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Record W4220763106 · doi:10.1177/01655515221081353

A web-based information intervention for family caregivers of patients with Dementia: A randomized controlled trial

2022· article· en· W4220763106 on OpenAlexaff
Simin Salehinejad, Nazanin Jannati, Mohammad Azami, Moghaddameh Mirzaee, Kambiz Bahaadinbeigy

Bibliographic record

VenueJournal of Information Science · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDementiaIntervention (counseling)Family caregiversMedicineRandomized controlled trialPsychological interventionPopulationGerontologyFamily medicinePhysical therapyNursing

Abstract

fetched live from OpenAlex

This study aimed to evaluate the efficacy of a web-based health information intervention on knowledge, care burden and attitudes of family caregivers of patients with dementia. This study is a unblinded randomised controlled trial. The study population consisted of family caregivers of patients with dementia ( n = 50) which were randomly allocated to the intervention group (access to the web-based health information) or control group (access to information as usual). The participants completed knowledge, care burden and attitude questionnaire at baseline and at two months follow-up. A total of 50 caregivers participated in this study. Before the intervention, there was no statistically significant difference between the knowledge, care burden and attitude score between the two groups. In comparison to the control group after the intervention, participants in the intervention group showed significant improvements in all outcomes. These findings provide further evidence that web-based information interventions helped caregivers feel more confident, empathetic and concerned about dementia care with less care burden.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.288
Teacher spread0.279 · 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 designRandomized 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

Citations7
Published2022
Admission routes1
Has abstractyes

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