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Record W2533741660 · doi:10.1177/0743558416673717

Teen Depression Groups on Facebook: A Content Analysis

2016· article· en· W2533741660 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Adolescent Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMental healthPsychologyDepression (economics)Intervention (counseling)Social mediaClinical psychologyContent analysisPsychiatryWorld Wide Web

Abstract

fetched live from OpenAlex

Major depressive disorder (MDD) is one of the most frequently diagnosed disorders in early adolescence and can lead to a multitude of negative life outcomes, highlighting the need for early and effective intervention to mitigate depressive symptoms. Recognizing the preference of youth to seek informal sources of help for mental health issues, which may include the Internet, the social networking site Facebook was investigated as a potential source of support and help for youth suffering depressive symptoms or disorder. This study examined the content of online Facebook support groups targeting adolescents with depression. A total of 508 posts from six Facebook groups were analyzed. The majority of post content on these Facebook groups consisted of self-disclosure (32.48%), feedback between posters (24.80%), and offers and recommendations of help (24.61%). Posters seem to utilize adolescent Facebook depression groups mainly to connect with those who might share a similar experience and to share information about mental health resources. Future studies should investigate the potential to use the information exchange that occurs in these groups to promote traffic to online and offline evidence-based mental health resources.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.202
GPT teacher head0.452
Teacher spread0.249 · 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