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Record W1990460445 · doi:10.1097/nur.0b013e31823bfb0f

Seeing the Glass Half Full

2011· article· en· W1990460445 on OpenAlexafffundabout
Roula Markoulakis, Paula C. Fletcher, Pamela J. Bryden

Bibliographic record

VenueClinical Nurse Specialist · 2011
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsToronto Public HealthUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMedicine

Abstract

fetched live from OpenAlex

PURPOSE: Autism spectrum disorders are the most common developmental disorders, affecting 1 in 165 Canadian children. Although the experiences of the caregivers of children with autism have been examined to some extent, a thorough investigation of the benefits of this experience is warranted. METHODS: The lived experiences of 8 married female primary caregivers of children with autism were assessed through a phenomenological study involving background questionnaires and one-on-one, semistructured interviews. All recruited participants completed the study. RESULTS: Benefits were found in all areas of questioning, including financial, social, familial, health, and employment implications, in addition to benefits arising from activities and involvements taken on as a result of raising a child with autism. The findings shed light on an unconventional aspect of the effects of raising a child with autism. CONCLUSIONS: Costs to these women's experiences were not predominant, and benefits arising from the caregiving role lead to positive accounts of their lived experiences. Results have broader implications for the understanding of the primary caregiver situation and the improvement of interactions with individuals with these lived experiences. In this way, clinical nurse specialists may encourage and contribute to support systems that foster a positive experience for caregivers of children with autism spectrum disorder, the children they care for, and their families.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.668
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0330.010

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 head0.218
GPT teacher head0.458
Teacher spread0.240 · 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; both teacher heads agree on what is shown here.

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

Citations61
Published2011
Admission routes3
Has abstractyes

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