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Record W2467301317 · doi:10.5539/ass.v12n8p192

Relationship between Social Support, Time Perspective and Suicide Ideations in Patients with Multiple Sclerosis

2016· article· en· W2467301317 on OpenAlexvenueno aff
Saeed Ariapooran, Masuod Rajabi, Amirhosein Goodarzi

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsnot available
Fundersnot available
KeywordsCorrelationNegative correlationPsychologyPositive correlationSocial supportClinical psychologyMultiple sclerosisInternal medicineMedicinePsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

<p><strong>Introduction:</strong> Patients with Multiple Sclerosis (MS) are at risk for Suicide Ideation (SI). The relationship between Social Support (SS) and Time Perspective (TP) with SI is important among patients with MS. This study was performed to determine the prevalence of SI and the correlation between SS and TP with SI in Iranian patients with MS in Nahavand and Malayer.</p><p><strong>Methods:</strong> Using a cross-sectional analytic research design, we selected 79 participants among patients with MS in Nahavand and Malayer, Iran. Beck Scale for Suicidal Ideation, Multidimensional Scale of Perceived Social Support and Zimbardo’s Time Perspective Inventory were used for collecting the data.</p><p><strong>Results:</strong> The obtained results indicated that 30.3% of the patients with MS suffered from SI. There was a negative correlation between SS (from family, friends and significant other), Past Positive (PP) and Future (F) orientations and a positive correlation between Past Negative (PN) orientation and SI; SS from significant other and PP negatively predicted the SI in patients with MS.</p><p><strong>Conclusion: </strong>Based on the obtained results, the relationship between SS, PN, PP, F and SI and the role of SS from significant other and PP in predicting the SI in Nahavand and Malayer patients with MS were confirmed. Thus, it is necessary to develop support systems and apply the TP-based treatments for patients with MS who are at risk for SI.</p>

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.092
GPT teacher head0.374
Teacher spread0.282 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

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