Measurement Bias Research Articles

The Impact of Sparse Datasets When Harmonizing Data from Studies with Different Measures of the Same Construct.

Prevention science has increasingly turned to integrative data analysis (IDA) to combine individual participant-level data from multiple studies of the same topic, allowing us to evaluate overall effect size, test and model heterogeneity, and examine mediation. Studies included in IDA often use different measures for the same construct, leading to sparse datasets. We introduce a graph theory method for summarizing patterns of sparseness and use simulations to explore the impact of different patterns on measurement bias within three different measurement models: a single common factor, a hierarchical model, and a bifactor model. We simulated 1000 datasets with varying levels of sparseness and used Bayesian methods to estimate model parameters and evaluate bias. Results clarified that bias due to sparseness will depend on the strength of the general factor, the measurement model employed, and the level of indirect linkage among measures. We provide an example using a synthesis dataset that combined data on youth depression from 4146 youth who participated in 16 randomized field trials of prevention programs. Given that different synthesis datasets will embody different patterns of sparseness, we conclude by recommending that investigators use simulation methods to explore the potential for bias given the sparseness patterns they encounter.

Does terminology matter when measuring stigmatizing attitudes about weight? Validation of a brief, modified attitudes toward obese persons scale.

Commonly used terms like "obese person" have been identified as stigmatizing by those with lived experience. Thus, this study sought to revise a commonly used measure of weight stigmatizing attitudes, the Attitudes Toward Obese Persons (ATOP) scale. The original terminology in the 20-item ATOP (e.g., "obese") was compared to a modified version using neutral terms (e.g., "higher weight"). Participants (N=832) were randomized to either receive the original or modified ATOP. There was a statistically significant difference, with a small effect size (d=-0.22), between the scores of participants who received the original ATOP (M=69.25) and the modified ATOP (M=72.85), t(414)=-2.27, p=0.024. Through principal component analysis, the modified ATOP was best used as a brief, 8-item unidimensional measure. In a second sample, confirmatory factor analysis verified the fit of the brief, 8-item factor structure. Findings suggest that a modified, brief version of the ATOP (ATOP-Heigher Weight; ATOP-HW) with neutral language is suitable for assessing negative attitudes about higher-weight people. The ATOP-HW may slightly underestimate weight stigma compared to the original ATOP, or the language in the ATOP may magnify negative attitudes. Further examination of the terminology used in weight stigma measures is needed to determine how to best assess weight stigma without reinforcing stigmatizing attitudes. The present study's findings suggest that the use of neutral terms in measures of anti-fat bias is a promising solution that warrants further investigation.

Associations of Major Lifetime and Everyday Discrimination with Cognitive Function among Middle-Aged and Older Adults.

We investigated the associations of lifetime and everyday discrimination with cognitive function. Data were from the Chicago Community Adult Health Study (n=2952, mean age=43 years [SD=17]). We fitted multivariable linear regression models to quantify the discrimination-cognition associations. Major lifetime (β1 vs 0 episodes of discrimination = 0.56; 95% CI, 0.15-0.96; β2+ vs 0 episodes of discrimination = 0.64, 95% CI, 0.31-0.97) and everyday (β=0.10, 95% CI, 0.06-0.14) discrimination were positively associated with cognition, and these associations did not differ by race/ethnicity. Among older adults, major lifetime discrimination, but not everyday discrimination, was positively associated with cognition (β2+ vs 0 episodes of discrimination =1.79; 95% CI, 0.79-2.79). Measurement and selection bias may partially explain the counterintuitive study findings. We call for longitudinal research to further investigate the discrimination-cognition relationship.

Imaging technology to assess tissue oxygen saturation of the gastric conduit in thoracic esophagectomy

ObjectiveThe objective of the study was to evaluate a novel imaging technology for assessing tissue oxygen saturation (StO2) in the gastric conduit during thoracic esophagectomy, comparing it to the traditional method of indocyanine green (ICG) fluorescence angiography, which has several limitations. MethodsThis prospective study included 60 patients with thoracic esophageal cancer undergoing thoracic esophagectomy, approved by the National Cancer Center Hospital’s institutional review board. A new videoscope system with oxygen saturation imaging (OXEI) mode was tested. Intraoperative StO2 and ICG measurements were taken at the tip of the gastric conduit, the demarcation line of visible perfusion, and the end of the right gastroepiploic artery. The study aimed to compare the correlation between StO2 and ICG values and evaluate the incidence of postoperative anastomotic leakage. ResultsOut of 60 patients, 57 were analyzed after excluding three for oncological reasons. Anastomotic leakage occurred in three patients. StO2 values decreased towards the tip of the conduit and were significantly lower at the tip compared to the demarcation line (P = 0.001). The mean StO2 at the anastomosis site was significantly lower in patients with leakage (P = 0.04). There was a negative correlation between StO2 and ICG values at the end of the right gastroepiploic artery (r = -0.361; P = 0.03). Two of the three patients with leakage had normal ICG values but low StO2 values and marked congestion. ConclusionStO2 imaging proved useful in determining the anastomotic site and addressed the limitations of the ICG method, which is contraindicated in patients with iodine allergy and subject to measurement biases. The OXEI method, being non-invasive and capable of real-time assessment, shows promise in predicting anastomotic leakage. Further prospective studies in larger, multi-center trials are planned to confirm these findings and evaluate the efficacy of OXEI compared to ICG.

Multimodal optical imaging of the oculofacial region using a solid tissue-simulating facial phantom.

Spatial frequency domain imaging (SFDI) applies patterned near-infrared illumination to quantify the optical properties of subsurface tissue. The periocular region is unique due to its complex ocular adnexal anatomy. Although SFDI has been successfully applied to relatively flat in vivo tissues, regions that have significant height variations and curvature may result in optical property inaccuracies. We characterize the geometric impact of the periocular region on SFDI imaging reliability. SFDI was employed to measure the reduced scattering coefficient ( ) and absorption coefficient ( ) of the periocular region in a cast facial tissue-simulating phantom by capturing images along regions of interest (ROIs): inferior temporal quadrant (ITQ), inferior nasal quadrant (INQ), superior temporal quadrant (STQ), central eyelid margin (CEM), rostral lateral nasal bridge (RLNB), and forehead (FH). The phantom was placed on a chin rest and imaged nine times from an "en face" or "side profile" position, and the flat back of the phantom was measured 15 times. The measured and of a cast facial phantom are accurate when comparing the ITQ, INQ, STQ, and FH to its flat posterior surface. Paired tests of ITQ, INQ, STQ, and FH and concluded that there is not enough evidence to suggest that imaging orientation impacted the measurement accuracy. Regions of extreme topographical variation, i.e., CEM and RLNB, did exhibit differences in measured optical properties. We are the first to evaluate the geometric implications of wide-field imaging along the periocular region using a solid tissue-simulating facial phantom. Results suggest that the ITQ, INQ, STQ, and FH of a generalized face have minimal impact on the SFDI measurement accuracy. Areas with heightened topographic variation exhibit measurement variability. Device and facial positioning do not appear to bias measurements. These findings confirm the need to carefully select ROIs when measuring optical properties along the periocular region.

Estimating Salmonella Typhimurium Growth on Chicken Breast Fillets Under Simulated Less-Than-Truckload Dynamic Temperature Abuse.

Companies may have insufficient freight to fill an entire truck/trailer, and instead only pay for space that their products occupy (i.e., "less-than-truckload" shipping; LTL). As LTL delivery vehicles make multiple stops, there is an increased opportunity for product temperature abuse, which may increase microbial food safety risk. To assess LTL effects on Salmonella Typhimurium growth, commercially produced boneless skinless chicken breast fillets were inoculated and incubated under dynamic 2-h temperature cycles (i.e., 2 h at 4°C and then 2 h at 25°C), mimicking a commercially relevant LTL scenario. Bacterial kinetics were measured over 24 h and then observations compared with predictions of three published Salmonella secondary models by bias and accuracy factor measurement. One model produced more "fail-safe" estimates of Salmonella growth than the other models, although all models were defined as "acceptable." These developed tertiary models can help shippers assess supply chain performance and produce proactive food safety risk management systems.

Comparison of automated corneal endothelial cell analysis in healthy and postoperative eyes with phakic intraocular lens: a cross-sectional study and literature review

PurposeMeasurement of corneal endothelial cells is critical for postoperative evaluation of phakic intraocular lens (pIOL) surgery. However, inter-instrument differences in corneal endothelial cell density (ECD) after pIOL implantation have not yet been reported. This study aimed to compare automated corneal endothelial cell analysis between CellChek-20 (Konan Medical, Hyogo, Japan) and EM-4000 (Tomey, Nagoya, Japan) in healthy and postoperative eyes with pIOL.MethodsWe retrospectively analyzed 154 healthy and 236 postoperative eyes after pIOL surgery. Endothelial cell measurements were performed using CellChek-20 and EM-4000 with autofocusing and automated image analysis. ECD, percentage of hexagonal cells (HEX), coefficient of variation in cell size (CoV), and central corneal thickness (CCT) were compared between the two devices.ResultsThe ECDs of the two devices were highly correlated in both healthy (Spearman’s correlation coefficient [r] = 0.805; p < 0.001) and postoperative (r = 0.901; p < 0.001) groups. ECD from CellChek-20 was higher than EM-4000 in both healthy (mean difference = 228.9 cells/mm2; p < 0.001) and postoperative (mean difference = 115.6 cells/mm2; p < 0.001) groups. The CCT values also showed a strong correlation in healthy eyes (r = 0.974; p < 0.001) and in postoperative eyes (r = 0.936; p < 0.001); however, significant inter-instrument differences were observed. HEX and CV showed significant differences and relatively weak correlations (r < 0.7) between the two devices in both healthy and postoperative groups.ConclusionThe ECD values between the two instruments were correlated, but that of the CellChek-20 was significantly higher than that of the EM-4000 in both healthy and postoperative eyes after pIOL surgery. Most previous studies have also shown that the Konan software overestimated the ECD compared to other products in automatic measurement mode. The possibility of measurement bias should be considered when replacing equipment used for corneal endothelial cell measurements.

On Kinematic Measurements of Self-gravity in Protoplanetary Disks

Using controlled injection and recovery experiments, we devised an analysis prescription to assess the quality of dynamical measurements of protoplanetary disk gas masses based on resolved (CO) spectral line data, given observational limitations (resolution, sampling, noise), measurement bias, and ambiguities in the geometry and physical conditions. With sufficient data quality, this approach performed well for massive disks (M d/M * = 0.1): we inferred M d posteriors that recovered the true values with little bias (≲20%) and uncertainties within a factor of two (2σ). The gas surface density profiles for such cases are recovered with remarkable fidelity. Some experimentation indicates that this approach becomes insensitive when M d/M * ≲ 5%, due primarily to degeneracies in the surface density profile parameters. Including multiple lines that probe different vertical layers, along with some improvements in the associated tools, might push that practical boundary down by another factor of ∼two in ideal scenarios. We also demonstrated this analysis approach using archival Atacama Large Millimeter/Submillimeter Array observations of the MWC 480 disk: we measured Md=0.13−0.01+0.04M⊙ (corresponding to M d/M * = 7% ± 1%) and identified kinematic substructures consistent with surface density gaps around 65 and 135 au. Overall, this (and similar work) suggests that these dynamical measurements offer powerful new constraints with sufficient accuracy and precision to quantify gas masses and surface densities at the high end of the M d/M * distribution, and therefore can serve as key benchmarks for detailed thermo-chemical modeling. We address some prospects for improvements, and discuss various caveats and limitations to guide future work.

The ALMA-ALPAKA survey. II. Evolution of turbulence in galaxy disks across cosmic time: Difference between cold and warm gas

The gas in the interstellar medium (ISM) of galaxies is supersonically turbulent. Measurements of turbulence typically rely on cold gas emission lines for low-$z$ galaxies and warm ionized gas observations for $z &gt; 0$ galaxies. Studies of warm gas kinematics at $z &gt; 0$ conclude that the turbulence strongly evolves as a function of redshift, due to the increasing impact of gas accretion and mergers in the early Universe. However, recent findings suggest potential biases in turbulence measurements derived from ionized gas at high-$z$, impacting our understanding of turbulence origin, ISM physics and disk formation. We investigate the evolution of turbulence using velocity dispersion (sigma ) measurements from cold gas tracers (i.e., CO CI CII ). The initial dataset comprises 17 galaxy disks with high data quality from the ALPAKA sample, supplemented with galaxies from the literature, resulting in a sample of 57 galaxy disks spanning the redshift range $z = 0 - 5$. This extended sample consists of main-sequence and starburst galaxies with stellar masses $ M_ odot $. The comparison with current Halpha kinematic observations and existing models demonstrates that the velocity dispersion inferred from cold gas tracers differ by a factor of $ 3$ from those obtained using emission lines tracing the warm, ionized gas. We show that stellar feedback is the main driver of turbulence measured from cold gas tracers and the physics of turbulence driving does not appear to evolve with time. This is fundamentally different from the conclusions of studies based on warm gas, which had to consider additional turbulence drivers to explain the high values of sigma . We present a model predicting the redshift evolution of turbulence in galaxy disks, attributing the increase of sigma with redshift to the higher energy injected by supernovae due to the elevated star-formation rate in high-$z$ galaxies. This supernova-driven model suggests that turbulence is lower in galaxies with lower stellar mass compared to those with higher stellar mass. Additionally, it forecasts the evolution of sigma in Milky-Way like progenitors.

Ranging Atom Probe Spectra to Reduce Measurement Bias

Ranging Atom Probe Spectra to Reduce Measurement Bias

Does Terminology Matter When Measuring Stigmatizing Attitudes About Weight? Validation of a Brief, Modified Attitudes Toward Obese Persons Scale.

Objective Commonly used terms like "obese person" have been identified as stigmatizing by those with lived experience. Thus, this study sought to revise a commonly used measure of weight stigmatizing attitudes, the Attitudes Toward Obese Persons (ATOP) scale. Methods The original terminology in the 20-item ATOP (e.g., "obese") was compared to a modified version using neutral terms (e.g., "higher weight"). Participants ( N = 832) were randomized to either receive the original or modified ATOP. Results There was a statistically significant difference, with a low effect size ( d =-0.26), between the scores of participants who received the original ATOP ( M = 69.25) and the modified ATOP ( M = 72.85), t (414) = -2.27, p = .024. Through principal component analysis, the modified ATOP was found to be best used as a brief, 8-item unidimensional measure. In a second sample, confirmatory factor analysis verified the fit of the brief, 8-item factor structure. Conclusions Findings suggest a modified, brief version of the ATOP (ATOP-Heigher Weight; ATOP-HW) with neutral language is suitable for assessing negative attitudes about higher-weight people. The ATOP-HW may slightly underestimate weight stigma compared to the original ATOP. Further examination of the terminology used in weight stigma measures is needed to determine how to best assess weight stigma without reinforcing stigmatizing attitudes. The findings of the present study suggest that the use of neutral terms in measures of anti-fat bias is a promising solution that warrants further investigation.

Measurement error and bias in real-world oncology endpoints when constructing external control arms

Measurement error and bias in real-world oncology endpoints when constructing external control arms

Provider Implicit Racial Bias in Pediatric Sickle Cell Disease.

This study is to (1) assess implicit racial bias among pediatric providers and (2) use virtual patient (VP) vignettes to determine the impact of implicit racial bias on clinical decision-making in pediatric sickle cell disease (SCD) pain care. This cross-sectional study was conducted at a mid-sized, freestanding children's hospital in the northeast. Participants (N = 52) were pediatric SCD providers (87% cisgender female, 90% White, M age = 38.78). Providers completed a demographic questionnaire, the race Implicit Association Test (IAT) with adult and child faces, and a measure of SCD explicit bias (5-point Likert scale). Providers also made clinical decisions for four VP vignettes depicting Black and White youth in the emergency department (ED) with either SCD or cancer pain. Frequency tables were calculated. On the race IAT, providers demonstrated a pro-White implicit bias for both adult (81%) and child (89%) faces. Responses to the explicit bias measure reflected low levels of agreement with negative stereotypes about SCD patients. No significant differences emerged in providers' pain treatment decisions for Black vs. White, or SCD vs. cancer VPs. Findings indicate pediatric providers harbor implicit racial bias similar to the general population. Findings from VP vignettes did not demonstrate that pain treatment decision-making differed based on race or diagnosis. This may be due to standardized protocols and procedures in the pediatric emergency setting. Future research is needed to clarify the role of implicit bias in clinical decision-making and the potential efficacy of treatment protocols in preventing biases from interfering with pediatric SCD pain care.

Optimization of cervical cord synthetic T1-weighted MRI for enhancing clinical application in neurodegenerative spinal cord disorders

Abstract Synthetic MRI offers the advantage of reducing acquisition time and enhancing flexibility through the reconstruction of various contrast weightings from a single set of MRI scans. However, the use of synthetic T1-weighted (synT1-w) MRI can lead to potentially biased measurements of the cross-sectional area (CSA) in the spinal cord when compared to conventionally acquired T1-weighted MRI. This disparity can have implications for comparability and sensitivity of MRI in assessing disease progression or treatment effects in neurodegenerative spinal cord disorders. Thus, this study aimed at improving the accuracy (i.e., difference between synthetic and acquired MRI) of cervical cord CSA measurements (C1-C3 level) based on synT1-w MRI implementing a longitudinal data set acquired from 23 acute spinal cord injury (SCI) patients and 21 healthy controls over 2 years. Moreover, the validity of using synT1-w MRI for tracking cervical cord atrophy following SCI over 2 years was verified. SynT1-w images were reconstructed from quantitative maps of proton density, longitudinal, and effective transverse relaxation rates derived from a multi-parameter mapping protocol. The results showed a minimal bias of -0.31 mm2 (-0.5%) in CSA measurements based on synT1-w compared to acquired MRI. Estimates of atrophy rates and average CSA were comparable between synthetic and acquired MRI. A sample size estimation for detecting treatment effects on CSA atrophy after 2 years following SCI revealed that the required sample size is reduced by 13.5% using synT1-w instead of acquired MRI. This study shows high accuracy of synT1-w MRI and demonstrates its applicability in clinical studies for optimizing long MRI protocols.

Developing a Technological Pedagogical and Content Knowledge (TPACK) survey for university teachers

Existing Technological Pedagogical and Content Knowledge (TPACK) surveys target pre-service or K-12 teachers, whereas none have been specifically adapted for university teachers. To adequately measure TPACK-competences of university teachers, the specific characteristics of teaching in a university context need to be taken into account. Survey items that are not contextualized to the target participants increase the risk of measurement error and bias. Therefore, we adapted existing TPACK surveys to specifically measure university teachers’ competences for teaching with technology. We shortlisted five existing TPACK surveys and scrutinized their respective subscales and items. We then adapted these items to more adequately capture context-specific experiences for university teachers to ensure construct validity. We collected two waves of data to test our adapted TPACK survey, which comprises 31 items distributed across seven subscales, among teachers from various disciplines in a large university. With confirmatory factor analysis, we confirmed the seven-factor structure of the adapted TPACK survey in both data waves. Moreover, the seven subscales showed adequate internal consistency. An exploration of TPACK competences among teachers from different disciplines showed both similarities as well as dissimilarities. An example of similarities is that university teachers from all disciplines felt most competent in CK and PCK, while they reported relatively low competence ratings for TPCK and TPK. Besides, an example of dissimilarities is PK; teachers from the discipline of science and engineering reported the highest score compared to other disciplines in the prior wave, while they evaluated themselves third lowest in the latter wave.

The Ambiguous Cue Task: Measurement reliability of an experimental paradigm for the assessment of interpretation bias and associations with mental health

Interpretation biases in the processing of ambiguous affective information are assumed to play an important role in the onset and maintenance of emotional disorders. Reports of low reliability for experimental measures of cognitive biases have called into question previous findings on the association of these measures with markers of mental health and demonstrated the need to systematically evaluate measurement reliability for measures of cognitive biases. We evaluated reliability and correlations with self-report measures of mental health for interpretation bias scores derived from the Ambiguous Cue Task (ACT), an experimental paradigm for the assessment of approach-avoidance behavior towards ambiguous affective stimuli. For a non-clinical sample, the measurement of an interpretation bias with the ACT showed high internal consistency (rSB = .91 – .96, N = 354) and acceptable 2-week test–retest correlations (rPearson = .61 – .65, n = 109). Correlations between the ACT interpretation bias scores and mental health-related self-report measures of personality and well-being were generally small (r ≤ |.11|) and statistically not significant when correcting for multiple comparisons. These findings suggest that in non-clinical populations, individual differences in the interpretation of ambiguous affective information as assessed with the ACT do not show a clear association with self-report markers of mental health. However, in allowing for a highly reliable measurement of interpretation bias, the ACT provides a valuable tool for studies considering potentially small effect sizes in non-clinical populations by studying bigger samples as well as for work on clinical populations, for which potentially greater effects can be expected.

A sum of its parts: A systematic review evaluating biopsychosocial and behavioral determinants of perinatal depression.

Depression is one of the most common yet underdiagnosed perinatal complications and our understanding of its pathophysiology remains limited. Though perinatal depression is considered to have a multifactorial etiology, integrative approaches to investigation are minimal. This review takes an integrative approach to systematically evaluate determinants (e.g., biological, behavioral, environmental, social) and interactions among determinants of perinatal depression and the quality of methods applied. Four databases (i.e., PubMed, CINAHL, APA PsycInfo, Web of Science) were systematically searched to identify studies examining determinants of perinatal depression in adult perinatal persons (≥ 18 years). Articles were excluded if the outcomes were not focused on perinatal persons and depression or depression symptoms, depression was examined in a specific subpopulation evidenced to have psychological consequences due to situational stressors (e.g., fetal/infant loss, neonatal intensive care unit admission), or was considered grey literature. The Critical Appraisal Skills Programme and AXIS tools were used to guide and standardize quality appraisal assessments and determine the level of risk of bias. Of the 454 articles identified, 25 articles were included for final review. A total of 14 categories of determinants were investigated: biological (5), behavioral (4), social and environmental (5). Though only 32% of studies simultaneously considered determinants under more than one domain, a pattern of interactions with the tryptophan pathway emerged. Concerns for risk of bias were noted or were unclear for three types of bias: 13 (52%) selection bias, 3 (12%) recall bias, and 24 (96%) measurement bias. Future research is needed to explore interactions among determinants and the tryptophan pathway; to strengthen the methods applied to this area of inquiry; and to generate evidence for best practices in reporting, selecting, and applying methods for measuring determinants and perinatal depression.

The life cycle of large language models in education: A framework for understanding sources of bias

AbstractLarge language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM‐based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education technology has renewed concerns over algorithmic bias, which may exacerbate educational inequalities. Building on prior work that mapped the traditional machine learning life cycle, we provide a framework of the LLM life cycle from the initial development of LLMs to customizing pre‐trained models for various applications in educational settings. We explain each step in the LLM life cycle and identify potential sources of bias that may arise in the context of education. We discuss why current measures of bias from traditional machine learning fail to transfer to LLM‐generated text (eg, tutoring conversations) because text encodings are high‐dimensional, there can be multiple correct responses, and tailoring responses may be pedagogically desirable rather than unfair. The proposed framework clarifies the complex nature of bias in LLM applications and provides practical guidance for their evaluation to promote educational equity. Practitioner notesWhat is already known about this topic The life cycle of traditional machine learning (ML) applications which focus on predicting labels is well understood. Biases are known to enter in traditional ML applications at various points in the life cycle, and methods to measure and mitigate these biases have been developed and tested. Large language models (LLMs) and other forms of generative artificial intelligence (GenAI) are increasingly adopted in education technologies (EdTech), but current evaluation approaches are not specific to the domain of education. What this paper adds A holistic perspective of the LLM life cycle with domain‐specific examples in education to highlight opportunities and challenges for incorporating natural language understanding (NLU) and natural language generation (NLG) into EdTech. Potential sources of bias are identified in each step of the LLM life cycle and discussed in the context of education. A framework for understanding where to expect potential harms of LLMs for students, teachers, and other users of GenAI technology in education, which can guide approaches to bias measurement and mitigation. Implications for practice and/or policy Education practitioners and policymakers should be aware that biases can originate from a multitude of steps in the LLM life cycle, and the life cycle perspective offers them a heuristic for asking technology developers to explain each step to assess the risk of bias. Measuring the biases of systems that use LLMs in education is more complex than with traditional ML, in large part because the evaluation of natural language generation is highly context‐dependent (eg, what counts as good feedback on an assignment varies). EdTech developers can play an important role in collecting and curating datasets for the evaluation and benchmarking of LLM applications moving forward.

Performance of Microsoft Azure Kinect DK as a tool for estimating human body segment lengths

The Microsoft Kinect depth sensor, with its built-in software that automatically captures joint coordinates without markers, could be a potential tool for ergonomic studies. This study investigates the performance of Kinect in limb segment lengths using dual-energy X-ray absorptiometry (DXA) as a reference. Healthy children and adults (n = 76) were recruited for limb length measurements by Kinect and DXA. The results showed consistent ratios of arm, forearm, thigh, and leg lengths to height, which were 0.16, 0.14, 0.23, and 0.22 respectively, for both age groups and methods. Kinect exhibited perfect correlation among all limb lengths, indicating fixed proportions assumed by its algorithm. Comparing the two methods, there was a strong correlation (R = 0.850–0.985) and good to excellent agreement (ICC = 0.829–0.977), except for the right leg in adults, where agreement was slightly lower but still moderate (ICC = 0.712). The measurement bias between the methods ranged from − 1.455 to 0.536 cm. In conclusion, Kinect yields outcomes similar to DXA, indicating its potential utility as a tool for ergonomic studies. However, the built-in algorithm of Kinect assumes fixed limb proportions for individuals, which may not be ideal for studies focusing on investigating limb discrepancies or anatomical differences.

Psychometric Properties of the Attitude Toward Statistics Scale on a Bangladeshi Sample

Existing literature suggested the attitude toward Statistics as a predictor of academic performance in Statistics. There was an unavailability of measures for assessing attitude toward Statistics in Bangladesh. The present study was designed to adapt the Attitude toward Statistics Scale (ATSS: Wise, 1985). The adaptation procedure was done by following the guidelines of the International Test Commission (ITC). The translated ATSS was administered on a sample of 238 students from the University of Chittagong who were selected through non-probability sampling techniques. The internal consistency reliabilities, test-retest reliability, standard error of measurement, face validity, content validity, construct validity, and item response bias were estimated for assessing the psychometric properties of the Bangla ATSS. The item-total correlations, Chronbach’s Alphas, split-half reliabilities, test-retest reliability, factor loadings, and DIF contrasts suggested that this measure would be a psychometrically sound measure to apply in Bangladesh context. The Chittagong Univ. J. B. Sci.,Vol. 10(1 &amp;2):81-94, 2020