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Record W3035591700 · doi:10.5430/jnep.v10n9p57

Quality of life of Zambian breast cancer women receiving care at the cancer diseases hospital Lusaka

2020· article· en· W3035591700 on OpenAlexvenueno aff
Masadza Wezzie, Siankulu Elaine, Kawalika Micheal, Victoria Mwiinga-Kalusopa, Patricia Katowa-Mukwato

Bibliographic record

VenueJournal of Nursing Education and Practice · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerQuality of life (healthcare)CancerHormonal therapySexual functionAffect (linguistics)MalignancyRadiation therapyGynecologyFamily medicineInternal medicineNursingPsychology

Abstract

fetched live from OpenAlex

Background: Breast cancer is the most frequently diagnosed malignancy among women in the world with an estimation of 1.67 million new diagnoses worldwide in 2012 estimated at 25% of all cancers. In Zambia, breast cancer is the second most common cancer affecting women and accounts for 9% of all histologically proven cancers among patients admitted at the country’s only Cancer Diseases Hospital Most of the patients receive multiple treatment modalities; Surgery, Chemotherapy, Radiation Therapy and Hormonal Therapy, each with its own long-term side effects with a potential to affect the women’s functionality, self-image and sexuality consequently the general quality of life of these women.Methods: A descriptive cross-sectional study design was used to investigate the Quality of Life (QoL) and factors influencing QoL among women with breast cancer receiving care at Zambia’s only Cancer Diseases Hospital. A total of 130 breast cancer patients on treatment who were willing to participate in the study were selected using simple random sampling. Data was collected using the European Organization for Research and Treatment in Cancer Quality of Life Questionnaire (EORTCQLQ–C30) and its breast cancer supplementary measure (QLQ-BR23). The tool assessed QoL across the physical, role, cognitive, emotional, and social functioning and sexual function domains.Results: Overall, just about half (52.5%) of the 130 respondents had high Quality of Life. QoL which was measured by the EORTCQLQ–C30 under the five domains (Physical, role, emotional, cognitive and sexual functioning) was high in four out of the five which scored above the global mean score of 68. Only the emotional functioning domain scored (65) below the mean. Conversely, the symptom scale scored high on all the eight sub items of fatigue, nausea and vomiting, pain, dyspnea, insomnia, appetite loss, constipation and diarrhea which signified high symptom experience among respondents. Similarly using the breast cancer supplementary measure (QLQ-BR23), two out of the four functional subscales (body image and sexual functioning) score high than average while sexual enjoyment and future perspectives score low. On the symptom scale, three out of the four scales scored higher than averages, signifying high symptom experience. Demographic characteristics which had significant association with QoL were age (p < .023), level of education (p < .023) and financial status (p < .000). Other factors that had significant association with QoL were type of treatment being received (p < .023), the severity of condition (p < .000), access to health care services (p < .000) and social support (p < .000).Conclusions: A diagnosis of breast cancer and its subsequent treatment affects several facets of a woman’s life ranging from physical, emotional, social and financial aspects consequently affecting the entire QoL. However the QoL varies and is influenced by a number of factors including age at diagnosis of cancer, level of education, financial status, type of treatment received, severity of the condition, access to health care facilities and social support. Therefore any intervention aimed at improving the QoL should be multidimensional.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.054
GPT teacher head0.418
Teacher spread0.364 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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