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Record W2394243436

Effect of 3R Therapy on Quality of Life and Subjective Well-being in Older Patients with Mild Cognitive Impairment in Ningbo Communities

2014· article· en· W2394243436 on OpenAlexaboutno aff
Zhang Jianyin

Bibliographic record

VenueZhongguo kangfu lilun yu shijian · 2014
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsQuality of life (healthcare)Montreal Cognitive AssessmentCognitionIntervention (counseling)Cognitive impairmentPsychologyGerontologyMedicinePhysical therapyClinical psychologyPsychiatryPsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

Objective To observe the effect of 3R therapy on quality of life and subjective well-being in older patients with mild cognitive impairment(MCI). Methods 158 patients with MCI were collected from 8 communities in Ningbo city with Diagnostic and Statistical Manual of Mental Disorders(DSM)-IV as the diagnostic criteria, and assessed by Montreal Cognitive Assessment(MoCA). The experimental group(n=79) was intervened by 3R(Reminiscence, Reality Orientation, Remotivation) for 12 weeks, and the control group(n=79) received no intervention. Their quality of life was assessed with WHO Quality of Life-BREF(WHOQOL-BREF) and the subjective well-being was assessed with Philadelphia Geriatric Center Morale Scale(PGC). Results Their quality of life and subjective well-being improved after intervention in the experimental group(P0.05), and were better in the experimental group than in the control group(P0.05). Conclusion 3R therapy could effectively improve the quality of life and subjective well-being in patients with MCI.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.307
Teacher spread0.295 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueZhongguo kangfu lilun yu shijianSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207