Evidence map›Paper›PMID 29793688›Full record

ArticleSocial science research2018

New options for national population surveys: The implications of internet and smartphone coverage.

Mick P Couper, Garret Gremel, William Axinn, Heidi Guyer, James Wagner, Brady T West

Open access · greenAbstract read
In one paragraph

Article in Social science research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
13.7field-weighted citation impact, top 1% of its field
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

13 citing papers in PubMed, 45 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Review
  10. Article
  11. Article
  12. Measures of the Degree of Departure from Ignorable Sample Selection.Journal of survey statistics and methodology · 2020
    Article
  13. Article
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

6 authors at 2 institutions in 2 countries.

Mick P CouperInstitute for Social Research, University of Michigan, United States; Joint Program in Survey Methodology, United States. Electronic address: mcouper@umich.edu.
Garret GremelInstitute for Social Research, University of Michigan, United States.
William AxinnInstitute for Social Research, University of Michigan, United States.
Heidi GuyerInstitute for Social Research, University of Michigan, United States.
James WagnerInstitute for Social Research, University of Michigan, United States; Joint Program in Survey Methodology, United States.
Brady T WestInstitute for Social Research, University of Michigan, United States; Joint Program in Survey Methodology, United States.
Michigan United · USInstitute for Social Research · NO

Funding

Scientific/Technical CoreP2CHD041028 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sarah A. Burgard · 2017 to 2026
$6.5M
NICHD NIH HHS P2C HD041028
6 · The paper itself

Abstract

Challenges to survey data collection have increased the costs of social research via face-to-face surveys so much that it may become extremely difficult for social scientists to continue using these methods. A key drawback to less expensive Internet-based alternatives is the threat of biased results from coverage errors in survey data. The rise of Internet-enabled smartphones presents an opportunity to re-examine the issue of Internet coverage for surveys and its implications for coverage bias. Two questions (on Internet access and smartphone ownership) were added to the National Survey of Family Growth (NSFG), a U.S. national probability survey of women and men age 15-44, using a continuous sample design. We examine 16 quarters (4 years) of data, from September 2012 to August 2016. Overall, we estimate that 82.9% of the target NSFG population has Internet access, and 81.6% has a smartphone. Combined, this means that about 90.7% of U.S. residents age 15-44 have Internet access, via either traditional devices or a smartphone. We find some evidence of compensatory coverage when looking at key race/ethnicity and age subgroups. For instance, while Black teens (15-18) have the lowest estimated rate of Internet access (81.9%) and the lowest rate of smartphone usage (72.6%), an estimated 88.0% of this subgroup has some form of Internet access. We also examine the socio-demographic correlates of Internet and smartphone coverage, separately and combined, as indicators of technology access in this population. In addition, we look at the effect of differential coverage on key estimates produced by the NSFG, related to fertility, family formation, and sexual activity. While this does not address nonresponse or measurement biases that may differ for alternative modes, our paper has implications for possible coverage biases that may arise when switching to a Web-based mode of data collection, either for follow-up surveys or to replace the main face-to-face data collection.

Indexed as

Coverage biasInternetSmartphoneSurvey data

Identifiers

PMID29793688
PMCPMC10799630
OpenAlexW2792417384

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.