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Record W4293113305 · doi:10.1002/nop2.1338

Nursing care for persons with developmental disabilities: Review of literature on barriers and facilitators faced by nurses to provide care

2022· review· en· W4293113305 on OpenAlexafffund
Nazilla Khanlou, Attia Khan, Christine Kurtz Landy, Rani Srivastava, Shirley McMillan, Susan VanDeVelde‐Coke, Luz María Vázquez

Bibliographic record

VenueNursing Open · 2022
Typereview
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsAutism CanadaCentre for Addiction and Mental HealthThompson Rivers UniversityYork University
FundersYork University
KeywordsNursingPsychologyNursing careMedicine

Abstract

fetched live from OpenAlex

AIMS: To identify barriers and facilitators to nursing care of individuals with developmental disabilities (DDs). BACKGROUND: Individuals with DDs experience health disparities. Nurses, although well positioned to provide optimal care to this population, face challenges. DESIGN: Narrative review of extant published peer-reviewed literature. DATA SOURCES: Electronic databases, ProQuest and EBSCO, were searched for studies published in English between 2000 and 2019. REVIEW METHODS: Three reviewers reviewed abstracts and completed data extraction. Knowledge synthesis was completed by evaluating the 17 selected studies. RESULTS: Emerging themes were: (1) barriers and challenges to nursing interventions; (2) facilitators to nursing care; and (3) recommendations for nursing education, policy and practice. CONCLUSION: Nursing has the potential to be a key partner in supporting the health of people with DDs. IMPACT: There is a need for specific education and training, so nurses are better equipped to provide care for people with DDs.

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)0.007
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.002
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 head0.074
GPT teacher head0.433
Teacher spread0.359 · 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 designNot applicable
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

Citations26
Published2022
Admission routes2
Has abstractyes

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