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Record W2072707007 · doi:10.3126/jiom.v35i1.8896

Prevalence and Associated Factors of Depression among Elderly Population Living in Geriatric Homes in Kathmandu Valley

2013· article· en· W2072707007 on OpenAlexaboutno aff
PS Choulagai, CK Sharma, BP Choulagai

Bibliographic record

VenueJournal of Institute of Medicine Nepal · 2013
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDepression (economics)Geriatric Depression ScaleQuarter (Canadian coin)GerontologyPovertyActivities of daily livingPopulationMental healthGeriatricsPsychiatryEnvironmental healthDepressive symptomsAnxiety

Abstract

fetched live from OpenAlex

Introduction: Depression generally presents in all age group but is more common among elderly population living in geriatric homes. Despite the growth of geriatric home health services, little is known about the mental health needs of geriatric people seen in their homes. Methods: This study is conducted in July – December 2010 to determine the prevalence and associated factors of depression among elderly population living in geriatric homes in Kathmandu Valley. A total of 78 elderly people were included in this study. Semi-structured questionnaires and in-depth interview guidelines were used to further exploring the associated factors of depression. The study participants were identified by using Geriatric Depression Scale. Results: The prevalence of depression was 51.3% with severe depression 15.4% and mild depression 35.9%. Most of the severely depressed respondents (75%) were widow/widower; most of the mild depressed respondents (85.7%) were illiterate; three quarter (75%) of severely depressed respondents had no children; and almost all of severely depressed respondents (90.9%) had difficulty in daily living activities due to health problems Conclusion: Majority of respondents were found to be living with varying level of depression. Poverty, presence of physical illness and lacking social and family support contributes to depression. Majority of depressed respondents mentioned their satisfaction with the living in geriatric home. DOI: http://dx.doi.org/10.2126/joim.v35i1.8896 Journal of Institute of Medicine, April, 2013; 35:39-44

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.017
GPT teacher head0.309
Teacher spread0.292 · 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 designObservational
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
Published2013
Admission routes1
Has abstractyes

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