Evidence map›Paper›PMID 23046097›Full record

ArticleHealth services research2013

Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias.

Jonathon R B Halbesleben, Marilyn V Whitman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Health services research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
129citing papers in PubMed, 1 pooled it
–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

129 citing papers in PubMed, 1 synthesis or guideline pooled it.

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69 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Jonathon R B HalbeslebenDepartment of Management & Marketing, Culverhouse College of Commerce & Business Administration, University of Alabama, Tuscaloosa, AL, USA.
Marilyn V Whitman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo address the issue of nonresponse as problematic and offer appropriate strategies for assessing nonresponse bias. STUDY

designA review of current strategies used to assess the quality of survey data and the challenges associated with these strategies is provided along with appropriate post-data collection techniques that researchers should consider. PRINCIPAL

findingsResponse rates are an incomplete assessment of survey data quality, and quick reactions to response rate should be avoided. Based on a five-question decision making framework, we offer potential ways to assess nonresponse bias, along with a description of the advantages and disadvantages to each.

conclusionsIt is important that the quality of survey data be considered to assess the relative contribution to the literature of a given study. Authors and funding agencies should consider the potential effects of nonresponse bias both before and after survey administration and report the results of assessments of nonresponse bias in addition to response rates.

Indexed as

BiasData CollectionData Interpretation, StatisticalHealth Services ResearchHumansResearch DesignSurveys and Questionnaires

Identifiers

PMID23046097
PMCPMC3681236

What OpenQuestion holds

Textmetadata
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.