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Record W4388601866 · doi:10.1177/16094069231211121

Co-designing Guidelines for Using Arts-based methods when Conducting Youth Mental Health Research in Online Environments

2023· article· en· W4388601866 on OpenAlex
Roberta L. Woodgate, Miriam González, John Christian Barrion, Tasmiah Hussain, Iman Shamraiz, Nicole Singcay, Stacie Smith, Nicole Thielmann, Erika Yazon

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

VenueInternational Journal of Qualitative Methods · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of OttawaCarleton UniversityMount Saint Vincent UniversityUniversity of Manitoba
Fundersnot available
KeywordsThematic analysisMental healthFocus groupInclusion (mineral)Online research methodsPsychologyThe artsTheme (computing)Medical educationApplied psychologyMultimediaQualitative researchComputer scienceWorld Wide WebSociologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Co-designing research-informed guidelines with youth for adapting research methods to other contexts has received little research attention. We report on guidelines co-designed with youth for adapting arts-based methods (ABM) for youth mental health (MH) research in online environments. Seven youth co-researchers participated in 3 co-design workshops and 2 graphic recording focus groups. Data analysis involved a thematic analysis approach. We identified one overarching theme (sustaining mindful presence when conducting research) and 4 subthemes (creating a safe space, youth having a say, facilitating meaningful engagement, paying receptive attention throughout the research process). Facilitating participants’ authentic expression in online environments requires: 1) Letting youth self-identify; 2) incorporating diversity and inclusion; 3) providing accommodations, recognition, and compensation; 4) language considerations; 5) offering ABM training and resources for creating art; 6) using virtual platforms youth use; 7) being mindful of ethical considerations and technology fatigue; 8) addressing barriers in accessing and using technology; 9) providing choice in type of ABM and research methods used; and 10) providing options for communicating during research activities and for engaging in research outside of allotted time (e.g., email, group chat). These research-informed guidelines can be useful for conducting youth MH research and other youth research in online environments.

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)0.297
metaresearch head score (Gemma)0.065
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.232
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2970.065
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.996
GPT teacher head0.883
Teacher spread0.113 · 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