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Record W2111587292 · doi:10.5014/ajot.59.3.249

Occupational Goals of Mothers of Children With Disabilities: Influence of Temporal, Social, and Emotional Contexts

2005· article· en· W2111587292 on OpenAlexaboutno aff
Jody Donovan, Betsy VanLeit, Terry K. Crowe, Elizabeth B. Keefe

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2005
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsWorkloadOccupational therapyPsychologyAffect (linguistics)Quality of life (healthcare)Developmental psychologyCognitive disabilitiesQualitative researchApplied psychologyNursingClinical psychologyMedicineCognitionPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to describe the occupational concerns and goals of mothers who care for children with disabilities. METHOD: Retrospective data collected from 38 mothers of children with disabilities using the Canadian Occupational Performance Measure (COPM) were analyzed qualitatively. RESULTS: Six themes emerged: (I) doing and being alone: taking care of my own health and well-being; (II) doing and being with others: expanding my social life; (III) improving my child's quality of life; (IV) household management: organizing time and resources; (V) balancing work, home, and community responsibilities; and (VI) sharing the workload. CONCLUSION: Overarching patterns in the data suggested that the occupational performance of mothers of children with disabilities is constrained by time, overlaid by difficult emotions, and involves a desire for increased social contact. Qualitative analysis of data from the COPM may provide insight into contextual factors that affect occupational performance as well as signaling point of entry for therapists to facilitate client-centered occupational goals.

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)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.101
GPT teacher head0.472
Teacher spread0.371 · 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 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

Citations43
Published2005
Admission routes1
Has abstractyes

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