If the results of an article are noteworthy, read the entire article; do not rely on the abstract alone

Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review

BACKGROUND

Depression symptom questionnaires are commonly used to assess symptom severity and as screening tools to identify patients who may have depression. They are not designed to ascertain diagnostic status and, based on published sensitivity and specificity estimates, would theoretically be expected to overestimate prevalence. Meta-analyses sometimes estimate depression prevalence based on primary studies that used screening tools or rating scales rather than validated diagnostic interviews. Our objectives were to determine classification methods used in primary studies included in depression prevalence meta-analyses, if pooled prevalence differs by primary study classification methods as would be predicted, whether meta-analysis abstracts accurately describe primary study classification methods, and how meta-analyses describe prevalence estimates in abstracts.

METHODS

We searched PubMed (January 2008-December 2017) for meta-analyses that reported pooled depression prevalence in the abstract. For each meta-analysis, we included up to one pooled prevalence for each of three depression classification method categories: (1) diagnostic interviews only, (2) screening or rating tools, and (3) a combination of methods.

RESULTS

In 69 included meta-analyses (81 prevalence estimates), eight prevalence estimates (10%) were based on diagnostic interviews, 36 (44%) on screening or rating tools, and 37 (46%) on combinations. Prevalence was 31% based on screening or rating tools, 22% for combinations, and 17% for diagnostic interviews. Among 2094 primary studies in 81 pooled prevalence estimates, 277 (13%) used validated diagnostic interviews, 1604 (77%) used screening or rating tools, and 213 (10%) used other methods (e.g., unstructured interviews, medical records). Classification methods pooled were accurately described in meta-analysis abstracts for 17 of 81 (21%) prevalence estimates. In 73 meta-analyses based on screening or rating tools or on combined methods, 52 (71%) described the prevalence as being for "depression" or "depressive disorders." Results were similar for meta-analyses in journals with impact factor ≥ 10.

CONCLUSIONS

Most meta-analyses combined estimates from studies that used screening tools or rating scales instead of diagnostic interviews, did not disclose this in abstracts, and described the prevalence as being for "depression" or "depressive disorders " even though disorders were not assessed. Users of meta-analyses of depression prevalence should be cautious when interpreting results because reported prevalence may exceed actual prevalence.

The over-representation of significant p values in abstracts compared to corresponding full texts: A systematic review of surgical randomized trials

Background

Abstracts are often the only read summaries of research findings, and it is essential that they accurately represent of the contents of the full text of the randomised control trial (RCT). We investigated whether outcomes in surgical trials were selectively reported in abstracts based on their statistical significance.

Objective

To compare the proportion of significant p-values reported in abstracts to their corresponding full texts in surgical RCTs.

Method

A Meta-analysis of 350 full text RCTs conducted on humans that compared a surgical intervention to any other intervention. An electronic search of MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) was conducted. All outcomes were extracted from the abstract and the full text. Frequency histograms were used to plot the distribution of numerically reported p-values across the statistical significance spectrum. For each RCT, a 2 × 2 table was populated with that trial's outcomes and whether the outcome was statistically significant (p < 0.05). From each 2 × 2 table, an odds ratio (OR) was calculated describing the association between statistical significance, and reporting in the abstract. ORs were pooled in random effects meta-analysis for an overall estimate of the association.

Results

A total of 8258 reported outcomes were included. Outcomes reported in a surgical RCT abstract had three times the odds of being significant when compared to the corresponding full text (OR = 3.0, 95% confidence interval 2.5–3.6, p < 0.001). This finding was consistent and not subject to heterogeneity (I² = 0%). Both histograms demonstrated a large drop in the frequency of reported p values between 0.04 and 0.05, and after the 0.06 thresholds.

Conclusions

Data presented in abstracts is biased to statistically significant outcomes. Clinicians and policy makers should do not rely solely on information presented in abstracts for their decision-making.