Evidence map›Paper›PMID 34462494›Full record

ArticleScientific reports2021

Health-seeking and diagnosis delay and its associated factors: a case study on COVID-19 infections in Shaanxi Province, China.

Wenyuan Zheng, Fabrice Kämpfen, Zhiyong Huang

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  6. Influencing Factors of Delayed Diagnosis of COVID-19 in Gangwon, South Korea.International journal of environmental research and public health · 2024
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  13. Factors Associated with Delayed Diagnosis among Patients with COVID-19 in Okinawa, Japan.International journal of environmental research and public health · 2022
    Article
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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

3 authors.

Wenyuan ZhengSchool of Insurance, Southwestern University of Finance and Economics, Chengdu, 611130, China.
Fabrice KämpfenPopulation Studies Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Zhiyong HuangCenter of Health Governance and Policy, Southwestern University of Finance and Economics, Chengdu, 611130, China. zhiyonghuang@swufe.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This time-to-event study examines social factors associated with health-seeking and diagnosis of 165 COVID-19 cases in response to the pandemic spread in Shaanxi Province, China. In particular, we investigate the differential access to healthcare in terms of delayed time from symptom onset to first medical visit and subsequently to diagnosis by factors such as sex, age, travel history, and type of healthcare utilization. We show that it takes more time for patients older than 60 (against those under 30) to seek healthcare after developing symptoms (+ 2.5 days, [Formula: see text]), surveillance on people with living or travel history to Wuhan helps shorten the time to the first doctor visit (- 0.8 days) and diagnosis (- 2.2 days, [Formula: see text]). A delay cut is associated with the adoption of intermediary and large hospitals rather than community-based care as primary care choices (- 1.6 days, [Formula: see text] and - 2.2 days, [Formula: see text]). One unit increase of healthcare workers per 1000 people saves patients 0.5 days ([Formula: see text]) for diagnosis from the first doctor visit and 0.6 days ([Formula: see text]) in total. Our analysis of factors associated with the time delay for diagnosis may provide a better understanding of the health-seeking behaviors of patients and the diagnosis capacity of healthcare providers during the COVID-19 pandemic.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsChinaCOVID-19Delayed DiagnosisFemaleHealth Services AccessibilityHelp-Seeking BehaviorHumansMaleMiddle AgedRisk AssessmentYoung Adult

Identifiers

PMID34462494
PMCPMC8405662

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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.