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Record W4413053800 · doi:10.1080/15401383.2025.2537197

<i>Loosening the Grip</i> : An Exploration of Women’s Lived Experiences of Psychological Distress Through Filmmaking

2025· article· en· W4413053800 on OpenAlexaff
Ian Gold, Michaela Grill, Lawrence Joseph, Abby Lippman

Bibliographic record

VenueJournal of Creativity in Mental Health · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsFilmmakingPsychologyDistressPsychological distressCreativityPsychotherapistSocial psychologyMental healthVisual artsArt

Abstract

fetched live from OpenAlex

This study explores the first-person experience of women’s psychological distress and interactions with the mental healthcare system through the lens of exploratory filmmaking. Six artists who identified as women participated in a multi-phase study, creating short films that engaged with their emotional and psychological journeys. Reflexive Thematic Analysis (RTA) was applied to semi-structured interviews conducted across three stages: pre-production, production, and post-production. Key themes were developed to reflect participants’ histories of distress, their creative processes, engagement in dialogue with an imagined audience, and the ways in which filmmaking produced therapeutic outcomes. The study highlights the value of filmmaking as a tool for externalizing distress and fostering agency and closure, or in the words of one of our participants, “loosening the grip” of past trauma on current experience. Our study suggests that creative methods like filmmaking may bridge gaps in mental healthcare approaches, promoting clinical empathy and patient empowerment.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.247

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.138
GPT teacher head0.419
Teacher spread0.281 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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