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Record W1900400570 · doi:10.1111/nhs.12222

Puppets as a strategy for communication with <scp>B</scp>razilian children with cancer

2015· article· en· W1900400570 on OpenAlexaff
Amanda Mota Pacciulio Sposito, Francine de Montigny, Valéria de Cássia Sparapani, Regina Aparecida Garcia de Lima, Fernanda Machado Silva‐Rodrigues, Luzia Iara Pfeifer, Lucila Castanheira Nascimento

Bibliographic record

VenueNursing and Health Sciences · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversité du Québec en Outaouais
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsIntervention (counseling)AutonomyPsychologyCognitionPediatric oncologyMedicineCancerMedical educationNursingPsychiatry

Abstract

fetched live from OpenAlex

Children are considered competent social actors. Although they are able to express their opinions, they may have some difficulties in answering direct verbal questions, requiring researchers and health professionals to enter their world by using auxiliary resources for communication. This study presents the experience of using finger puppets as a playful strategy for improving interaction and communication with hospitalized children with cancer, aged seven to 12. It describes the strategy of making and using puppets as an auxiliary tool to communicate with children with cancer and presents the results and limitations of using puppets in clinical practice. The use of the puppets, creatively and in accordance with the children's motor, cognitive, and emotional development, showed benefits, such as allowing the children to freely express themselves; respecting their autonomy; and minimizing the hierarchical adult-child relationship. The use of puppets is an appropriate strategy to communicate with hospitalized children. This tool can also enrich clinical practice, as it encourages children with cancer to report their experience of being ill and also helps the health team during evaluation and intervention.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.146
GPT teacher head0.450
Teacher spread0.305 · 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

Citations53
Published2015
Admission routes1
Has abstractyes

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