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Record W3012613573 · doi:10.2196/17854

Development of a Short Instrument for Measuring Health-Related Quality of Life in Oncological Patients for Clinical Use: Protocol for an Observational Study

2020· article· en· W3012613573 on OpenAlexvenueno aff
Theresa Schrage, Mirja Görlach, Christian Betz, Carsten Bokemeyer, Volkmar Müller, Cordula Petersen, Andreas Krüll, Holger Schulz, Christiane Bleich

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyMedicineProtocol (science)Quality of life (healthcare)Context (archaeology)Health careMedical physicsClinical PracticeIntensive care medicinePhysical therapyAlternative medicineFamily medicineNursingPathology

Abstract

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BACKGROUND: Cancer patients often suffer from the physical and psychological burden of their disease and its treatment. This is frequently insufficiently identified and addressed in clinical practice. In the context of improving patient-centered care in oncological patients, patient-reported outcomes (PROs) represent an important addition to current routine care. So far, available PRO questionnaires for cancer patients are unsuitable for routine procedures due to their length and complexity. OBJECTIVE: This study aimed to develop and psychometrically test a short questionnaire to measure health-related quality of life (HrQoL) in cancer patients for use in routine care. METHODS: This observational study consists of two parts: (1) a qualitative study to develop a short questionnaire measuring HrQoL and (2) a quantitative study to psychometrically test this questionnaire in five oncological departments of a comprehensive cancer center. In part 1 of the study, semistructured interviews with 28 cancer patients, as well as five focus groups with 22 clinicians and nurses, were conducted to identify clinically relevant dimensions of HrQoL. The identified dimensions were complemented with related dimensions from empirical studies and reviewed via expert discussion. Based on this, a short instrument was developed. In part 2 of the study, the developed questionnaire was tested in cancer in- and outpatients at five participating oncological clinics using additional standardized questionnaires assessing HrQoL and other important PROs. The questionnaire was presented to more than 770 patients twice during treatment. RESULTS: The project started in May 2017 with recruitment for study phase I beginning in December 2017. Recruitment for study phases I and II ended in April 2018 and February 2019, respectively. After study phase II and psychometrical analyses, the newly developed questionnaire measuring the HrQoL of all cancer entities in routine care was finalized. CONCLUSIONS: With five to six dimensions and one item per dimension, the developed questionnaire is short enough to not disrupt routine procedures during treatment and is profound enough to inform clinicians about the patient's HrQoL impairments and status. TRIAL REGISTRATION: Open Science Framework Registries 10.17605/OSF.IO/Y7XCE; https://osf.io/y7xce/. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/17854.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.038
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.038
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.030
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.003
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0220.006

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 head0.944
GPT teacher head0.700
Teacher spread0.244 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations2
Published2020
Admission routes1
Has abstractyes

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