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Record W3159609484 · doi:10.3389/fpsyg.2021.621850

A Systematic Review of Fear of Cancer Recurrence Among Indigenous and Minority Peoples

2021· review· en· W3159609484 on OpenAlexaffabout
Kate Anderson, Allan Ben Smith, Abbey Diaz, Joanne Shaw, Phyllis Butow, Louise Sharpe, Afaf Girgis, Sophie Lebel, Haryana M. Dhillon, Linda Burhansstipanov, B. Tighe, Gail Garvey

Bibliographic record

VenueFrontiers in Psychology · 2021
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Ottawa
FundersNational Health and Medical Research CouncilMenzies School of Health Research
KeywordsIndigenousEthnic groupAnxietyPopulationCancerPsychological interventionInclusion (mineral)MedicineDemographyGerontologyPsychologyClinical psychologyPsychiatryEnvironmental healthSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

While cancer survivors commonly experience fear and anxiety, a substantial minority experience an enduring and debilitating fear that their cancer will return; a condition commonly referred to as fear of cancer recurrence (FCR). Despite recent advances in this area, little is known about FCR among people from Indigenous or other ethnic and racial minority populations. Given the high prevalence and poor outcomes of cancer among people from these populations, a robust understanding of FCR among people from these groups is critical. The current review identified and aggregated existing literature on FCR amongst adult cancer survivors from Indigenous and minority populations. The protocol of this review was registered with PROSPERO in July 2020 (Registration number: CRD42020161655). A systematic search of bibliographic databases was conducted for relevant articles published from 1997 to November 2019. Data from eligible articles were extracted and appraised for quality by two independent reviewers. Nineteen articles from four countries (United States of America, Canada, Australia and the United Kingdom) met the inclusion criteria, including 14 quantitative, 4 qualitative and 1 mixed-methods study. Only one article reported on an Indigenous population. Few studies reported on FCR prevalence ( n = 3) or severity ( n = 9). While the variation in tools used to measure FCR hindered a robust estimate of severity, results suggested some differences in FCR severity between minority and dominant populations, although these may have been due to study metholodological differences. Few factors were reported as being associated with FCR in minorities across multiple studies. The qualitative synthesis found five themes associated with the lived experience of FCR: (i) variations in the lived experience of FCR; (ii) spirituality and worldview impacting on FCR; (iii) the importance of staying positive; (iv) complexities around support; and (v) increasing cancer knowledge. The findings of this review highlight differences in FCR across cultures and contexts, which reinforces the need for culturally-specific approaches to this condition. The dearth of research in this area is of concern given the significant burden of cancer in these populations. A deeper understanding of this condition among Indigenous and minority populations is critical to developing and delivering appropriate and effective psychosocial care for cancer survivors from these groups. Systematic Review Registration: identifier [CRD42020161655].

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)0.010
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0150.014
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.375
Teacher spread0.348 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations36
Published2021
Admission routes2
Has abstractyes

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