MétaCan
Menu
Back to cohort
Record W3047264444 · doi:10.1177/1084822320947073

The Effect of Combined Drug Management and an Exercise Program on Symptoms and the Happiness Level in Elderly Women

2020· article· en· W3047264444 on OpenAlexaboutno aff
Seçil Gülhan Güner, Arzu Erden, Nesrın Nural

Bibliographic record

VenueHome Health Care Management & Practice · 2020
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessMedicineSadnessPhysical therapyIntervention (counseling)Test (biology)InsomniaPsychiatryPsychologyAnger

Abstract

fetched live from OpenAlex

The aim of this study was to determine the effect of combined drug management and an exercise program on symptoms and the happiness levels of elderly women people living at home. This interventional study included a total of 35 women, aged 65 to 74 years, who were registered at the Family Healthcare Centre. A 14-week program was combined with exercise and drug management. Pre-test and post-test evaluations results were recorded. The Edmonton Symptom Assessment Scale (ESAS), Oxford Happiness Questionnaire-Short Form (OHQ-SF) and a sociodemographic form and Follow-Up form were used for data collection. The mean ESAS points of the symptoms of pain, tiredness, sadness, and insomnia showed a significant decrease after intervention and the sense of well-being improved ( p < .001). A statistically significant increase was determined in the happiness levels of the participants after intervention. The combined program of drug management and exercise was found to be effective in raising happiness levels and reducing symptoms in elderly women.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.009
GPT teacher head0.318
Teacher spread0.309 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueHome Health Care Management & PracticeSame topicSleep and related disordersFrench-language works237,207