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Efficacy of Therapeutic Listening� Quickshifts in Children with Sensory Processing Difficulties

2017· dissertation· en· W2585423140 on OpenAlexaboutno aff
Shannon Preto, Ann Malloy

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningSensory processingPsychologyIntervention (counseling)Occupational therapyTest (biology)ArousalSocial skillsDevelopmental psychologyClinical psychologyMotor skillActivities of daily livingAudiologySensory systemMedicineCognitive psychologyPsychotherapistPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Few empirical studies provide evidence for the effectiveness of Therapeutic Listening - Quickshifts (TL-Q). However, anecdotally, therapists and clients report TL-Q produces consistent positive results as an intervention for children with learning and developmental problems. In this study, the researchers examined the effectiveness of TL-Q intervention for five children with sensory processing difficulties to improve participation and function in (1) self-regulation and arousal, (2) activities of daily living (ADLs), (3) social/emotional skills, and (4) sensorimotor skills. Over the course of an 8-week prospective study, the researchers conducted a pre-test, post-test, prospective case study. During the intervention period, occupational therapist with TL-Q expertise chose the specific musical track depending on the needs of each child. Outcome measures included: Canadian Occupational Performance Measure, Sensory Processing Measure, Clinical Observations of Motor Performance, Beery-Buktenica Test of Visual Motor Integration and parent journals. Results showed an overall positive increase in quantitative scores and through qualitative reports. Most notably, in the areas of social interaction and sensorimotor skills. This study provided evidence for the support of TL-Q in the clinical setting and developed an effective protocol for future research.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.299
Teacher spread0.283 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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