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P141 Young Ambassadors Project: engaging patients attending a specialised young adult clinic

2020· article· en· W3018457876 on OpenAlexaff
Ines Soares, Caroline Cotton, Lorraine Brinkley, C. Estrach

Bibliographic record

VenueLara D. Veeken · 2020
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsMedicineYoung adultBiopsychosocial modelFlexibility (engineering)NursingMedical educationGerontologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Emerging literature has highlighted that transition to adult services is a challenging time where many young patients are lost to follow up and disengage with health services. Furthermore, developmentally appropriate healthcare improves adherence and empowers young people. This recognises the changing biopsychosocial development needs of young people and advocates for a ‘young-person-friendly’ service. Aintree Hospital runs a young adult clinic based on the EULAR guidelines. Attending patients suggested that their positive experience could support and improve engagement of peers ready for transition. At the same time, they raised that the existing shared clinical area did not feel tailored to them given the lack of age-appropriate literature and lack of representation in the existing displays. This feedback led the team to a review of the service with the ultimate aim to improve patient engagement and satisfaction. Methods Using Plan-Do-Study-Act (PDSA) quality improvement methodology, a multidisciplinary healthcare team alongside a group of willing young adult patients (Young Ambassadors) identified a strategy to improve the young adult clinical area and facilitate transition peer support. Pilot funding was obtained from the Trust, with the aim to expand the methods to other specialities if successful. Results The team worked with the Young Ambassadors and a professional media company to produce ‘pop-ups’ featuring photographs of our young adult patients with positive inspirational messages. These were purposefully produced as mobile units rather than static posters to increase flexibility of use. We also improved the availability of age-appropriate literature in the waiting room (e.g. literature from Arthur’s Place, a magazine and social network for young adults with arthritis). Additionally, we developed a set of videos featuring three of our Young Ambassadors talking about their transition experience and how this affected their day-to-day lives. The videos will be available to patients ready to enter transition while still in children’s services. We envisage that this initiative will provide a patient perspective of living with chronic conditions, empower young people to take control of their health needs and therefore increase adherence, independence and promote positive career and life goals. Lastly, through the project and focus group sessions, our patients have already started a support network for young patients with rheumatic diseases. Conclusion Our young patients are keen to be involved in service development and wish to raise awareness of their life with chronic rheumatic diseases. We will measure the impact of our interventions through patient satisfaction questionnaires, group feedback sessions and by auditing patient attendance rates pre- and post-project. By working with our Young Ambassadors, we have successfully developed patient-led initiatives, tailored to young adult patients with the aim of improving future engagement and empowerment. Disclosures I. Soares None. C. Cotton None. L. Brinkley None. C. Estrach None.

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)0.008
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0070.002
Scholarly communication0.0040.002
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.098
GPT teacher head0.407
Teacher spread0.309 · 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 designQualitative
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".

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Citations0
Published2020
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Has abstractyes

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