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Record W3091404314 · doi:10.1017/s071498082000029x

Intervention Fidelity of a Volunteer-Led Montessori-Based Intervention in a Canadian Long-Term Care Home

2020· article· en· W3091404314 on OpenAlexaffabout
Paulette V. Hunter, Amanda Rissling, Leticia Pickard, Lilian Thorpe, Thomas Hadjistavropoulos

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2020
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of ReginaUniversity of Saskatchewan
Fundersnot available
KeywordsFidelityIntervention (counseling)Psychological interventionVolunteerDementiaNursingPsychologyMedicinePerceptionGerontologyFamily medicine

Abstract

fetched live from OpenAlex

Montessori-based interventions (MBIs) were developed to promote guided participation in meaningful activities by people with dementia patients. In this study, we assessed nursing home volunteers' fidelity to an MBI, relying primarily on a qualitative descriptive design. We completed a deductive content analysis of eight volunteer interviews using the Conceptual Framework for Intervention Fidelity. We also calculated average volunteer and resident scores on the Visiting Quality Questionnaire (VQQ), which assesses volunteers' and residents' perceptions of visits. We found good evidence that volunteers attended scheduled visits, made use of pre-designed activities, and attended to training recommendations. Most reported enjoying the visits (VQQ $ \overline{x} $ = 6.12, standard deviation [SD] = 0.75) and receiving a positive response from residents (VQQ $ \overline{x} $ = 5.46, SD = 0.88). Nevertheless, use of pre-designed activities and response to the MBI was lower for volunteers working with residents who had late-stage dementia. Therefore, overall, fidelity depended on the cognitive status of the resident.

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)0.022
metaresearch head score (Gemma)0.037
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.602

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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

Citations4
Published2020
Admission routes2
Has abstractyes

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Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicFamily and Disability Support ResearchFrench-language works237,207