Quality of life among female cancer survivors in Africa: An integrative literature review
Bibliographic record
Abstract
Quality of life (QOL) has been studied extensively among cancer populations in high income countries where cancer care resources are available to many. Little is known concerning the QOL of cancer groups residing in Africa where resources can be scarce. The integrative review of the literature explored and critically examined studies that had addressed QOL in female cancer survivors in Africa. The extent to which QOL studies incorporated a cultural perspective was also examined. Research studies published between 2005 and 2015 were retrieved from five databases: CINAHL, MEDLINE, SCOPUS, ProQuest dissertations and Theses full text, and GlobalHealth. Primary qualitative or quantitative studies regardless of sample size or setting were included. A total of 300 studies were identified and 28 full text studies were retrieved and assessed for eligibility. Eight studies met inclusion criteria. Factors that affected the QOL were socio-demographic especially age, education, employment, income and residence; illness-related factors such as having advanced cancer and multiple symptoms; treatment-related factors associated with surgery and radiotherapy; psychosocial factors such as support and anxiety; and cultural factors including fatalism and bewitching. Practice implications entail increasing awareness among nurses and allied healthcare providers of the potential effects on QOL of a cancer diagnosis and treatment of female cancers such as pain, fatigue, sexual dysfunction, hormonal and body image changes, anxiety, depression and cultural practices. Failure to identify and deal with these may result in poor treatment adherence, low self-esteem, and ultimately poor QOL.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".