MétaCan
Menu
← Back to cohort

Evaluation of responsiveness to change to psychosocial group therapy (PGT) and to the process of dying of psychosocial and quality of life (QOL) measures

2005· article· en· W2246597450 on OpenAlexaff
Julie Lemieux, Dorcas Beaton, Louise Bordeleau, Sheilah Hogg‐Johnson, Peter Goodwin

Bibliographic record

VenueJournal of Clinical Oncology · 2005
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsInstitute for Work & Health
Fundersnot available
KeywordsMedicinePsychosocialProfile of mood statesQuality of life (healthcare)Visual analogue scaleMoodPhysical therapyBreast cancerCancerInternal medicineClinical psychologyOncologyPsychiatryNursing

Abstract

fetched live from OpenAlex

8035 Background: Responsiveness, the ability of a measure to accurately detect change when it has occurred, is essential for questionnaires used in intervention trials. Good responsiveness minimizes false negative trials and lowers the sample size (SS) needed to detect an effect. Methods: Using data from the “Breast Expressive-Supportive Therapy” study in metastatic breast cancer (Goodwin PJ NEJM 2001), we assessed group responsiveness to two types of change: the PGT (between group difference of within person changes) and the process of dying (within person changes). Questionnaires are: Profile of Mood States (POMS), Impact of Events Scale (IES), Psychosocial Adjustment to Illness Scale (PAIS), EORTC QLQ-C30, Mental Adjustment to Cancer (MAC) and a pain visual analog scale (PAIN-VAS). The effect size (ES) is the difference in scores divided by the baseline standard deviation (SD) (positive reflecting improvement, negative reflecting deterioration). Results were similar when ES was calculated using SD of change. Results: POMS was the most responsive to PGT (ES 0.30). The MAC, IES and the EORTC emotional subscale were not responsive (ES 0.09, 0.02, -0.01 respectively). The PAIS was intermediate (ES 0.24). For the process of dying, responsiveness was high for the EORTC (ES functional scales -0.71, global QOL -0.70 and symptoms -0.57), PAIN-VAS (ES -0.79) and PAIS (ES -0.65). It was low for POMS (ES -0.22), MAC (-0.21) and IES (0.11). Based on the relative efficiency (square of T-statistic ratio), SS needed to detect what was observed to be an ES of 0.3 for PGT using POMS as the standard are: 348 pts using POMS, 621 using PAIS and > 1000 for the other questionnaires. For the process of dying, SS needed to detect what was observed to be an ES of -0.7 in global QOL using EORTC as the standard are: 16 pts using the EORTC, 27 using the PAIS and 107 using the POMS. Conclusions: This study shows that POMS is the most responsive questionnaire to the effect of PGT,whereas the EORTC and PAIS (addressing symptoms and function) are the most responsive to end of life deterioration. Most responsive questionnaires require the smallest SS. Thus, choice of questionnaire is dependent on the research question. No significant financial relationships to disclose.

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)0.082
metaresearch head score (Gemma)0.135
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.435

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0820.135
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.407
GPT teacher head0.571
Teacher spread0.163 · 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 designObservational
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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicCancer survivorship and care→French-language works237,207→