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Record W4324309793 · doi:10.1080/07370016.2022.2133566

Effect of Home-Based Self-Management Intervention for Community-Dwelling Patients with Early Parkinson’s Disease: A Feasibility Study

2023· article· en· W4324309793 on OpenAlexaff
Hui Young So, Sung Reul Kim, Sunho Kim, Yu Sun Park, Sungyang Jo, Kye Won Park, Nari Choi, Seung Hyun Lee, Yun Su Hwang, Mi Sun Kim, Sun Ju Chung

Bibliographic record

VenueJournal of Community Health Nursing · 2023
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of British Columbia
FundersNational Research Foundation of Korea
KeywordsIntervention (counseling)MedicinePhysical therapySelf-managementRandomized controlled trialMotor symptomsPhysical medicine and rehabilitationDiseaseParkinson's diseaseNursingSurgery

Abstract

fetched live from OpenAlex

PURPOSE: This study aimed to evaluate the effect of a home-based self-management intervention in community-dwelling patients with early Parkinson's diseases (PD). DESIGN: A randomized-controlled design. METHODS: Thirty-two patients participated (15=intervention, 17=control), and the intervention group received 16 weeks of the intervention. FINDINGS: Physical activity and non-motor symptoms improved more in the intervention group than in the control group. CONCLUSION: Home-based self-management intervention was effective in improving physical activity and non-motor symptoms for them. CLINICAL EVIDENCE: Home-based intervention - comprising education, telephone counseling, smartphone-based message and information, and smart wearable devices - was feasible for patients with early PD.

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)0.003
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: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.034
GPT teacher head0.369
Teacher spread0.335 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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