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Record W4321352903 · doi:10.2196/46281

Telehealth-Based Music Therapy Versus Cognitive Behavioral Therapy for Anxiety in Cancer Survivors: Rationale and Protocol for a Comparative Effectiveness Trial

2023· article· en· W4321352903 on OpenAlexvenueno aff
Kevin T. Liou, Kelly M. McConnell, Beatriz Currier, Raymond E. Baser, Jodi MacLeod, Desiree Walker, Camila Casaw, Greta Wong, Lauren Piulson, Karen Popkin, Ana María López, Katherine S. Panageas, Joke Bradt, Jun J. Mao

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
FundersNational Cancer InstitutePatient-Centered Outcomes Research Institute
KeywordsAnxietyTelehealthWorryMoodRandomized controlled trialMusic therapyCognitive behavioral therapyQuality of life (healthcare)Psychological interventionMedicineClinical psychologyPsychiatryPhysical therapyPsychologyTelemedicinePsychotherapistHealth careInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer survivors represent one of the fastest growing populations in the United States. Unfortunately, nearly 1 in 3 survivors experience anxiety symptoms as a long-term consequence of cancer and its treatment. Characterized by restlessness, muscle tension, and worry, anxiety worsens the quality of life; impairs daily functioning; and is associated with poor sleep, depressed mood, and fatigue. Although pharmacological treatment options are available, polypharmacy has become a growing concern for cancer survivors. Music therapy (MT) and cognitive behavioral therapy (CBT) are evidence-based, nonpharmacological treatments that have demonstrated effectiveness in treating anxiety symptoms in cancer populations and can be adapted for remote delivery to increase access to mental health treatments. However, the comparative effectiveness of these 2 interventions delivered via telehealth is unknown. OBJECTIVE: The aims of the Music Therapy Versus Cognitive Behavioral Therapy for Cancer-related Anxiety (MELODY) study are to determine the comparative effectiveness of telehealth-based MT versus telehealth-based CBT for anxiety and comorbid symptoms in cancer survivors and to identify patient-level factors associated with greater anxiety symptom reduction for MT and CBT. METHODS: The MELODY study is a 2-arm, parallel-group randomized clinical trial that aims to compare the effectiveness of MT versus CBT for anxiety and comorbid symptoms. The trial will enroll 300 English- or Spanish-speaking survivors of any cancer type or stage who have experienced anxiety symptoms for at least 1 month. Participants will receive 7 weekly sessions of MT or CBT delivered remotely via Zoom (Zoom Video Communications, Inc) over 7 weeks. Validated instruments to assess anxiety (primary outcome), comorbid symptoms (fatigue, depression, insomnia, pain, and cognitive dysfunction), and health-related quality of life will be administered at baseline and at weeks 4, 8 (end of treatment), 16, and 26. Semistructured interviews will be conducted at week 8 with a subsample of 60 participants (30 per treatment arm) to understand individual experiences with the treatment sessions and their impact. RESULTS: The first study participant was enrolled in February 2022. As of January 2023, 151 participants have been enrolled. The trial is expected to be completed by September 2024. CONCLUSIONS: This study is the first and largest randomized clinical trial to compare the short- and long-term effectiveness of remotely delivered MT and CBT for anxiety in cancer survivors. Limitations include the lack of usual care or placebo control groups and the lack of formal diagnostic assessments for psychiatric disorders among trial participants. The study findings will help guide treatment decisions for 2 evidence-based, scalable, and accessible interventions to promote mental well-being during cancer survivorship. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46281.

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)0.005
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.317
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.738
GPT teacher head0.694
Teacher spread0.044 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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