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Record W1895723749

공식적․비공식적 사회적 지지가 농촌노인의 심리적 복지감에 미치는 영향

2013· article· ko· W1895723749 on OpenAlexaboutno aff
이정임

Bibliographic record

Venue한국가정관리학회 학술발표대회 자료집 · 2013
Typearticle
Languageko
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsnot available
Fundersnot available
KeywordsSocial supportPsychologyFamily supportSupporterQuarter (Canadian coin)PopulationRural areaGerontologySocial psychologyDemographySociologyMedicineGeography
DOInot available

Abstract

fetched live from OpenAlex

This research tried to provide basic data to the social support strengthening plan for it investigated whether the social support reached any effect on the psychological well-being of the rural elderly, or not increasing the psychological well-being of the rural elderly. For this purpose, this research classified the social support level which the rural elderly is late into the family support, relative support, and public support according to the social supporter and looked into. And it classified the rural elderly psychological well-being level into the positive well-being and negative well-being and looked into the first. Second, the difference of the social support according to the population sociology characteristic and psychological well-being were looked into. Third, in the preceding research, after controlling the age, confirmed as the factor having an effect on the social support of the rural elderly and psychological well-being monthly income, and health condition, the relatively influence that family support, relative support, and public support reaches to the psychological well-being of the rural elderly was looked into. In this research, the survey was performed for 170 old peoples more than the lives in Kyongsangbuk-do Chungdo-gun quarter age of 65. The investigation which supplemented and which it looks at from September 10th in 2011 until September 24th was performed. The total 190 part of questionnaires was distributed and 170 parts except was insincere or is not completed 20 parts of answer were used for the final analysis. Summarizing the result, it is obtained from this research, it is like the next. First, the level of the social support shows in this order-family support, relatives support, public supports. Namely, the rural elderly recognize the families support highest, on the other hand, recognjze the public support lowest. The social support of the rural elderly shows negative well-being higher than positive well-being. It shows that two dimension have negative relationship. Second, the result of analyze the difference of the social support according to the population sociology characteristic of the rural elderly and psychological well-being are as follows. First, as the age was low if we looked at the social support, the rural elderly recognized the whole social support and family support and relative support. And high the family support was high recognized as the monthly income was high. The more the age was high if we looked at the psychological well-being, the negative well-being of the psychological well-being was exposed to be high recognized as the health condition was bad. Third, in case the more the result of looking into the effect that the social support of the rural elderly reaches to the psychological well-being and health condition were similar, the rural elderly psychological well-being level t was high, the positive well-being of the psychological well-being which the rural elderly realizes as the official support was high showed high. In addition, the more the rural elderly psychological well-being level was low in case the monthly income was similar, the negative well-being of the psychological well-being which the rural elderly recognizes as the official support was low was shown up to be high. The theoretical, political, and practical undertone was presented based upon this kind of research result.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0500.131

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 head0.080
GPT teacher head0.481
Teacher spread0.402 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

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