Evidence map›Paper›PMID 38275580›Full record

ArticleBioengineering (Basel, Switzerland)2024

Predictive Model of Anxiety and Depression Perception in Multiple Sclerosis Patients: Possible Implications for Clinical Treatment.

María Cuerda-Ballester, Antonio Bustos, David Sancho-Cantus, David Martínez-Rubio, Jesús Privado, Jorge Alarcón-Jiménez, Carlos Villarón-Casales, Nieves de Bernardo, Esther Navarro Illana, José Enrique de la Rubia Ortí

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.1field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

María Cuerda-BallesterDoctoral Degree School, Catholic University San Vicente Mártir, 46001 Valencia, Spain.ORCID 0000-0002-8844-8461
Antonio BustosPhysical Therapy Clinic, Antonio Bustos, 46007 Valencia, Spain.
David Sancho-CantusDepartment of Nursing, Catholic University San Vicente Mártir, 46001 Valencia, Spain.ORCID 0000-0002-4911-5058
David Martínez-RubioDepartment of Nursing and Physiotherapy, University of Lleida, 25006 Lleida, Spain.ORCID 0000-0002-9346-3869
Jesús PrivadoDepartment of Methodology of Behavioral Sciences, Universidad Complutense de Madrid, Campus de Somosaguas, Pozuelo de Alarcón, 28223 Madrid, Spain.
Jorge Alarcón-JiménezDepartment of Physiotherapy, Universidad Católica de Valencia, 46900 Valencia, Spain.ORCID 0000-0002-8904-3749
Carlos Villarón-CasalesBiomechanics & Physiotherapy in Sports (BIOCAPS), Faculty of Health Sciences, European University of Valencia, 46001 Valencia, Spain.ORCID 0000-0003-2717-3342
Nieves de BernardoDepartment of Nursing, Catholic University San Vicente Mártir, 46001 Valencia, Spain.ORCID 0000-0002-8125-8972
Esther Navarro IllanaDepartment of Nursing, Catholic University San Vicente Mártir, 46001 Valencia, Spain.ORCID 0000-0001-6350-3113
José Enrique de la Rubia OrtíDepartment of Nursing, Catholic University San Vicente Mártir, 46001 Valencia, Spain.ORCID 0000-0001-6808-9505
Valencia Catholic University Saint Vincent Martyr · ESUniversidad Complutense de Madrid · ESUniversitat de Lleida · ESUniversitat de València · ES

Funding

Catholic University Foundation San Vicente Mártir 2018-203-001
6 · The paper itself

Abstract

Multiple Sclerosis (MS) is a neurodegenerative disease characterized by motor and non-motor symptoms, including emotional distress, anxiety, and depression. These emotional symptoms currently have a pharmacological treatment with limited effectiveness; therefore, it is necessary to delve into their relationship with other psychological, functional, or prefrontal alterations. Additionally, exploring non-pharmacological therapeutic alternatives that have shown benefits in addressing emotional distress in MS patients is essential.

aimTo establish a predictive model for the presence of anxiety and depression in MS patients, based on variables such as psychological well-being, functional activity, and prefrontal symptoms. Additionally, this study aimed to propose non-pharmacological therapeutic alternatives based on this model. MATERIALS AND

methodsA descriptive, observational, and cross-sectional study was conducted with a sample of 64 diagnosed MS patients who underwent functional and cognitive assessments using the following questionnaires and scales: Functional Activities Questionnaire (FAQ), Acceptance and Action Questionnaire (AAQ-II), Experiences Questionnaire (EQ), Self-Compassion Scale Short Form (SCS-SF), Beck Depression Inventory II (BDI-II), State-Trait Anxiety Inventory (STAI), and Prefrontal Symptoms Inventory (PSI).

resultsThe model showed an excellent fit to the data and indicated that psychological well-being was the most significant predictor of the criteria (β = -0.83), followed by functional activity (β = -0.18) and prefrontal symptoms (β = 0.15). The latter two are negatively related to psychological well-being (β = -0.16 and β = -0.75, respectively).

conclusionsLow psychological well-being is the variable that most significantly predicts the presence of anxiety and depression in MS patients, followed by functional activity and prefrontal alterations. Interventions based on mindfulness and acceptance are recommended, along with nutritional interventions such as antioxidant-enriched ketogenic diets and moderate group physical exercise.

Indexed as

anxietydepressionfunctional activitymultiple sclerosisprefrontal activitypsychological well-being

Identifiers

PMID38275580
PMCPMC10813122
OpenAlexW4391111107

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.