Evidence map›Paper›PMID 28593128›Full record

ArticlePreventive medicine reports2017

Including mobile-only telephone users in a statewide preventive health survey-Differences in the prevalence of health risk factors and impact on trends.

Bernard Baffour, Tim Roselli, Michele Haynes, Joshua J Bon, Mark Western, Susan Clemens

Abstract read
In one paragraph

Article in Preventive medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Bernard BaffourThe Institute for Social Science Research, The University of Queensland, 80 Meiers Road, Indooroopilly, Queensland 4068, Australia.
Tim RoselliPreventive Health Branch, Department of Health, Queensland Government, Level 1, 15 Butterfield Street, Herston, Queensland 4006, Australia.
Michele HaynesThe Institute for Social Science Research, The University of Queensland, 80 Meiers Road, Indooroopilly, Queensland 4068, Australia.
Joshua J BonThe Institute for Social Science Research, The University of Queensland, 80 Meiers Road, Indooroopilly, Queensland 4068, Australia.
Mark WesternThe Institute for Social Science Research, The University of Queensland, 80 Meiers Road, Indooroopilly, Queensland 4068, Australia.
Susan ClemensPreventive Health Branch, Department of Health, Queensland Government, Level 1, 15 Butterfield Street, Herston, Queensland 4006, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Queensland preventive health survey is conducted annually to monitor the prevalence of behavioural risk factors in the north-east Australian state. Prompted by domestic and international trends in mobile telephone usage, the 2015 survey incorporated both mobile and landline telephone numbers from a list-based sampling frame. Estimates for landline-accessible and mobile-only respondents are compared to assess potential bias in landline-only surveys in the context of public health surveillance. Significant differences were found in subcategories of all health prevalence estimates considered (alcohol consumption, body mass index, smoking, and physical activity) from 2015 survey results. Results from Australian and international studies that have considered mobile telephone non-coverage bias are also summarised and discussed. We find that adjusting for sampling biases of telephone surveys by weighting does not fully compensate for the differences in prevalence estimates. However, predicted trends from previous years' surveys only differ significantly for the 2015 prevalence estimates of alcohol consumption. We conclude that the inclusion of mobile telephones into standard telephones surveys is important for obtaining valid, reliable and representative data to reduce bias in health prevalence estimates. Importantly, unlike some international experiences, the addition of mobiles telephones into the Queensland preventive health survey occurred before population trends were significantly affected.

Indexed as

Dual-frame surveyHealth prevalence estimatesNon-coverage biasPublic health surveillanceTelephone surveys

Identifiers

PMID28593128
PMCPMC5459564

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.