Reducing overestimation in reported mobile phone use associated with epidemiological studies

Case-control studies of mobile phones are commonly based on retrospective, self-reported exposure information, which are often characterized as involving substantial uncertainty concerning data validity. We assessed the validity of self-reported mobile phone use and developed a statistical model to account for the over-reporting of exposure. We collected information on mobile phone use from 70 volunteers using two sources of data: self-report in an interview and network operator records. We used regression models to obtain bias-corrected estimates of exposure. A correlation coefficient of 0.71 was obtained between the self-reported and the network operators' data on average calling time (log-transformed minutes per month). A simple linear regression model, where the duration of calls acquired from network operators is explained with the self-reported duration fitted the data reasonably well (adjusted R(2) 0.51). The constant term was 2.71 and the regression coefficient 0.49 (logarithmic scale). No significant improvement in the model fit was achieved by including potential predictors of accuracy in self-reported exposure estimates, such as the pattern of mobile phone use, the modality of response to the questionnaire or demographic characteristics. Overestimation in self-reported intensity of mobile phone use can be accounted for by the use of regression calibration. The estimates obtained in our study may not be applicable in other contexts, but similar methods could be used to reduce bias in other studies.     

Temperature biofeedback and relaxation training in the treatment of migraine headaches. One-year follow-up.

In a previous controlled group outcome study, a comparison of temperature biofeedback with progressive relaxation indicated that relaxation training was more effective in reducing migraine headache activity at the end of treatment. However, follow-up data obtained at 1, 2, and 3 months after the completion of treatment showed no difference between the two groups on any dependent measure. In the current study, 18 of 26 subjects who completed treatment in the original investigation collected headache data and completed a headache questionnaire 1 year subsequent to the conclusion of treatment in order to evaluate the long-term effectiveness of the two treatments. The results indicated that gains achieved in the reduction of headaches during both treatments were maintained at a 1-year follow-up. With the exception of medication consumption (for which relaxation training led to better long-term results) the 1-year follow-up data reveal no differential efficacy for temperature biofeedback or progressive relaxation in treating migraine headaches.     

Temperature biofeedback and relaxation training in the treatment of migraine headaches

In a previous controlled group outcome study, a comparison of temperature biofeedback with progressive relaxation indicated that relaxation training was more effective in reducing migraine headache activity at the end of treatment. However, follow-up data obtained at 1, 2, and 3 months after the completion of treatment showed no difference between the two groups on any dependent measure. In the current study, 18 of 26 subjects who completed treatment in the original investigation collected headache data and completed a headache questionnaire I year subsequent to the conclusion of treatment in order to evaluate the long-term effectiveness of the two treatments. The results indicated that gains achieved in the reduction of headaches during both treatments were maintained at a 1-year follow-up. With the exception of medication consumption (for which relaxation training led to better long-term results) the 1-year follow-up data reveal no differential efficacy for temperature biofeedback or progressive relaxation in treating migraine headaches.     

The effects of 884 MHz GSM wireless communication signals on headache and other symptoms: an experimental provocation study

Findings from prior studies of possible health and physiological effects from mobile phone use have been inconsistent. Exposure periods in provocation studies have been rather short and personal characteristics of the participants poorly defined. We studied the effect of radiofrequency field (RF) on self-reported symptoms and detection of fields after a prolonged exposure time and with a well defined study group including subjects reporting symptoms attributed to mobile phone use. The design was a double blind, cross-over provocation study testing a 3-h long GSM handset exposure versus sham. The study group was 71 subjects age 18-45, including 38 subjects reporting headache or vertigo in relation to mobile phone use (symptom group) and 33 non-symptomatic subjects. Symptoms were scored on a 7-point Likert scale before, after 1(1/2) and 2(3/4) h of exposure. Subjects reported their belief of actual exposure status. The results showed that headache was more commonly reported after RF exposure than sham, mainly due to an increase in the non-symptom group. Neither group could detect RF exposure better than by chance. A belief that the RF exposure had been active was associated with skin symptoms. The higher prevalence of headache in the non-symptom group towards the end of RF exposure justifies further investigation of possible physiological correlates. The current study indicates a need to better characterize study participants in mobile phone exposure studies and differences between symptom and non-symptom groups.     

Binary Regression Analysis with Pooled Exposure Measurements: A Regression Calibration Approach

Summary It has become increasingly common in epidemiological studies to pool specimens across subjects to achieve accurate quantitation of biomarkers and certain environmental chemicals. In this article, we consider the problem of fitting a binary regression model when an important exposure is subject to pooling. We take a regression calibration approach and derive several methods, including plug‐in methods that use a pooled measurement and other covariate information to predict the exposure level of an individual subject, and normality‐based methods that make further adjustments by assuming normality of calibration errors. Within each class we propose two ways to perform the calibration (covariate augmentation and imputation). These methods are shown in simulation experiments to effectively reduce the bias associated with the naive method that simply substitutes a pooled measurement for all individual measurements in the pool. In particular, the normality‐based imputation method performs reasonably well in a variety of settings, even under skewed distributions of calibration errors. The methods are illustrated using data from the Collaborative Perinatal Project.     

Latent variable models for harmonization of test scores: A case study on memory

Combining data from different studies has a long tradition within the scientific community. It requires that the same information is collected from each study to be able to pool individual data. When studies have implemented different methods or used different instruments (e.g., questionnaires) for measuring the same characteristics or constructs, the observed variables need to be harmonized in some way to obtain equivalent content information across studies. This paper formulates the main concepts for harmonizing test scores from different observational studies in terms of latent variable models. The concepts are formulated in terms of calibration, invariance, and exchangeability. Although similar ideas are present in measurement reliability and test equating, harmonization is different from measurement invariance and generalizes test equating. In addition, if a test score needs to be transformed to another test score, harmonization of variables is only possible under specific conditions. Observed test scores that connect all of the different studies, are necessary to be able to test the underlying assumptions of harmonization. The concepts of harmonization are illustrated on multiple memory test scores from three different Canadian studies.     

Next generation fluidized bed granulator automation

A system for fluidized bed granulator automation with in-line multichannel near infrared (NIR) moisture measurement and a unique air flow rate measurement design was assembled, and the information gained was investigated. The multivariate process data collected was analyzed using principal component analysis (PCA). The test materials (theophylline and microcrystalline cellulose) were granulated and the calibration behavior of the multichannel NIR set-up was evaluated against full Fourier Transform (FT) NIR spectra. Accurate and reliable process air flow rate measurement proved critical in controlling the granulation process. The process data describing the state of the process was projected in two dimensions, and the information from various trend charts was outlined simultaneously. The absorbence of test material at correction wavelengths (NIR region) and the nature of material-water interactions affected the detected in-line NIR water signal. This resulted in different calibration models for the test materials. Development of process analytical methods together with new data visualization algorithms creates new tools for in-process control of the fluidized bed granulation.     

The Contribution of Systematic Review and Meta-Analysis Methods to Human Health Risk Assessment: Neurobehavioral Effects of Manganese

Current methods of human health risk assessment may lack transparency in respect of identification, review, and synthesis of potentially relevant human and animal evidence. The nature, degree, and source of uncertainties are often unclear. This article aims to demonstrate the contribution that systematic review and meta-analysis methods can make to providing more structured, transparent, and systematic risk assessments. We focus on disparities between five risk assessments for neurobehavioral effects of manganese, and then illustrate advantages of a systematic approach. Fifty-five human epidemiological studies and 37 animal experiments were identified. Where appropriate, meta-analysis methods demonstrated consistent adverse effects associated with manganese exposure across species. In particular, there was reduced activity in subjects exposed to manganese, although exposed rats tended to be more active than controls. Limitations of exposure measurement and reporting restricted use of more quantitative methods of evidence synthesis. From a methodological viewpoint, we conclude that systematic review and meta-analysis methods can contribute to a more systematic and transparent human health risk assessment making more efficient use of available evidence, compared to current methods of risk assessment. More complex methods could encompass further differences between relevant studies and so further improve the risk assessment process.     

A force plate based method for the calibration of force/torque sensors

This study describes a novel calibration method for six-degrees-of-freedom force/torque sensors (FTsensors) using a pre-calibrated force plate (FP) as a reference measuring device. In this calibration method, the FTsensor is rigidly connected to a FP and force/torque data are synchronously recorded while a dynamic functional loading procedure is applied by the researcher. Based on these data an accurate calibration matrix for the FTsensor can easily be obtained via least-squares optimization. Using this calibration method, this study further investigated what loading methods are appropriate for the calibration of FTsensors intended for ambulatory measurement of ground reaction forces (GRFs). Seven different loading methods were compared (e.g., walking, pushing while standing on the FTsensor). Calibration matrices were calculated based on the raw data from the seven loading methods individually and all loading methods combined. Performance of these calibration matrices was subsequently compared in an in situ trial. During the in situ trial, five common work tasks (e.g., walking, manual lifting, pushing) were performed by an experimenter, while standing on the FP wearing a "ForceShoe" with two calibrated FTsensors attached to its sole. Root-mean-square differences (RMSDs) between the FTsensor and FP outcomes were calculated over all tasks. Using the calibration matrices based on all loading methods combined resulted in small RMSDs (GRF: <8 N, center of pressure: <2 mm). Using the calibration matrices based on "pushing against manual resistance" resulted in similar RMSDs, proving it to be the best single loading method.     

On measuring the response of mesophyll conductance to carbon dioxide with the variable J method

The response of mesophyll conductance to CO(2) (g(m)) to environmental variation is a challenging parameter to measure with current methods. The 'variable J' technique, used in the majority of studies of g(m), assumes a one-to-one relationship between photosystem II (PSII) fluorescence and photosynthesis under non-photorespiratory conditions. When calibrating this relationship for Populus trichocarpa, it was found that calibration relationships produced using variation in light and CO(2) were not equivalent, and in all cases the relationships were non-linear-something not accounted for in previous studies. Detailed analyses were performed of whether different calibration procedures affect the observed g(m) response to CO(2). Past linear and assumed calibration methods resulted in systematic biases in the fluorescence estimates of electron transport. A sensitivity analysis on modelled data (where g(m) was held constant) demonstrated that biases in the estimation of electron transport as small as 2% (～0.5 μmol m(-2) s(-1)) resulted in apparent changes in the relationship of g(m) to CO(2) of similar shape and magnitude to those observed with past calibration techniques. This sensitivity to biases introduced during calibrations leads to results where g(m) artefactually decreases with CO(2), assuming that g(m) is constant; if g(m) responds to CO(2), then biases associated with past calibration methods would lead to overestimates of the slope of the relationship. Non-linear calibrations were evaluated; these removed the bias present in past calibrations, but the method remained sensitive to measurement errors. Thus measurement errors, calibration non-linearities leading to bias, and the sensitivity of variable J g(m) hinders its use under conditions of varying CO(2) or light.     

The application of generalizability theory to surface electromyographic measurements during psychophysiological stress testing: how many measurements are needed?

Generalizability theory is an extension of classical reliability theory that allows multiple sources of measurement error in an experimental design to be investigated simultaneously. In the present study, generalizability theory was used to evaluate measurement error in psychophysiological test procedures used to differentiate tension headache patients from normal controls based upon measures of electromyographic (EMG) responding. Thirty-three subjects who met diagnostic criteria for tension-type headache and 40 normal control subjects who rarely or never experienced headache participated in two laboratory sessions. EMG activity of head and neck muscles was recorded while subjects performed baseline, relaxation, choice reaction time, psychomotor tracking, and cold pressor tasks. Variance components were computed for an experimental design having subjects nested within experimenters and crossed with sessions and replications. Generalizability coefficients were computed for combinations of various numbers of sessions and replications. The generalizability of EMG measures was highly variable, depending on the experimental conditions in force. The largest sources of measurement error were attributed to the unique responsiveness of individual subjects under a particular set of treatment conditions. For some stress tests currently in use, data from several testing sessions may need to be averaged in order to achieve acceptable levels of generalizability. Generalizability greater than 0.80 can be expected only rarely when data are collected during a single session. In the research setting, low generalizability may account for the failure of EMG-based stress tests to differentiate tension headache patients from controls during stressful task performance. In the clinical setting, the generalizability of information derived from "stress profiling" or muscle "scanning" techniques, which depend on results obtained during a single testing session, is doubtful.     

Poor-to-moderate agreement between self and proxy interviews of mobile phone use

In epidemiological studies, cases cannot always be interviewed due to them being too ill or already deceased. Under these circumstances, proxy interviews are often conducted; however, the veridicality of information about mobile phone use gained by proxy interviews has been doubted. The issue is undecided due to the lack of empirical data. We conducted a study of 119 heterosexual couples. Both partners answered two questionnaires about mobile phone use, one about their own use and one about their partner's use. Overall agreement assessed using Cohen's kappa, Passing and Bablok regression, and concordance coefficients between self and proxy data was poor to moderate (e.g., concordance coefficients of 0.55 for duration of use). The only item with good agreement was whether or not a prepaid phone was used (Cohen's kappa 0.78 and 0.63 for male and female estimates, respectively), and to a lesser degree, the onset of mobile phone use (concordance coefficients of 0.66 and 0.61). Poorest agreement was obtained for the side of the head the mobile phone was held during calls (kappa coefficients of 0.20 and 0.24 for female and male estimates, respectively). We conclude that the assessment of mobile phone use by proxy data cannot be relied on except for information about onset of mobile phone use, use of prepaid or contract phones, and, to a lesser degree, duration of daily use. Agreement concerning the important information about side of the head the mobile phone is held during calls was poorest and only slightly better than chance. Bioelectromagnetics 33:561–567, 2012. © 2012 Wiley Periodicals, Inc.     

Daily Rhythms in Mobile Telephone Communication

Circadian rhythms are known to be important drivers of human activity and the recent availability of electronic records of human behaviour has provided fine-grained data of temporal patterns of activity on a large scale. Further, questionnaire studies have identified important individual differences in circadian rhythms, with people broadly categorised into morning-like or evening-like individuals. However, little is known about the social aspects of these circadian rhythms, or how they vary across individuals. In this study we use a unique 18-month dataset that combines mobile phone calls and questionnaire data to examine individual differences in the daily rhythms of mobile phone activity. We demonstrate clear individual differences in daily patterns of phone calls, and show that these individual differences are persistent despite a high degree of turnover in the individuals’ social networks. Further, women’s calls were longer than men’s calls, especially during the evening and at night, and these calls were typically focused on a small number of emotionally intense relationships. These results demonstrate that individual differences in circadian rhythms are not just related to broad patterns of morningness and eveningness, but have a strong social component, in directing phone calls to specific individuals at specific times of day.     

Empirically simulated study to compare and validate sampling methods used in aerial surveys of wildlife populations

This paper compares the distribution, sampling and estimation of abundance for two animal species in an African ecosystem by means of an intensive simulation of the sampling process under a geographical information system (GIS) environment. It focuses on systematic and random sampling designs, commonly used in wildlife surveys, comparing their performance to an adaptive design at three increasing sampling intensities, using the root mean square errors (RMSE). It further assesses the impact of sampling designs and intensities on estimates of population parameters. The simulation is based on data collected during a prior survey, in which geographical locations of all observed animals were recorded. This provides more detailed data than that usually available from transect surveys. The results show precision of estimates to increase with increasing sampling intensity, while no significant differences are observed between estimates obtained under random and systematic designs. An increase in precision is observed for the adaptive design, thereby validating the use of this design for sampling clustered populations. The study illustrates the benefits of combining statistical methods with GIS techniques to increase insight into wildlife population dynamics.     

Accurate,reproducible measurement of blood pressure.

The diagnosis of mild hypertension and the treatment of hypertension require accurate measurement of blood pressure. Blood pressure readings are altered by various factors that influence the patient, the techniques used and the accuracy of the sphygmomanometer. The variability of readings can be reduced if informed patients prepare in advance by emptying their bladder and bowel, by avoiding over-the-counter vasoactive drugs the day of measurement and by avoiding exposure to cold, caffeine consumption, smoking and physical exertion within half an hour before measurement. The use of standardized techniques to measure blood pressure will help to avoid large systematic errors. Poor technique can account for differences in readings of more than 15 mm Hg and ultimately misdiagnosis. Most of the recommended procedures are simple and, when routinely incorporated into clinical practice, require little additional time. The equipment must be appropriate and in good condition. Physicians should have a suitable selection of cuff sizes readily available; the use of the correct cuff size is essential to minimize systematic errors in blood pressure measurement. Semiannual calibration of aneroid sphygmomanometers and annual inspection of mercury sphygmomanometers and blood pressure cuffs are recommended. We review the methods recommended for measuring blood pressure and discuss the factors known to produce large differences in blood pressure readings.     

Systematic bias and the phylogeny of Coleoptera—A response to Cai et al. (2022) following the responses to Cai et al. (2020)

Systematic bias is one of the major phylogenetic issues arising over the last two decades. Using methods designed to reduce compositional and rate heterogeneity, hence systematic bias, Cai and co-workers (2022) (= CEA22) reanalyzed the DNA sequence dataset for Coleoptera of Zhang et al. (2018) (= ZEA). CEA22 suggest that their phylogenetic results and major evolutionary hypotheses about the Coleoptera should be favoured over other recently published studies. Here, we discuss the methodology of CEA22 with particular attention to how their perfunctory reanalysis of ZEA obfuscates rather than illuminates beetle phylogeny. Similar to published rebuttals of an earlier study of theirs, we specifically find that many of their claims are misleading, unsupported, or false. Critically, CEA22 fail to establish the stated premise for their reanalysis. They fail to demonstrate how composition or rate heterogeneity supposedly impacted the phylogeny estimate of ZEA, let alone the results of other recent studies. Moreover, despite their claim of comprehensive sampling of Coleoptera, their dataset is neither the most diverse with respect to species and higher taxa included, nor anywhere near the largest in terms of sequence data and sampled loci. Although CEA22 does contribute additional fossils for calibration, those seeking the best available estimate for Coleoptera phylogeny and evolution based on molecular data are advised to look elsewhere.     

Biases in Multicenter Longitudinal PET Standardized Uptake Value Measurements

This study investigates measurement biases in longitudinal positron-emission tomography/computed tomography (PET/CT) studies that are due to instrumentation variability including human error. Improved estimation of variability between patient scans is of particular importance for assessing response to therapy and multicenter trials. We used National Institute of Standards and Technology-traceable calibration methodology for solid germanium-68/gallium-68 (⁶⁸Ge/⁶⁸Ga) sources used as surrogates for fluorine-18 (¹⁸F) in radionuclide activity calibrators. One cross-calibration kit was constructed for both dose calibrators and PET scanners using the same 9-month half-life batch of ⁶⁸Ge/⁶⁸Ga in epoxy. Repeat measurements occurred in a local network of PET imaging sites to assess standardized uptake value (SUV) errors over time for six dose calibrators from two major manufacturers and for six PET/CT scanners from three major manufacturers. Bias in activity measures by dose calibrators ranged from -50% to 9% and was relatively stable over time except at one site that modified settings between measurements. Bias in activity concentration measures by PET scanners ranged from -27% to 13% with a median of 174 days between the six repeat scans (range, 29 to 226 days). Corresponding errors in SUV measurements ranged from -20% to 47%. SUV biases were not stable over time with longitudinal differences for individual scanners ranging from -11% to 59%. Bias in SUV measurements varied over time and between scanner sites. These results suggest that attention should be paid to PET scanner calibration for longitudinal studies and use of dose calibrator and scanner cross-calibration kits could be helpful for quality assurance and control.     

A Robust Bayesian Random Effects Model for Nonlinear Calibration Problems

Summary In the context of a bioassay or an immunoassay, calibration means fitting a curve, usually nonlinear, through the observations collected on a set of samples containing known concentrations of a target substance, and then using the fitted curve and observations collected on samples of interest to predict the concentrations of the target substance in these samples. Recent technological advances have greatly improved our ability to quantify minute amounts of substance from a tiny volume of biological sample. This has in turn led to a need to improve statistical methods for calibration. In this article, we focus on developing calibration methods robust to dependent outliers. We introduce a novel normal mixture model with dependent error terms to model the experimental noise. In addition, we propose a reparameterization of the five parameter logistic nonlinear regression model that allows us to better incorporate prior information. We examine the performance of our methods with simulation studies and show that they lead to a substantial increase in performance measured in terms of mean squared error of estimation and a measure of the average prediction accuracy. A real data example from the HIV Vaccine Trials Network Laboratory is used to illustrate the methods.     

Bias-free estimation of information content in temporally sparse neuronal activity

Applying information theoretic measures to neuronal activity data enables the quantification of neuronal encoding quality. However, when the sample size is limited, a naïve estimation of the information content typically contains a systematic overestimation (upward bias), which may lead to misinterpretation of coding characteristics. This bias is exacerbated in Ca²⁺ imaging because of the temporal sparsity of elevated Ca²⁺ signals. Here, we introduce methods to correct for the bias in the naïve estimation of information content from limited sample sizes and temporally sparse neuronal activity. We demonstrate the higher accuracy of our methods over previous ones, when applied to Ca²⁺ imaging data recorded from the mouse hippocampus and primary visual cortex, as well as to simulated data with matching tuning properties and firing statistics. Our bias-correction methods allowed an accurate estimation of the information place cells carry about the animal’s position (spatial information) and uncovered the spatial resolution of hippocampal coding. Furthermore, using our methods, we found that cells with higher peak firing rates carry higher spatial information per spike and exposed differences between distinct hippocampal subfields in the long-term evolution of the spatial code. These results could be masked by the bias when applying the commonly used naïve calculation of information content. Thus, a bias-free estimation of information content can uncover otherwise overlooked properties of the neural code.     

Impact of random and systematic recall errors and selection bias in case--control studies on mobile phone use and brain tumors in adolescents (CEFALO study)

Whether the use of mobile phones is a risk factor for brain tumors in adolescents is currently being studied. Case--control studies investigating this possible relationship are prone to recall error and selection bias. We assessed the potential impact of random and systematic recall error and selection bias on odds ratios (ORs) by performing simulations based on real data from an ongoing case--control study of mobile phones and brain tumor risk in children and adolescents (CEFALO study). Simulations were conducted for two mobile phone exposure categories: regular and heavy use. Our choice of levels of recall error was guided by a validation study that compared objective network operator data with the self-reported amount of mobile phone use in CEFALO. In our validation study, cases overestimated their number of calls by 9% on average and controls by 34%. Cases also overestimated their duration of calls by 52% on average and controls by 163%. The participation rates in CEFALO were 83% for cases and 71% for controls. In a variety of scenarios, the combined impact of recall error and selection bias on the estimated ORs was complex. These simulations are useful for the interpretation of previous case-control studies on brain tumor and mobile phone use in adults as well as for the interpretation of future studies on adolescents.