Exercising in Times of Lockdown: The Impact of Digital Health Technologies on Adolescents' Healthy Lifestyles and Mental Health in China

The study investigates how the COVID-19 pandemic, with its widespread lockdowns and reduced access to outdoor exercise and equipment, adversely affected adolescents’ and young adults’ physical activity and mental health. While digital health technologies (DHTs; e.g., Fitbit, Keep, smartwatches) gained popularity for health management during the pandemic, evidence on their effectiveness for behavior change is mixed and mechanisms are unclear. Prior research focuses largely on adults in developed countries, leaving a gap regarding adolescents and young adults in developing contexts such as China. This study aims to examine whether and how the use and social interactions around DHTs influence healthy lifestyles and mental health among Chinese adolescents and youngsters, and whether behavioral regulation mediates these relationships, drawing on the Behavioral Intervention Technology (BIT) model.

Adolescents’ access to smartphones is widespread, and many report using apps and wearables for health-related purposes, including fitness, nutrition, sleep monitoring, and step counting. DHTs encompass mHealth apps and wearables that can support behavior change via goal-setting, self-monitoring, and feedback. Prior studies indicate potential benefits of DHTs for physical activity, diet, sleep, and stress reduction, and highlight the role of social features (e.g., sharing activity data, social networks) in promoting activity. However, meta-analytic evidence is mixed on the efficacy of apps for sustained behavior change, and mechanisms are underexplored. Healthy lifestyle components include diet, physical activity, stress management, and related behaviors, which are linked to mental health (e.g., depressive symptoms). The BIT model suggests self-regulation processes (self-awareness, self-management, self-efficacy) are key for translating technological interventions into behavior change; within self-determination theory, behavioral regulation (introjected and identified regulation) may drive changes. Hypotheses: H1a/H2a posit positive associations of DHT use and social interactions with healthy lifestyles; H3a/H4a posit positive associations with mental health; H1b–H4b posit mediation by behavioral regulation.

Design: Cross-sectional nationwide survey in China (May–June 2021) using cluster-randomized sampling. Participants: Adolescents and young adults aged 15–24 years (M = 18.71, SD = 1.814). Initial N = 3,330 from 31 provinces/metropolitan areas; after excluding non-users of DHTs and responses with >10% missing, valid N = 2,297 (effective rate 68.98%). Gender: 1,179 males (51.3%), 1,118 females (48.7%). BMI categories: Underweight 20.8%, Healthy 62.1%, Overweight 12.4%, Obesity 2.9%. Procedures: Pretested and refined questionnaire; anonymous classroom administration by trained investigators with informed consent. Session ~20 minutes. Measures: - Demographics: Gender, age, grade, BMI (self-reported height/weight). - Use of DHTs: Frequency per week and minutes per use over the past month for most-used device/app; responses binned into six equal-interval levels; mean of two items as overall DHT use score. - Social interactions of DHTs: Two items on frequency of sharing sports-related content via devices/apps on social media and talking to others about device/app use in the past month (1=never to 5=two or more times per week); averaged as social interaction score. - Behavioral regulation: 12-item Behavioral Regulation in Exercise Questionnaire (BREQ)-based scale (e.g., valuing benefits of exercise, guilt when not exercising) rated 1–5; averaged (M = 2.70, SD = 0.76, α = 0.88). - Healthy lifestyles: 23-item Health-Promoting Lifestyle Profile Scale (HPLP-S)-based measure covering nutrition, physical activity, stress management, etc., rated 1–5; averaged (M = 3.02, SD = 0.66, α = 0.88). - Mental health (depressive symptoms): CESD-10 Chinese version (10 items; 1–4), summed (M = 10.21, SD = 5.60, α = 0.81); higher scores = worse mental health. Descriptives on DHTs: Most-used technologies: Keep (75.9%), smartwatches (39.1%), Sports World Campus (13.3%). Common functions: exercise record (62.8%), exercise guidance (46.6%), body index monitoring (38.3%), check-in (37.8%), sleep monitoring (33.2%), diet management (25.3%). Statistical analysis: Descriptive statistics and Pearson correlations (two-tailed) in SPSS 25. Mediation analyses via PROCESS v3.5 (Model 4) with 5,000 bootstrap samples, estimating standardized/unstandardized coefficients and 95% CIs; significance at p < 0.05. All models controlled for age, gender, grade, and BMI.

- Healthy lifestyles: Both DHT use and DHT social interactions positively predicted healthy lifestyles. • DHT use: β = 0.188, t = 9.333, p < 0.001; direct effect after mediation c′ = 0.107, t = 6.089, p < 0.001. • DHT social interactions: β = 0.146, t = 7.147, p < 0.001; direct effect after mediation c′ = 0.041, t = 2.252, p = 0.024. • Mediation by behavioral regulation: – Use → Healthy lifestyle: Indirect effect ab = 0.022 (95% CI reported as [0.164, 0.028]); behavioral regulation accounted for 42.69% of total effect. – Social interactions → Healthy lifestyle: Indirect effect ab = 0.079 (95% CI = [0.062, 0.096]); behavioral regulation accounted for 72.01% of total effect. • Paths: a1 (Use → Behavioral regulation) = 0.161***; b1 (Behavioral regulation → Healthy lifestyle) = 0.497***. a2 (Social interactions → Behavioral regulation) = 0.209***; b2 = 0.503***. - Mental health (depressive symptoms; higher = worse): • Direct effects: DHT use did not directly predict depression (β = 0.002, t = 0.092, p = 0.927), failing H3a. DHT social interactions positively predicted depression (β = 0.119, t = 5.610, p < 0.001), indicating worse mental health and contrary to H4a. • Indirect effects via behavioral regulation: Both significant. – Use → Mental health: ab = 0.009 (95% CI = [0.006, 0.012]); after mediation, direct effect c′ = −0.043, t = −2.062, p = 0.039 (i.e., lower depression, better mental health). Behavioral regulation accounted for 22.75% of total effect. – Social interactions → Mental health: ab = 0.030 (95% CI = [0.022, 0.039]); after mediation, direct effect c′ = 0.064, t = 3.038, p = 0.002 (higher depression). Behavioral regulation accounted for 46.24% of total effect. - Overall, H1a and H2a supported; H3a not supported; H4a contradicted. Mediation hypotheses H1b–H4b supported. - Descriptive highlights: Valid N = 2,297; 51.3% male; mean age 18.71. Most common DHT: Keep (75.9%); most used functions: exercise recording (62.8%) and guidance (46.6%).

Findings indicate that for Chinese adolescents and young adults, both the use and social interactions of DHTs are associated with healthier lifestyles, in part through enhanced behavioral regulation, consistent with the BIT model emphasizing self-regulation mechanisms in behavior change. For mental health, mere use of DHTs showed no direct association, but when behavioral regulation was considered, DHT use predicted lower depressive symptoms, suggesting that technology-supported activity benefits mental health primarily when internal regulation processes are engaged. Conversely, higher social interaction around DHTs was associated with worse mental health both directly and after accounting for mediation, potentially reflecting greater online social engagement among lonelier or more distressed individuals seeking support, or the presence of negative social interactions. The study extends evidence from predominantly Western adult samples to a large, national Chinese youth sample and underscores the central role of behavioral regulation in translating DHT engagement into health benefits.

Grounded in the BIT model, this national study of Chinese adolescents and young adults shows that DHT use and social interactions promote healthier lifestyles, largely via behavioral regulation. DHT use relates to better mental health when behavioral regulation is engaged, whereas greater DHT-related social interaction correlates with worse mental health. The results provide theoretical and practical guidance for youth health promotion and DHT design, emphasizing features that cultivate self-regulation. Future research should refine measurement of social interaction dimensions and examine causal pathways with longitudinal or experimental designs.

- Measurement of social interactions relied on two items; social interaction is multifaceted and includes positive and negative dimensions, warranting more granular assessment. - Cultural and social contextual factors influencing social interaction among Chinese youth were not fully considered. - Self-reported measures may introduce bias; cross-sectional design limits causal inference. Future work should employ randomized controlled trials and panel designs for long-term, generalizable conclusions.