Evidence map›Paper›PMID 37510614›Full record

ReviewInternational journal of environmental research and public health2023

Impact of COVID-19 Pandemic on Mental Health among the Population in Jordan.

Ghaith Salameh, Debbi Marais, Rawan Khoury

Abstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

3 authors.

Ghaith SalamehSchool of Health, University of Essex, Colchester CO4 3SQ, UK.ORCID 0009-0006-0230-0308
Debbi MaraisWarwick Medical School, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0002-9073-0706
Rawan KhouryHelp Age International, London SE1 7RL, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental health is a key indicator for public health measures. Jordan is one of the countries that has a high prevalence of mental illness and disorders. The COVID-19 pandemic has affected all health services in the country with a high refugee population. The aim of this review is to assess the impact of the pandemic on mental health in Jordan and identify key factors affecting it, in addition to addressing lessons learned from the pandemic.

methodsA systematic search was conducted on Medline Plus, Embase, Web of Science, EBSCOHost Psycinfo and Cinhal, following the PRISMA guidelines. Articles were selected based on predefined inclusion and exclusion criteria. Data were extracted and synthesized using narrative descriptive analysis.

resultsThe pandemic had a significant impact on PTSD, psychological distress, anxiety, depression and stress. Predictors of a higher impact on mental health were related to gender, socio-economic status and comorbidities. The healthcare workers group was the most affected by mental disorders.

conclusionsThe COVID-19 pandemic's impact on mental health was associated with high levels of PTSD, anxiety, depression and stress. In a country with a high prevalence of mental disorders, prompt and quick measures are needed to support the health system to absorb the effect of the pandemic and be responsive to dealing with the existing high prevalence.

Indexed as

COVID-19AnxietyDepressionHealth PersonnelHumansJordanMental HealthPandemicsCOVID-19 pandemicgeneral populationJordanmental disordersmental health

Identifiers

PMID37510614
PMCPMC10379603

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.