Perspectives on Smartphone Ownership and Use by Early Adolescents

Moreno, Megan A.; Kerr, Bradley; Jenkins, Marina C; Lam, Esther; Malik, Faisal

doi:10.1016/j.jadohealth.2018.08.017

Cited by 30 publications

(17 citation statements)

References 11 publications

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“…Although there are clearly some negative effects of technology on this age group, including behavioral addiction, cyber-bullying, depression, sexual exploitation, and abuse [10][11][12], the use of digitally enabled technology is considered a promising platform for preventing morbidity and enhancing well-being and quality of life [13]. Critically, digital technologies may offer especially critical support for adolescents and young people in low-resource settings where barriers to care may be numerous and insurmountable.…”

Section: Introductionmentioning

confidence: 99%

Evidence on Digital Mental Health Interventions for Adolescents and Young People: Systematic Overview

Lehtimaki¹,

Martic²,

Wahl³

et al. 2021

JMIR Ment Health

229

119

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Background An estimated 1 in 5 adolescents experience a mental health disorder each year; yet because of barriers to accessing and seeking care, most remain undiagnosed and untreated. Furthermore, the early emergence of psychopathology contributes to a lifelong course of challenges across a broad set of functional domains, so addressing this early in the life course is essential. With increasing digital connectivity, including in low- and middle-income countries, digital health technologies are considered promising for addressing mental health among adolescents and young people. In recent years, a growing number of digital health interventions, including more than 2 million web-based mental health apps, have been developed to address a range of mental health issues. Objective This review aims to synthesize the current evidence on digital health interventions targeting adolescents and young people with mental health conditions, aged between 10-24 years, with a focus on effectiveness, cost-effectiveness, and generalizability to low-resource settings (eg, low- and middle-income countries). Methods We searched MEDLINE, PubMed, PsycINFO, and Cochrane databases between January 2010 and June 2020 for systematic reviews and meta-analyses on digital mental health interventions targeting adolescents and young people aged between 10-24 years. Two authors independently screened the studies, extracted data, and assessed the quality of the reviews. Results In this systematic overview, we included 18 systematic reviews and meta-analyses. We found evidence on the effectiveness of computerized cognitive behavioral therapy on anxiety and depression, whereas the effectiveness of other digital mental health interventions remains inconclusive. Interventions with an in-person element with a professional, peer, or parent were associated with greater effectiveness, adherence, and lower dropout than fully automatized or self-administered interventions. Despite the proposed utility of digital interventions for increasing accessibility of treatment across settings, no study has reported sample-specific metrics of social context (eg, socioeconomic background) or focused on low-resource settings. Conclusions Although digital interventions for mental health can be effective for both supplementing and supplanting traditional mental health treatment, only a small proportion of existing digital platforms are evidence based. Furthermore, their cost-effectiveness and effectiveness, including in low- and middle-income countries, have been understudied. Widespread adoption and scale-up of digital mental health interventions, especially in settings with limited resources for health, will require more rigorous and consistent demonstrations of effectiveness and cost-effectiveness vis-à-vis the type of service provided, target population, and the current standard of care.

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Section: Introductionmentioning

confidence: 99%

Evidence on Digital Mental Health Interventions for Adolescents and Young People: Systematic Overview

Lehtimaki¹,

Martic²,

Wahl³

et al. 2021

JMIR Ment Health

229

119

View full text Add to dashboard Cite

show abstract

“… 12 Notwithstanding the seeming convenience associated with smartphone apps, the proportion of patients reporting that their transmission system was convenient was similar. 13 LINQ and CONFIRM patients also reported similar rates of confidence that transmissions were reaching the medical team despite the differences in transmitting system interface.…”

Section: Discussionmentioning

confidence: 76%

Comparing patient and family usability of insertable cardiac monitors in a pediatric cohort: Patient external activator versus smartphone transmission

et al. 2021

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…It was not surprising to observe a low adherence to filling out the follow-up paper diary documenting the patients’ pain level and use of analgesic medications. Recent surveys have shown that approximately 75% of adolescents own a smartphone [ 24 ]. The same survey highlighted how teenagers prefer texting to talking to their peers.…”

Section: Discussionmentioning

confidence: 99%

Feasibility of Conducting Long-term Health and Behaviors Follow-up in Adolescents: Longitudinal Observational Study

Cucchiaro¹,

Ahumada²,

Gray³

et al. 2022

JMIR Form Res

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Background Machine learning uses algorithms that improve automatically through experience. This statistical learning approach is a natural extension of traditional statistical methods and can offer potential advantages for certain problems. The feasibility of using machine learning techniques in health care is predicated on access to a sufficient volume of data in a problem space. Objective This study aimed to assess the feasibility of data collection from an adolescent population before and after a posterior spine fusion operation. Methods Both physical and psychosocial data were collected. Adolescents scheduled for a posterior spine fusion operation were approached when they were scheduled for the surgery. The study collected repeated measures of patient data, including at least 2 weeks prior to the operation and 6 months after the patients were discharged from the hospital. Patients were provided with a Fitbit Charge 4 (consumer-grade health tracker) and instructed to wear it as often as possible. A third-party web-based portal was used to collect and store the Fitbit data, and patients were trained on how to download and sync their personal device data on step counts, sleep time, and heart rate onto the web-based portal. Demographic and physiologic data recorded in the electronic medical record were retrieved from the hospital data warehouse. We evaluated changes in the patients’ psychological profile over time using several validated questionnaires (ie, Pain Catastrophizing Scale, Patient Health Questionnaire, Generalized Anxiety Disorder Scale, and Pediatric Quality of Life Inventory). Questionnaires were administered to patients using Qualtrics software. Patients received the questionnaire prior to and during the hospitalization and again at 3 and 6 months postsurgery. We administered paper-based questionnaires for the self-report of daily pain scores and the use of analgesic medications. Results There were several challenges to data collection from the study population. Only 38% (32/84) of the patients we approached met eligibility criteria, and 50% (16/32) of the enrolled patients dropped out during the follow-up period—on average 17.6 weeks into the study. Of those who completed the study, 69% (9/13) reliably wore the Fitbit and downloaded data into the web-based portal. These patients also had a high response rate to the psychosocial surveys. However, none of the patients who finished the study completed the paper-based pain diary. There were no difficulties accessing the demographic and clinical data stored in the hospital data warehouse. Conclusions This study identifies several challenges to long-term medical follow-up in adolescents, including willingness to participate in these types of studies and compliance with the various data collection approaches. Several of these challenges—insufficient incentives and personal contact between researchers and patients—should be addressed in future studies.

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Perspectives on Smartphone Ownership and Use by Early Adolescents

Cited by 30 publications

References 11 publications

Evidence on Digital Mental Health Interventions for Adolescents and Young People: Systematic Overview

Evidence on Digital Mental Health Interventions for Adolescents and Young People: Systematic Overview

Comparing patient and family usability of insertable cardiac monitors in a pediatric cohort: Patient external activator versus smartphone transmission

Feasibility of Conducting Long-term Health and Behaviors Follow-up in Adolescents: Longitudinal Observational Study

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