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Record W4404868511 · doi:10.4103/jehp.jehp_1427_23

Alexithymia and attachment on mental health of people with multiple sclerosis: The mediating role of perceived social support and loneliness

2024· article· en· W4404868511 on OpenAlexaboutno aff
Farnaz Doostdari, Amir Sam Kianimoghadam, Mahyar Arzpeyma, Saina Fatollahzadeh, Nassim Zakibakhsh Mohammadi, Abbas Masjedi‐Arani, Reza Hajmanouchehri

Bibliographic record

VenueJournal of Education and Health Promotion · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersShahid Beheshti University of Medical Sciences
KeywordsLonelinessAlexithymiaStructural equation modelingToronto Alexithymia ScaleMental healthPsychologySocial supportClinical psychologyAffect (linguistics)UCLA Loneliness ScaleAttachment theoryPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Multiple sclerosis and its progressive relapsing-remitting nature for MS patients is challenging and significantly affects the mental health of people with MS. We examined the direct effects of alexithymia and attachment on mental health and the indirect effect of attachment, alexithymia, loneliness, and perceived social support on the mental health of people with MS. MATERIALS AND METHODS: Three hundred and forty-five diagnosed with multiple sclerosis (MS) were deemed eligible for inclusion in the study and selected through the Iranian MS Association. Measures included the Toronto Alexithymia Scale (TAS20), Attachment Style Questionnaire (ASQ), General Health Questionnaire (GHQ28), Social and Emotional Loneliness Scale for Adults (SELSA-S), and Perceived Social Support from Family and Friends Questionnaire (PSS-FA and PSS-F). The mental health of MS patients was analyzed using structural equation models (SEM), examining how alexithymia, attachment, social support, and loneliness, directly and indirectly, affect their mental health. The fit of the model to the data was analyzed using the discrepancy function divided by degrees of freedom (CMIN/DF), Normed Fit Index (NFI), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). RESULTS: = 0.28) of the mental health changes are explained via study predictors. Alexithymia and attachment directly affect mental health. Attachment style indirectly affects social support and loneliness, while loneliness and family support indirectly affect the mental health of MS patients. CONCLUSION: The study findings provide valuable insights into the fundamental structures that influence the mental health of individuals with MS. Loneliness and social support are critical mediating factors that significantly impact the mental well-being of these patients. In the times ahead, healthcare professionals must prioritize attachment, alexithymia, social support, and loneliness in their medical and psychological interventions for individuals diagnosed with multiple sclerosis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.411
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2024
Admission routes1
Has abstractyes

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