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Record W2884877336 · doi:10.21926/obm.geriatr.1803006

Positive Life Experiences Following a Dementia Diagnosis

2018· article· en· W2884877336 on OpenAlexaboutno aff
Shoshana H. Bardach, Christina Moore, Sarah Holmes, Richard Murphy, Allison Gibson, Gregory A. Jicha

Bibliographic record

VenueOBM Geriatrics · 2018
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaClinical psychologyCognitive impairmentDiseaseCognitionQuarter (Canadian coin)PsychologyMedicineGerontologyPsychiatryPathology

Abstract

fetched live from OpenAlex

Background: Given the stigma and fear associated with Alzheimer’s disease (AD), combined with the progressive nature of the disease, the diagnosis of AD or mild cognitive impairment (MCI) is often very difficult; yet, there may still be ways to experience some positive outcomes following diagnosis. We aim to assess the psychological impact of a diagnosis of MCI or early dementia on positive well-being. Methods: Individuals with a diagnosis of MCI or AD were mailed surveys with the Silver-Lining Questionnaire. Results: Completed surveys were returned from 38 individuals and were analyzed in relation to demographic and cognitive data. All respondents reported at least one positive response to diagnosis, with just over a quarter reporting positive responses to at least half of the items. Positivity was not significantly related to any of the demographic or cognitive variables examined. Conclusions: These results suggest the importance of diagnostic disclosure and the need for additional research to better understand how to maximize the likelihood of a positive responses and support healthy behaviors and future care planning.

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 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 score0.087
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.316
Teacher spread0.298 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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