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Assessment of demographic and perinatal predictors of non-response and impact of non-response on measures of association in a population-based case control study: findings from the Georgia Study to…

Overview of attention for article published in Emerging Themes in Epidemiology, August 2018
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  • Above-average Attention Score compared to outputs of the same age (59th percentile)

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Title
Assessment of demographic and perinatal predictors of non-response and impact of non-response on measures of association in a population-based case control study: findings from the Georgia Study to Explore Early Development
Published in
Emerging Themes in Epidemiology, August 2018
DOI 10.1186/s12982-018-0081-y
Pubmed ID
Authors

Laura A. Schieve, Shericka Harris, Matthew J. Maenner, Aimee Alexander, Nicole F. Dowling

Abstract

Participation in epidemiologic studies has declined, raising concerns about selection bias. While estimates derived from epidemiologic studies have been shown to be robust under a wide range of scenarios, additional empiric study is needed. The Georgia Study to Explore Early Development (GA SEED), a population-based case-control study of risk factors for autism spectrum disorder (ASD), provided an opportunity to explore factors associated with non-participation and potential impacts of non-participation on association studies. GA SEED recruited preschool-aged children residing in metropolitan-Atlanta during 2007-2012. Children with ASD were identified from multiple schools and healthcare providers serving children with disabilities; children from the general population (POP) were randomly sampled from birth records. Recruitment was via mailed invitation letter with follow-up phone calls. Eligibility criteria included birth and current residence in study area and an English-speaking caregiver. Many children identified for potential inclusion could not be contacted. We used data from birth certificates to examine demographic and perinatal factors associated with participation in GA SEED and completion of the data collection protocol. We also compared ASD-risk factor associations for the final sample of children who completed the study with the initial sample of all likely ASD and POP children invited to potentially participate in the study, had they been eligible. Finally, we derived post-stratification sampling weights for participants who completed the study and compared weighted and unweighted associations between ASD and two factors collected via post-enrollment maternal interview: infertility and reproductive stoppage. Maternal age and education were independently associated with participation in the POP group. Maternal education was independently associated with participation in the ASD group. Numerous other demographic and perinatal factors were not associated with participation. Moreover, unadjusted and adjusted odds ratios for associations between ASD and several demographic and perinatal factors were similar between the final sample of study completers and the total invited sample. Odds ratios for associations between ASD and infertility and reproductive stoppage were also similar in unweighted and weighted analyses of the study completion sample. These findings suggest that effect estimates from SEED risk factor analyses, particularly those of non-demographic factors, are likely robust.

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The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 20%
Student > Master 5 12%
Student > Bachelor 4 10%
Researcher 3 7%
Student > Postgraduate 3 7%
Other 7 17%
Unknown 11 27%
Readers by discipline Count As %
Psychology 8 20%
Medicine and Dentistry 7 17%
Nursing and Health Professions 5 12%
Social Sciences 4 10%
Economics, Econometrics and Finance 1 2%
Other 2 5%
Unknown 14 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 August 2018.
All research outputs
#8,478,408
of 25,385,509 outputs
Outputs from Emerging Themes in Epidemiology
#86
of 155 outputs
Outputs of similar age
#129,369
of 324,991 outputs
Outputs of similar age from Emerging Themes in Epidemiology
#3
of 3 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 155 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 324,991 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.