MétaCan
Menu
Back to cohort
Record W4404055271 · doi:10.1177/10732748241298331

Challenges and Recommendations for Improving Cancer Research and Practice in Nigeria: <i>A Qualitative Study With Multi-Stakeholders in Oncology Research and Practice</i>

2024· article· en· W4404055271 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Control · 2024
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsQueen's University
FundersNational Institute of Environmental Health SciencesNational Cancer InstituteUniversity of Chicago MedicineBreast Cancer Research Foundation
KeywordsMedicineWorkforceMentorshipQualitative researchOncologyThematic analysisHealth careGovernment (linguistics)Internal medicineNursing researchNursingMedical education

Abstract

fetched live from OpenAlex

BACKGROUND: Cancers, with increasing incidence and mortality rates, constitute a leading public health problem in Nigeria. As the burden of cancer in Nigeria increases, research and quality service delivery remain critical strategies for improved cancer control across the continuum of care. This study contextualizes the challenges and gaps in oncology research and practice in Nigeria, and presents recommendations to address the gaps. METHODS: This qualitative study was conducted among interprofessional and interdisciplinary stakeholders in oncology healthcare practice and research in academic settings, between July and September 2021. Key-informant interviews were held with six stakeholders and leaders in nursing, pharmacy, and medicine across the six geopolitical zones of Nigeria, and twenty-four in-depth interviews with early- or mid-career researchers or healthcare professionals involved in cancer prevention and treatment were conducted. The data were analyzed using a deductive thematic analysis approach and coded using the NVIVO 12 software. RESULTS: Five sub-themes were identified as major challenges to oncology research, including poor funding, excessive workload, interprofessional rivalry, weak collaboration, and denial of cancer diagnosis by patients. Challenges identified for oncology practice were poor governance and financing, high costs of oncology treatments, poor public awareness of cancer, workforce shortage, and interprofessional conflicts. Recommended strategies for addressing these challenges were improved financing of oncology research and practice by government and relevant stakeholders, increasing interest of medical, nursing, and pharmaceutical students in oncology research through curricula-based approach and mentorship, increased oncology workforce, and improved intra- and inter-professional collaboration. CONCLUSION: These data highlight the challenges and barriers in oncology practice and research in Nigeria, and underscore the urgent need for increased investments in infrastructure to provide interdisciplinary and interprofessional research training for high-quality care. Only then can Nigeria effectively tackle the current and impending cancer burden in the country.

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.

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)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.755
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.398
GPT teacher head0.622
Teacher spread0.224 · 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