Preschoolers' body-knowledge inaccuracy: perceptual self-deficit and attitudinal bias

Body image research with young children has typically examined their body satisfaction and overlooked developmental theories pertaining to their emergent body-knowledge. Though existing research suggests that preschoolers do demonstrate anti-fat attitudes and weight-related stigmatisation, body dissatisfaction can be difficult to assess in preschoolers due to developmental differences in their (i) ability to perceive their actual body size accurately and (ii) make comparisons with a hypothetical ideal. We review current findings on the attitudinal component of body image in preschoolers, together with findings on the accuracy of their body size perceptions and their emergent body awareness abilities. Such an integration of the cognitive development literature is key to identifying when and how young children understand their physical size and shape; this in turn is critical for informing methodological design targeted at assessing body dissatisfaction and anti-fat attitudes in early childhood.

Economic Bias of Weather Forecasting: A Spatial Modeling Approach

The value of accurate weather forecast information is substantial. In this paper we examine competition among forecast providers and its implications for the quality of forecasts. A simple economic model shows that an economic bias geographical inequality in forecast accuracy arises due to the extent of the market. Using the unique data on daily high temperature forecasts for 704 U.S. cities, we find that forecast accuracy increases with population and income. Furthermore, the economic bias gets larger when the day of forecasting is closer to the target day; i.e. when people are more concerned about the quality of forecasts. The results hold even after we control for location-specific heterogeneity and difficulty of forecasting.

Bias and precision of measures of survival gain from right-censored data

In cost-effectiveness analyses of drugs or health technologies, estimates of life years saved or quality-adjusted life years saved are required. Randomised controlled trials can provide an estimate of the average treatment effect; for survival data, the treatment effect is the difference in mean survival. However, typically not all patients will have reached the endpoint of interest at the close-out of a trial, making it difficult to estimate the difference in mean survival. In this situation, it is common to report the more readily estimable difference in median survival. Alternative approaches to estimating the mean have also been proposed. We conducted a simulation study to investigate the bias and precision of the three most commonly used sample measures of absolute survival gain - difference in median, restricted mean and extended mean survival - when used as estimates of the true mean difference, under different censoring proportions, while assuming a range of survival patterns, represented by Weibull survival distributions with constant, increasing and decreasing hazards. Our study showed that the three commonly used methods tended to underestimate the true treatment effect; consequently, the incremental cost-effectiveness ratio (ICER) would be overestimated. Of the three methods, the least biased is the extended mean survival, which perhaps should be used as the point estimate of the treatment effect to be inputted into the ICER, while the other two approaches could be used in sensitivity analyses. More work on the trade-offs between simple extrapolation using the exponential distribution and more complicated extrapolation using other methods would be valuable.

Empirical evidence of recall bias for primary health care visits

BACKGROUND: While it is common for an economic evaluation of health care to rely on trial participants for self-reported health service utilisation, there is variability in the accuracy of this data due to potential recall bias. The aim of this study was to quantify the level of recall bias in self-reported primary health care general practitioner (GP) visits following inpatient rehabilitation over a 12 month period.

METHODS: This report is a secondary analysis from a larger randomised control trial of an economic evaluation of additional Saturday inpatient rehabilitation. Participants were adults who had been discharged into the community following admission to an acute general rehabilitation hospital. Participants were asked to recall primary health care visits, including community GP visits, via a telephone questionnaire which was administered at 6 and 12 months following discharge from inpatient rehabilitation. Participants were asked to recall health service utilisation over each preceding 6 month period. The self-reported data were compared to equivalent claims data from the national insurer, over the same period.

RESULTS: 751 participants (75% of the full trial) with a mean age of 74 years (SD 13) were included in this analysis. Over the 12 month period following discharge from rehabilitation there was an under-reporting of 14% in self-reported health service utilisation for GP visits compared to national insurer claims data over the same period. From 0 to 6 months following discharge from rehabilitation, there was an over-reporting of self-reported GP visits of 35% and from 7 to 12 months there was an under-reporting of self-reported GP visits of 36%, compared to national insurer claims data over the same period. 46% of patients reported the same or one number difference in self-reported GP visits between the 0 to 6 and the 7 to 12 month periods.

CONCLUSION: Based on these findings we recommend that an economic evaluation alongside a clinical trial for an elderly adult rehabilitation population include a sensitivity analysis that inflates self-reported GP visits by 16% over 12 months. However caution is required when utilising self-reported GP visits as the data may contain periods of both over and under reporting. Where general practitioner visits are expected to vary significantly between intervention and control groups we recommend that administrative data be included in the trial to accurately capture resources for an economic evaluation.

Cancer risk among people with type 1 and type 2 diabetes: disentangling true associations, detection bias, and reverse causation

 OBJECTIVE: Evidence indicates an increased risk of certain cancers among people with type 2 diabetes. Evidence for rarer cancers and for type 1 diabetes is limited. We explored the excess risk of site-specific cancer incidence and mortality among people with type 1 and type 2 diabetes, compared with the general Australian population. RESEARCH DESIGN AND METHODS: Registrants of a national diabetes registry (953,382) between 1997 and 2008 were linked to national death and cancer registries. Standardized incidence and mortality ratios (SIRs/SMRs) are reported. RESULTS: For type 1 diabetes, significant elevated SIRs were observed for pancreas, liver, esophagus, colon and rectum (females only [F]), stomach (F), thyroid (F), brain (F), lung (F), endometrium, and ovary, and decreased SIRs were observed for prostate in males. Significantly increased SMRs were observed for pancreas, liver, and kidney (males only), non-Hodgkin's lymphoma, brain (F), and endometrium. For type 2 diabetes, significant SIRs were observed for almost all site-specific cancers, with highest SIRs observed for liver and pancreas, and decreased risks for prostate and melanoma. Significant SMRs were observed for liver, pancreas, kidney, Hodgkin's lymphoma, gallbladder (F), stomach (F), and non-Hodgkin's lymphoma (F). Cancer risk was significantly elevated throughout follow-up time but was higher in the first 3 months postregistration, suggesting the presence of detection bias and/or reverse causation. CONCLUSIONS: Type 1 and type 2 diabetes are associated with an excess risk of incidence and mortality for overall and a number of site-specific cancers, and this is only partially explained by bias. We suggest that screening for cancers in diabetic patients is important.

Bias in peripheral depression biomarkers

BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect sizes has been conducted. METHODS: Here, we performed a comprehensive review of meta-analyses of peripheral nongenetic biomarkers that could discriminate individuals with MDD from nondepressed controls. PubMed/MEDLINE, EMBASE, and PsycINFO databases were searched through April 10, 2015. RESULTS: From 15 references, we obtained 31 eligible meta-analyses evaluating biomarkers in MDD (21,201 cases and 78,363 controls). Twenty meta-analyses reported statistically significant effect size estimates. Heterogeneity was high (I2 ≥ 50%) in 29 meta-analyses. We plausibly assumed that the true effect size for a meta-analysis would equal the one of its largest study. A significant summary effect size estimate was observed for 20 biomarkers. We observed an excess of statistically significant studies in 21 meta-analyses. The summary effect size of the meta-analysis was higher than the effect of its largest study in 25 meta-analyses, while 11 meta-analyses had evidence of small-study effects. CONCLUSIONS: Our findings suggest that there is an excess of studies with statistically significant results in the literature of peripheral biomarkers for MDD. The selective publication of 'positive studies' and the selective reporting of outcomes are possible mechanisms. Effect size estimates of meta-analyses may be inflated in this literature.

Social desirability bias in the reporting of alcohol consumption: a randomized trial

OBJECTIVE: To investigate reporting of alcohol consumption, we manipulated the contexts of questions in ways designed to induce social desirability bias. METHOD: We undertook a two-arm, parallel-group, individually randomized trial at an Australian public university. Students were recruited by email to a web-based "Research Project on Student Health Behavior." Respondents answered nine questions about their physical activity, diet, and smoking. They were unknowingly randomized to a group presented with either (A) three questions about their alcohol consumption or (B) seven questions about their alcohol dependence and problems (under a prominent header labeled "Alcohol Use Disorders Identification Test"), followed by the same three alcohol consumption questions from (A). RESULTS: A total of 3,594 students (mean age = 27, SD = 10) responded and were randomized: 1,778 to Group A and 1,816 to Group B. Outcome measures were the number of days they drank alcohol, the typical number of drinks they consumed per drinking day, and the number of days they consumed six or more drinks. The primary analysis included participants with any alcohol consumption in the preceding 4 weeks (1,304 in Group A; 1,340 in Group B) using between-group, two-tailed t tests. RESULTS: In Groups A and B, respectively, means (and SDs) of the number of days drinking were 5.89 (5.92) versus 6.06 (6.12), p = .49; typical number of drinks per drinking day: 4.02 (3.87) versus 3.82 (3.76), p = .17; and number of days consuming six or more drinks: 1.69 (2.94) versus 1.67 (3.25), p = .56. CONCLUSIONS: We could not reject the null hypothesis because earlier questions about alcohol dependence and problems showed no sign of biasing the respondents' subsequent reports of alcohol consumption. These data support the validity of university students' reporting of alcohol consumption in web-based studies.

A systemist approach to the analysis of gender gender bias in Iranian high school English textbooks

This chapter aims to see if English textbooks written for high school students in Iran are in favor of a particular gender. To this end, four English textbooks currently taught in the Iranian high schools were analysed on the basis of Systemic Functional Linguistics. Five categories were identified and two types of analyses were conducted- content analysis and linguistic. The result of the content analysis demonstrated a significant difference between the frequencies in male-female distribution. The linguistic analysis revealed that there are more males in theme and rheme positions as well as participants role, expecting for the Sensor role, The differences could be attributed to the writers' attitudes, culture, and patriarchal structure of the Iranian families.

Bias in emerging biomarkers for bipolar disorder

BACKGROUND: To date no comprehensive evaluation has appraised the likelihood of bias or the strength of the evidence of peripheral biomarkers for bipolar disorder (BD). Here we performed an umbrella review of meta-analyses of peripheral non-genetic biomarkers for BD. METHOD: The Pubmed/Medline, EMBASE and PsycInfo electronic databases were searched up to May 2015. Two independent authors conducted searches, examined references for eligibility, and extracted data. Meta-analyses in any language examining peripheral non-genetic biomarkers in participants with BD (across different mood states) compared to unaffected controls were included. RESULTS: Six references, which examined 13 biomarkers across 20 meta-analyses (5474 BD cases and 4823 healthy controls) met inclusion criteria. Evidence for excess of significance bias (i.e. bias favoring publication of 'positive' nominally significant results) was observed in 11 meta-analyses. Heterogeneity was high for (I 2 ⩾ 50%) 16 meta-analyses. Only two biomarkers met criteria for suggestive evidence namely the soluble IL-2 receptor and morning cortisol. The median power of included studies, using the effect size of the largest dataset as the plausible true effect size of each meta-analysis, was 15.3%. CONCLUSIONS: Our findings suggest that there is an excess of statistically significant results in the literature of peripheral biomarkers for BD. Selective publication of 'positive' results and selective reporting of outcomes are possible mechanisms.

Bias of damage awards and free options in securities litigation

Damage measures in securities fraud cases are very imprecise because they are based on security price changes that reflect both the correction of previous misrepresentation and other independent information. Consequently, potential plaintiffs have a valuable “free option” to decide whether or not to file suit, and average damage awards are greater than actual damages, much greater when markets are volatile. The “Private Securities Litigation Reform Act of 1995” was intended to curb abusive litigation and to address the problem of excessive damage awards. Motivated by a misdiagnosis that excess awards are due to temporary price drops, the Act limits damages to the difference between the purchase price and the time-averaged trading price from the release of the corrective information until 90 days later or until the sale of the security, whichever is first. Unfortunately, the Act's modified measure of damages suffers from a more severe free-option problem than did the traditional measure. Also, the Act introduced an additional new option to time the sale of the security; the effects of these options may be mitigated by the impact of the positive drift in stock prices over time, if the time-averaged price is not adjusted for market movements. As a result, the bias can be larger or smaller under the new Act, depending on how severe the free-option problem is. We propose an alternative approach to addressing the issue of excessive damages: courts should adopt a threshold of measured damages below which no damage would be awarded. The threshold would depend on several factors, most notably the volatility of the stock in the period under question. That is, damages will be awarded only if measured damages exceed the threshold, and awards would be capped by the formula presented in the Reform Act.