MétaCan
Menu
Back to cohort
Record W3141737870 · doi:10.3389/fneur.2021.652177

Association of Fatigue Severity With Maladaptive Coping in Multiple Sclerosis: A Data-Driven Psychodynamic Perspective

2021· article· en· W3141737870 on OpenAlexaboutno aff
Gesa E. A. Pust, Jennifer Randerath, Lutz Goetzmann, Roland Weierstall, Michael Korzinski, Stefan M. Gold, Christian Dettmers, Barbara Ruettner, Roger Schmidt

Bibliographic record

VenueFrontiers in Neurology · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersDeutschen Multiple Sklerose GesellschaftMultiple Sclerosis Society
KeywordsPsychologyCoping (psychology)Clinical psychologyBeck Depression InventoryPsychiatryAnxiety

Abstract

fetched live from OpenAlex

Fatigue in persons with multiple sclerosis (PwMS) is severely disabling. However, the underlying mechanisms remain incompletely understood. Recent research suggests a link to early childhood adversities and psychological trait variables. In line with these studies, this paper took a psychodynamic perspective on MS-fatigue. It was hypothesized that fatigue could represent a manifestation of maladaptive coping with intense emotions. The schema therapeutic mode model served as a theoretical and empirically validated framework, linking psychodynamic theory and empirical research methods. The study was based on a data set of N = 571 PwMS that has also served as the basis for another publication. Data was collected online. The Schema Mode Inventory was used to quantify regulatory strategies to cope with emotionally stressful experiences. In addition, depressive symptoms (Beck's Depression Inventory - FastScreen), physical disability (Patient Determined Disease Steps), alexithymia (Toronto Alexithymia Scale-26), adverse childhood experiences (Childhood Trauma Questionnaire), and self-reported fatigue (Fatigue Scale for Motor and Cognitive Functions) were assessed. Latent profile analysis revealed three distinct groups of PwMS, based on their coping mode profiles: (1) PwMS with low maladaptive coping, (2) PwMS with avoidant/submissive coping styles, and (3) PwMS with avoidant/overcompensatory coping styles. Multivariate comparisons showed no significant difference in physical disability across the three groups. However, heightened levels of self-reported fatigue and depression symptoms occurred in PwMS with maladaptive coping styles. A path model uncovered that self-reported fatigue was robustly related to physical disability (β = 0.33) and detached/avoidant coping (Detached Protector; β = 0.34). There was no specific relation between any of the maladaptive coping modes and depression symptoms. Detached/avoidant coping was in turn predicted by childhood emotional abuse and neglect. The results indicate that childhood adversity and detached/avoidant coping styles may be associated with variability in MS-fatigue severity: PwMS that resort to detached/avoidant coping in response to negative emotions also tend to report heightened levels of fatigue, although they do not differ in their perceived disability from PwMS with low levels of fatigue and maladaptive coping. A link between MS-fatigue and the psychodynamic traumatic conversion model is discussed. The implications of these findings for therapeutic interventions require further study.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.317
Teacher spread0.236 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NeurologySame topicMultiple Sclerosis Research StudiesFrench-language works237,207