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Record W2997915772 · doi:10.1080/24750573.2019.1699738

Use of multisensory stimulation interventions in the treatment of major neurocognitive disorders

2019· article· en· W2997915772 on OpenAlexaff
Catherine Cheng, Glen B. Baker, Serdar Dursun

Bibliographic record

VenuePsychiatry and Clinical Psychopharmacology · 2019
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychological interventionNeurocognitiveDementiaQuality of life (healthcare)DistressMoodBrain stimulationCognitionMedicinePsychologyClinical psychologyPsychiatryDiseasePsychotherapistPhysical medicine and rehabilitationNeuroscienceStimulationPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: Behavioral and psychological symptoms of dementia (BPSD) are a heterogeneous constellation of non-cognitive symptoms and behaviours that can cause significant patient distress and present complex management challenges. Behavioural and pharmacological treatments are used to decrease the symptoms, preserve function and increase quality of life. In the treatment of individuals with a major neurocognitive disorder, non-pharmacological interventions are often preferred as first-line treatment over pharmacological interventions, which often have modest efficacy, notable side effects and significant risks. Multisensory stimulation (MSS) interventions have become increasingly popular in the treatment of BPSD, particularly with disease progression. The objective of this review paper is to provide a brief overview of the types of MSS interventions currently used in the treatment of major neurocognitive disorders. METHODS: Searches for papers published in this area were conducted using PubMed and the Web of Science Core Collection. The searches were done for the period covering the past 20 years, and key phrases used were “multisensory stimulation for treatment of BPSD,” “multisensory stimulation for treatment of major cognitive disorders,” “multisensory stimulation for treatment of dementia” and “multisensory stimulation for treatment of neurodegenerative disorders.” RESULTS: Multisensory environments, multisensory tools and multisensory group therapies are discussed. There is growing support for the use of MSS interventions to improve mood, behaviour and quality of life in seniors with dementia and BPSD. However, currently the utilization of these interventions is highly variable and strong evidence for their use is limited. CONCLUSION: MSS interventions in the form of multisensory environments, tools and group therapies present tremendous potential as first-line treatments or as adjuncts to pharmacological interventions in the treatment of major neurocognitive disorders. However, the body of quality evidence that currently exists is limited. A lack of evidence does not necessarily mean a lack of efficacy, and there is a pressing need for studies with improved power and study design to determine the effectiveness of specific MSS interventions and to ascertain for whom they may be most beneficial.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.227
GPT teacher head0.428
Teacher spread0.202 · 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

Citations24
Published2019
Admission routes1
Has abstractyes

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