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Record W2414250014 · doi:10.1017/s0317167100054147

An International Needs Assessment of Caregivers for Frontotemporal Dementia

2011· article· en· W2414250014 on OpenAlexafffundvenue
Tiffany W. Chow, Fabricio J. Pio, Kenneth Rockwood

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2011
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsBaycrest HospitalUniversity of TorontoDalhousie University
FundersAlzheimer Society
KeywordsFrontotemporal dementiaDementiaAffect (linguistics)PsychologyFamily caregiversClinical psychologyPsychiatryMedicineGerontologyDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: To guide development of public awareness and caregiver support resources for frontotemporal dementia (FTD) syndromes. METHODS: We used an online survey to explore their needs. The survey was self-administered by self-identified, English-speaking caregivers for patients with FTD in several countries. RESULTS: Of 79 caregiver respondents, approximately half were caring for patients with behavioural variant FTD or semantic dementia. The most common initial symptoms were Changes in Thinking and Judgment. Half of the respondents identified "failure to recognize the early stage of illness as a dementia" as the most troublesome aspect. Accordingly, over 40% of respondents had difficulty obtaining an accurate diagnosis for the patient. Caregivers prioritized family counseling and the public educational message that dementia can affect young people. CONCLUSION: The largest international survey of FTD caregivers to-date showed that support is needed for all family members adapting to the shock of early-onset dementia, and this may be most readily provided online.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.064
GPT teacher head0.346
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), 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

Citations56
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207