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Record W3112523603 · doi:10.2196/21644

Social Media Use and Monitoring for Adolescents With Depression and Implications for the COVID-19 Pandemic: Qualitative Study of Parent and Child Perspectives

2020· article· en· W3112523603 on OpenAlexvenueno aff
Candice Biernesser, Gerald T. Montano, Elizabeth Miller, Ana Radović

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2020
Typearticle
Languageen
FieldPsychology
TopicMental Health via Writing
Canadian institutionsnot available
FundersNational Institute of Mental HealthAgency for Healthcare Research and QualityUniversity of Pittsburgh
KeywordsPsychologyDepression (economics)Social distanceQualitative researchClinical psychologyDevelopmental psychologyPsychiatryMedicineCoronavirus disease 2019 (COVID-19)Disease

Abstract

fetched live from OpenAlex

BACKGROUND: Although youth report many positive experiences with social media (SM) use in their daily lives, adolescents with depression are more vulnerable to the risks of SM use than adolescents without depression. Parents protect adolescents with depression from the risks of SM use by monitoring their child's SM activity; however, this comes into conflict with the adolescent's need for autonomy in their web-based communication. The implications of SM use and monitoring for adolescents with depression and their parents are of particular relevance to the COVID-19 pandemic, as rates of SM use have increased in response to physical distancing measures. OBJECTIVE: This study aims to explore parent and child perspectives regarding the use and function of SM in the daily lives of adolescents with depression and parents' perceptions of and experience with monitoring their child's SM use. METHODS: We conducted qualitative interviews with adolescents with depression (n=23) and one parent of each adolescent (n=23) between July 2013 and September 2014. The adolescents were patients seeking treatment for depression in Pittsburgh, Pennsylvania. Data analysis included dyadic analysis of the adolescents' and parents' perspectives and qualitative descriptions of individual parent interviews to explore their experiences with SM use and monitoring. The construct of parental knowledge and factors hypothesized to contribute to parental knowledge, including adolescent disclosure, parental solicitation, and parental control, were used to guide the codebook and dyadic data analysis. RESULTS: Dyadic analyses showed that parents and their children disagreed on the use and function of SM in the daily lives of adolescents with depression, with adolescents viewing SM as a forum for honest expression of their emotions, whereas parents felt that their children's posts were inconsequential and interfered with the adolescents' lives. Furthermore, parents reported using a wide range of strategies to gain knowledge of their child's SM use to monitor their safety on SM, including direct solicitation and indirect solicitation, such as keeping the child's passwords, asking friends or siblings about their child's SM use, and restricting SM behavior and access to devices. CONCLUSIONS: Clinicians should support adolescents with depression and their parents in finding common ground for an effective and acceptable monitoring approach. Resources are provided for clinicians navigating conversations about SM use and monitoring with adolescents with depression and their parents during the COVID-19 pandemic.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0020.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.216
GPT teacher head0.485
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2020
Admission routes1
Has abstractyes

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