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Record W4317907776 · doi:10.3390/curroncol30020116

The Effects of Lack of Awareness in Age-Related Quality of Life, Coping with Stress, and Depression among Patients with Malignant Melanoma

2023· article· en· W4317907776 on OpenAlexvenueno aff
Ana-Olivia Toma, Estera Boeriu, Luminita Decean, Vlad Bloancă, Felix Bratosin, Mihaela Codrina Levai, Neeharika Gayatri Vasamsetti, Satish Alambaram, Andrada Oprişoni, Bogdan Miuţescu, Kakarla Hemaswini, Iulius Juganaru, Andrei-Cristian Bondar, Marius Liviu Moise

Bibliographic record

VenueCurrent Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMelanomaAnxietyPsychosocialMoodCoping (psychology)Depression (economics)Quality of life (healthcare)SadnessSkin cancerInternal medicineClinical psychologyCancerPsychiatryAngerNursing

Abstract

fetched live from OpenAlex

Almost one-third of all malignant melanoma patients exhibit emotional stress indicating the need for professional care. Considering this, patients’ psychological needs are routinely overlooked and unfulfilled, even though there is substantial evidence that psychological therapies may enhance psychosocial outcomes for melanoma patients, such as low mood, sadness, and anxiety. Among developing countries and some health systems in developed regions, the lack of awareness and screening methods for skin cancer creates a high risk of psychological issues associated with more advanced diseases. Therefore, the current study aimed to investigate and compare the impact of malignant melanoma awareness for screening, prevention, and treatment on the patient’s quality of life and coping with stress and depression, based on patients’ age. This cross-sectional study recruited 238 patients with malignant melanoma distributed into two groups, Group A patients between 18 and 65 years and Group B patients older than 65. There were no significant gender differences and cancer staging differences between groups, although self-reported depressed mood and anhedonia were significantly more frequent in younger adults with malignant melanoma (43.8% vs. 28.9%). From the unstandardized surveys, it was observed that significantly fewer patients from Group B knew that melanoma could be caused by sun exposure (34.2% vs. 52.2%), and they were less likely to use sunscreen or visit a doctor to evaluate their skin moles (25.9% vs. 14.5%). Elderly patients preferred television as the main source of information, and only 68.4% of patients from Group B were using smart devices. There was a significantly higher physical score on the SF-12 scale among Group A patients, although patients from Group B scored higher in the mental health assessment, and the perceived helplessness on the PSS-10 scale was significantly higher compared to younger adults with melanoma (2.97 vs. 2.71, p-value = 0.036). Lower scores on the physical and mental SF-12 questionnaire determined a higher presence of depressive symptoms (rho = −0.352, respectively rho = −0.273). Higher scores on the DLQI sexual difficulties and treatment difficulties also correlated significantly with the presence of depressive symptoms and anhedonia (rho = 0.341, respectively rho = 0.264). Awareness campaigns for malignant melanoma should focus on the elderly population, too, using the television as the main communication channel. On the other hand, the more informed and knowledgeable group of adults younger than 65 are more likely to experience psychological problems and should be targeted for psycho-oncological aid.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.351
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2023
Admission routes1
Has abstractyes

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