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Chen D, Zhao G, Fu J, Shun S, Su L, He Z, Chen R, Jiang T, Hu X, Li Y, Shen F. Effects of structured and unstructured interventions on fundamental motor skills in preschool children: a meta-analysis. Front Public Health 2024; 12:1345566. [PMID: 39005985 PMCID: PMC11242925 DOI: 10.3389/fpubh.2024.1345566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 05/17/2024] [Indexed: 07/16/2024] Open
Abstract
Background It has been suggested that higher levels of fundamental motor skills (FMS) promote the physical health of preschool-aged children. The impacts of structured and unstructured interventions on FMS in children aged 10-16 years have been widely acknowledged in previous studies. However, there is a lack of relevant studies in preschool-aged children. Objective This meta-analysis aimed to compare the effects of structured and unstructured interventions on FMS in preschool-aged children. Methods The PubMed, Web of Science, and Google Scholar databases were searched from inception to 1 November 2023 to identify experiments describing structured and unstructured interventions for FMS in preschool-aged children. The Downs and Black Checklist was used to assess the risk of bias. A random effects model was used for the meta-analysis to evaluate the pooled effects of interventions on FMS. Subgroup analyses based on the duration and characteristics of the intervention were conducted to identify sources of heterogeneity. Results A total of 23 studies with 4,068 participants were included. There were 12 studies examining structured interventions, 9 studies examining unstructured interventions, and 6 studies comparing structured vs. unstructured interventions. The risk of bias in the included studies was generally low. All interventions significantly improved FMS in preschool-aged children compared to control treatments (p < 0.05). Structured interventions had more significant effects on locomotor skills (LMSs) in preschool-aged children than unstructured interventions (Hedges' g = 0.44, p = 0.04). The effects of structured interventions were strongly influenced by the total intervention duration, such that long-term interventions were more effective (Hedge's g = 1.29, p < 0.001). Conclusion Structured interventions play a crucial role in enhancing FMS among young children, especially when considering LMSs. These interventions require consistent and repeated practice over time to reach proficiency. Systematic review registration PROSPERO, identifier number CRD42023475088, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023475088.
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Affiliation(s)
- Delong Chen
- School of Physical Education, Nanchang University, Nanchang, China
| | - Guanggao Zhao
- School of Physical Education, Nanchang University, Nanchang, China
| | - Jinmei Fu
- Jiangxi Sports Science and Medicine Center, Nanchang, China
| | - Sunli Shun
- Jiangxi Sports Science and Medicine Center, Nanchang, China
| | - Liqiang Su
- Physical Education College, Jiangxi Normal University, Nanchang, China
| | - Zihao He
- School of Sports and Human Sciences, Beijing Sport University, Beijing, China
| | - Ruiming Chen
- School of Physical Education, Nanchang University, Nanchang, China
| | - Tianle Jiang
- School of Physical Education, Nanchang University, Nanchang, China
| | - Xuewen Hu
- School of Physical Education, Nanchang University, Nanchang, China
| | - Yunong Li
- School of Physical Education, Nanchang University, Nanchang, China
| | - Fanchao Shen
- School of Physical Education, Nanchang University, Nanchang, China
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Leyrat C, Eldridge S, Taljaard M, Hemming K. Practical considerations for sample size calculation for cluster randomized trials. JOURNAL OF EPIDEMIOLOGY AND POPULATION HEALTH 2024; 72:202198. [PMID: 38477482 DOI: 10.1016/j.jeph.2024.202198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/16/2024] [Accepted: 01/17/2024] [Indexed: 03/14/2024]
Abstract
Cluster randomized trials are an essential design in public health and medical research, when individual randomization is infeasible or undesirable for scientific or logistical reasons. However, the correlation among observations within clusters leads to a decrease in statistical power compared to an individually randomised trial with the same total sample size. This correlation - often quantified using the intra-cluster correlation coefficient - must be accounted for in the sample size calculation to ensure that the trial is adequately powered. In this paper, we first describe the principles of sample size calculation for parallel-arm CRTs, and explain how these calculations can be extended to CRTs with cross-over designs, with a baseline measurement and stepped-wedge designs. We introduce tools to guide researchers with their sample size calculation and discuss methods to inform the choice of the a priori estimate of the intra-cluster correlation coefficient for the calculation. We also include additional considerations with respect to anticipated attrition, a small number of clusters, and use of covariates in the randomisation process and in the analysis.
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Affiliation(s)
- Clémence Leyrat
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.
| | - Sandra Eldridge
- Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Monica Taljaard
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
| | - Karla Hemming
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
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Ball S, Reardon T, Creswell C, Taylor L, Brown P, Ford T, Gray A, Hill C, Jasper B, Larkin M, Macdonald I, Morgan F, Pollard J, Sancho M, Sniehotta FF, Spence SH, Stainer J, Stallard P, Violato M, Ukoumunne OC. Statistical analysis plan for a cluster randomised controlled trial to compare screening, feedback and intervention for child anxiety problems to usual school practice: identifying Child Anxiety Through Schools-identification to intervention (iCATS-i2i). Trials 2024; 25:62. [PMID: 38233861 PMCID: PMC10795300 DOI: 10.1186/s13063-023-07898-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024] Open
Abstract
BACKGROUND The Identifying Child Anxiety Through Schools-identification to intervention (iCATS-i2i) trial is being conducted to establish whether 'screening and intervention', consisting of usual school practice plus a pathway comprising screening, feedback and a brief parent-led online intervention (OSI: Online Support and Intervention for child anxiety), bring clinical and health economic benefits compared to usual school practice and assessment only - 'usual school practice', for children aged 8-9 years in the following: (1) the 'target population', who initially screen positive for anxiety problems according to a two-item parent-report child anxiety questionnaire - iCATS-2, and (2) the 'total population', comprising all children in participating classes. This article describes the detailed statistical analysis plan for the trial. METHODS AND DESIGN iCATS-i2i is a definitive, superiority, pragmatic, school-based cluster randomised controlled trial (with internal pilot), with two parallel groups. Schools are randomised 1:1 to receive either screening and intervention or usual school practice. This article describes the following: trial objectives and outcomes; statistical analysis principles, including detailed estimand information necessary for aligning trial objectives, conduct, analyses and interpretation when there are different analysis populations and outcome measures to be considered; and planned main analyses, sensitivity and additional analyses. TRIAL REGISTRATION ClinicalTrials.gov ISRCTN76119074. Registered on 4 January 2022.
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Affiliation(s)
- Susan Ball
- National Institute for Health and Care Research (NIHR) Applied Research Collaboration (ARC) South West Peninsula (PenARC), Department of Health and Community Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
| | - Tessa Reardon
- Departments of Experimental Psychology and Psychiatry, University of Oxford, Oxford, UK
| | - Cathy Creswell
- Departments of Experimental Psychology and Psychiatry, University of Oxford, Oxford, UK
- Oxford NHS Foundation Trust, Oxford, UK
| | - Lucy Taylor
- Departments of Experimental Psychology and Psychiatry, University of Oxford, Oxford, UK
- Oxford NHS Foundation Trust, Oxford, UK
| | - Paul Brown
- Bransgore C of E Primary School, Christchurch, UK
| | - Tamsin Ford
- University of Cambridge and Cambridge and Peterborough Foundation Trust, Cambridge, UK
| | - Alastair Gray
- Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK
| | - Claire Hill
- School of Psychology & Clinical Language Sciences, University of Reading, Reading, UK
| | - Bec Jasper
- Parents and Carers Together, Suffolk, UK
| | - Michael Larkin
- Life and Health Sciences, Aston University, Birmingham, UK
| | | | | | - Jack Pollard
- Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK
- UK Health Security Agency, HCAI, Fungal, AMR, AMU and Sepsis Division, London, UK
| | | | - Falko F Sniehotta
- NIHR Policy Research Unit Behavioural Science, Newcastle University, Newcastle upon Tyne, UK
- Division of Public Health, Social and Preventive Medicine, Center for Preventive Medicine and Digital Health (CPD), Universitätsmedizin Mannheim, Heidelberg University, Heidelberg, Germany
| | - Susan H Spence
- School of Applied Psychology and Australian Institute of Suicide Research and Prevention, Griffith University, Brisbane, Australia
| | | | | | - Mara Violato
- Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK
| | - Obioha C Ukoumunne
- National Institute for Health and Care Research (NIHR) Applied Research Collaboration (ARC) South West Peninsula (PenARC), Department of Health and Community Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
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Ramirez MR, Seedorff J, Cavanaugh JE, Ryan A, Xiong BN, Hatzenbuehler ML. Does Implementation Matter? Associations Between Implementation of Maine's Anti- Bullying Law and Bullying Victimization Among High School Youth. J Adolesc Health 2024; 74:161-168. [PMID: 37804295 DOI: 10.1016/j.jadohealth.2023.08.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 07/15/2023] [Accepted: 08/07/2023] [Indexed: 10/09/2023]
Abstract
PURPOSE To characterize the relationship between implementation of an antibullying law and bullying rates among high school youth. METHODS School staff (administrators, counselors, and teachers) from public high schools in Maine completed a survey assessing: (1) the frequency with which they implemented 17 components of their district's antibullying policy as mandated by state law; and (2) confidence in implementing the law. Their responses were linked to data on bullying victimization among high school respondents to the Maine Integrated Youth Health Survey, which created a population-based dataset of 84 high schools with 29,818 student responses. RESULTS Students in schools where administrators (adjusted odds ratio = 0.93; 95% CI: 0.89, 0.97) and counselors (adjusted odds ratio = 0.86; 95% CI: 0.81, 0.92) reported implementing more mandated components of the law experienced notable reductions in the odds of bullying, controlling for student-level characteristics (sex, race, grade) and for school-level bullying rates assessed prior to the passage of the law. With respect to specific implementation components, bullying was most consistently reduced in schools where staff reported increased referrals for counseling and other supports for targets of bullying and in schools where counselors and teachers were interviewed as part of bullying investigations. Students in schools where teachers reported increased confidence in implementing the antibullying law also had reduced odds of bullying. DISCUSSION These data provide some of the first evidence that the efficacy of a state's antibullying law depends in part on the extent to which school personnel implement the law.
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Affiliation(s)
- Marizen R Ramirez
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, Minnesota; Department of Environmental and Occupational Health, Program in Public Health, University of California, Irvine, Irvine, California.
| | - Jacob Seedorff
- Department of Biostatistics, College of Public Health, The University of Iowa, Iowa City, Iowa
| | - Joseph E Cavanaugh
- Department of Biostatistics, College of Public Health, The University of Iowa, Iowa City, Iowa
| | - Andrew Ryan
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Bao Nhia Xiong
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, Minnesota
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