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Record W2734834113 · doi:10.1080/08039488.2017.1334819

International multi-site survey on the use of online support groups in bipolar disorder

2017· article· en· W2734834113 on OpenAlexaff
Rita Bauer, Jörn Conell, Tasha Glenn, Martin Alda, Raffaella Ardau, Bernhard T. Baune, Michael Berk, Yuly Bersudsky, Amy C. Bilderbeck, Alberto Bocchetta, Letizia Bossini, Angela Marianne Paredes Castro, Eric Yat Wo Cheung, Caterina Chillotti, Sabine Choppin, Maria Del Zompo, Rodrigo da Silva Dias, Seetal Dodd, Anne Duffy, Bruno Étain, Andrea Fagiolini, Miryam Fernández Hernández, Julie Garnham, John Geddes, Jonas Gildebro, Ana González‐Pinto, Guy M. Goodwin, Paul Grof, Hirohiko Harima, Stefanie Hassel, Chantal Henry, Diego Hidalgo‐Mazzei, Vaisnvy Kapur, Girish Kunigiri, Beny Lafer, Erik Roj Larsen, Ute Lewitzka, Rasmus Wentzer Licht, Anne Hvenegaard Lund, Błażej Misiak, Patryk Piotrowski, Scott Monteith, Rodrigo Muñoz, Takako Nakanotani, René Ernst Nielsen, Claire O’Donovan, Y Okamura, Yamima Osher, Andreas Reif, Philipp Ritter, Janusz Rybakowski, Kemal Sagduyu, Brett Sawchuk, Elon Schwartz, Ângela Miranda Scippa, Claire Slaney, Ahmad Hatim Sulaiman, Kirsi Suominen, Aleksandra Suwalska, Peter Tam, Yoshitaka Tatebayashi, Leonardo Tondo, Eduard Vieta, Maj Vinberg, Biju Viswanath, Julia Volkert, Mark Zetin, Peter C. Whybrow, Michael Bauer

Bibliographic record

VenueNordic Journal of Psychiatry · 2017
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversity of TorontoUniversity of CalgaryDalhousie University
FundersNational Health and Medical Research Council
KeywordsBipolar disorderPsychologyPsychiatryClinical psychologyMood

Abstract

fetched live from OpenAlex

BACKGROUND: Peer support is an established component of recovery from bipolar disorder, and online support groups may offer opportunities to expand the use of peer support at the patient's convenience. Prior research in bipolar disorder has reported value from online support groups. AIMS: To understand the use of online support groups by patients with bipolar disorder as part of a larger project about information seeking. METHODS: The results are based on a one-time, paper-based anonymous survey about information seeking by patients with bipolar disorder, which was translated into 12 languages. The survey was completed between March 2014 and January 2016 and included questions on the use of online support groups. All patients were diagnosed by a psychiatrist. Analysis included descriptive statistics and general estimating equations to account for correlated data. RESULTS AND CONCLUSIONS: The survey was completed by 1222 patients in 17 countries. The patients used the Internet at a percentage similar to the general public. Of the Internet users who looked online for information about bipolar disorder, only 21.0% read or participated in support groups, chats, or forums for bipolar disorder (12.8% of the total sample). Given the benefits reported in prior research, clarification of the role of online support groups in bipolar disorder is needed. With only a minority of patients using online support groups, there are analytical challenges for future studies.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.019
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.410
Teacher spread0.303 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2017
Admission routes1
Has abstractyes

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