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Record W2917902864 · doi:10.2196/12453

Effective Information Provision About the Side Effects of Treatment for Malignant Lymphoma: Protocol of a Randomized Controlled Trial Using Video Vignettes

2019· article· en· W2917902864 on OpenAlexvenueno aff
Nanon Labrie, Sandra van Dulmen, Marie José Kersten, Hanneke J.C.J.M. de Haes, Arwen H. Pieterse, Julia C.M. van Weert, Dick Johan van Spronsen, Ellen M.A. Smets

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsRecallEmpathyRandomized controlled trialAffect (linguistics)MedicineCognitionProtocol (science)Task (project management)PsychologySocial psychologyAlternative medicineCognitive psychologyPsychiatryCommunicationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Informing patients with cancer about the possible implications of prospective treatment is a crucial yet challenging task. Unfortunately, patients' recall of medical information is generally poor and their information needs are not met. Effective information giving entails that oncologists help patients understand and recall the implications of their treatment, meanwhile fostering a trusting physician-patient relationship. Communication strategies that are often suggested to be effective are structuring and tailoring (cognition-oriented) but also are oncologists' expressions of caring or empathy (affect-oriented). OBJECTIVE: The aim of this study is to provide evidence concerning the pathways linking physician communication to (improved) consultation outcomes for patients. More specifically, the aim is to determine the effects of information structuring and information tailoring, combined with physician caring, on information recall, satisfaction with information, and trust in the physician (primary objective) and on symptom distress (secondary objective). METHODS: A randomized controlled trial, systematically testing the effects of information structuring and information tailoring, each combined with caring, in 2 video-vignette experiments (2×2 and 2×2×2 design). Using an online survey platform, participants will be randomly allocated (blinded) to 1 of 12 conditions in which they are asked to view a video vignette (intervention) in which an oncologist discusses a treatment plan for malignant lymphoma with a patient. The independent variables of interest are systematically varied across conditions. The outcome measures are assessed in a survey, using validated instruments. Study participants are (former) patients with cancer and their relatives recruited via online panels and patient organizations. This protocol discusses the trial design, including the video-vignette design, intervention pretesting, and a pilot study. RESULTS: Data collection has now been completed, and preliminary analyses will be available in Spring 2019. A total of 470 participants completed the first part of the survey and were randomized to receive the intervention. CONCLUSIONS: The results of the proposed trial will provide evidence concerning the pathways linking physician information, giving skills to (improved) consultation outcomes for patients. TRIAL REGISTRATION: Netherlands Trial Register NTR6153; https://www.trialregister.nl/trial/6022 (Archived by Webcite at http://www.webcitation.org/76xVV9xC8). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12453.

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)0.042
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.042
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.046
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0090.005
Bibliometrics0.0030.004
Science and technology studies0.0040.004
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0390.006

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 head0.242
GPT teacher head0.577
Teacher spread0.335 · 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 designRandomized trial
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

Citations14
Published2019
Admission routes1
Has abstractyes

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