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Record W4402974503 · doi:10.2196/53440

Scope, Findability, and Quality of Information About Music-Based Interventions in Oncology: Quantitative Content Analysis of Public-Facing Websites at National Cancer Institute–Designated Cancer Centers

2024· article· en· W4402974503 on OpenAlexvenueno aff
Carol Ann Blank, Sarah Biedka, Abigail Montalmant, Katelyn Saft, Miranda Lape, Kate Mao, Joke Bradt, Kevin T. Liou

Bibliographic record

VenueJMIR Cancer · 2024
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsPreprintScope (computer science)Content analysisPsychological interventionQuality (philosophy)MedicineInternet privacyWorld Wide WebComputer scienceSociologyNursing

Abstract

fetched live from OpenAlex

Background: Music-based interventions (MBIs) are evidence-based, nonpharmacological treatments that include music therapy (MT) delivered by board-certified music therapists, as well as music services (MS) delivered by other health professionals and volunteers. Despite MBI's growing evidence base in cancer symptom management, it remains unclear how MBI-related information is presented to the public. Over 80% of people with cancer use the internet to find health-related information. In the United States, the National Cancer Institute (NCI) identifies certain Cancer Centers (CCs) as NCI-designated CCs or Comprehensive Cancer Centers (CCCs) based on their excellence in research. As NCI-designated CCs and CCCs are considered the gold standard in cancer care, their websites are viewed by the public as important sources of information. Objective: We aimed to determine scope, findability, and quality of MBI-related information on public-facing websites of NCI-designated CCs/CCCs. Methods: We reviewed 64 NCI-designated CC/CCC websites (excluding basic laboratories) between November 2022 and January 2023. We extracted data on the scope of information: (1) type of MBI offered (MT or MS), (2) format (individual, group), (3) method of delivery (in person or remotely delivered), (4) setting (inpatient or outpatient), (5) target population (pediatric or adult), (6) MBI practitioner qualifications, (7) clinical indications or benefits, (8) presence of testimonials, (9) cost, and (10) scheduling or referral information. We also extracted data on findability (ie, presence of direct link or drop-down menu and the number of clicks to locate MBI-related information). Based on the scope and findability data, we rated the information quality as high, moderate, or low using an adapted scale informed by prior research. Results: Thirty-one (48%) of the 64 CC/CCCs described MBIs on their websites. Of these, 6 (19%) mentioned both MT and MS, 16 (52%) mentioned MT only, and 9 (29%) mentioned MS only. The most common format was hybrid, involving individuals and groups (n=20, 65%). The most common delivery method was in person (n=16, 52%). The most common target population was adults (n=12, 39%). The most common MBI practitioners were board-certified music therapists (n=21, 68%). The most described indications or benefits were psychological. Twenty-eight (90%) websites lacked testimonials, and 26 (84%) lacked cost information. Twenty-six (84%) websites provided scheduling or referral information. MBI-related information was found with an average of 4 (SD 1) clicks. Nine (29%) websites were of high quality, 18 (58%) were moderate, and 4 (13%) were low. Conclusions: Based on public websites, MBIs were most commonly delivered in person by board-certified music therapists to outpatient and inpatient adults, using individual and group formats to provide psychological benefits. The findability and quality of this information should be improved to promote the dissemination of MBIs for cancer symptom management.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.416
GPT teacher head0.527
Teacher spread0.111 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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