Evidence map›Paper›PMID 36810455›Full record

ArticleEpidemiologia (Basel, Switzerland)2023

Mental Health System Responsiveness during COVID-19 in People with Pre-Existing Psychiatric Disorders: Experiences from Iran.

Maryam Zabihi Poursaadati, Samaneh Hosseinzadeh, Masoomeh Maarefvand, Jafar Bolhari, Jagdish Khubchandani

Abstract read
In one paragraph

Article in Epidemiologia (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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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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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Maryam Zabihi PoursaadatiDepartment of Social Work, School of Social Health, University of Social Welfare and Rehabilitation Sciences, Tehran 1985713871, Iran.ORCID 0000-0003-0741-1243
Samaneh HosseinzadehSchool of Rehabilitation Sciences, University of Social Welfare and Rehabilitation Sciences, Tehran 1985713871, Iran.
Masoomeh MaarefvandDepartment of Social Work, School of Social Health, University of Social Welfare and Rehabilitation Sciences, Tehran 1985713871, Iran.
Jafar BolhariDepartment of Psychiatry, Spiritual Health Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran.
Jagdish KhubchandaniDepartment of Public Health, College of Health Education and Social Transformation, New Mexico State University, Las Cruces, NM 88011, USA.ORCID 0000-0002-9058-4278

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mental health system responsiveness (MHSR) is one of the important indicators in measuring the performance of mental health systems. Recognizing this function can be effective in responding appropriately to the needs of People with Pre-Existing Psychiatric Disorders (PPEPD). This study aimed to investigate MHSR during the COVID-19 period in PPEPD in Iran. Using stratified random sampling, 142 PPEPD who were admitted to a Psychiatric Hospital in Iran one year before the onset of the COVID-19 pandemic were recruited for this cross-sectional study. Participants completed a demographic and clinical characteristics questionnaire as well as a Mental Health System Responsiveness Questionnaire through telephone interviews. The results show that the indicators of prompt attention, autonomy, and access to care were reported as the worst-performing and the confidentiality indicator as the best-performing. The type of insurance affected the access to care and the quality of basic amenities. MHSR has been reported to be poor in Iran in general and this problem worsened during the COVID-19 pandemic. Considering the prevalence of psychiatric disorders in Iran and the degree of disability of these disorders, structural and functional changes are needed for adequate MHSR.

Indexed as

COVID-19mental health systempsychiatric disorderresponsiveness

Identifiers

PMID36810455
PMCPMC9944841

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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.