Evidence map›Paper›PMID 36514571›Full record

ArticleCureus2022

The Effects of the COVID-19 Pandemic on Mental Health: A Web-Based Study Among Romanian Adults.

Elena Popa, Teodora Tetia, Mihaela Poroch, Monica Ungureanu, Adriana Cosmescu, Liliana Barbacariu, Ana Maria Slanina, Agnes Bacusca, Antoneta Petroae, Otilia Novac and 4 more

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. 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

14 authors at 1 institution in 1 country.

Elena PopaPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Teodora TetiaPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Mihaela PorochPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Monica UngureanuPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Adriana CosmescuPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Liliana BarbacariuPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Ana Maria SlaninaPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Agnes BacuscaPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Antoneta PetroaePreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Otilia NovacPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Mihaela ManolePreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Dana Anton-PaduraruPediatrics, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Andrei Emilian PopaPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Elena-Adorata ComanPreventive Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iași, ROU.
Grigore T. Popa University of Medicine and Pharmacy · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background In Romania, as in other parts of the world, the family doctor is the first to make contact with a healthy patient and is also the first to notice even the smallest pathological changes. In the context of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the patient's communication with the family doctor became even closer and some behavioral changes could be easily noticed. Objective To assess the symptoms of anxiety and depression in the Romanian population using social media platforms in the context of the COVID-19 pandemic. Methods We conducted an anonymous, web-based cross-sectional survey consisting of 31 questions related to general characteristics (age, gender, education, inhabitancy, residence, smoking status, and alcohol consumption) and adapted GAD-7 (7-item General Anxiety Disorders questionnaire) and PHQ-9 (9-item Patient Health Questionnaire). This questionnaire was sent to volunteers in an electronic format through a social network (Facebook, Twitter). The data collected were statistically processed using IBM SPSS v25.0 (IBM Corp., Armonk, NY). The inclusion criteria were age over 18 years and no history of chronic disease. The exclusion criteria consisted of the absence of a mental illness diagnosis. Results From the 1254 respondents, 1232 cases were selected for statistical analysis after applying the exclusion criteria. The mean age was 35.94 (SD = 11.4, 95%CI=10.9-11.9) with a minimum of 18 years and a maximum of 97 years. Eighty-four point nine percent (84.9%; N=1046) of all study participants are female and 79.13% (N= 975) live in the urban area. A total of 188 (15.25%) were diagnosed with COVID-19 of which 31 (16.66%) were male and 157 (15%) were female. N=170 (13.8%) reported moderate symptoms of anxiety during the last two weeks before the survey while N=96 (7.8%) had severe anxiety. Twenty-two point two percent (22.2%; N=274) of the participants reported moderate symptoms of depression while 10.1% (N=125) had moderately severe symptoms and 6.6% (N=81) could be diagnosed with severe depression. A greater likelihood of screening for depression diagnosis was associated with ages between 25 and 34 years (OR=0.90, 95%CI=0.86-0.94,

Indexed as

anxietycovid-19depressionfamily medicinesurvey

Identifiers

PMID36514571
PMCPMC9741121
OpenAlexW4308713974

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.