MétaCan
Menu
Back to cohort
Record W2784840101 · doi:10.26443/ijwpc.v5i1.153

Mindfulness group for mentally ill patients in remission

2018· article· en· W2784840101 on OpenAlexaffvenueabout
Suzanne Lamarre, Lily Gozlan, Eric Billon

Bibliographic record

VenueInternational Journal of Whole Person Care · 2018
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsMcGill University Health CentreImmunoPrecise (Canada)St Mary's Hospital Centre
Fundersnot available
KeywordsMindfulnessMeditationAttendancePsychologyPsychotherapistConscienceReferralMental healthSession (web analytics)MedicinePsychiatryClinical psychologyNursing

Abstract

fetched live from OpenAlex

For the last four years the Institut de Pleine Conscience Appliquée de Montréal (IPCAM) and the Department of Psychiatry of the St. Mary Hospital Center, an affiliated McGill Community Hospital, have been offering a weekly 140 minutes session to mentally ill patients in remission. The sessions are held outside the hospital in the institute.The objectives of the authors are:1. To empower the Health Care Professionals (HCP) and the Expert in Mindfulness (EIM) to start such a co-op group for patients who otherwise might feel unable to discuss their mental health problems while trying to integrate mindfulness practice.2. To describe the outlines of such a group, such as the referral forms, the expected goals for attendance, the meditation exercises and some particular aspects of the sharing periods.3. To propose to the HCP and the EIM some practical tips in order to orient the patients in healthy habits of acceptance of themselves rather than maintaining themselves in maladaptive thoughts, emotions and behaviours. As we all know people who have had a difficult childhood could use mindfulness inadvertently for avoidance rather than acceptance.4. Finally to share with the HCP and the EIM the enriching experience of such a co-op group for the leaders as much as for the participants.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.363
Teacher spread0.341 · 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 designNot applicable
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
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Whole Person CareSame topicPsychotherapy Techniques and ApplicationsFrench-language works237,207