Bridging gaps throughout a patient’s journey with melanoma: a systematic review
Bibliographic record
Abstract
BACKGROUND: Melanoma is one of the most fatal skin cancers, with rising incidence and mortality worldwide. From diagnosis to treatment, patient experiences often involve anxiety, symptom burden, and limited access to information which profoundly impacts health outcomes. OBJECTIVE: This systematic review aims to identify and analyze major barriers melanoma patients face throughout their healthcare journey. METHODS: Studies were identified from PubMed, Scopus, Web of Science, Embase, and Cochrane Library, supplemented by manual hand-searching. Eligible studies focused on the experiences of melanoma patients, addressed knowledge gaps and barriers to care throughout the patient journey, and were published in English between 2013 and 2023. Screening and extraction were conducted independently and in duplicate. The methodological quality of the included studies was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. RESULTS: Out of 2,257 screened articles, 183 met the inclusion criteria. Studies were categorized into four major themes: intersectionality, treatment, diagnosis/prognosis, and patient/societal burden. Commonly explored subcategories included self-examination, risk factors, and drug efficacy. CONCLUSIONS: Melanoma patients experience significant gaps throughout their healthcare journey. Identifying areas of improvement in current practices is the first step toward developing targeted solutions that improve the patient experience and quality of life.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".