Literature DB >> 19618786

Measuring health behaviors and landline telephones: potential coverage bias in a low-income, rural population.

Fatma Shebl1, Carolyn E Poppell, Min Zhan, Diane M Dwyer, Annette B Hopkins, Carmela Groves, Faye Reed, C Devadason, Eileen K Steinberger.   

Abstract

OBJECTIVES: Population-based landline telephone surveys are potentially biased due to inclusion of only people with landline telephones. This article examined the degree of telephone coverage bias in a low-income population.
METHODS: The Charles County Cancer Survey (CCCS) was conducted to evaluate cancer screening practices and risk behaviors among low-income, rural residents of Charles County, Maryland. We conducted face-to-face interviews with 502 residents aged 18 years and older. We compared the prevalence of health behaviors and cancer screening tests for those with and without landline telephones. We calculated the difference between whole sample estimates and estimates for only those respondents with landline telephones to quantify the magnitude of telephone coverage bias.
RESULTS: Of 499 respondents who gave information on telephone use, 80 (16%) did not have landline telephones. We found differences between those with and without landline telephones for race/ethnicity, health-care access, insurance coverage, and several types of cancer screening. The absolute coverage bias ranged up to 6.5 percentage points. Simulation scenarios showed the magnitude of telephone coverage bias decreases as the percent of the population with landline telephone coverage increases, and as landline telephone coverage increases, the estimates from a landline telephone survey would approximate the estimates from a face-to-face survey.
CONCLUSIONS: Our findings highlighted the need for targeted face-to-face surveys to supplement telephone surveys to more fully characterize hard-to-reach subpopulations. Our findings also indicated that landline telephone-based surveys continue to offer a cost-effective method for conducting large-scale population studies in support of policy and public health decision-making.

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Year:  2009        PMID: 19618786      PMCID: PMC2693163          DOI: 10.1177/003335490912400406

Source DB:  PubMed          Journal:  Public Health Rep        ISSN: 0033-3549            Impact factor:   2.792


  9 in total

1.  Telephone ownership and deaf people: implications for telephone surveys.

Authors:  S Barnett; P Franks
Journal:  Am J Public Health       Date:  1999-11       Impact factor: 9.308

2.  Telephone coverage and health survey estimates: evaluating the need for concern about wireless substitution.

Authors:  Stephen J Blumberg; Julian V Luke; Marcie L Cynamon
Journal:  Am J Public Health       Date:  2006-03-29       Impact factor: 9.308

3.  Summary health statistics for U.S. adults: National Health Interview Survey, 2005.

Authors:  John R Pleis; Margaret Lethbridge-Cejku
Journal:  Vital Health Stat 10       Date:  2006-12

4.  Telephone coverage and measurement of health risk indicators: data from the National Health Interview Survey.

Authors:  J E Anderson; D E Nelson; R W Wilson
Journal:  Am J Public Health       Date:  1998-09       Impact factor: 9.308

5.  Characteristics of survey participants with and without a telephone: findings from the third National Health and Nutrition Examination Survey.

Authors:  E S Ford
Journal:  J Clin Epidemiol       Date:  1998-01       Impact factor: 6.437

6.  Telephone surveys in public health research.

Authors:  A C Marcus; L A Crane
Journal:  Med Care       Date:  1986-02       Impact factor: 2.983

7.  Collecting data to evaluate the effect of health policies on vulnerable populations.

Authors:  A B Bindman; K Grumbach; D Keane; N Lurie
Journal:  Fam Med       Date:  1993-02       Impact factor: 1.756

8.  Personal versus telephone surveys for collecting household health data at the local level.

Authors:  M F Weeks; R A Kulka; J T Lessler; R W Whitmore
Journal:  Am J Public Health       Date:  1983-12       Impact factor: 9.308

9.  State smoking prevalence estimates: a comparison of the Behavioral Risk Factor Surveillance System and current population surveys.

Authors:  D R Arday; S L Tomar; D E Nelson; R K Merritt; M W Schooley; P Mowery
Journal:  Am J Public Health       Date:  1997-10       Impact factor: 9.308

  9 in total
  4 in total

1.  Barriers to effective tobacco-dependence treatment for the very poor.

Authors:  Bruce Christiansen; Kevin Reeder; Maureen Hill; Timothy B Baker; Michael C Fiore
Journal:  J Stud Alcohol Drugs       Date:  2012-11       Impact factor: 2.582

2.  Telephone Surveys Underestimate Cigarette Smoking among African-Americans.

Authors:  Hope Landrine; Irma Corral; Denise Adams Simms; Scott C Roesch; Latrice C Pichon; Diane Ake; Feion Villodas
Journal:  Front Public Health       Date:  2013-09-25

3.  Potential use of telephone-based survey for non-communicable disease surveillance in Sri Lanka.

Authors:  H M M Herath; N P Weerasinghe; T P Weerarathna; A Hemantha; A Amarathunga
Journal:  BMC Public Health       Date:  2017-12-29       Impact factor: 3.295

Review 4.  Reaching the hard-to-reach: a systematic review of strategies for improving health and medical research with socially disadvantaged groups.

Authors:  Billie Bonevski; Madeleine Randell; Chris Paul; Kathy Chapman; Laura Twyman; Jamie Bryant; Irena Brozek; Clare Hughes
Journal:  BMC Med Res Methodol       Date:  2014-03-25       Impact factor: 4.615

  4 in total

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