924-P: A Latent Class Analysis of Adolescent Preferences on Social Media Use by Diabetes Care Teams to Support Type 1 Diabetes Management

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 924-P
Author(s):  
FAISAL MALIK ◽  
ALICE M. ELLYSON ◽  
DIMITRI CHRISTAKIS ◽  
RITA MANGIONE-SMITH ◽  
CATHERINE PIHOKER ◽  
...  
Keyword(s):  
Social Media ◽  
Type 1 Diabetes ◽  
Latent Class Analysis ◽  
Diabetes Care ◽  
Latent Class ◽  
Diabetes Management ◽  
Media Use ◽  
Class Analysis ◽  
Social Media Use

scholarly journals PDB92 GETTING THE MOST OUT OF LATENT-CLASS ANALYSIS IN MODELING PREFERENCES FOR AN INTERCEPTION TREATMENT IN TYPE 1 DIABETES

2020 ◽  
Vol 23 ◽  
pp. S125
Author(s):  
J. Sutphin ◽  
C. Mansfield ◽  
R. Disantostefano ◽  
K. Klein ◽  
M. Boeri
Keyword(s):  
Type 1 Diabetes ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis

scholarly journals The course of social media use problems in secondary school adolescents: A latent class growth analysis

2021 ◽  
Author(s):  
Maartje Boer ◽  
gonneke stevens ◽  
Catrin Finkenauer ◽  
Regina van den Eijnden
Keyword(s):  
Social Media ◽  
Secondary School ◽  
Growth Analysis ◽  
Latent Class ◽  
Media Use ◽  
Latent Class Growth Analysis ◽  
Social Media Use ◽  
Immigrant Background ◽  
Low Levels ◽  
Latent Class Growth

Little is known about how addiction-like social media use (SMU) problems evolve over time. Using four waves of longitudinal data collected in 2015-2019 from 1,414 adolescents (Mage = 12.5, 46.0% girl, 21.9% immigrant background), this study aimed to identify adolescents’ trajectories of SMU problems in parallel with their trajectories of SMU intensity. Latent class growth analysis identified two subgroups with persistently high levels of SMU problems, of which one with high (24.7%) and one with average SMU intensity (14.8%), and two subgroups with persistently low levels of SMU problems, of which one with low (22.3%) and one with high SMU intensity (38.2%). Compared to the largest subgroup, the two subgroups with high levels of SMU problems showed more problematic profiles.

scholarly journals “It Got Likes, But I Don’t Think People Understood”: A Qualitative Study of Adolescent Experiences Discussing Type 1 Diabetes on Social Media

2020 ◽  
pp. 193229682096558
Author(s):  
Kristen Chalmers ◽  
Mia Smith ◽  
Megan Moreno ◽  
Faisal Malik
Keyword(s):  
Social Media ◽  
Type 1 Diabetes ◽  
Diabetes Management ◽  
Social Consequences ◽  
Structured Interviews ◽  
Daily Lives ◽  
Social Media Engagement ◽  
Social Media Platforms ◽  
Management Advice

Background: The majority of adolescents with type 1 diabetes (T1D) integrate social media engagement into their daily lives. The aim of this study was to explore adolescents’ experiences and perspectives discussing their T1D on social media. Methods: Semi-structured interviews with adolescents with T1D were conducted in person and via telephone. Questions focused on the participant’s experiences utilizing social media to discuss T1D and factors that informed the nature of T1D-related social media engagement. Open coding and thematic content analysis were used to identify emergent themes that aligned with accepted domains of social media affordances. Results: Participants included 35 adolescents with T1D. Adolescents’ experiences related to discussing T1D on social media aligned with four affordances of social media: identity, cognitive, emotional, and social. The identity affordances of social media platforms allowed adolescents to curate online personas that selectively included their diagnosis of T1D, while managing the potential negative emotional and social implications linked to the stigma of T1D. Adolescents who decided to discuss T1D on social media leveraged cognitive affordances by providing and receiving diabetes management advice, emotional affordances by obtaining affirmation from peers, and social affordances by extending their network to include other individuals with T1D. Conclusions: Adolescents with T1D flexibly leverage the affordances offered by social media to access emotional support, information, and identity affirmation resources while navigating stigma-based social consequences. Our findings highlight the value of developing tools to support adolescents with T1D in comfortably discussing and receiving appropriate support about T1D on social media.

scholarly journals Adolescent Social Media User Types and their Mental Health and Well-being: results from a longitudinal survey of 13–14-year-olds in the United Kingdom

2021 ◽  
Author(s):  
Lizzy Winstone ◽  
Becky Mars ◽  
CMA Haworth ◽  
Jon Heron ◽  
Judi Kidger
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Screen Time ◽  
Online Survey ◽  
Latent Class ◽  
Media Use ◽  
Well Being ◽  
Poor Mental Health ◽  
Social Media Use ◽  
Health And Well Being

Background There is mixed evidence as to the effects of different types of social media use on mental health, but previous research has been platform-specific and has focused on an oversimplified distinction between active and passive use. This study aimed to identify different underlying subgroups of adolescent social media user based on their pattern of social media activities and test associations between user type and future mental health. Methods Students from nineteen schools (N=2,456) in south-west England completed an online survey measuring thirteen social media activities and four psychosocial outcomes (past year self-harm, depression, anxiety and poor well-being) at age 13 years (October 2019) and repeated a year later (October 2020; aged 14 years). Latent class analysis using Mplus identified distinct classes of social media user. A bias-adjusted three-step model was used to test associations between class membership at baseline and mental health at follow-up. Analyses were adjusted for gender, ethnicity, sexual orientation, socio-economic status, disability, social media screen-time and baseline mental health.Results A four-class model of social media user at baseline was selected based on fit statistics and interpretability. User types were labelled High Communicators; Moderate Communicators; Broadcasters; and Minimal users. Broadcasters at age 13 had the poorest mental health outcomes at age 14, with mental health and well-being generally better in the two Communicator groups. Conclusions Findings suggest that adolescents with high levels of content sharing – in addition to socialising and browsing online – are most likely to be experiencing poor mental health a year later. Recommendations regarding social media use should move beyond screen-time to consider different user types, and mental health implications of their engagement with different online activities.

scholarly journals The patterns of problematic social media use (SMU) and their relationship with online flow, life satisfaction, depression, anxiety and stress symptoms in Lithuania and in Germany

2021 ◽  
Author(s):  
Julia Brailovskaia ◽  
Inga Truskauskaite-Kuneviciene ◽  
Evaldas Kazlauskas ◽  
Jürgen Margraf
Keyword(s):  
Social Media ◽  
Life Satisfaction ◽  
Structural Equation ◽  
Latent Class ◽  
Structural Equation Models ◽  
Media Use ◽  
Self Control ◽  
Social Media Use ◽  
Stress Symptoms ◽  
Problematic Social Media Use

AbstractThe present study investigated problematic social media use (SMU) in Lithuania and in Germany. In two student samples (Lithuania: N = 1640; Germany: N = 727), problematic SMU, flow experienced during SMU, life satisfaction, depression, anxiety and stress symptoms were assessed by online surveys. Latent Class Analysis resulted in a four-group classification of participants due to their levels of problematic SMU characteristics: low-symptom, low-withdrawal, high-withdrawal, and high-symptom. The proportion of participants in the low-symptom group was significantly higher in Germany than in Lithuania. In contrast, significantly more Lithuanian participants belonged to both withdrawal groups. No significant country differences were found for the composition of the high-symptom group. In both countries, a series of Structural Equation Models showed that the level of flow, depression, anxiety and stress symptoms was the highest in the high-symptom group, and the lowest in the low-symptom group. Life satisfaction revealed the reversed result pattern. The current findings show that students from Lithuania and Germany can be grouped considering their problematic SMU level. Individuals in the four groups differ due to their level of mental health. Especially members of the high-symptom group might benefit from external controlling strategies of their time spent on SM, while members of the withdrawal groups are suggested to train their SMU self-control.

scholarly journals Adolescent Perspectives on the Use of Social Media to Support Type 1 Diabetes Management: Focus Group Study

10.2196/12149 ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. e12149 ◽  
Author(s):  
Faisal S Malik ◽  
Neil Panlasigui ◽  
Jesse Gritton ◽  
Harsimrat Gill ◽  
Joyce P Yi-Frazier ◽  
...  
Keyword(s):  
Social Media ◽  
Type 1 Diabetes ◽  
Focus Group ◽  
Diabetes Management ◽  
Focus Group Study ◽  
Use Of Social Media

scholarly journals Using Latent Class Analysis to Identify Political Behavior of Moroccan Citizens on Social Media

2020 ◽  
Vol 9 (4) ◽  
pp. 1273-1282
Keyword(s):  
Social Media ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Point Of View ◽  
Political Activity ◽  
Class Analysis ◽  
Political Issues ◽  
Political Interaction ◽  
Use Of Social Media ◽  
Political Actions

The high use of social media has led to a new form of political involvement and participation. In this paper, we use Latent Class Analysis to identify participants’ behavior regarding political participation and engagement based on the nature of their interaction on social media. The LCA findings reveal three statistically distinct and behavioral classes regarding political interaction on social media. The profiles were ranged from ‘Activist’ that show more engagement in political activity, such as following candidates and political parties, posting and participating in discussions related to economic, social or political issues or, encouraging others to debate their point of view, to ‘Agitator’ and ‘Outsider’ profiles that show a low probability of interacting on social media and engaging in political actions. The LCA technique has provided meaningful and distinct information on the participants’ political profile than clustering classical techniques.

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