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Record W4296778042 · doi:10.1093/pch/21.supp5.e90c

Inner-City Fathers of Children Affected by Chronic Illness: A Systematic Scoping Review of Their Experiences

2016· article· en· W4296778042 on OpenAlexaff
A Kobylianskii, T Jegathesan, E Young, Karen Fung, J Huber, R Minhas

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsToronto Public Health
Fundersnot available
KeywordsCINAHLPsycINFOSocioeconomic statusEthnic groupStressorMEDLINEMedicineSocial supportRefugeePsychologyGerontologyPsychological interventionClinical psychologyNursingPopulationSociologySocial psychologyEnvironmental healthGeographyPolitical science

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Childhood chronic illness often impacts not just the child but the whole family, particularly the parents. Parents from inner-city backgrounds (defined as low income/socioeconomic status, unemployed, immigrant, refugee, or ethnic minority, and living in an urban area) face additional challenges. Research has traditionally centred on the mother’s role in caring for a child with a chronic illness, but with the increasing role of fathers caring for these children, research has shifted its focus on paternal experience. However, the experiences of inner-city fathers remain largely unknown. OBJECTIVES: This systematic scoping review aims to explore the experiences of fathers of children with disabilities or chronic health conditions from inner city families, using the Double ABCX model as a conceptual framework. DESIGN/METHODS: A systematic scoping review was conducted between November 2014 and January 2015 using the Arksey and O'Malley framework. Seven databases were searched (Medline, PsycInfo, Embase, Web of Science, CINAHL, Scopus, and Social Work Abstracts). Titles and abstracts meeting inclusion and exclusion criteria were included in the full text review for further assessment. Qualifying articles were critically appraised and relevant data were extracted. The Double ABCX model was used to qualitatively evaluate the articles in terms of stressors, resources, perception, coping, and adaptation. RESULTS: 5114 articles were initially identified and 14 articles met the inclusion criteria. Most of the included studies were conducted in the USA. Most articles discussed fathers from low income/SES backgrounds, while others discussed ethnic minority, immigrant/refugee, and unemployed fathers. Fathers' stressors included financial strain and barriers to accessing healthcare. Fathers' resources, or sources of support, ranged from immediate to extended family members, depending on ethnicity. In terms of perceptions, fathers had different approaches to reconciling the care-giver role with cultural gender norms. Inner-city fathers had more desire for information about their children’s health, but some were uncomfortable with asking physicians. Inner-city fathers were more at risk for coping difficulties and used different coping strategies compared to higher income fathers. Inner-city fathers were at higher risk for maladaptation, including depression, PTSD and less acceptance of the child. CONCLUSION: Fathers from inner-city backgrounds caring for their children affected by chronic illnesses and disabilities have unique experiences requiring a comprehensive approach to providing and communicating care to these children and caregivers. Findings from this review can be used to guide pediatricians in advocating for resources to reduce stressors, enhance coping, and promote positive adaptation for inner-city fathers.

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)0.012
metaresearch head score (Gemma)0.049
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 score0.012
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0110.015
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.304
Teacher spread0.287 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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