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Record W2795986943 · doi:10.22374/jmhan.v1i1.11

A Mindfulness Based Support Group for Families in Early Psychosis: A pilot qualitative study

2017· article· en· W2795986943 on OpenAlexaffvenue
D. Whitehorn, Mary E. Campbell, Patricia G. Cosgrove, Sabina Abidi, Philip G. Tibbo

Bibliographic record

VenueJournal of Mental Health and Addiction Nursing · 2017
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsIzaak Walton Killam Health CentreNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsMindfulnessPsychologyFocus groupClinical psychologyContext (archaeology)Coping (psychology)Mental healthIntervention (counseling)PsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Background and Objectives To explore a mindfulness-based support group for parents of young people in care for a first episode of psychosis with an Early Intervention Service (EIS). Material and Methods Family members in EIS were recruited for a one year research protocol with 8 group sessions during which mindfulness practices were introduced. Participants were supported in developing an ongoing mindfulness practice. Focus groups and individual interviews provided data for qualitative analysis of participant experience. Results Participants reported that mindfulness practice was associated with (1) a greater sense of ease, (2) increased awareness, (3) less emotional reactivity, and (4) improved interpersonal relationships. Factors involved in developing a sustained mindfulness practice included the age and stage of illness of the offspring, the stage of family development and prior exposure to mindfulness. Conclusions Sustained mindfulness practice, developed in the context of a mindfulness-based family support group, can provide support in regard to coping and communication for parents of young people in care for a first episode of psychosis. Further exploration of the use of mindfulness to support families encountering mental illness seems warranted.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.497

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 studies0.0010.000
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 head0.071
GPT teacher head0.453
Teacher spread0.382 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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