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Record W2921171563 · doi:10.5539/ijps.v11n2p9

The Level of Optimism and Pessimism and its Relationship to the Quality of Life in Patients with Renal Failure in the Government and Private Hospitals in Irbid

2019· article· en· W2921171563 on OpenAlexvenueno aff
Fatima N. Al Jarrah, Falastine R. Hamdan, Munther R. Hamdan, Alaa Fraihat, Abed Alnaser A. Alazzam

Bibliographic record

VenueInternational Journal of Psychological Studies · 2019
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsOptimismPessimismQuality of life (healthcare)PsychologyScale (ratio)PopulationDemographyClinical psychologySocial psychologySociology

Abstract

fetched live from OpenAlex

The aim of this study was to detect the level of optimism and pessimism and its relation to the quality of life in patients with renal failure in the government and private hospitals in Irbid in light of the variables: gender, age, duration of disease and educational level of patients, the sample of the study consisted of (93) patients with kidney failure, who were randomly selected from the study population. The researchers used optimism and pessimism scale and the quality of life scales, their validity and reliability were verified. Results of the study showed that the means for optimism scale ranged between (3.602-3.075) with a medium degree, and the means for pessimism scale ranged between (4.086-3.118) with a high and medium degree, while the means for quality of life scale ranged between (4.054-2.957) with a high and medium degree. Results also showed the existence of a correlation between the level of optimism and the level of quality of life and this relationship is a moderate relationship, and a lack of correlation between level of optimism and level of pessimism and level of pessimism and quality of life. There are no statistically significant differences at the level of significance (0.05) in the patients' responses on the optimism, pessimism scales according to (gender, family income, medical insurance and origin).

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)0.002
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 score0.009
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.090
GPT teacher head0.389
Teacher spread0.299 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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