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How well do commonly used data presentation formats support comparative effectiveness evaluations?

ABSTRACT: Good decisions depend on an accurate understanding of the comparative effectiveness of decision alternatives. The best way to convey data needed to support these comparisons is unknown.To determine how well 5 commonly used data presentation formats convey comparative effectiveness information.The study was an Internet survey using a factorial design. Participants consisted of 279 members of an online survey panel. Study participants compared outcomes associated with 3 hypothetical screening test options relative to 5 possible outcomes with probabilities ranging from 2 per 5000 (0.04%) to 500 per 1000 (50%). Data presentation formats included a table, a "magnified" bar chart, a risk scale, a frequency diagram, and an icon array. Outcomes included the number of correct ordinal judgments regarding the more likely of 2 outcomes, the ratio of perceived versus actual relative likelihoods of the paired outcomes, the intersubject consistency of responses, and perceived clarity.The mean number of correct ordinal judgments was 12 of 15 (80%), with no differences among data formats. On average, there was a 3.3-fold difference between perceived and actual likelihood ratios (95% confidence interval = 3.0-3.6). Comparative judgments based on flowcharts, icon arrays, and tables were all significantly more accurate and consistent than those based on risk scales and bar charts (P < 0.001). The most clearly perceived formats were the table and the flowchart. Low subjective numeracy was associated with less accurate and more variable data interpretations and lower perceived clarity for icon displays, bar charts, and flow diagrams.None of the data presentation formats studied can reliably provide patients, especially those with low subjective numeracy, with an accurate understanding of comparative effectiveness information.

SUBMITTER: Dolan JG

PROVIDER: S-EPMC3515653 | biostudies-literature | 2012 Nov-Dec

REPOSITORIES: biostudies-literature

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Project description:BackgroundAnopheles gambiae M and S molecular forms, the major malaria vectors in the Afro-tropical region, are ongoing a process of ecological diversification and adaptive lineage splitting, which is affecting malaria transmission and vector control strategies in West Africa. These two incipient species are defined on the basis of single nucleotide differences in the IGS and ITS regions of multicopy rDNA located on the X-chromosome. A number of PCR and PCR-RFLP approaches based on form-specific SNPs in the IGS region are used for M and S identification. Moreover, a PCR-method to detect the M-specific insertion of a short interspersed transposable element (SINE200) has recently been introduced as an alternative identification approach. However, a large-scale comparative analysis of four widely used PCR or PCR-RFLP genotyping methods for M and S identification was never carried out to evaluate whether they could be used interchangeably, as commonly assumed.ResultsThe genotyping of more than 400 A. gambiae specimens from nine African countries, and the sequencing of the IGS-amplicon of 115 of them, highlighted discrepancies among results obtained by the different approaches due to different kinds of biases, which may result in an overestimation of MS putative hybrids, as follows: i) incorrect match of M and S specific primers used in the allele specific-PCR approach; ii) presence of polymorphisms in the recognition sequence of restriction enzymes used in the PCR-RFLP approaches; iii) incomplete cleavage during the restriction reactions; iv) presence of different copy numbers of M and S-specific IGS-arrays in single individuals in areas of secondary contact between the two forms.ConclusionsThe results reveal that the PCR and PCR-RFLP approaches most commonly utilized to identify A. gambiae M and S forms are not fully interchangeable as usually assumed, and highlight limits of the actual definition of the two molecular forms, which might not fully correspond to the two A. gambiae incipient species in their entire geographical range. These limits are discussed and operational suggestions on the choice of the most convenient method for large-scale M- and S-form identification are provided, also taking into consideration technical aspects related to the epidemiological characteristics of different study areas.

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How well do commonly used data presentation formats support comparative effectiveness evaluations?

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