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Record W2898852644 · doi:10.1080/07347332.2018.1469564

Through our eyes: A photovoice intervention for adolescents on active cancer treatment

2018· article· en· W2898852644 on OpenAlexafffund
Georgi Georgievski, Wendy Shama, Sonia Lucchetta, Mark Niepage

Bibliographic record

VenueJournal of Psychosocial Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsCentre for Addiction and Mental HealthHospital for Sick ChildrenUniversity of Toronto
FundersGarron Family Cancer CentreHospital for Sick Children
KeywordsPhotovoiceIntervention (counseling)PsychologyMedicineCancerDevelopmental psychologyPsychotherapistClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

RESEARCH APPROACH: Photovoice, a participatory action research methodology, is a novel and promising intervention for adolescents with cancer. Photovoice was used as an intervention for eliciting and addressing the psychosocial needs of adolescents on active cancer treatment. PARTICIPANTS: Six adolescents, aged thirteen to seventeen years old, who were on active treatment or had completed treatment in the three months prior to recruitment participated in a seven-week photovoice group that took place from March to May 2017. Methodological Approach: Each of the seven sessions was recorded and later transcribed. A content analysis was used to identify themes that were analyzed using an integrated framework developed earlier. The framework broadly categorized the themes into six domains: (i) physical changes, (ii) psychosocial impacts, (iii) short-term social impacts, (iv) long-term social impacts, (v) impacts on holistic well-being, and (vi) informational needs. INTERPRETATION: Photovoice is an effective intervention for eliciting and addressing the psychosocial needs of adolescents on active cancer treatment.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.082
GPT teacher head0.482
Teacher spread0.400 · 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

Citations20
Published2018
Admission routes2
Has abstractyes

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