Declining physical activity and rising sedentary behavior among adolescents pose a significant public health concern, exacerbated by the COVID-19 pandemic. This inactivity is linked to negative health outcomes, including increased fat mass, reduced physical fitness (cardiorespiratory capacity and muscular fitness), and impaired cognitive performance. School-based interventions, particularly those incorporating technology like mobile apps, offer promising strategies for increasing physical activity. Previous research suggests that mobile app interventions can be effective in promoting physical activity initially, but adherence often wanes over time. However, little is known about the differential effects of such interventions based on gender and academic year, factors known to influence physical activity levels and technology use in adolescents. This study aimed to address this gap by investigating (a) differences in mobile app usage based on gender and academic year, (b) the efficacy of the intervention on physical activity, kinanthropometric variables, and fitness depending on gender, and (c) the efficacy of the intervention on these same variables depending on academic year.

The existing literature highlights the critical need for interventions to combat the rising levels of physical inactivity among adolescents. School-based interventions have shown effectiveness in improving physical activity enjoyment and cardiorespiratory fitness. Interventions using electronic devices, especially mobile apps, are gaining popularity due to adolescents' familiarity with technology and the ease of monitoring. However, studies show that adherence to such interventions declines over time. The research also points to differences in physical activity levels and technology use between genders and across age groups. Females might be more motivated by academic rewards, while older adolescents may exhibit greater mobile phone use and different technology preferences. The lack of consensus on gender differences in using step tracker apps highlights the need for more research, particularly studies involving educational settings.

This study employed a randomized controlled trial (RCT) design with pre- and post-intervention measurements over 10 weeks. 400 adolescents (210 males, 190 females; mean age 13.96 ± 1.21 years) from two secondary schools were randomly assigned to either an experimental group (n=240) or a control group (n=160) using a cluster randomized design. The experimental group used one of four mobile apps (Strava, Pacer, MapMyWalk, Pokémon Go) for a minimum of three times a week, with weekly distance targets increasing progressively (7000 steps/day to 12,500 steps/day). The control group continued their usual physical activity routines. Data collected included physical activity levels (using the PAQ-A questionnaire), kinanthropometric variables (body mass, height, skinfolds, girths, BMI, fat mass, etc.), and fitness variables (20-m shuttle run test for VO2 max, handgrip strength test, countermovement jump (CMJ), and curl-up test). Statistical analyses included chi-square tests to compare app usage, ANCOVA to analyze pre-post changes, and MANOVA to investigate the effects of app use, gender, and academic year. Blinding was used where appropriate to minimize bias.

Females (71.1%) used the mobile apps more frequently than males (50.0%), and app use was significantly higher in fourth-year (74.4%) compared to first-year (53.8%) adolescents (p < 0.001). The intervention prevented the increase of variables related to fat accumulation (BMI, fat mass, skinfolds, waist and hip girths). Significant gender differences were found post-intervention in BMI, corrected calf girth, fat mass, handgrip strength (both arms), and CMJ, with the improvements being generally more pronounced in males. Significant differences by academic year were observed in height, sum of three skinfolds, waist girth, hip girth, corrected calf girth, and fat mass, with the fourth-year students in the intervention group showing a decrease in many of the fat-related variables, but there were differences found in height between experimental and control groups. The control group showed no significant changes in most variables.

The higher app usage among females and older adolescents may be attributed to their increased mobile phone usage and potentially greater concern for academic achievement, as the intervention included an academic reward. The study's findings demonstrate the potential benefits of mobile app interventions in curbing fat accumulation, particularly in females, and improving certain fitness markers, particularly in males. The differences between genders in fitness improvements may be explained by biological factors like hormonal changes (testosterone levels) and neuromuscular adaptations that are influenced by physical activity levels. The differences by academic year might reflect the changing priorities and technology use patterns throughout adolescence. However, it is important to consider the limitations mentioned in the study regarding the measurement of physical activity and the potential influence of uncontrolled factors like diet.

This study highlights the importance of considering gender and academic year when designing and implementing mobile app interventions to promote physical activity in adolescents. The findings suggest that mobile apps can be effective in preventing fat accumulation and improving certain fitness components, although the effects vary depending on gender and age. Future research should explore the role of motivation and technology preferences across different age and gender groups, incorporating objective physical activity measures, more control over lifestyle factors such as diet, and analyzing the effects of varying training variables such as intensity and volume. Further investigation is needed to optimize the design and implementation of mobile app interventions to maximize their effectiveness in promoting healthy lifestyles in adolescents.

The study's limitations include the use of a self-reported questionnaire for physical activity (PAQ-A), which may lead to subjective bias, and lack of control over participants' dietary habits, which can influence body composition. The effect of maturation was not specifically controlled. The cluster randomized design may limit the individual-level interpretability of the data, especially in regards to app choice. The knowledge of the intervention by the control group might have introduced some bias in data collection. Future studies should address these limitations for improved robustness.