Evidence map›Paper›PMID 19897942›Full record

ArticleJournal of epidemiology2010

Factors influencing participation rate in a baseline survey of a genetic cohort in Japan.

Megumi Hara, Yasuki Higaki, Takeshi Imaizumi, Naoto Taguchi, Kazuyo Nakamura, Hinako Nanri, Tatsuhiko Sakamoto, Mikako Horita, Koichi Shinchi, Keitaro Tanaka

Abstract read
In one paragraph

Article in Journal of epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 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

10 authors.

Megumi HaraDepartment of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan. harameg@cc.saga-u.ac.jp
Yasuki Higaki
Takeshi Imaizumi
Naoto Taguchi
Kazuyo Nakamura
Hinako Nanri
Tatsuhiko Sakamoto
Mikako Horita
Koichi Shinchi
Keitaro Tanaka

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough many studies have examined factors that influence the response to postal questionnaires, few have addressed baseline recruitment for cohort studies involving genetic analyses. The aim of this study was to describe the method used for a baseline survey, the Japan Multi-institutional Collaborative Cohort Study (J-MICC Study), in Saga Prefecture, and to examine the factors that might influence the recruitment of participants in such studies.

methodsThe Saga J-MICC Study is an ongoing population-based prospective cohort study of the genetic and environmental interactions associated with lifestyle-related disease. From 2005 through 2007, a total of 61 447 residents between the ages of 40 and 69 were invited by mail to participate in this study. The survey date and time were arranged by telephone.

resultsAmong that population, 31 002 (50.5%) responded and 12 078 (19.7%) agreed to participate. A completed questionnaire and blood pressure and anthropometric data were collected from all participants; blood, DNA specimens, and accelerometer measures were obtained from the great majority of them. Female sex and older age were associated with a higher participation rate. In addition, the convenience of the survey location and the sending of a reminder significantly improved the participation rate (odds ratio, 1.3).

conclusionsOur findings suggest that making the survey location as convenient as possible and sending a reminder can both substantially improve participation rate in population-based studies.

Indexed as

Patient SelectionAdultAgedAge FactorsBlood Specimen CollectionData CollectionFemaleGenetic ResearchHumansJapanMaleMiddle AgedPatient Acceptance of Health CareProspective StudiesReminder SystemsSex Factors

Identifiers

PMID19897942
PMCPMC3900778

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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.