Individual and Parental Factors of Adolescents' mHealth App Use: Nationally Representative Cross-sectional Study

Response Rate Patterns in Adolescents With Concussion Using Mobile Health and Remote Patient Monitoring: Observational Study

Background

A concussion is a common adolescent injury that can result in a constellation of symptoms, negatively affecting academic performance, neurobiological development, and quality of life. Mobile health (mHealth) technologies, such as apps for patients to report symptoms or wearables to measure physiological metrics like heart rate, have been shown to be promising in health maintenance. However, there is limited evidence about mHealth engagement in adolescents with a concussion during their recovery course.

Objective

This study aims to determine the response rate and response rate patterns in concussed adolescents reporting their daily symptoms through mHealth technology. It will also examine the effect of time-, demographic-, and injury-related characteristics on response rate patterns.

Methods

Participants aged between 11-18 years (median days since injury at enrollment: 11 days) were recruited from the concussion program of a tertiary care academic medical center and a suburban school's athletic teams. They were asked to report their daily symptoms using a mobile app. Participants were prompted to complete the Post-Concussion Symptom Inventory (PCSI) 3 times (ie, morning, afternoon, and evening) per day for 4 weeks following enrollment. The primary outcome was the response rate pattern over time (by day since initial app use and the day since injury). Time-, demographic-, and injury-related differences in reporting behaviors were compared using Mann Whitney U tests.

Results

A total of 56 participants were enrolled (mean age 15.3, SD 1.9 years; n=32, 57% female). The median response rate across all days of app use in the evening was 37.0% (IQR 27.2%-46.4%), which was significantly higher than the morning (21.2%, IQR 15.6%-30.5%) or afternoon (26.4%, IQR 21.1%-31.5%; P<.001). The median daily response was significantly different by sex (female: 53.8%, IQR 46.2%-64.2% vs male: 42.0%, IQR 28.6%-51.1%; P=.003), days since injury to app use (participants starting to use the app >7 days since injury: 54.1%, IQR 47.4%-62.2% vs starting to use the app ≤7 days since injury: 38.0%, IQR 26.0%-53.3%; P=.002), and concussion history (participants with a history of at least one prior concussion: 57.4%, IQR 44.5%-70.5% vs participants without concussion history: 42.3%, IQR 36.8%-53.5%; P=.03). There were no significant differences by age. Differences by injury mechanism (sports- and recreation-related injury: 39.6%, IQR 36.1%-50.4% vs non-sports- or recreation-related injury: 30.6%, IQR 20.0%-42.9%; P=.04) and initial symptom burden (PCSI scores greater than the median score of 47: 40.9%, IQR 35.2%-53.8% vs PCSI scores less than or equal to the median score: 31.9%, IQR 24.6%-40.6%; P=.04) were evident in the evening response rates; however, daily rates were not statistically different.

Conclusions

Evening may be the optimal time to prompt for daily concussion symptom assessment among concussed adolescents compared with morning or afternoon. Multiple demographic- and injury-related characteristics were associated with higher daily response rates, including for female participants, those with more than 1 week from injury to beginning mHealth monitoring, and those with a history of at least one previous concussion. Future studies may consider incentive strategies or adaptive digital concussion assessments to increase response rates in populations with low engagement.

Nomophobia and eHealth literacy among adolescents: A cross-sectional study

PURPOSE

This study was conducted to determine adolescents' nomophobia behaviors, eHealth literacy levels, and their predictive factors.

DESIGN AND METHODS

A cross-sectional design was used. The population consisted of ninth, 10th, and 11th-grade adolescents (aged 14-17) in a high school in Turkiye (N = 1013). The study was completed with 719 voluntary adolescents. A questionnaire, the eHealth Literacy Scale, and the Nomophobia Questionnaire were used to collect data. Multiple linear regression was run for data analysis.

RESULTS

Of the adolescents, 44.9% were found to have moderate, and 14.8% had severe nomophobia behaviors. Adolescents who were girls, the ninth and 10th graders, who used smartphone two hours or more daily, social media users, who watched videos on the smartphone and surfed on the Internet had higher nomophobia behaviors. Adolescents who were boys, who searched for health information online, found health information on the Internet helpful, and found accessing health resources on the Internet important had higher eHealth literacy levels.

CONCLUSION

Adolescents should be educated about rational smartphone and Internet usage to comprehend the accuracy of health-related information.

PRACTICE IMPLICATIONS

School nurses could design activities to increase eHealth literacy to encourage adolescents. Nurses could help proactively prepare nomophobia severity map and an eHealth literacy enhancement curriculum for adolescents to form functional preventive interventions. Nurse leaders can contribute to developing policies and strategies to prevent nomophobia behaviors among adolescents.