Evidence map›Paper›PMID 31670823›Full record

ArticleInternational health2019

Digging deeper in Shanghai: towards a 'mechanism-rich' epidemiology.

Jie Li, Nick Manning, Andrea Mechelli

Abstract read
In one paragraph

Article in International health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jie LiSchool of Tourism Management, Sun Yat-Sen University, Tangjiawan Town, Zhuhai, Guangdong, China.
Nick ManningDepartment of Global Health & Social Medicine, School of Global Affairs, King's College London, 30 Aldwych, London WC2B 4BG, UK.
Andrea MechelliDepartment of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are very few close-up sociological or anthropological data informing epidemiological and psychiatric research design and/or contributing to our understanding of the relationship between mental health and specific forms of urban life. Furthermore, research on the relationships between urbanicity and mental disorder has paid little attention to the global diversity of urban experience, such as in cities in China, India and Brazil.

methodsTwo innovative methods can be employed to unveil the diversified urban experience of migrants in China, i.e. an ethnography-informed sociological deep surveying instrument and an ecological momentary assessment with a smartphone app. This article introduces the design and pilot survey of these new instruments towards a 'mechanism-rich' epidemiology.

resultsThe ethnography-informed survey instrument enabled us to include some of the issues from the ethnography and successfully 'dig deeper' into respondents' social experience. The pilot of the smartphone app serves as 'proof of principle' that we can recruit respondents in Shanghai, and that we can receive and use the data.

conclusionsBoth of these pilots have demonstrated good feasibility for studying mobility, urban life and mental health. Our next steps will be to extend the Shanghai sample, to use the app in Sao Paulo and Toronto and then hopefully in India and Africa.

Indexed as

Health StatusMobile ApplicationsAdultAgedAged, 80 and overAnthropology, CulturalChinaCitiesFemaleHumansMaleMental DisordersMental HealthMiddle AgedSurveys and QuestionnairesTransients and Migrantsecological assessmentethnography-informed surveymental healthmigrantmobilitysmartphone app

Identifiers

PMID31670823
PMCPMC6822688

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.