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Record W7117302410 · doi:10.1002/alz70858_102891

Changes in Self‐Perceived Competence Following a Virtual Workshop on Cognitive Assessment

2025· article· en· W7117302410 on OpenAlexaffabout
David Cowan, Jennifer Siemon, Anjali Sarkar, Rachel Plagos, Emily Speelziek, Katie Harder, S Gregg

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsCanadian Mental Health AssociationMcMaster UniversityGrand River HospitalHamilton Health SciencesProvidence Health CareCambridge Memorial Hospital
Fundersnot available
KeywordsCognitive Assessment SystemHealth careCognitionCompetence (human resources)Social cognitive theorySocial competenceVariety (cybernetics)Cognitive skill

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive assessment is a necessary part of diagnosing Alzheimer's Disease and related disorders, monitoring disease progression, and measuring treatment effectiveness. Geriatricians and other healthcare providers have observed that cognitive tests are often not administered in a standardized manner, compromising their validity. As well, they are often not administered on the appropriate population or in the appropriate setting. The Cognitive Assessment Tools (CAT) workshop is a half-day, interactive, small group program delivered virtually by trained and experienced healthcare providers. The CAT workshop equips participants with knowledge on the appropriate usage, interpretation, and standardized administration and scoring of cognitive assessment tools, including the Standardized Mini-Mental Status Exam (sMMSE), Montreal Cognitive Assessment (MoCA®), Trail Making Test (TMT), Clock Drawing Test (CDT), and Geriatric Depression Scale (GDS). This workshop was previously offered in person, in both small- and large-group formats. The present study aims to evaluate outcomes of this novel workshop delivered in a virtual format. METHOD: Workshop participants completed pre- post-workshop surveys. Participants utilized a scale from 1 (no proficiency) to 7 (mastery) to report their self-perceived competency. RESULT: 53 participants from 9 workshops completed pre- and post- workshop evaluations (57% response rate). Participants' professions included: nursing (56%), social work (9%), occupational therapy (6%), therapeutic recreation (6%), medicine (4%), physiotherapy (4%), personal support worker (4%), and other (11%). Results of paired t-tests indicated a significant difference between before and after scores for all cognitive assessments. Pre-post mean differences for each cognitive test: sMMSE=1.81; MoCA®=1.70; TMT=2.47; CDT=1.75; GDS=2.11, all p <0.001. There was a significant difference in participants' understanding of why cognitive assessments are used (pre-post mean difference = 1.15), and their knowledge of selecting the appropriate tool to use (pre-post mean difference = 2.21), both p <0.001. Ninety-four percent of participants would recommend the workshop to a colleague. CONCLUSION: The CAT workshop is associated with significant increases in healthcare workers' self-reported competency in selecting, administering, scoring and interpreting common cognitive assessment tools. The workshop attracts a variety of healthcare and social care professionals, and is well-received by learners.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.355
Teacher spread0.326 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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