Perceptions of Social Media Use to Augment Health Care Among Adolescents and Young Adults With Cystic Fibrosis: Survey Study.
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ABSTRACT: Background
For individuals with cystic fibrosis (CF), adolescence and young adulthood are times of significant vulnerability and have been associated with clinical and psychosocial challenges. Social media may offer innovative care delivery solutions to address these challenges.Objective
This study explored motivations and attitudes regarding current social media use and preferences for a social media platform in a sample of adolescents and young adults (AYA) with CF.Methods
A cross-sectional survey was administered to 50 AYA with CF followed at a large pediatric-adult CF center. The survey included questions regarding social media platform utilization, attitudes toward general and CF-specific online activities, and preferences for a CF-specific care delivery platform.Results
YouTube, Snapchat, and Instagram were the most commonly used social media platforms. AYA with CF do not report routinely using social media for health-related information acquisition, social support, or help with adherence. However, their perceptions of social media utilization and preferences for platform development suggest interest in doing so in the future.Conclusions
AYA with CF use social media and expressed interest in the development of a social media platform. Platform development will allow for gaps in health care delivery to be addressed by improving social support and adherence while augmenting current methods of health information acquisition.
SUBMITTER: Perkins RC
PROVIDER: S-EPMC8406102 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundTechnological interventions may help support and improve mental health. However young peoples' perspectives on using different technologies to detect deteriorating mental health in those already diagnosed with a mental health condition is lacking. The study aim was to explore the perspectives of young patients on the feasibility and acceptability of using wearables, social media and technologies to detect mental health deterioration.MethodsThe study was co-produced with young adults with past mental health difficulties. Semi-structured interviews were conducted with young adults with a severe mental health condition in a private room at a community mental health site. Data was triangulated by comparing codes and ideas across the two co-researchers and two researchers over two virtual meetings. Themes were finalised and presented in a thematic map.ResultsSixteen participants were interviewed (81% female). There were four main themes: dealing with mental health symptoms, signs of mental health deterioration, technology concerns and technological applications to identify worsening mental health. Wearables and mobile apps were considered acceptable and feasible to detect mental health deterioration in real-time if they could measure changes in sleep patterns, mood or activity levels as signs of deterioration. Getting help earlier was deemed essential particularly in reference to dissatisfaction with the current non-technological mental health services. However, patients identified issues to consider before implementation including practicality, safeguarding and patient preference.ConclusionWearables and mobile apps could be viable technological options to help detect deterioration in young people in order to intervene early and avoid delay in accessing mental health services. However, immediate action following detection is required for the patient to trust and use the intervention.
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Project description:BackgroundDigital technology use is nearly ubiquitous among young adults; this use provides both benefits and risks. The risks of technology use include maladaptive technology use or technology addiction. Several conceptualizations of these addictions have emerged, each with its own assessment tools. These conditions include problematic internet use (PIU), internet gaming disorder (IGD), and social media addiction (SMA). These conditions have been associated with health outcomes such as problematic alcohol use, sleep disorders, and mental illness. These maladaptive technology conditions have been most commonly studied in isolation from each other.ObjectiveThe aim of this study is to examine PIU, IGD, and SMA together to better inform future research approaches and provider screening practices for young adults.MethodsThis cross-sectional survey study was conducted using Qualtrics panel-based recruitment and survey hosting. We recruited US young adults aged 18-25 years. The survey assessed PIU, IGD, and SMA. Survey measures also included assessments of problematic alcohol use, sleep, depression, and anxiety. We evaluated the frequency of and overlap in positive screening scores among PIU, IGD, and SMA and modeled each condition using multivariate logistic regression. Finally, we calculated sensitivity and specificity, as well as the positive predictive value and negative predictive value of the screening tools using the most prevalent maladaptive technology type.ResultsOur 6000 participants had an average age of 21.7 (SD 2.5) years. Of these 6000 participants, 3062 (51.03%) were female, 3431 (57.18%) were Caucasian, 1686 (28.1%) were in a 4-year college program, and 2319 (38.65%) worked full time. The mean PIU score was 3.5 (SD 3.1), and 53.58% (3215/6000) of participants met the criteria for PIU. The mean IGD score was 2.7 (SD 2.6), and 24.33% (1460/6000) of participants met the criteria for IGD. The mean SMA score was 7.5 (SD 5.7), and 3.42% (205/6000) met the criteria for SMA. Across all 3 maladaptive technology use diagnoses, there were varied associations with demographic variables and similar overlap with health outcomes. The sensitivity of PIU screening to detect IGD was 82% and to detect SMA was 93%, whereas the specificity and positive predictive value were much lower (37%-54% specificity; 6%-37% positive predictive value).ConclusionsThis cross-sectional survey screened a large national sample of adolescents and young adults for PIU, IGD, and SMA to determine prevalence and overlap, demographic associations with each, and associations between these technology-related conditions and health outcomes. There was overlap across PIU, IGD, and SMA in some associated demographic variables and health outcomes. However, the patterns in the associated variables demonstrated unique qualities of each of these conditions.
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