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Record W4210900269 · doi:10.1177/15347354221077229

“Part of the Conversation”: A Qualitative Study of Oncology Healthcare Professionals’ Experiences of Integrating Standardized Assessment and Documentation of Complementary Medicine

2022· article· en· W4210900269 on OpenAlexafffund
Lynda G. Balneaves, Cody Z. Watling

Bibliographic record

VenueIntegrative Cancer Therapies · 2022
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsUniversity of Manitoba
FundersCanadian Cancer Society Research Institute
KeywordsDocumentationThematic analysisMedicineQualitative researchAgency (philosophy)Health careConversationOncologyFamily medicineMedical educationInternal medicineNursingPsychology

Abstract

fetched live from OpenAlex

INTRODUCTION: The use of complementary medicine (CM) among individuals with cancer is common, however, it is infrequently assessed or documented by oncology healthcare professionals (HCPs). A study implementing standardized assessment and documentation of CM was conducted at a provincial cancer agency. The purpose of this study was to understand the perspectives and experience of oncology HCPs who took part in the study, as well as withdrew, regarding the feasibility and the challenges associated with assessment and documentation of CM use. METHODS: An interpretive descriptive study methodology was used. A total of 20 HCPs who participated, managed staff, or withdrew from the study were interviewed. Interviews were recorded and transcribed verbatim. Thematic, inductive analysis was used to code and analyse themes from the data. RESULTS: Oncology HCPs who participated in the study felt that CM use was common among patients and recognized it went underreported and was poorly documented. Facilitating factors for the implementation of standardized assessment and documentation of CM use included having a standard assessment form, embedding assessment within existing screening processes, and leveraging self-report by patients. Barriers included limited time, perceived lack of knowledge regarding CM, hesitancy to engage patients in discussion about CM, and lack of institutional support and resources. Recommendations for future implementation included having explicit policies related to addressing CM at point-of-care, leveraging existing electronic patient reporting systems, including the electronic health record, and developing information resources and training for HCPs. CONCLUSIONS: With the high prevalence of CM use among individuals with cancer, oncology HCPs perceive addressing CM use to be feasible and an essential part of high-quality, person-centered cancer care. Institutional and professional challenges, however, must be overcome to support the assessment, documentation and discussion of CM in patient-HCP consultations.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.091
GPT teacher head0.514
Teacher spread0.423 · 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 designQualitative
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

Citations11
Published2022
Admission routes2
Has abstractyes

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