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Record W7043461865

Supporting and enhancing the implementation of outcome measures in Children and Young People’s Occupational Therapy.

2021· dissertation· en· W7043461865 on OpenAlexaboutno aff

Bibliographic record

VenueQueen Margaret University Publications Repository (Queen Margaret University) · 2021
Typedissertation
Languageen
FieldMaterials Science
TopicEnzyme Structure and Function
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyGeneral partnershipService (business)Government (linguistics)Outcome (game theory)Work (physics)Best practice
DOInot available

Abstract

fetched live from OpenAlex

Executive summary This project involved a partnership between NHS Borders Children and Young People’s (CYP) occupational therapy service and a Queen Margaret University (QMU) fourth year student (Appendix 1). NHS Borders CYP occupational therapy is a community-based team, providing services to CYP with a diverse range of difficulties aged from 0-18 years. They work with CYP who experience difficulties with the functional skills necessary for everyday life, aiming to ensure all CYP are physically, psychologically and socially as independent as possible (NHS Borders 2020). NHS Borders CYP lead occupational therapist identified the use of outcome measures as an area of their practice requiring further development1. The service required to gain a clearer understanding with regards to which outcome measures are currently used in practice and the impact of using them. The Royal College of Occupational Therapists (RCOT) (2020) acknowledge outcome measures as a fundamental aspect of occupational therapy practice. The use of outcome measures is recognised in the Scottish Government (2016) policy Ready to Act where Allied Health Professionals (AHP) are required to evidence the effectiveness of their interventions. The agreed aim of this project was to develop an electronic leaflet containing information about outcome measures used within CYP occupational therapy. This project was guided by service development. Service development involves implementing changes in order to advance practice. To develop the leaflet, information had to be gathered. A survey was selected as the most cost and time effective method of gathering information direct from CYP occupational therapists, regarding the use of 1 The project leader worked with the lead occupational therapist in NHS Borders CYP occupational therapy service, however the project was conducted for the benefit of the service as a whole. 2 outcome measures in their practice. A qualitative survey was distributed online in order to gain a range of responses and opinions. The information gained was analysed and developed into an electronic leaflet. Three outcome measures commonly used with CYP emerged from the findings and were included in the leaflet. These included the Canadian Occupational Performance Measure (COPM), the Perceived Efficacy and Goal Setting (PEGS) and Talking Mats. There were three common benefits of using outcome measures in CYP occupational therapy highlighted in the findings. These included “creates evidence”, “provides motivation” and “provides focus”. Two common challenges of using outcome measures in CYP occupational therapy were established, including “children’s needs” and “time and workload”. The electronic leaflet developed provided NHS Borders CYP occupational therapy service with information about outcome measures they could use with CYP, as well as the benefits and challenges of using them. As a result, the service should be able to use the leaflet to consider the selection and implementation of outcome measures within their practice. Overall, this could improve their service delivery and ensure the needs of CYP are met. An abstract for the World Federation of Occupational Therapists (WFOT) upcoming conference ‘Occupational R-Evolution’ is presented in Appendix 2.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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