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Record W4377099281 · doi:10.1024/1662-9647/a000314

Caring Through COVID

2023· article· en· W4377099281 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

VenueGeroPsych · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicPsychology2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Group psychotherapyPsychotherapistClinical psychologyMedicineGerontologyDisease

Abstract

fetched live from OpenAlex

Abstract: This multisite quality improvement (QI) project reports on a psychotherapy group for family care partners of persons living with neurodegenerative conditions. Following the plan-do-study-act model, a team of geropsychologists iteratively developed, implemented, and refined the 8-week “Caring Through COVID” psychotherapy group across five cycles from January 2021 to April 2022. Participants were 21 spouses or adult children of persons living with neurodegenerative conditions. Across two clinics, participants evidenced moderate improvements in caregiver burden ( d = .59), self-efficacy for caregiving ( d = −.64), and self-efficacy for emotion regulation ( d = −.60). The group was perceived positively by participants. This QI project demonstrates the real-world implementation of a psychotherapy group developed during the COVID-19 pandemic and refined to remain ongoing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.023

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 head0.158
GPT teacher head0.448
Teacher spread0.289 · 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