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Record W6990612034

Dor Neuropática e Processos de Regulação Emocional em Doentes com o Diagnóstico de Esclerose Múltipla: um modelo preditivo dos sintomas psicopatológicos de depressão

2020· dissertation· pt· W6990612034 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2020
Typedissertation
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaAnxietyDASSToronto Alexithymia ScaleCognition
DOInot available

Abstract

fetched live from OpenAlex

Introdução: A Esclerose Múltipla (EM) é uma doença neurológica crónica, desmielinizante do sistema nervoso central. Esta doença tem um curso progressivo e, normalmente, gera incapacidade. A depressão é uma perturbação mental de elevada comorbilidade com a EM. Todavia, ainda são escassos os estudos acerca dos preditores da depressão em pacientes com EM. Objetivo: O presente estudo propôs-se a explorar o valor preditivo da dor neuropática e de processos de regulação emocional disfuncionais - supressão do pensamento, alexitimia, fusão cognitiva e atitude autocrítica - para o desenvolvimento de sintomatologia depressiva em portadores de EM. Método: Este estudo transversal integrou os seguintes grupos de participantes: 100 doentes com o diagnóstico de EM e sem outros diagnósticos do foro neurológico (grupo clínico com EM) e 110 indivíduos da população geral sem outras doenças neurológicas identificadas (grupo da população geral sem EM). Esta última amostra destinou-se a caracterizar os participantes com EM comparativamente aos participantes sem EM relativamente às variáveis em estudo e a construir o modelo preditivo. Os dois grupos responderam aos seguintes questionários de autorresposta: Questionário Sociodemográfico e Clínico Para Doentes Com Esclerose Múltipla, Pain Detect Questionnaire (PD-Q); Depression, Anxiety and Stress Scale (DASS-21), Toronto Alexithymia Scale (TAS-20), Cognitive Fusion Questionnaire (CFQ), Self-Compassion Scale (SCS) e o White Bear Suppression Inventory (WBSI). Resultados: O grupo clínico com EM caracterizou-se por apresentar valores significativamente superiores de sintomatologia depressiva e em relação a todos os potenciais preditores. O modelo preditivo é estatisticamente significativo, explicando cerca de 23% da variância dos sintomas depressivos em doentes com EM, tendo retido como preditor significativo a atitude autocrítica. Discussão: Intervenções psicológicas com o objetivo de prevenir e reduzir a depressão em pacientes com EM devem incluir estratégias destinadas a flexibilizarem uma atitude autocrítica enquanto processo de regulação emocional. A terapia Focada na Compaixão é promissora para este fim, contribuindo, assim, para a promoção da saúde mental na referida população clínica e para a eventual minimização da progressão da EM. / Introduction: Multiple sclerosis (MS) is a chronic neurological disease, demyelinating of the central nervous system. This disease has a progressive course and usually generates disability. Depression is a mental disorder with high comorbidity with MS. However, studies on predictors of depression in MS patients are still scarce. Objective: The present study aimed to explore the predictive value of neuropathic pain, dysfunctional emotional regulation processes - suppression of thought, alexithymia, cognitive fusion and self-critical attitude – in the development of depressive symptoms in MS patients. Method: This cross-sectional study included the following participant groups: 100 patients diagnosed with MS (clinical group with MS) and without other neurological diagnoses and 110 individuals from the general population without other identified neurological diseases (group from the general population without MS). This last sample was intended to characterize participants with MS compared to participants without MS in relation to the variables under study and to build the predictive model. Both groups answered the following self-answer questionnaires: Sociodemographic and Clinical Questionnaire for Patients with Multiple Sclerosis, Pain Detect Questionnaire (PD-Q); Depression, Anxiety and Stress Scale (DASS-21), Toronto Alexithymia Scale (TAS-20), Cognitive Fusion Questionnaire (CFQ), Self-Compassion Scale (SCS) and the White Bear Suppression Inventory (WBSI). Results: The clinical group with MS was characterized by presenting significantly higher values of depressive symptoms and in relation to all potential predictors. The model is statistically significant, explaining about 23% of the variance of depressive symptoms in patients with MS, having retained the self-critical attitude as a significant predictor. Discussion: Psychological interventions aimed at preventing and reducing depression in patients with MS should include strategies aimed at making a self-critical attitude more flexible as a process of emotional regulation. The therapy focused on compassion is promising for this purpose, thus contributing to the promotion of mental health in the referred clinical population and to the possible minimization of the progression 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)0.010
metaresearch head score (Gemma)0.023
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.009
Science and technology studies0.0040.003
Scholarly communication0.0010.002
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 head0.076
GPT teacher head0.393
Teacher spread0.317 · 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 designSimulation or modeling
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
Published2020
Admission routes1
Has abstractyes

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