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Record W3124364424 · doi:10.1080/08870446.2021.1872791

The experiences of mothers who have a child diagnosed with cancer

2021· article· en· W3124364424 on OpenAlexaff
Bernie McEvoy, Mary Creaner

Bibliographic record

VenuePsychology and Health · 2021
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsTrinity College
Fundersnot available
KeywordsSuperordinate goalsPsychosocialInterpretative phenomenological analysisPsychologyQualitative researchIdentity (music)Developmental psychologyChildhood cancerClinical psychologyCancerSocial psychologyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

Objective: This qualitative study explored the experiences of mothers who had a child diagnosed with cancer.Design and Outcome Measure: Informed by Interpretative Phenomenological Analysis, semi-structured interviews were completed with 13 participants, transcribed verbatim with individual and cross-case analysis conducted.Results: One superordinate theme, Protecting My Child, Whatever the Cost, was identified with five related subordinate themes. Participants battled to protect the development of their ill child. They richly described the personal costs and losses experienced, including putting their life on hold, and lost time with their healthy children. Participants faced realities of cancer treatment that were incongruent with their goal of protecting their child. Self-care awareness was significant for well-being as they protected themselves from reminders of their child’s mortality. Despite living in a crisis, participants reported changes suggestive of posttraumatic growth.Conclusion: Childhood cancer brings profound psychosocial and biographical disruption to the lives of mothers as they lose socially valued roles and have their identity as competent mothers challenged. Mothers protect their child, often at a cost to their health and well-being but also bringing positive consequences. The findings offer insights for psychologists in supporting mothers to reclaim their identity as competent mothers and renegotiate their mothering expectations.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.049
GPT teacher head0.421
Teacher spread0.372 · 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 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".

Quick stats

Citations13
Published2021
Admission routes1
Has abstractyes

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