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Record W7002265097

Modelo de Stresse para a Esclerose Múltipla: explorando o contributo preditivo da dor neuropática, fusão cognitiva, alexitimia, supressão do pensamento e mindfulness

2021· dissertation· pt· W7002265097 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2021
Typedissertation
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessAnxietyAlexithymiaCognitionVerbal fluency test
DOInot available

Abstract

fetched live from OpenAlex

Introdução: A Esclerose Múltipla (EM) é a doença desmielinizante mundialmente mais prevalente, tende a ser incapacitante e a ter início em idades jovens, representando-se, por tal, como um problema de saúde pública. O stresse pode contribuir para o seu agravamento. Contudo, é reduzido o conhecimento científico sobre os preditores de stresse nos doentes com EM. Objetivos: Explorar um novo modelo preditivo de sintomas psicopatológicos de stresse em doentes com EM, composto pelos seguintes potenciais preditores: dor neuropática (sintoma característico da EM) e processos psicológicos relacionados com a regulação emocional e a (in)flexibilidade psicológica, nomeadamente, fusão cognitiva, alexitimia relacionada com dificuldades em identificar e descrever sentimentos, supressão do pensamento (estratégias especificas de evitamento experiencial) e mindfulness (estratégia de aceitação experiencial). Método: Este estudo transversal incluiu 107 doentes com EM e 97 indivíduos da população geral, ambos sem outras doenças neurológicas. O protocolo de avaliação incluiu os seguintes instrumentos de autorresposta: Questionário Sociodemográfico e Clínico para Doentes com EM, escala visual analógica do Pain Detect Questionnaire; subescala de stresse da Depression, Anxiety and Stress Scale, subescala dificuldade em identificar sentimentos do Toronto Alexithymia Scale, Cognitive Fusion Questionnaire, White Bear Suppression Inventory e a subescala mindfulness da Self-Compassion Scale. Resultados: Todos os potenciais preditores apresentaram diferenças entre os grupos clínico com EM e da população geral sem EM, exceto o mindfulness que exibiu uma diferença próxima da significância estatística. Estas variáveis correlacionaram-se com os sintomas de stresse nos doentes com EM e, incluídas em modelos de regressão linear simples, predisseram significativamente esses sintomas. Assim, integraram o modelo de regressão linear múltipla, que explicou 41.5% da variância dos sintomas de stresse e apresentou como preditores significativos a faceta da alexitimia relacionada com a dificuldade em identificar sentimentos e o mindfulness, respetivamente, com valores beta positivo e negativo. Discussão: Os resultados sugerem que a dificuldade em identificar sentimentos (alexitimia) e o mindfulness são, respetivamente, fatores de risco e protetor do stresse em doentes com EM. Assim, intervenções psicológicas destinada a desenvolver competências de aceitação experiencial e de mindfulness parecem adequadas para prevenir e/ou reduzir o stresse nos referidos doentes, para melhorar a sua saúde mental e, possivelmente, para diminuir o efeito do stresse no agravamento da EM. / Introduction: Multiple Sclerosis (MS), the most prevalent demyelinating disease worldwide, tends to be disabling and start at young ages, representing, therefore, a public health problem. Stress can contribute to its aggravation. However, scientific knowledge about stress predictors in MS patients is limited. Objectives: Explore a new predictive model of psychopathological symptoms of stress in patients with MS, comprising the following potential predictors: neuropathic pain (a typical symptom of MS) and psychological processes associated with emotional regulation and psychological (in)flexibility, namely, cognitive fusion, alexithymia related to difficulties in identifying and describing feelings, thought suppression (specific experiential avoidance strategies) and mindfulness (experiential acceptance strategy). Method: This cross-sectional study included 107 patients with MS and 97 individuals from the general population, both without other neurological diseases. The assessment protocol included the following self-response instruments: Sociodemographic and Clinical Questionnaire for Patients with MS, visual analogue scale from the Pain Detect Questionnaire; stress subscale from Depression, Anxiety and Stress Scale, difficulty in identifying feelings subscale from the Toronto Alexithymia Scale, Cognitive Fusion Questionnaire, White Bear Suppression Inventory and the mindfulness subscale from the Self-Compassion Scale. Results: All potential predictors have shown differences between the clinical groups with MS and the general population without MS, except for mindfulness, which exhibited a difference close to statistical significance. These variables correlated with the symptoms of stress in MS patients and, included in simple linear regression models, significantly predicted these symptoms. Thus, they integrated the multiple linear regression model, which explained 41.5% of the variance of stress symptoms and presented as significant predictors the side of alexithymia related to the difficulty in identifying feelings and mindfulness, with positive and negative beta values, respectively. Discussion: The results suggest that the difficulty in identifying feelings (alexithymia) and mindfulness are, respectively, risk and protective factors for stress in patients with MS. Thus, psychological interventions aimed at developing experiential acceptance and mindfulness skills seem adequate to prevent and/or reduce stress in these patients, to improve their mental health and, possibly, to reduce the effect of stress on the worsening of MS.

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)0.014
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesScience and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.011
Science and technology studies0.0040.004
Scholarly communication0.0020.002
Open science0.0050.002
Research integrity0.0010.003
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 head0.119
GPT teacher head0.412
Teacher spread0.293 · 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 designOther design
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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