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Record W1988135382 · doi:10.1177/1471301212474143

Development and evaluation of a telehealth videoconferenced support group for rural spouses of individuals diagnosed with atypical early-onset dementias

2013· article· en· W1988135382 on OpenAlexaff
Megan E. O’Connell, Margaret Crossley, Allison Cammer, Debra Morgan, Wendy Allingham, Betty Cheavins, Donna Dalziel, Maurice Lemire, Sheri Mitchell, Ernie Morgan

Bibliographic record

VenueDementia · 2013
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTelehealthIntervention (counseling)DementiaPsychological interventionMedicineDiseasePsychologyGerontologyPsychiatryTelemedicineHealth care

Abstract

fetched live from OpenAlex

Atypical and early-onset dementias can be particularly problematic for family caregivers, and support groups aimed at memory loss and Alzheimer's disease are not always helpful. Unfortunately, little has been developed specifically for caregivers of individuals with atypical dementias such as the frontotemporal dementias. Compounding the lack of access to interventions targeted specifically at caregivers of individuals with atypical and early-onset dementias are the unique needs of rural caregivers. Due to the relative infrequency of these particular dementias and the large geographical distances between rural caregivers, technology-facilitation is required for any group-based intervention. This paper describes the development of a secure telehealth videoconferenced support group for rural spouses of individuals with atypical and early-onset dementias. In addition, we provide preliminary evidence of effectiveness and describe a template for future groups based on the key therapeutic aspects of this novel technology-facilitated intervention.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.042
GPT teacher head0.340
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations102
Published2013
Admission routes1
Has abstractyes

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