Enterprise AI Analysis
Evaluation of a web-based back prevention program for primary school children: a randomized controlled trial
This randomized controlled trial evaluated a 12-week web-based preventive back-care intervention for 141 children (6-11 years). The intervention group (n=71) received exercise and back-oriented education videos, while controls (n=70) received general health promotion. The intervention significantly increased back-related knowledge (p<.001) and positive self-compassion (p=.011). However, it did not lead to significant group differences in posture, back pain prevalence, trunk muscle endurance, functional mobility, self-concept, negative self-compassion, or daily sitting time. Adherence varied, highlighting challenges in digital health promotion for young children and suggesting future programs may benefit from increased interactivity, parental involvement, and in-person components.
Executive Impact at a Glance
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Back-Related Knowledge Increase
0.0
Positive Self-Compassion Increase
0
Total Participants
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Program Duration
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Key Findings
The study found a significant increase in back-related knowledge and positive self-compassion in the intervention group. However, no significant differences were observed in posture, back pain, trunk muscle endurance, functional mobility, self-concept, negative self-compassion, or daily sitting time between groups. Adherence to the program varied considerably among participants.
Methodology
A randomized controlled trial design was used with 141 children (6-11 years) over 12 weeks. The intervention group received exercise and back-oriented educational videos, while the control group received general health promotion videos. Assessments included postural evaluation, back pain, postural endurance, trunk endurance, functional mobility (FMS), back-related knowledge, and psychological well-being (self-compassion, self-concept). Parental background information was also collected.
Limitations
Key limitations include the lack of a standard medical examination for posture assessment, which relied on visual inspection. The study also faced recruitment challenges, not meeting the preregistered sample size, which reduced statistical power to detect small-to-moderate effects. Adherence to the remote program varied, and there was no direct supervision of exercises. The relatively young and broad age range of participants also presented developmental variability challenges. No long-term follow-up was conducted.
22.8%
Increase in back-related knowledge (partial η²)
Intervention Design Flow
Participant Recruitment (n=177)
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Randomization (IG=89, CG=88)
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12-Week Intervention Period
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Post-Test Assessment
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Data Analysis (n=141)
| Outcome | Intervention Group Improvement | Control Group Improvement |
|---|---|---|
| Back-Related Knowledge |
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| Positive Self-Compassion |
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| Posture Anomalies |
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| Back Pain Prevalence |
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| Trunk Muscle Endurance |
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| Functional Mobility |
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Challenges in Digital Health Promotion for Children
The study highlights several challenges in implementing digital health interventions for primary school children. Variable adherence to the web-based program, the lack of direct supervision for exercises, and the broad developmental age range of participants (6-11 years) likely contributed to the mixed results. Children in this age group exhibit significant variability in physical and cognitive development, motivation, and attention spans, making sustained engagement difficult in a remote setting. The authors suggest that future programs could benefit from increased interactivity, parental involvement, and in-person components to improve effectiveness and support spinal health in this demographic.
Calculate Your Potential AI ROI
The implementation of AI-powered digital health platforms in educational settings for preventive care. Consider the efficiency gains from early intervention, reducing future healthcare costs related to chronic back pain, and improved educational outcomes due to better health.
Projected Annual Savings
$0
Reclaimed Annual Hours
0
Your AI Implementation Roadmap
A structured approach to integrating AI-driven insights into your enterprise operations, ensuring measurable impact and sustained growth.
Phase 1: Pilot & Customization
Deploy a tailored AI-powered back health program in a pilot school, gathering feedback on content, interactivity, and parental engagement mechanisms. Focus on refining the platform to suit the specific developmental needs and attention spans of primary school children.
Phase 2: Integration & Teacher Training
Integrate the refined program into existing school health curricula and train teachers/school staff on program facilitation and monitoring. Develop tools for parents to actively participate and monitor their children's adherence and progress.
Phase 3: Scaled Deployment & Long-Term Monitoring
Expand the program to additional schools, incorporating enhanced gamification and in-person components (e.g., school workshops). Implement long-term monitoring strategies to assess sustained behavioral change and health outcomes into adolescence.
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