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Record W2412886620 · doi:10.1177/1533317516650806

Ecopsychosocial Interventions in Cognitive Decline and Dementia

2016· article· en· W2412886620 on OpenAlexaff
John Zeisel, ‌Barry Reisberg, Peter J. Whitehouse, Bob Woods, Ad Verheul

Bibliographic record

VenueAmerican Journal of Alzheimer s Disease & Other Dementias® · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersNational Institute on AgingNational Institutes of HealthFisher Center for Alzheimer's Research FoundationU.S. Department of Health and Human Services
KeywordsDementiaCognitive declinePsychological interventionPsychologyCognitionGerontologyMedicinePsychiatryDisease

Abstract

fetched live from OpenAlex

Dementia is a major medical and social scourge. Neither pharmacological nor nonpharmacological interventions and treatments have received sufficient funding to be meaningful in combatting this tsunami. Because the term-"nonpharmacological"-refers to what these interventions are not, rather than what they are, nonpharmacological treatments face a special set of challenges to be recognized, accepted, funded, and implemented. In some ways, the current situation is analogous to using the term "nonhate" to mean "love." This article presents a carefully reasoned argument for using the terminology "ecopsychosocial" to describe the full range of approaches and interventions that fall into this category. These include interventions such as educational efforts with care partners, social support programs for individuals with various levels of dementia, efforts to improve community awareness of dementia, an intergenerational school where persons with dementia teach young children, and the design of residential and community settings that improve functioning and can reduce behavioral symptoms of dementia. The proposed terminology relates to the nature of the interventions themselves, rather than their outcomes, and reflects the broadest range of interventions possible under the present rubric-nonpharmacological. The goal of this new label is to be better able to compare interventions and their outcomes and to be able to see the connections between data sets presently not seen as fitting together, thereby encouraging greater focus on developing new ecopsychosocial interventions and approaches that can improve the lives of those with dementia, their care partners, and the broader society.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.453
Teacher spread0.386 · 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

Citations51
Published2016
Admission routes1
Has abstractyes

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