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Record W2801395807 · doi:10.7939/r3ht2gj6d

Playfulness in children with severe cerebral palsy when using a robot

2014· article· en· W2801395807 on OpenAlexaboutno aff
Rios Rincon

Bibliographic record

VenueUniversity of Alberta Library · 2014
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCerebral palsyPhysical medicine and rehabilitationPsychologyMedicine

Abstract

fetched live from OpenAlex

Free play is not only one of the most important means through which children develop and know their world, but also it is the way in which they show their physical, cognitive, social and creative abilities. Children with severe physical disabilities have motor control problems that affect gross and fine motor skills, and in turn, manipulation. Without manipulation, children’s play is less effective for exploring. Thus, it is much more difficult for these children to learn and to develop because they cannot interact easily with the environment. Generally, they are observers of other’s play rather than active participants in play. Consequently, the children’s development is delayed. This study investigated the effect of a robot-based intervention on 1) child’s playfulness; 2) mother’s directiveness, responsiveness, and affect/animation; and 3) child’s play performance and satisfaction with their play. The family’s satisfaction with the robotic intervention was determined. The study’s protocol was tested in a pilot study with a child with cerebral palsy and her mother followed by a partially non-concurrent multiple baseline design with four children with cerebral palsy and their mothers. All children were level IV or V in both the Gross Motor Classification System and the Manual Ability Classification System. The intervention was the availability of a Lego robot during free play at home. Playfulness was measured through the Test of Playfulness version 4, play performance was measured through the Canadian Occupational Performance Measure, and the maternal interactive behavior Maternal Behavior Rating Scale revised. The total length of the study was different for each mother-child dyad with the majority participating about 14 weeks with two sessions per week. Each session was 15 minutes long. The study had three phases; a baseline (5-8 sessions), an intervention (10 sessions) and a one month follow-up (three sessions). During the entire study children played with their mothers at home with their own toys. During the baseline and the follow-up phases the child and mother played without the robot. The robot was available to the mother and child in the free play sessions only during the intervention phase. Children were trained in the use of the switches in order to make the robot move and carry objects according to a protocol before starting the intervention phase. According to the standards for assessing the levels of evidence for single case design, the main findings of this study provided strong evidence that the robotic-based intervention increased playfulness in children with severe motor impairment due to cerebral palsy; moderate evidence that it decreased mother’s directiveness; and no evidence that it increased mothers’ responsiveness during the intervention. The robotic intervention improved the mothers’ perception about their children’s play performance and increased their satisfaction with their children’s play performance. Future research may be oriented towards improving the level of evidence provided by the present study; exploring the impact of robots in other aspects of the play experience of children with CP such as pretend play and play with peers; and comparing traditional interventions for improving mother-child interaction with robotic interventions.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.183
Teacher spread0.175 · 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 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

Citations9
Published2014
Admission routes1
Has abstractyes

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