Accuracy Of Self-reported Data Research Articles

Expanding the methodological toolbox: Machine-based item desirability ratings as an alternative to human-based ratings

The accuracy of self-reported data in the social and behavioral sciences may be compromised by response biases such as socially desirable responding. Researchers and scale developers therefore obtain item desirability ratings, in order to maintain item neutrality, and parity with alternative options when creating forced-choice items. Gathering item desirability ratings from human judges can be time-consuming and costly, with no consistent guidelines with regard to required sample size and composition. However, recent advancements in natural language processing have yielded large language models (LLMs) with exceptional abilities to identify abstract semantic attributes in text. The presented research highlights the potential application of LLMs to estimate the desirability of items, as evidenced by the re-analysis of data from 14 distinct studies. Findings indicate a significant and strong correlation between human- and machine-rated item desirability of .80, across 521 items. Results furthermore showed that the proposed fine-tuning approach of LLMs results in predictions that explained 19 % more variance beyond that of sentiment analysis. These results demonstrate the feasibility of relying on machine-based item desirability ratings as a viable alternative to human-based ratings and contribute to the field of personality psychology by expanding the methodological toolbox available to researchers, scale developers, and practitioners.

A Survey Bias Index Based on Unmanned Aerial Vehicle Imagery to Review the Accuracy of Rural Surveys

Field surveys and questionnaires are a cornerstone of rural socioeconomic research, providing invaluable firsthand data regarding on-the-ground situations. However, cost-effective and efficient methods for validating the accuracy of self-reported data in such questionnaires are lacking. Biased data are likely to lead to incorrect conclusions. In this study, we propose a new index, the survey bias index (SBI), for evaluating the degree of survey bias in field surveys. This index was obtained by comparing the data recorded in questionnaires with those from portable unmanned aerial vehicles (UAVs). In a case study, we employed SBI to reveal the degree of survey bias of questionnaires in field surveys on rural homesteads. The SBI of self-reported areas of rural homesteads reached 0.439, implying that 43.9% of data were significantly different from those collected using UAVs. A greater SBI was obtained in the pre-urban zone (0.515) than in the pure rural zone (0.258). These results indicate that homestead areas in the pre-urban zone have more incentive to expand than those in the pure rural zone. UAV remote sensing can strongly support research in the field of social economy, which reveals key information hidden in field surveys and questionnaires.

Novel insights into the molecular mechanisms underlying risk of colorectal cancer from smoking and red/processed meat carcinogens by modeling exposure in normal colon organoids.

Tobacco smoke and red/processed meats are well-known risk factors for colorectal cancer (CRC). Most research has focused on studies of normal colon biopsies in epidemiologic studies or treatment of CRC cell lines in vitro. These studies are often constrained by challenges with accuracy of self-report data or, in the case of CRC cell lines, small sample sizes and lack of relationship to normal tissue at risk. In an attempt to address some of these limitations, we performed a 24-hour treatment of a representative carcinogens cocktail in 37 independent organoid lines derived from normal colon biopsies. Machine learning algorithms were applied to bulk RNA-sequencing and revealed cellular composition changes in colon organoids. We identified 738 differentially expressed genes in response to carcinogens exposure. Network analysis identified significantly different modules of co-expression, that included genes related to MSI-H tumor biology, and genes previously implicated in CRC through genome-wide association studies. Our study helps to better define the molecular effects of representative carcinogens from smoking and red/processed meat in normal colon epithelial cells and in the etiology of the MSI-H subtype of CRC, and suggests an overlap between molecular mechanisms involved in inherited and environmental CRC risk.

Consistently biased: documented consistency in self-reported holiday healthfulness behaviors and associated social desirability bias

Holiday healthfulness conversations are dominated by overindulgence of consumption and then, largely in reference to resolutions to do better, physical activity, and exercise aspirations. Consistency was found in self-reported agreement with a series of holiday healthfulness statements, across time, holidays (Thanksgiving versus Christmas), and samples of respondents. The largest proportion of respondents displaying social desirability bias (SDB) were found in response to two statements, namely “I will consume more alcohol during the holiday season than at other times of the year” at (63–66%) and “I make it a New Year’s Resolution to lose weight” (60–63%). Cheap talk was tested as a mechanism to reduce SDB in holiday healthfulness reporting, but showed only limited efficacy compared to the control group surveyed simultaneously. Nonetheless, the consistency across time in reporting and SDB are notable in both self-reporting of health-related data and in studying a unique consumption period around the holidays. Healthcare providers and researchers alike seek to improve the accuracy of self-reported data, making understanding of biases in reporting on sensitive topics, such as weight gain and eating over the holiday season, of particular interest.

Understanding Physical Activity (PA) in College Students: A Comparison of Self-Reported and Objective Measures

Abstract Date Presented 03/27/20 The purpose of this study was to compare perceived PA levels as reported by college students to actual PA levels measured by an actigraph. Preliminary analysis of 15 participants showed weekly averages of moderate PA that meet the activity guidelines by the US Surgeon General. Additional findings regarding the accuracy of self-reported data will also be presented. Primary Author and Speaker: Elena Donoso Brown Additional Authors and Speakers: Caroline Crilly, Aubrey Boucher Contributing Authors: Kimberly Szucs, Kelly Burton, Natalie Falcione

Self-monitoring of lower leg skin temperature: accuracy of self-reported data and adherence to a cooling protocol for the prevention of venous leg ulcers.

BackgroundFor intervention studies that require the use of participant self-reports, the quality and accuracy of recorded data and variability in participant adherence rates to the treatment can cause significant outcome bias.PurposeTo assess the quality and accuracy of participant documentation of daily self-monitoring of leg skin temperature, adherence to a graduated cooling treatment protocol to prevent venous leg ulcers, and the potential for bias in treatment effect in a randomized controlled trial that included a population with chronic venous disease.MethodsIndividuals were randomized to a leg cooling intervention or placebo treatment group to daily self-monitor and record lower leg skin temperature over a 9-month period on monthly paper study logs. Returned study logs for the first 100 completed participants (n=54 cooling intervention, n=46 control) were reviewed for quality and accuracy. Adherence was determined from evaluating the accuracy of participant documentation. To examine potential outcome bias in treatment effect, mean between group and within group comparisons of the before and after treatment differences were conducted using an intention-to-treat (ITT) versus a modified intention-to-treat (mITT) analysis approach with an 85% accuracy cut-off rate. Data were collected in 2011–2014.ResultsOf the expected 900 study logs, 91.8% (826/900) were returned and 8.2% (74/900) were not. Non-mutually exclusive main error types in returned documentation included: 59.2% (489/826) white-outs, cross-off and/or overwrites, 34.9% (288/826) entries omitted, 29.4% (243/826) no performance of daily self-monitoring, 28.7% (237/826) no performance of the treatment intervention per the prescribed protocol regime, 26.8% (221/826) extraneous data, 8.6% (71/826) suspected fabrication, and 7.6% (63/826) questionable validity. Under ITT analysis, 38.4% (346/900) of all returned logs were <85% accurate, 25.0% (225/900) were 85%–99% accurate, and 36.6% (329/900) were 100% accurate. Mean overall participant adherence rates were: 22.0% at <85% accuracy, 53.0% at 85%–99% accuracy, and 25.0% at 100% accuracy. Under the mITT analysis, 54.0% (483/900) of returned logs were deemed adherent with ≥85% accuracy.ConclusionThis study found good rates of adherence. Under ITT analysis, 78.0% of participants were deemed adherent to the study protocol with ≥85% accuracy in documenting daily self-monitoring of skin temperatures in response to a topically applied experimental cooling cuff intervention for the prevention of venous leg ulcers.

The Need for Biological Outcomes to Complement Self-Report in Adolescent Research.

* Abbreviations: HIV — : human immunodeficiency virus PSA — : prostate-specific antigen STD — : sexually transmitted disease Yc-PCR — : Y-chromosome polymerase chain reaction Adolescents’ self-reported health behaviors inform medical care and serve as primary intervention outcome measures. Strategies to bolster the validity and reliability of self-report combined with objective biological markers of behavior are urgently needed. We illustrate such strategies within the context of adolescent sexual health research. Research that informs human immunodeficiency virus (HIV) and sexually transmitted disease (STD) prevention efforts and public health policy involves many challenges. One key challenge is the accurate measurement of HIV risk behaviors, particularly sexual behaviors. Adolescent HIV risk reduction intervention trials have relied mainly on outcomes measured via participants’ self-reports of past behavior to evaluate programmatic efficacy. Few trials have complemented participant self-report with biological measures of sexual behaviors (eg, laboratory-confirmed STDs). Indeed, of the 20 US Centers for Disease Control and Prevention evidence-based interventions for adolescents, only 4 have included biological outcomes as trial end points in addition to self-reported measures.1 Although adolescents’ self-reported behaviors have been the most widely measured trial end points, the accuracy of self-report data may be affected by myriad factors, including the cognitive demands of recalling past behaviors and motivational biases that can lead adolescents to misreport behavior.2 Furthermore, inconsistencies between self-reported sexual behaviors and biological end points raise questions about the validity of relying solely on self-report to evaluate the efficacy of HIV risk reduction interventions. Thus, a need exists to both improve the validity of self-report and to integrate biological markers of sexual risk behaviors into future adolescent HIV risk reduction interventions. Motivational biases may result in distortion of self-reported past behaviors to avoid shame or embarrassment or to appear in a more favorable light. … Address correspondence to Jennifer L. Brown, PhD, Department of Psychological Sciences, Texas Tech University, MS 2051, Lubbock, TX 79409-2051. E-mail: jennifer.brown{at}ttu.edu

Impact of Data Editing Methods on Estimates of Smoking Prevalence, Global Youth Tobacco Survey, 2007–2009

Accuracy of self-reported data may be improved by data editing, a mechanism to produce accurate information by excluding inconsistent data based on a set number of predetermined decision rules. We compared data editing methods in the Global Youth Tobacco Survey (GYTS) with other editing approaches and evaluated the effects of these on smoking prevalence estimates. We evaluated 5 approaches for handling inconsistent responses to questions regarding cigarette use: GYTS, do-nothing, gatekeeper, global, and preponderance. Compared with GYTS data edits, the do-nothing and gatekeeper approaches produced similar estimates, whereas the global approach resulted in lower estimates and the preponderance approach, higher estimates. Implications for researchers using GYTS include recognition of the survey’s data editing methods and documentation in their study methods to ensure cross-study comparability.

Validity of self-reported use of sulphadoxine-pyrimethamine intermittent presumptive treatment during pregnancy (IPTp): a cross-sectional study

BackgroundMalaria in pregnancy is a major health problem that can cause maternal anaemia, stillbirth, spontaneous abortion, low birth weight and intra-uterine stunting. The WHO recommends use of sulphadoxine-pyrimethamine (SP) for intermittent preventive treatment of malaria during pregnancy (IPTp) in endemic areas. Towards monitoring and assessing IPTp coverage in the population, the Roll Back Malaria Partnership recommends the use of self-reported data. The aim of this study was to assess the validity of self-reported IPTp by testing for sulphadoxine in maternal blood at delivery.MethodsTwo hundred and four pregnant women were consented and enrolled in a cross-sectional study in Mulago National Referral Hospital in Kampala Uganda. - Participants who reported a history of taking sulpha-containing drugs like co-trimoxazole , those who were not sure of dates relating to last menstrual period or who took IPTp within the first 20 weeks of gestation were excluded from the study. Data on demographic characteristics, obstetric history, and delivery outcome were collected. At birth, maternal venous blood was taken off aseptically and used to make thick blood smears for malaria parasites and plasma for determining sulphadoxine using high performance liquid chromatography (HPLC).ResultsOf 120 participants who self reported to have used IPTp, 35 (29.2%) tested positive for sulphadoxine by HPLC, while 63 (75%) of 84 patients who reported not having used IPTp tested negative for sulphadoxine. Participants possessing post-primary education were more likely to have reported using IPTp. The low agreement (kappa coefficient = 0.037) between self-report and actual presence of the drug in the blood casts doubt on the validity of self-reported data in estimating IPTp coverage.ConclusionsThe results of this study question the accuracy of self-reported data in estimating IPTp coverage in the population. More studies on validity of self reported data are recommended. Since the validity of IPTp self reports is vital for guiding policy on malaria control in pregnancy, ways should be sought to improve accuracy of the information from such reports.

Recruitment into diabetes prevention programs: what is the impact of errors in self-reported measures of obesity?

BackgroundError in self-reported measures of obesity has been frequently described, but the effect of self-reported error on recruitment into diabetes prevention programs is not well established. The aim of this study was to examine the effect of using self-reported obesity data from the Finnish diabetes risk score (FINDRISC) on recruitment into the Greater Green Triangle Diabetes Prevention Project (GGT DPP).MethodsThe GGT DPP was a structured group-based lifestyle modification program delivered in primary health care settings in South-Eastern Australia. Between 2004–05, 850 FINDRISC forms were collected during recruitment for the GGT DPP. Eligible individuals, at moderate to high risk of developing diabetes, were invited to undertake baseline tests, including anthropometric measurements performed by specially trained nurses. In addition to errors in calculating total risk scores, accuracy of self-reported data (height, weight, waist circumference (WC) and Body Mass Index (BMI)) from FINDRISCs was compared with baseline data, with impact on participation eligibility presented.ResultsOverall, calculation errors impacted on eligibility in 18 cases (2.1%). Of n = 279 GGT DPP participants with measured data, errors (total score calculation, BMI or WC) in self-report were found in n = 90 (32.3%). These errors were equally likely to result in under- or over-reported risk. Under-reporting was more common in those reporting lower risk scores (Spearman-rho = −0.226, p-value < 0.001). However, underestimation resulted in only 6% of individuals at high risk of diabetes being incorrectly categorised as moderate or low risk of diabetes.ConclusionsOverall FINDRISC was found to be an effective tool to screen and recruit participants at moderate to high risk of diabetes, accurately categorising levels of overweight and obesity using self-report data. The results could be generalisable to other diabetes prevention programs using screening tools which include self-reported levels of obesity.

The accuracy of self-reported fisheries data: Oregon trawl logbook fishing locations and retained catches

Self-reporting of information is an inexpensive means for collecting data on fishing or other human activities, but the accuracy of self-reported data can be difficult to measure. Logbooks that record fishing activities are a common form of self-reporting that can provide vast amounts of information about a fishery. Using logbook data from trawlers from Oregon ports operating along the US Pacific coast during 1987–2001, this study examined (a) the consistency of reported tow locations and bottom depths and (b) the accuracy of reported retained catches of four groundfish species groups. Because logbook data during this period played no direct role in fishery management or stock assessments, there were no obvious incentives for trawl captains to deliberately report false logbook information. To evaluate consistency between tow locations and corresponding bottom depths, each tow was assigned to a 100-m bottom depth-band based on the reported tow location on a digital chart. The depth-bands based on the tow locations were then compared one-to-one with the depths reported in the logbooks and analysed to determine factors (e.g., year, quarter, vessel) contributing to the consistency between the reported locations and depths. Consistency was highest in the shallowest depth-bands and there was a strong interaction between depth and vessel. To evaluate the accuracy of the retained catches reported by the captains, the tow-by-tow logbook data were summed to the fishing-trip-level and compared to the official landing weights, recorded at the fish processing plants when the catches were off-loaded and weighed. The logbook weights relative to the corresponding official landing weights were analysed using zero-inflated generalized Poisson (ZIGP) regression models to determine factors (year, quarter, vessel) that were important explanatory variables. The analysis found strong year, quarter, and vessel effects for all three parts of the ZIGP: the mean value, the dispersion, and the proportion of zeros. The vessel effect was strongest. In a combined analysis, based on results from the other two analyses, vessels that were consistent in recording their depths and fishing locations had only a weak tendency to be accurate in recording their catches.

Concordance of self- and program-reported rates of cardiac rehabilitation referral, enrollment and participation

Despite potential bias, researchers often rely on patient self-reported data of health care use. However, the validity and accuracy of self-reported data on cardiac rehabilitation (CR) use are unknown. To assess the concordance between patient self-report and site-verified CR referral, enrollment and participation. A consecutive sample of 661 coronary artery disease inpatients (mean [+/- SD] age 61.27+/-1.31 years; 157 women [23.8%]) treated at three acute care sites was recruited (75% response rate) as part of a larger study comparing automatic with usual referral methods. CR referral, enrollment (attendance at intake assessment) and participation (percentage of program attended) were discerned in a mailed survey nine months following discharge (n=506; 84.3% retention). A total of 24 CR sites were contacted for verification. A total of 276 participants (54.5%) self-reported CR referral, and CR sites verified receipt of 262 referrals (51.8%) (Cohen's kappa 0.899). A total of 232 participants (45.8%) self-reported CR enrollment, with site-verification for 208 participants (41.1%) (Cohen's kappa 0.846). Self-reported data indicated that participants attended a mean of 81.78+/-25.84% of prescribed CR sessions, with CR sites reporting that participants completed 80.75+/-31.27% of the program (r=0.662; P<0.001). Equivalency testing revealed that the self-reported and site-verified rates of program participation were equivalent (z<1.96). The almost perfect agreement between the self-reported and site-verified use of CR services suggests that self-administered items are highly valid in this population.

Overweight and obesity from childhood to adulthood: a follow‐up of participants in the 1985 Australian Schools Health and Fitness Survey

To examine overweight and obesity in Australian children followed through to adulthood. A cohort study of 8498 children aged 7-15 years who participated in the 1985 Australian Schools Health and Fitness Survey; of these, 2208 men and 2363 women completed a follow-up questionnaire at age 24-34 years in 2001-2005. Height and weight were measured in 1985, and self-reported at follow-up. The accuracy of self-reported data was checked in 1185 participants. Overweight and obesity in childhood were defined according to international standard definitions for body mass index (BMI), and, in adulthood, as a BMI of 25-29.9 and > or =30 kg/m2, respectively, after correcting for self-report error. In those with baseline and follow-up data, the prevalence of overweight and obesity in childhood was 8.3% and 1.5% in boys and 9.7% and 1.4% in girls, respectively. At follow-up, the prevalence was 40.1% and 13.0% in men and 19.7% and 11.7% in women. The relative risk (RR) of becoming an obese adult was significantly greater for those who had been obese as children compared with those who had been a healthy weight (RR = 4.7; 95% CI, 3.0-7.2 for boys and RR = 9.2; 95% CI, 6.9-12.3 for girls). The proportion of adult obesity attributable to childhood obesity was 6.4% in males and 12.6% in females. Obesity in childhood was strongly predictive of obesity in early adulthood, but most obese young adults were a healthy weight as children.

Lower agreement on behavioral factors than on medical conditions in self-reported data among pregnant latina women

Background Agreement between self-reported data and data obtained from medical records is far from perfect and few studies have analyzed the element of language when self-reported data are given in one language and this information is recorded in another language in the medical record. Our objective was to assess agreement between self-reported data and medical record data with regard to prenatal risk factors in pregnant Latina women. Methods We interviewed 350 Latina women at ≥20 weeks' gestation regarding alcohol use, tobacco use, use of prenatal vitamins, age, education, use of prenatal care, and medical conditions. Kappa statistic (κ) and 95% confidence intervals (95% CIs) were used to calculate agreement between self-reported responses and medical record data. Multiple logistic regression analysis was used to evaluate effect of maternal characteristics on likelihood of disagreement. Results Agreement between self-reported and medical record data was generally lower for behavioral factors (alcohol κ = 0.37 and prenatal vitamin use κ = 0.09) than for medical conditions (anemia κ = 0.63, gestational diabetes κ = 0.83, and hypertension κ = 0.68). In general, maternal characteristics did not significantly predict patterns of disagreement. Conclusions Among pregnant Latina women, self-reported data on behavioral factors had lower agreement than self-reported data on medical conditions. Further study is needed to define the effect of other factors, such as social norms, on accuracy of self-reported data during pregnancy.

Comparison of self-report versus agency records of service utilization in a community sample of individuals with alcohol use disorders

Health services research has become an important area for evaluating the cost effectiveness of interventions. When used in treatment outcome research, the accuracy of self-report data is essential. The reliability and validity of self-report service utilization among alcohol and drug addicted individuals is questionable and largely unexplored. This study assessed the accuracy of self-report utilization of services compared to service record abstraction in a sample of treatment seeking individuals with alcohol use disorders. The results of the comparative analysis found that the level of agreement for some services, particularly medical, psychiatric and substance abuse inpatient admissions, and social service involvement was good. There was less agreement in emergency room visits and arrests. Factors related to discrepancies between self-report and records were explored.

The Validity of Self-Reported Criminal Arrest History Among Clients of a Psychiatric Probation and Parole Service

Self-report data have consistently demonstrated acceptable reliability and validity in prior studies by exhibiting high correlations with other criterion related measures of criminal frequency and arrest history. Mental health factors and substance abuse factors are suspected to affect the quality and accuracy of self-reported data. This analysis sought to examine the impact of major mental illness and substance abuse factors on the validity of self-reported criminal history data as given by clients of a psychiatric probation and parole service. After controlling for socio-de-mographic variables, the number of officially recorded arrests, high number of lifetime hospitalizations and overall years spent in jail significantly explained the number of self-reported arrests. The predominance of the official record in explaining self-reported arrest history suggests that self-reported arrest history data given by a psychiatric offender population is as valid as that given by general offender populations. Substance abuse factors and mental illness factors did not affect the quality and accuracy of self-reported arrest history.

Stigmatized Behaviors, Cultural Context, and Accuracy of Self-Reported Data in the STD Field

Stigmatized Behaviors, Cultural Context, and Accuracy of Self-Reported Data in the STD Field

Self-measurement of blood glucose. Accuracy of self-reported data and adherence to recommended regimen.

Reflectance meters containing memory chips were used in a study that addressed several questions concerning routine use of self-monitoring of blood glucose (SMBG), including accuracy of patient blood glucose (BG) diaries, reliability of self-reported frequency of SMBG, and adherence to recommended SMBG regimen. Thirty adults with insulin-dependent diabetes used memory meters and recorded test results in diaries for 2 wk while performing their normal SMBG regimen. Analysis of glucose diaries showed that only 23% of the subjects had no diary errors and 47% had clinically accurate diaries (less than 10% error rate). The most common types of errors were omissions of values contained in meter memory and additions of values not contained in meter memory, with significantly more omissions than additions. Alterations of test values (e.g., changing a 300-mg/dl reading to 200 mg/dl) were extremely rare. There was no difference in the rate of errors that resulted in a more positive clinical profile (omitting unacceptable values and adding acceptable values) or a more negative clinical profile (omitting acceptable values and adding unacceptable values). Examination of the actual frequency of SMBG showed that most subjects (56.6%) measured their BG an average of two to three times each day. Self-report of SMBG frequency correlated with both actual frequency and HbA1. Although actual frequency of SMBG was not related to physicians' recommendations, the majority (64%) of subjects were self-testing as often or more often than they had been instructed.

Self-Understanding and the Accuracy of Behavioral Expectations

While Nisbett and Wilson (1977) and other researchers (e.g., Ericsson &amp; Simon, 1980) argue about the accuracy of self-reported data, the distinction between the ability and the willingness to accurately self-report has been somewhat overlooked. Namely, issues of self-understanding must be differentiated from those of self-presentation. Further, self-understanding that relates to specific behavioral domains must be differentiated from general self-understanding. The present article argues that general self-understanding is a potentially important individual difference variable that has been neglected in the literature. The relationship between general self-understanding and the accuracy of self-reported behavioral expectations is discussed and provocative preliminary findings are reported that suggest that further research on the topic is warranted.

The Accuracy of Self-Reported Data and Prediction of Political Activity

Misreported information, whether deliberately falsified or not, constitutes a source of error in most, if not all, surveys. Methodological procedures have been developed to handle the difficulties created by misinformation, and the sophisticated researcher has at his disposal a variety of techniques designed to minimize the adverse effect of invalid responses. In a gross sense, these procedures and techniques have been designed with one or both of the following problems in mind: (1) preventing the occurrence of misinformation, or (2) assessing the influence of misinformation after it has occurred. The present note is addressed to the second of these general problems. A problem frequently facing the survey researcher is that of employing a set of independent variables in an effort to describe or predict variation on some dependent variable. While error can have a number of important consequences and can enter into the situation in a variety of ways, one fundamental instance involves the case where misinformation influences the classification of respondents in terms of the dependent variable. For example, in determining the correlates of voting behavior, self-reports of such behavior have been utilized. In such instances, voters are composed of two classes of respondents: (1) those who report they have voted and who actually have voted, and (2) those who report they have voted but who actually have not voted. Under such circumstances, three questions are of particular interest. First, what is the character of the sub-population of misinformants? Second, how does such measurement error with respect to the dependent variable affect the ability to make predictions concerning that variable? Third, what is the utility of using a single item to identify inaccurate informants? The data employed in addressing these questions were derived from a larger study of the use of attitude measures as predictors of student political behavior. Attitude toward personal participation in student politics was measured using five different measurement approaches.' In addition, five indexes of political behavior were con-