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Record W2800075173 · doi:10.5430/jnep.v8n9p55

Experiences of local residents who portrayed patients in simulated patient exercises

2018· article· en· W2800075173 on OpenAlexvenueno aff
Masako Shomura, Haruka Okabe, Satoshi Iwamoto, Futoshi Ohyama, Yoshikazu Kojima

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacy and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPrideNursingCitizen journalismValue (mathematics)PsychologyMedical educationMedicinePolitical science

Abstract

fetched live from OpenAlex

With a view toward developing Simulated Patient Exercises (SPE) together with local residents, we aimed to ascertain the role that instructors should play, and the coordination they should undertake to achieve this goal. We interviewed local residents in their 60s and 70s who participated in the participatory SPE program of Tokai University’s Adult Nursing Department. We asked the residents about what they gained from, and how they felt about, their experience in the program, and about the kind of support they need to play their role effectively. From the interview data and qualitative inductive analysis, we derived four themes describing the residents’ experiences: “Self-encouragement and growth”, “hardships as a Simulated Patient”, “efforts to improve the training of simulated patients”, and “wishes for nursing students”. Many of the statements described hardships the residents faced as Simulated Patients, including their nervousness and the burden of learning their role. On the other hand, we also heard many positive statements about how the residents felt encouraged and achieved growth through the experience. For example, in serving as simulated patients, the residents were encouraged by a sense of pride at how they were helping to train nursing students who will in the future help them and their family members, and they felt inspired by the students’ earnestness and their cordial learning attitudes, as well as by the camaraderie with fellow Simulated Patients. These positive statements illustrate the value of local residents participating in the program, and they explain why the residents continued to participate.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.163
GPT teacher head0.547
Teacher spread0.384 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2018
Admission routes1
Has abstractyes

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