MétaCan
Menu
Back to cohort
Record W7029440677

Investigation of the Activities and Participation of Nursing Home Residents: A Pilot Study

2013· article· en· W7029440677 on OpenAlexaboutno aff

Bibliographic record

VenueDergiPark (Istanbul University) · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsnot available
Fundersnot available
KeywordsBathingActivities of daily livingNursing homesDepression (economics)Reading (process)Independence (probability theory)
DOInot available

Abstract

fetched live from OpenAlex

Purpose: This study was conducted to evaluate the activity levels and independence of the individuals residing at a nursing home and to determine their participation in activities. Material and Methods: Mini Mental State Examination (MMSE), Geriatric Depression Scale, Canadian Occupational Performance Measure (COPM), Functional Independence Measure (FIM) were administered to the residents. Results: The total FIM score was found 119.13±13.73. It has been found that according to COPM the mean activity performance score was 6.48±2.96; satisfaction from performance’s score was 6.08±2.92. 31 people said that the performance areas that they had the most problem were as follows: 23% walking (performance score (ps): 3.89; satisfaction score (ss): 3.80), 19% bathing (pp: 4.17; ss: 4.00), 16% performing prayer (ps: 4.1; ss: 4.6), reading book (ps:5.2; ss: 4.2), 13% reading newspaper (ps: 4.6; ss: 5.75), 9% visiting friends (ps:4; ss: 4.2), chatting (ps: 4.5; ss: 3.8), watching tv (ps: 4.7; ss: 4.7, 6% puzzle-solving (ps: 5.5; ss: 6), gardening (ps:3.5; ss: 3), travelling (ps:6; ss: 4.5, jewellery design(ps:6.5; ss: 6.5), painting (ps:5.5; ss: 7.5). conclusion: In our study, it was found that within self-care activities, bathing was the activity that bothered the nursing home residents the most. Other activities are leisure-time activities. We found the nursing home provided a good level of self-care activities, but leisure-time activities needed to be configured emphasizing an individual-centred approach

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.208
Teacher spread0.155 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueDergiPark (Istanbul University)Same topicLibraries and Information ServicesFrench-language works237,207