Evidence map›Paper›PMID 39634393›Full record

ArticleHeliyon2024

Change in mental health service utilization from pre- to post-COVID-19 period in the United States.

Md Rezaul Kader, Mohammod Mahmudur Rahman, Piali Dey Bristi, Foyez Ahmmed

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

4 authors.

Md Rezaul KaderDepartment of Statistics, University of Dhaka, Dhaka, 1000, Bangladesh.
Mohammod Mahmudur RahmanDepartment of Statistics, University of Dhaka, Dhaka, 1000, Bangladesh.
Piali Dey BristiDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Foyez AhmmedDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to explore the change in mental health service utilization before and after the COVID-19 pandemic as well as determine the association of various sociodemographic characteristics and comorbidities on the utilization pattern. Methods: Data from the National Health Interview Survey (NHIS) 2019 and 2022 were explored in this study. Along with the univariate analysis, bivariate analysis was conducted using the Chi-square and Cochran-Armitage trend tests. Stepwise binary logistic regression was implemented to find the best-fitted model and examine the effects of different factors on mental healthcare utilization. We also conducted a subgroup analysis for the variables that showed heterogeneous changes in utilization from 2019 to 2022. Results: Analysis of a total of 53,856 complete cases showed that the percentage of mental healthcare utilization changed from 20% in 2019 to 23.31% in 2022. Logistic regression results showed that the odds of mental health service utilization in the post-COVID period is 1.41 times of the pre-COVID [95% CI odds ratio (OR) = (1.26, 1.58)]. Sex, age, race, education, income group, insurance coverage, birth country, marital status, limitations of social functioning, having a place for healthcare, symptoms and history of depression/anxiety, diabetes, and hypertension had significant effects on the odds of receiving mental healthcare. Subgroup analysis revealed that the utilization changed significantly from 2019 to 2022 for age group "18-34" [OR = 1.41, 95% CI = (1.26, 1.58)], "35-49" [OR = 1.35, 95% CI = (1.21, 1.50)], and "50-64" [OR = 1.12, 95% CI = (1.01, 1.24)], while for the age group "above 64" was not significant. Conclusion: Pre- and post-COVID periods were found to be significantly different in terms of the utilization of mental healthcare utilization. Changes in the utilization was also found to differ in terms of different age groups.

Indexed as

COVID-19DepressionMental health service utilizationPost-pandemic

Identifiers

PMID39634393
PMCPMC11616595

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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.