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Record W2889411190 · doi:10.1177/1043454218794667

The Balancing Act: Mothers’ Experiences of Providing Care to Their Children With Cancer

2018· article· en· W2889411190 on OpenAlexaffabout
Monica L. Molinaro, Paula C. Fletcher

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsWilfrid Laurier UniversityWestern University
Fundersnot available
KeywordsPsychologyNursingMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

The effect of pediatric cancer and its treatment are overwhelming-these effects are multifaceted and felt by the entire family unit throughout the diagnosis and treatment process. Children experience a plethora of effects as a result of the treatment process; however, it is imperative to remember that a pediatric cancer diagnosis affects parents physically, emotionally, and psychologically as well. While much of the pediatric cancer treatment occurs at the hospital or in clinics, parents are often faced with additional caregiving responsibilities at home, and in many cases, it is mothers who provide care to their children, while also attempting to care for the siblings of their ill children. This secondary data analysis examines the caregiving responsibilities of mothers from Southern Ontario, Canada, during the time from diagnosis to after their children's pediatric cancer treatment. Three subthemes emerged from the overall theme of caregiving: (1) "We tried to do as much as we could outside of the clinic," (2) "I had to be there for everything," and (3) "Most of the time we relied on other people." Each will be discussed in turn. The findings from this work provides insight to health care professionals on how to create or improve the current supports and resources provided to caregivers of children with cancer.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.343
Teacher spread0.325 · 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 teacher head, not a consensus.

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

Citations29
Published2018
Admission routes2
Has abstractyes

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