In today's rapidly digitalizing world, the landscape of health education, particularly for adolescents, is undergoing a significant transformation. Traditional in-person health education methods are increasingly being complemented and, in some instances, replaced by digital platforms. This shift towards online education platforms has spurred an important debate regarding the effectiveness of these methods in positively influencing adolescent health behaviors. Adolescence is a critical developmental stage marked by rapid physical, emotional, and cognitive changes. During this period, young individuals are particularly vulnerable to developing habits that could have lasting impacts on their overall health and well-being, thus making effective education a pivotal element of their development.[1]

Online health education presents several advantages, including improved accessibility and scalability, which allow it to reach a broader audience at potentially lower costs. This aspect of digital education is particularly relevant in today's context, where adolescents spend a considerable amount of their time online, engaging with digital content across various platforms. The digital nature of these educational tools aligns seamlessly with the lifestyle and preferences of modern youth, suggesting a potential for higher receptivity and engagement.[2]

However, the benefits of online education come with certain limitations that might impact its overall effectiveness. The relatively impersonal nature of online learning environments, coupled with the high potential for distractions that the internet invariably provides, can significantly undermine the engagement levels necessary for effective learning. Unlike traditional in-person methods, online learning often lacks the dynamic interaction between educator and student, which is crucial for motivating students, addressing their unique learning needs, and providing immediate feedback. These interactions are not only essential for academic learning but are especially crucial in health education, where personal attitudes and behaviors are directly influenced by the educational content.[3]

Moreover, the effectiveness of health education through digital platforms can vary widely depending on several factors such as the design of the educational content, the platforms used, and the individual user’s learning environment. For instance, the lack of tailored content that addresses specific personal or community health challenges can result in generic information that may not resonate with all adolescents. Furthermore, the success of online health education heavily relies on the user's self-motivation and ability to regulate their learning pace, which can be a significant barrier for many adolescents.[4]

In-person health education, on the other hand, benefits from real-time interactions that foster a more engaging and responsive learning environment. Educators can adapt their teaching strategies based on the immediate feedback they receive from students, thus enhancing understanding and retention of knowledge. Additionally, in-person settings typically provide a structured learning environment that minimally competes with the distractions often found in a home or casual setting. This structured environment is conducive to sustained attention and engagement, which are essential for effective learning and behavior change.[5]

Furthermore, the social aspect of in-person learning cannot be understated. Learning in a communal environment can enhance motivation and accountability, encourage healthy social interactions, and enable direct support networks, which are particularly effective in reinforcing health-related behaviors. Peer influences are significant in adolescence, and in-person education can harness these dynamics effectively to promote healthier lifestyles.[6]

Aim

To compare the effectiveness of online versus in-person health education on improving health behaviors among adolescents.

Objectives

1. To assess changes in nutritional habits among adolescents following online versus in-person health education sessions.
2. To evaluate changes in physical activity levels among adolescents after receiving health education through both modalities.
3. To compare the impact of online and in-person health education on adolescent mental health and substance use behaviors.

Source of Data

The study utilized primary data collected directly from adolescents participating in the health education programs.

Study Design

This was a randomized controlled trial designed to evaluate the effectiveness of online versus in-person health education.

Study Location

The study was conducted at person health education centres.

Study Duration

The duration of the study was from January 2024 to December 2024.

Sample Size

The sample size for the study was 200 adolescents, randomly divided into two groups of 100 each for online and in-person education modalities.

Inclusion Criteria

Participants included were adolescents aged 12 to 18 years, enrolled in the participating schools, and who consented to participate in the study.

Exclusion Criteria

Excluded from the study were adolescents with diagnosed cognitive impairments that could interfere with understanding the educational material, those already participating in other similar studies, and those without internet access at home for the online group.

Procedure and Methodology:

Both groups received equivalent educational content tailored to adolescent health issues, including nutrition, physical activity, mental health, and substance abuse prevention.

The in-person education was delivered through interactive workshops held in school settings, facilitated by trained health educators.

Online education was delivered through a structured digital course platform featuring videos, interactive quizzes, and discussion forums, accessible via computers or smartphones.

Sample Processing

Not applicable, as this study did not involve biological samples.

Statistical Methods

Data analysis was conducted using SPSS software. Chi-square tests were used for categorical data, and t-tests were used for continuous data to compare differences between the two groups. A p-value of less than 0.05 was considered statistically significant.

Data Collection

Baseline data on health behaviors were collected through self-administered questionnaires.

Follow-up assessments were conducted immediately post-intervention and at six months to evaluate the retention of behavior changes.

Data on program engagement and satisfaction were also collected to assess the quality of the educational experience in each modality.

Table 1: Comparative Effectiveness of Online vs. In-Person Health Education on Improving Health Behaviors among Adolescents

Table 1 delineates the comparative effectiveness on overall health behaviors including nutrition improvement, physical activity increase, mental health awareness, and substance use awareness. Notably, in-person health education showed a statistically significant higher effectiveness across all categories compared to online formats. The p-values indicate significant differences, with the most substantial impacts observed in mental health awareness and substance use awareness, where the confidence intervals further underscore the considerable differences in effectiveness between the two modalities.

Table 2: Changes in Nutritional Habits among Adolescents Following Online vs. In-Person Health Education Sessions

Table 2 focuses on changes in nutritional habits among adolescents following the health education sessions. Here, in-person sessions appear to have fostered more favorable outcomes in daily fruit and vegetable intake, and reduced consumption of fast food and sugary drinks, with all results being statistically significant. The negative values of test statistics for fast food and sugary drink consumption indicate that in-person education was more effective at reducing these unhealthy behaviors compared to online education.

Table 3: Changes in Physical Activity Levels among Adolescents after Receiving Health Education through Both Modalities

Table 3 examines the changes in physical activity levels. The in-person education group demonstrated higher weekly hours of exercise, increased participation in sports, and more daily steps compared to the online group. Additionally, the in-person group exhibited less sedentary behavior. The significant p-values and the direction of the confidence intervals indicate that in-person health education was more effective at promoting physical activity and reducing sedentary behaviors among adolescents.

Table 4: Impact of Online and In-Person Health Education on Adolescent Mental Health and Substance Use Behaviors

Table 4 evaluates the impact on adolescent mental health and substance use behaviors. The results show that in-person health education significantly reduced stress and anxiety levels and was more effective in encouraging the use of coping strategies and reducing substance use. The confidence intervals and p-values provide robust evidence of the superiority of in-person interventions over online methods for these specific outcomes.

Table 1 demonstrates that in-person health education is more effective across various behavioral domains including nutrition, physical activity, mental health awareness, and substance use awareness. The chi-square test indicates significant differences favoring in-person interactions. For instance, a study by Au LE et al. (2017)[7] similarly found that direct interaction in health education significantly enhances engagement and comprehension among adolescents compared to online methods, which often suffer from distractions and lower engagement levels.

Table 2 highlights specific improvements in nutritional habits from in-person education compared to online formats. The statistical analysis shows significant improvements in daily intake of fruits and vegetables and reductions in fast food and sugary drink consumption. These findings align with those of Azevedo LB et al. (2022)[8], who noted that tactile and sensory experiences in in-person settings can reinforce learning and behavior change more effectively than virtual lessons.

Table 3 focuses on physical activity levels, where in-person education again shows superior outcomes. This is consistent with research by Azevedo LB et al. (2022)[8], which emphasized the role of social interactions and peer support available in in-person settings that are often crucial for motivating physical activity among adolescents. The significant reductions in sedentary behavior also support findings by Au LE et al. (2016)[9], who argue that direct supervision and structured physical environments contribute to more active lifestyles.

Table 4 explores mental health and substance use behaviors, with in-person education demonstrating greater efficacy in reducing stress and anxiety levels, and in managing substance use and coping strategies. This is supported by the work of Shapka JD et al. (2016)[10], which suggested that the immediate feedback and personalized support provided in in-person settings are vital for addressing sensitive issues like mental health and substance abuse.

The comparative study of online versus in-person health education on adolescent health behaviors has demonstrated significant findings that underscore the importance of direct, interactive educational experiences. The analysis revealed that in-person health education modalities consistently outperform their online counterparts across a range of behavioral outcomes, including nutrition improvement, physical activity levels, mental health awareness, and substance use behaviors.

In-person education proves to be more effective in fostering meaningful engagement, facilitating better understanding, and promoting healthier behaviors among adolescents. This superiority can be attributed to the real-time interaction, immediate feedback, and the more engaging and responsive environment that in-person settings offer. These elements are crucial for effective learning and behavior change, particularly in the formative adolescent years when personal interaction and peer influence are significant. Furthermore, the study highlights the limitations of online education in contexts where interpersonal dynamics and hands-on activities enhance the learning experience. While online education offers broader accessibility and convenience, it often lacks the personal touch and immediacy that drive behavioral change, especially in health-related behaviors that benefit significantly from personalized guidance and support.

In conclusion, while online health education is a valuable tool for disseminating information widely, our findings advocate for the continued prioritization and enhancement of in-person health education programs to more effectively influence positive health behaviors among adolescents. This approach not only supports better health outcomes but also aligns with the developmental needs of young people for interaction and direct engagement. Therefore, stakeholders in educational and health sectors are encouraged to consider these findings in designing and implementing health education strategies to maximize their impact on adolescent health and well-being.

LIMITATIONS OF STUDY

1. Generalizability: The study was conducted in a specific geographic area and involved a limited demographic of adolescents. Therefore, the results may not be universally applicable to all populations. Different cultural, socio-economic, and educational environments might influence the effectiveness of online and in-person education differently.
2. Participant Selection: The study participants were selected from schools that agreed to participate, which may introduce selection bias. Schools with resources to support in-person learning effectively might show different outcomes compared to those with limited resources.
3. Measurement of Outcomes: The assessment of health behaviors was based on self-reported data, which can be subject to bias. Participants might overestimate or underestimate their behaviors due to social desirability bias or recall inaccuracies.
4. Intervention Consistency: The consistency and quality of the health education programs (both online and in-person) could vary. Instructors' skills, engagement techniques, and the interactive tools used could affect the results, which were not controlled for in this study.
5. Technological Access and Literacy: The effectiveness of online education can be significantly influenced by the participants' access to reliable internet and technology, as well as their digital literacy skills. Variations in these factors were not fully accounted for, which could impact the engagement and learning outcomes of the online education group.
6. Short Duration and Follow-up: The study was limited to a short duration without an extensive follow-up period to assess the long-term retention of behavioral changes. Long-term effects and sustainability of the learned behaviors were not evaluated.
7. Control of External Variables: There might be external factors influencing the adolescents' learning and behavior that were not controlled or accounted for in this study, such as parental involvement, peer influence, and personal motivation.
8. Interactivity in Online Modules: The level of interactivity and engagement in online modules can vary widely. This study did not differentiate between different types of online educational content, such as passive video watching versus interactive learning platforms.

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