Evidence map›Paper›PMID 35329424›Full record

ArticleInternational journal of environmental research and public health2022

The Influence of Research Follow-Up during COVID-19 Pandemic on Mental Distress and Resilience: A Multicenter Cohort Study of Treatment-Resistant Depression.

Pham Thi Thu Huong, Chia-Yi Wu, Ming-Been Lee, Wei-Chieh Hung, I-Ming Chen, Hsi-Chung Chen

Abstract readMulticenter Study
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Pham Thi Thu HuongSchool of Nursing, National Taiwan University College of Medicine, Taipei 10051, Taiwan.ORCID 0000-0002-8206-2541
Chia-Yi WuSchool of Nursing, National Taiwan University College of Medicine, Taipei 10051, Taiwan.ORCID 0000-0003-1756-557X
Ming-Been LeeTaiwan Suicide Prevention Center, Taiwanese Society of Suicidology, Taipei 10051, Taiwan.
Wei-Chieh HungSchool of Nursing, National Taiwan University College of Medicine, Taipei 10051, Taiwan.
I-Ming ChenDepartment of Psychiatry, National Taiwan University Hospital, Taipei 10051, Taiwan.
Hsi-Chung ChenDepartment of Psychiatry, National Taiwan University Hospital, Taipei 10051, Taiwan.ORCID 0000-0003-3191-0093

Funding

Ministry of Science and Technology MOST106-2314-B-002-010-MY3
6 · The paper itself

Abstract

Background: During the COVID-19 outbreak, patients with mental disorders have faced more negative psychological consequences than the public. For people with treatment-resistant depression (TRD), it is unclear whether research engagement would protect them from the deterioration of their symptoms. The study aimed to examine if chronic depressive patients would have improved resilience and mental distress levels after follow-up interviews during an observation period under COVID-19. Methods: The study was nested within a three-year prospective cohort study. A two-group comparison design was conducted, i.e., the follow-up group with regular research interviews every three months after baseline assessment and the control group with one assessment-only interview. The two groups were compared with demographics, psychosocial, and suicide information. Results: Baseline assessments were not significantly different in sociodemographic variables, suicide risks, mental distress, and resilience between groups. Significant differences were detected in resilient coping and mental distress levels (p < 0.05). The follow-up group (n = 46) experienced a higher level of resilient coping (37% vs. 25%) and lower level of mental distress (47.8% vs. 64.7%) than the control group (n = 68). Conclusions: Findings highlight under universal government strategy against COVID-19, TRD patients receiving regular research follow-ups exhibited better resilience and less mental distress than those without regular support from healthcare providers.

Indexed as

COVID-19Depressive Disorder, Treatment-ResistantResilience, PsychologicalDepressionFollow-Up StudiesHumansPandemicsProspective StudiesCOVID-19follow-up studymental distressresilient copingtreatment-resistant depression

Identifiers

PMID35329424
PMCPMC8950889

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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.