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Record W4389049409 · doi:10.1186/s12960-023-00877-7

Characterising support and care assistants in formal hospital settings: a scoping review

2023· review· en· W4389049409 on OpenAlexaboutno aff
Vincent Kagonya, Onesmus Onyango, Michuki Maina, David Gathara, Mike English, Abdulazeez Imam

Bibliographic record

VenueHuman Resources for Health · 2023
Typereview
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
FundersNational Institute for Health and Care ResearchNational Institute for Health and Care Research Applied Research Collaboration Oxford and Thames ValleyWellcome TrustWellcome
KeywordsCINAHLWorkforceHealth careNursingPopulation healthMedicinePopulationContext (archaeology)Health administrationHealth services researchAcute careDocumentationThematic analysisPsychologyQualitative researchPublic healthPsychological interventionPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: A 15 million health workforce shortage is still experienced globally leading to a sub-optimal healthcare worker-to-population ratio in most countries. The use of low-skilled care assistants has been suggested as a cost-saving human resource for health strategy that can significantly reduce the risks of rationed, delayed, or missed care. However, the characterisation, role assignment, regulation, and clinical governance mechanisms for unlicensed assistive workforce remain unclear or inconsistent. The purpose of this study was to map and collate evidence of how care assistants are labelled, utilised, regulated, and managed in formal hospital settings as well as their impact on patient care. METHODS: We conducted a scoping review of literature from PUBMED, CINAHL, PsychINFO, EMBASE, Web of Science, Scopus, and Google Scholar. Searches and eligibility screening were conducted using the Participants-Context-Concepts framework. Thematic content analysis guided the synthesis of the findings. RESULTS: 73 records from a total of 15 countries were included in the final full-text review and synthesis. A majority (78%) of these sources were from high-income countries. Many titles are used to describe care assistants, and these vary within and across countries. On ascribed roles, care assistants perform direct patient care, housekeeping, clerical and documentation, portering, patient flow management, ordering of laboratory tests, emergency response and first aid duties. Additional extended roles that require higher competency levels exist in the United States, Australia, and Canada. There is a mixture of both positive and negative sentiments on their impact on patient care or nurses' perception and experiences. Clinical and organisational governance mechanisms vary substantially across the 15 countries. Licensure, regulatory mechanisms, and task-shifting policies are largely absent or not reported in these countries. CONCLUSIONS: The nomenclature used to describe care assistants and the tasks they perform vary substantially within countries and across healthcare systems. There is, therefore, a need to review and update the international and national classification of occupations for clarity and more meaningful nomenclature for care assistants. In addition, the association between care assistants and care outcomes or nurses' experience remains unclear. Furthermore, there is a dearth of empirical evidence on this topic from low- and middle-income countries.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.074
GPT teacher head0.439
Teacher spread0.365 · 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.

Study designSystematic review
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

Citations20
Published2023
Admission routes1
Has abstractyes

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