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Record W3108195654 · doi:10.3389/fpsyg.2020.561997

Testing the Treatment Integrity of the Managing Cancer and Living Meaningfully Psychotherapeutic Intervention for Patients With Advanced Cancer

2020· article· en· W3108195654 on OpenAlexaff
Susan Koranyi, R Philipp, Leonhard Quintero Garzón, Katharina Scheffold, Frank Schulz‐Kindermann, Martin Härter, Gary Rodin, Anja Mehnert

Bibliographic record

VenueFrontiers in Psychology · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Institutes of HealthUniversität LeipzigDeutsche KrebshilfeDeutsche Forschungsgemeinschaft
KeywordsSadnessRandomized controlled trialIntervention (counseling)Likert scalePsychologyClinical psychologyCancer treatmentCancerAnxietyScale (ratio)PsychotherapistMedicinePsychiatryInternal medicineDevelopmental psychologyAnger

Abstract

fetched live from OpenAlex

Introduction The Managing Cancer and Living Meaningfully (CALM) therapy for patients with advanced cancer was tested against a supportive psycho-oncological counseling intervention (SPI) in a randomized controlled trial (RCT). We investigated whether CALM was delivered as intended (therapists’ adherence); whether CALM therapists with less experience in psycho-oncological care show higher adherence scores; and whether potential overlapping treatment elements between CALM and SPI can be identified (treatment differentiation). Methods Two trained and blinded raters assessed on 19 items four subscales of the Treatment Integrity Scale covering treatment domains of CALM (SC: Symptom Management and Communication with Health Care Providers; CSR: Changes in Self and Relationship with Others; SMP: Spiritual Well-being and Sense of Meaning and Purpose; FHM: Preparing for the Future, Sustaining Hope and Facing Mortality). A random sample of 150 audio recordings (75 CALM, 75 SPI) were rated on a three-point Likert scale with 1 = “adherent to some extent,” 2 = “adherent to a sufficient extent,” 3 = “very adherent.” Results All 19 treatment elements were applied, but in various frequencies. CALM therapists most frequently explored symptoms and/or relationship to health care providers (SC_1: n_applied = 62; 83%) and allowed expression of sadness and anxiety about the progression of disease (FHM_2: n_applied = 62; 83%). The exploration of CALM treatment element SC_1 was most frequently implemented in a satisfactory or excellent manner (n_sufficient or very adherent = 34; 45%), whereas the treatment element SMP_4: Therapist promotes acknowledgment that some life goals may no longer be achievable (n_sufficient or very adherent = 0; 0%) was not implemented in a satisfactory manner. In terms of treatment differentiation, no treatment elements could be identified which were applied significantly more often by CALM therapists than by SPI therapists. Conclusion Results verify the application of CALM treatment domains. However, CALM therapists’ adherence scores indicated manual deviations. Furthermore, raters were not able to significantly distinguish CALM from SPI, implying that overlapping treatment elements were delivered to patients.

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)0.014
metaresearch head score (Gemma)0.030
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.032
GPT teacher head0.329
Teacher spread0.297 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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