Background: Although physical activity (PA) is associated with significant health benefits, only a small percentage of adolescents meet recommended PA levels. This systematic review with meta-analysis explored the modifiable determinants of adolescents’ device-based PA and/or sedentary behaviour (SB), evaluated in previous interventions and examined the associations between PA/SB and these determinants in settings. Methods: A search was conducted on five electronic databases, including papers published from January 2010 to July 2023. Randomized Controlled Trials (RCTs) or Controlled Trials (CTs) measuring adolescents’ device-based PA/SB and their modifiable determinants at least at two time points: pre- and post-intervention were considered eligible. PA/SB and determinants were the main outcomes. Modifiable determinants were classified after data extraction adopting the social-ecological perspective. Robust Bayesian meta-analyses (RoBMA) were performed per each study setting. Outcomes identified in only one study were presented narratively. The risk of bias for each study and the certainty of the evidence for each meta-analysis were evaluated. The publication bias was also checked. PROSPERO ID: CRD42021282874. Results: Fourteen RCTs (eight in school, three in school and family, and one in the family setting) and one CT (in the school setting) were included. Fifty-four modifiable determinants were identified and were combined into 33 broader determinants (21 individual–psychological, four individual–behavioural, seven interpersonal, and one institutional). RoBMAs revealed none or negligible pooled intervention effects on PA/SB or determinants in all settings. The certainty of the evidence of the impact of interventions on outcomes ranged from very low to low. Narratively, intervention effects in favour of the experimental group were detected in school setting for the determinants: knowledge of the environment for practicing PA, d = 1.84, 95%CI (1.48, 2.20), behaviour change techniques, d = 0.90, 95%CI (0.09, 1.70), choice provided, d = 0.70, 95%CI (0.36, 1.03), but no corresponding effects on PA or SB were found. Conclusions: Weak to minimal evidence regarding the associations between the identified modifiable determinants and adolescents’ device-based PA/SB in settings were found, probably due to intervention ineffectiveness. Well-designed and well-implemented multicomponent interventions should further explore the variety of modifiable determinants of adolescents’ PA/SB, including policy and environmental variables.

Previous physical activity interventions for children (5-12yrs) have aimed to change determinants associated with self-report physical activity behaviour (PAB) and/or sedentary behaviour (SB), however, the associations between these determinants and PAB/SB in different settings are uncertain. The present study aimed to identify modifiable determinants targeted in previous PAB/SB interventions for children. Intervention effects on the determinants and their associations with self-report PAB/SB were assessed across settings. Search of relevant interventions from pre-defined databases was conducted up to July 2023. Randomized and non-randomized controlled trials with modifiable determinants were included. Data extraction and risk of bias assessments were conducted by two independent researchers. Where data could be pooled, we performed Robust Bayesian meta-analyses. Heterogeneity, publication bias and certainty of evidence were assessed. Fifteen studies were deemed eligible to be included. Thirty-seven unique determinants within four settings were identified–school, family, school with family/home, and community with(out) other settings. Ninety-eight percent of determinants belonged to individual/interpersonal determinant categories. Narratively, intervention effects on student perception of teachers’ behaviour (school), self-management, perceived barriers, external motivation, exercise intention, parental modeling on SB (school with family/home) and MVPA expectations (community) were weak to strong, however, corresponding PAB/SB change was not evident. There were negligible effects for all other determinants and the corresponding PAB/SB. Meta-analyses on self-efficacy, attitude, subjective norm and parental practice and PAB/SB in two settings showed weak to strong evidence against intervention effect, while the effect on knowledge could not be determined. Similarly, publication bias and heterogeneity for most analyses could not be ascertained. We found no concrete evidence of association between the modifiable determinants and self-report PAB/SB in any settings. This is presumably due to intervention ineffectiveness. Design of future interventions should consider to follow the systems-based approach and identify determinants unique to the context of a setting, including policy and environmental determinants.

Background: To combat the high prevalence of physical inactivity among children, there is an urgent need to develop and implement real-world interventions and policies that promote physical activity (PA) and reduce sedentary behaviour (SB). To inform policy makers, the current body of evidence for children’s PA/SB interventions needs to be translated. Objectives: The current systematic review and meta-analysis aimed to identify modifiable determinants of device-measured PA and SB targeted in available intervention studies with randomized controlled trial (RCT) and controlled trial (CT) designs in children and early adolescents (5–12 years) and to quantify the effects of the interventions within their respective settings on the determinants of PA/SB and the outcomes PA and SB. Methods: A systematic search was conducted in MEDLINE, PsycINFO, Web of Science, SPORTDiscus and CENTRAL. Studies were considered if they were randomized controlled trials (RCTs) or controlled trials (CTs), included children and/or early adolescents (5–12 years; henceforth termed children), measured PA and/or SB using device-based methods and measured PA and/or SB and determinants of PA/SB at least at two timepoints. Risk of bias was assessed using the Cochrane Risk of Bias Tool for Randomised Trials (RoB2) for RCTs and Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I) for CTs. The quality of the generated evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE). Robust Bayesian meta-analysis was conducted to quantify the effects of the interventions on the determinants of PA/SB, and the outcomes PA and SB, stratifying by study design, duration of PA/SB measurement, intervention setting and duration of follow-up measurement. Study characteristics and interventions were summarized. Results: Thirty-eight studies were included with a total sample size of n = 14,258 (67% girls). Settings identified were school, family/home, community and combinations of these. The review identified 38 modifiable determinants, spanning seven categories on individual, interpersonal and physical environmental levels, with 66% of determinants on the individual level. Overall, the results indicated trivial-to-moderate effects of the interventions on the determinants of PA and SB, with mostly trivial level of evidence for the presence of an effect (as indicated by a small Bayes factor; BF₁₀ < 3.00). The exceptions were moderate effects on parental PA modelling in the family/home setting and SB measured during specific parts of the school day. Higher quality of evidence was found in the family/home setting compared with other settings. Discussion: Overall, the results indicated that interventions have neither been effective in modifying the determinants of PA/SB, nor changing the PA/SB outcomes in children. In general, the approach in the current review revealed the breadth of methodological variability in children’s PA interventions. Research is needed to address novel approaches to children’s PA research and to identify potential determinants to inform policy and future interventions. Registration: International prospective register of systematic reviews (PROSPERO): CRD42021282874.

In this study, we aimed to determine the exercise intensities eliciting the highest (FAT_max) and the lowest (FAT_min) fat oxidation rate in male cyclists and to compare these intensities with their individual aerobic (AeT) and anaerobic (AnT) thresholds, respectively. Twenty‐two moderately trained male cyclists performed a 2‐min stage graded exercise test until exhaustion using breath‐by‐breath gas analysis to determine maximal oxygen consumption (VO_2max). The fat oxidation rate was calculated using a stoichiometric equation, with metabolic thresholds being determined by ventilatory gas analysis. In the present group of subjects, FAT_max was found at a 21.34 ± 3.64 ml·kg⁻¹·min⁻¹ corresponding to 45.05 ± 7.68% VO_2max. AeT occurred at an exercise intensity of 22.15 ± 4.84 ml·kg⁻¹·min⁻¹, matching 46.76 ± 10.24% VO_2max. AnT and FAT_min were located at intensities equivalent to 32.56 ± 5.52 ml·kg⁻¹·min⁻¹ and 32.30 ± 5.35 ml·kg⁻¹·min⁻¹ which corresponded to 68.74 ± 11.65 and 68.19 ± 11.29% VO_2max, respectively. The correlation between FAT_max and AeT was strong (r = 0.80, p < 0.05). No statistical difference was observed between FAT_min and AnT (r = 0.99, p < 0.05). The strong relationship between observed indices can be used to provide a more tailored exercise approach.

Regular exercise at the intensity matching maximal fat oxidation (FAT_max) has been proposed as a key element in both athletes and clinical populations when aiming to enhance the body’s ability to oxidize fat. In order to allow a more standardized and tailored training approach, the connection between FAT_max and the individual aerobic thresholds (AerT) has been examined. Although recent findings strongly suggest that a relationship exists between these two intensities, correlation alone is not sufficient to confirm that the intensities necessarily coincide and that the error between the two measures is small. Thus, this systematic review and meta-analysis aim to examine the agreement levels between the exercise intensities matching FAT_max and AerT by pooling limits of agreement in a function of three parameters: (i) the average difference, (ii) the average within-study variation, and (iii) the variation in bias across studies, and to examine the influence of clinical and methodological inter- and intra-study differences on agreement levels. This study was registered with PROSPERO (CRD42021239351) and ClinicalTrials (NCT03789045). PubMed and Google Scholar were searched for studies examining FAT_max and AerT connection. Overall, 12 studies with forty-five effect sizes and a total of 774 subjects fulfilled the inclusion criteria. The ROBIS tool for risk of bias assessment was used to determine the quality of included studies. In conclusion, the overall 95% limits of agreement of the differences between FAT_max and AerT exercise intensities were larger than the a priori determined acceptable agreement due to the large variance caused by clinical and methodological differences among the studies. Therefore, we recommend that future studies follow a strict standardization of data collection and analysis of FAT_max- and AerT-related outcomes.