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Record W2119479212 · doi:10.5430/jnep.v4n2p186

The use of puppets as a strategy for communicating with children with type 1 diabetes mellitus

2013· article· en· W2119479212 on OpenAlexaffvenue
Valéria de Cássia Sparapani, Eufémia Jacob, Francine de Montigny, Luzia Iara Pfeifer, Amanda Mota Pacciulio Sposito, Regina Aparecida Garcia de Lima, Lucila Castanheira Nascimento

Bibliographic record

VenueJournal of Nursing Education and Practice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversité du Québec en Outaouais
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsType 2 Diabetes MellitusMedicineType 2 diabetesDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

The use of puppets is an effective strategy for promoting children to express thoughts and feelings about daily experiences . However, very little information is available about its use in children with type 1 diabetes mellitus. The procedures for using puppets during qualitative interviews in children with Type 1 diabetes mellitus were described, which involved three steps : 1) constructing the scenario − a “stage ” that simulates the environments they encounter (school, home) ; 2) making puppets that represent the child and people (parents, teachers, siblings, friends) encountered daily , and 3) promoting expression of thoughts and feelings using puppets during qualitative interviews . The advantages of using puppets were to allow children with type 1 diabetes mellitus to freely express thoughts and feelings about living with diabetes , to provide them with opportunities to demonstrate diabetes management behaviors , and expose factors that may interfere with diabetes management . A limitation to the use of puppets was the interviewer requiring skills to dynamically engage the child and encourage their active participation during the interaction . The use of puppets was recommended as a creative strategy for use in children with type 1 diabetes mellitus during qualitative interviews .

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)0.001
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 score0.816
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.156
GPT teacher head0.435
Teacher spread0.279 · 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

Citations13
Published2013
Admission routes2
Has abstractyes

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