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Record W1965501749 · doi:10.1177/1078390306291514

Effects of Music in Reducing Disruptive Behavior in a General Hospital

2006· article· en· W1965501749 on OpenAlexaff
Edward Helmes, Donna C. Wiancko

Bibliographic record

VenueJournal of the American Psychiatric Nurses Association · 2006
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsRandomized controlled trialPsychological interventionMedicineAudiologyIntervention (counseling)Noise (video)PsychologyPhysical therapyPsychiatrySurgery

Abstract

fetched live from OpenAlex

There are few controlled studies in acute care of the effectiveness of distracting music in reducing the frequency of noise produced by dementing individuals. OBJECTIVE: The authors tested whether a randomized intervention of playing baroque music for 30-min periods would reduce the frequency of repetitive shouting and banging in elderly patients in a teaching hospital. STUDY DESIGN: Single case studies with 9 participants (7 females, 2 males), with a mean age of 82.7 years (SD = 7.44). Observations were made at different times of day for a minimum of four sessions. RESULTS: Trials with distracting music in seven cases had a reduced frequency of disruptive noises of from 89% to 63% from peak levels in control trials. In 2 participants with an extremely high frequency of incidents, the frequency of outbursts of noise was reduced by up to 31% on trials with music compared to control trials. CONCLUSIONS: The use of music to reduce disruptive noise in an acute care setting appears to be as effective as other such interventions have been in residential care facilities.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.003
GPT teacher head0.260
Teacher spread0.257 · 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 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

Citations14
Published2006
Admission routes1
Has abstractyes

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Same venueJournal of the American Psychiatric Nurses AssociationSame topicIntensive Care Unit Cognitive DisordersFrench-language works237,207