage motivation or behaviour. This paper describes the development of a compendium of self-enactable techniques, combining behaviour- and motivation-regulation techniques across six existing classifications of behaviour change techniques and three scoping reviews. The compendium includes 123 techniques, each of which is labelled, defined and presented with instructive examples to facilitate self-enactment. Qualitative feedback was gathered from intervention developers and the general public to improve the utility, congruence and ease of self-enactability of the techniques. This integrative index of self-enactable techniques can assist intervention developers in selecting appropriate self-directed techniques to help people self-manage their motivation and behaviour. Future research with this compendium can expand on the number of behaviours covered by the instructive examples and link techniques with their potential impacts on factors that influence behaviours.

Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let's Move It trial.

Background: Visualisations and readily-accessible web-based supplementary files can improve data reporting and transparency. In this paper, we make use of recent developments in software and psychological network analysis to describe the baseline cohort of a trial testing the Let's Move It intervention, which aimed to increase physical activity (PA) and reduce sedentary behaviours (SB) among vocational school students. Methods: At baseline, 1166 adolescents, distributed across 6 school clusters and four educational tracks, completed measures of PA and SB, theoretical predictors of these behaviours, and body composition. Within a comprehensive website supplement, which includes all code and analyses, data were tabulated and visualised, and network analyses explored relations between predictor variables and outcomes. Results: Average daily moderate-to-vigorous PA was 65 min (CI95: 57min-73 min), and SB 8h44 min (CI95: 8h04min-9h24 min), with 25.8 (CI95: 23.5-28.0) interruptions to sitting. Cluster randomisation appeared to result in balanced distributions for baseline characteristics between intervention and control groups, but differences emerged across the four educational tracks. Self-reported behaviour change technique (BCT) use was low for many but not all techniques. A network analysis revealed direct relationships between PA and behavioural experiments, planning and autonomous motivation, and several BCTs were connected to PA via autonomous motivation. Visualisation uncovered a case of Simpson's paradox. Conclusions: Data-visualisation and data exploration techniques (e.g. network analysis) can help reveal the dynamics involved in complex multi-causal systems - a challenging task with traditional data presentations. The benefits of presenting complex data visually should encourage researchers to publish extensive analyses and descriptions as website supplements, which would increase the speed and quality of scientific communication, as well as help to address the crisis of reduced confidence in research findings. We hope that this example will serve as a template for other investigators to improve upon in the future.

Simple and rationale-providing SMS reminders to promote accelerometer use: a within-trial randomised trial comparing persuasive messages.

BACKGROUND: Literature on persuasion suggests compliance increases when requests are accompanied with a reason (i.e. the "because-heuristic"). The reliability of outcomes in physical activity research is dependent on sufficient accelerometer wear-time. This study tested whether SMS reminders-especially those that provided a rationale-are associated with increased accelerometer wear-time. METHODS: We conducted a within-trial partially randomised controlled trial during baseline data collection in a school-based physical activity intervention trial. Of 375 participants (mean age = 18.1), 280 (75%) opted to receive daily SMS reminders to wear their accelerometers. These 280 participants were then randomised to receive either succinct reminders or reminders including a rationale. Data was analyzed across groups using both frequentist and Bayesian methods. RESULTS: No differences in total accelerometer wear minutes were detected between the succinct reminder group (Mdn = 4909, IQR = 3429-5857) and the rationale group (Mdn = 4808, IQR = 3571-5743); W = 8860, p = 0.65, CI95 = - 280.90-447.20. Similarly, we found no differences in wear time between participants receiving SMS reminders (Mdn = 4859, IQR = 3527-5808) and those not receiving them (Mdn = 5067, IQR = 3201-5885); W = 10,642.5, p = 0.77, CI95 = - 424.20-305.30. Bayesian ANOVA favored a model of equal weartime means, over one of unequal means, by a Bayes Factor of 12.05. Accumulated days of valid accelerometer wear data did not differ either. Equivalence testing indicated rejection of effects more extreme than a Cohen's d (standardised mean difference) of ±~0.3. CONCLUSIONS: This study casts doubt on the effectiveness of using the because-heuristic via SMS messaging, to promote accelerometer wear time among youth. The because-heuristic might be limited to face-to-face communication and situations where no intention for or commitment to the behavior has yet been made. Other explanations for null effects include non-reading of messages, and reminder messages undermining the self-reminding strategies which would occur naturally in the absence of reminders. TRIAL REGISTRATION: DRKS DRKS00007721 . Registered 14.04.2015. Retrospectively registered.

Over a Thousand Years of Evolutionary History of Domestic Geese from Russian Archaeological Sites, Analysed Using Ancient DNA.

The European domestic goose is a widely farmed species known to have descended from the wild greylag goose (Anser anser). However, the evolutionary history of this domesticate is still poorly known. Ancient DNA studies have been useful for many species, but there has been little such work on geese. We have studied temporal genetic variation among domestic goose specimens excavated from Russian archaeological sites (4th⁻18th centuries) using a 204 base pair fragment of the mitochondrial control region. Specimens fell into three different genetic clades: the domestic D-haplogroup, the F-haplogroup that includes both wild and domestic geese, and a clade comprising another species, the taiga bean goose. Most of the subfossil geese carried typical domestic D-haplotypes. The domestication status of the geese carrying F-haplotypes is less certain, as the haplotypes identified were not present among modern domestic geese and could represent wild geese (misclassified as domestics), introgression from wild geese, or local domestication events. The bones of taiga bean goose were most probably misidentified as domestic goose but the domestication of bean goose or hybridization with domestic goose is also possible. Samples from the 4th to 10th century were clearly differentiated from the later time periods due to a haplotype that was found only in this early period, but otherwise no temporal or geographical variation in haplotype frequencies was apparent.

Bayesian evaluation of behavior change interventions: a brief introduction and a practical example.

INTRODUCTION: Evaluating effects of behavior change interventions is a central interest in health psychology and behavioral medicine. Researchers in these fields routinely use frequentist statistical methods to evaluate the extent to which these interventions impact behavior and the hypothesized mediating processes in the population. However, calls to move beyond the exclusive use of frequentist reasoning are now widespread in psychology and allied fields. We suggest adding Bayesian statistical methods to the researcher's toolbox of statistical methods. OBJECTIVES: We first present the basic principles of the Bayesian approach to statistics and why they are useful for researchers in health psychology. We then provide a practical example on how to evaluate intervention effects using Bayesian methods, with a focus on Bayesian hierarchical modeling. We provide the necessary materials for introductory-level readers to follow the tutorial. CONCLUSION: Bayesian analytical methods are now available to researchers through easy-to-use software packages, and we recommend using them to evaluate the effectiveness of interventions for their conceptual and practical benefits.

Randomised controlled feasibility study of a school-based multi-level intervention to increase physical activity and decrease sedentary behaviour among vocational school students.

BACKGROUND: No school-based physical activity (PA) interventions among older adolescents have demonstrated long-term effectiveness, and few of them so far have addressed sedentary behaviour (SB). Based on behavioural theories and evidence, we designed a multi-level intervention to increase PA and decrease SB among vocational school students. This study investigates feasibility and acceptability of two main intervention components and research procedures. We also examine uptake of behaviour change techniques (BCTs) by the participants. METHODS: Design was an outcome assessor blinded, cluster-randomised controlled trial. Four classes of students (matched pairs) were randomised into one intervention and one control arm. The intervention consisted of (1) a 6-h group-based intervention for students, (2) two 2-h training workshops to reduce their students' sitting in class for teachers, and (3) provision of light PA equipment in classrooms. At baseline (T1), mid-intervention (T2) at 3 weeks, post-intervention (T3) and 6 months after baseline (T4) we measured hypothesised psychosocial mediators and self-reported PA and sitting. Objective assessment of PA and SB (7-day accelerometry) was conducted at T1, T3 and T4. Body composition (bioimpedance) was measured at T1 and T4. Students and teachers in the intervention arm filled in acceptability questionnaires at T3. RESULTS: Recruitment rate was 64% (students) and 88.9% (teachers), and at T3, all post-intervention measurements were completed by 33 students (retention 76.7%) and 15 teachers (retention 93.8%). Acceptability ratings of sessions were high (students M = 6.29, scale 1-7), and data collection procedures were feasible. Intervention arm students reported increased use of BCTs, but uptake of some key BCTs was suboptimal. BCT use correlated highly with objective measures of PA. Based on both self-report and student evaluation, teachers in the intervention arm increased the use of sitting reduction strategies at post-intervention and T4 follow-up (p < .05). CONCLUSIONS: We detected willingness of the target groups to participate, good response rates to questionnaires, adequate retention, as well as acceptability of the trial protocol. Investigation of BCT use among students helped further enhance intervention procedures to promote BCT use. After making necessary modifications identified, intervention effectiveness can next be tested in a definitive trial. TRIAL REGISTRATION: ISRCTN34534846 . Registered 23 May 2014. Retrospectively registered.

What explains the socioeconomic status gap in activity? Educational differences in determinants of physical activity and screentime.

BACKGROUND: Designing evidence-based interventions to address socioeconomic disparities in health and health behaviours requires a better understanding of the specific explanatory mechanisms. We aimed to investigate a comprehensive range of potential theoretical mediators of physical activity (PA) and screen time in different socioeconomic status (SES) groups: a high SES group of high school students, and a low SES group of vocational school students. The COM-B system, including the Theoretical Domains Framework (TDF), was used as a heuristic framework to synthesise different theoretical determinants in this exploratory study. METHODS: Finnish vocational and high school students (N = 659) aged 16-19, responded to a survey assessing psychological, social and environmental determinants of activity (PA and screen time). These determinants are mappable into the COM-B domains: capability, opportunity and motivation. The outcome measures were validated self-report measures for PA and screen time. The statistical analyses included a bootstrapping-based mediation procedure. RESULTS: Regarding PA, there were SES differences in all of the COM-B domains. For example, vocational school students reported using less self-monitoring of PA, weaker injunctive norms to engage in regular PA, and fewer intentions than high school students. Mediation analyses identified potential mediators of the SES-PA relationship in all of three domains: The most important candidates included self-monitoring (CI95 for b: 0.19-0.47), identity (0.04-0.25) and material resources available (0.01-0.16). However, SES was not related to most determinants of screentime, where there were mainly gender differences. Most determinants were similarly related with both behaviours in both SES groups, indicating no major moderation effect of SES on these relationships. CONCLUSIONS: This study revealed that already in the first years of educational differentiation, levels of key PA determinants differ, contributing to socioeconomic differences in PA. The analyses identified the strongest mediators of the SES-PA association, but additional investigation utilising longitudinal and experimental designs are needed. This study demonstrates the usefulness of combining constructs from various theoretical approaches to better understand the role of distinct mechanisms that underpin socioeconomic health behaviour disparities.

'Let's Move It' - a school-based multilevel intervention to increase physical activity and reduce sedentary behaviour among older adolescents in vocational secondary schools: a study protocol for a cluster-randomised trial.

BACKGROUND: Physical activity (PA) has been shown to decline during adolescence, and those with lower education have lower levels of activity already at this age, calling for targeted efforts for them. No previous study has demonstrated lasting effects of school-based PA interventions among older adolescents. Furthermore, these interventions have rarely targeted sedentary behaviour (SB) despite its relevance to health. The Let's Move It trial aims to evaluate the effectiveness and the cost-effectiveness of a school-based, multi-level intervention, on PA and SB, among vocational school students. We hypothesise that the intervention is effective in increasing moderate-to-vigorous-intensity physical activity (MVPA), particularly among those with low or moderate baseline levels, and decreasing SB among all students. METHODS: The design is a cluster-randomised parallel group trial with an internal pilot study. The trial is conducted in six vocational schools in the Helsinki Metropolitan area, Finland. The intervention is carried out in 30 intervention classes, and 27 control classes retain the standard curriculum. The randomisation occurs at school-level to avoid contamination and to aid delivery. Three of the six schools, randomly allocated, receive the 'Let's Move It' intervention which consists of 1) group sessions and poster campaign targeting students' autonomous PA motivation and self-regulation skills, 2) sitting reduction in classrooms via alterations in choice architecture and teacher behaviour, and 3) enhancement of PA opportunities in school, home and community environments. At baseline, student participants are blind to group allocation. The trial is carried out in six batches in 2015-2017, with main measurements at pre-intervention baseline, and 2-month and 14-month follow-ups. Primary outcomes are for PA, MVPA measured by accelerometry and self-report, and for SB, sedentary time and breaks in sedentary time (accelerometry). Key secondary outcomes include measured body composition, self-reported well-being, and psychological variables. Process variables include measures of psychosocial determinants of PA (e.g. autonomous motivation) and use of behaviour change techniques. Process evaluation also includes qualitative interviews. Intervention fidelity is monitored. DISCUSSION: The study will establish whether the Let's Move It intervention is effective in increasing PA and reducing SB in vocational school students, and identify key processes explaining the results. TRIAL REGISTRATION: ISRCTN10979479 . Registered: 31.12.2015.