Inherent Bias Research Articles

Future temperature-related mortality in the UK under climate change scenarios: Impact of population ageing and bias-corrected climate projections

BackgroundExposure to heat and cold poses a serious threat to human health. In the UK, hotter summers, milder winters and an ageing population will shift how populations experience temperature-related health burdens. Estimating future burdens can provide insights on the drivers of temperature-related health effects and removing biases in temperature projections is an essential step to generating these estimates, however, the impact of various methods of correction is not well examined. MethodsWe conducted a detailed health impact assessment by estimating mortality attributable to temperature at a baseline period (2007–2018) and in future decades (2030s, 2050s and 2070s). Epidemiological exposure-response relationships were derived for all England regions and UK countries, to quantify cold and heat risk, and temperature thresholds where mortality increases. UK climate projections 2018 (UKCP18)were bias-corrected using three techniques: correcting for mean bias (shift or SH), variability (bias-correction or BC) and extreme values (quantile mapping or QM). These were applied in the health impact assessment, alongside consideration of population ageing and growth to estimate future temperature-related mortality. FindingsIn the absence of adaptation and assuming a high-end emissions scenario (RCP8.5), annual UK temperature-related mortality is projected to increase, with substantial differences in raw vs. calibrated projections for heat-related mortality, but smaller differences for cold-related mortality. The BC approach gave an estimated 29 deaths per 100,000 in the 2070s, compared with 50 per 100,000 using uncorrected future temperatures. We also found population ageing may exert a bigger impact on future mortality totals than the impact from future increases in temperature alone. Estimating future health burdens associated with heat and cold is an important step towards equipping decision-makers to deliver suitable care to the changing population. Correcting inherent biases in temperature projections can improve the accuracy of projected health burdens to support health protection measures and long-term resilience planning.

O-320 Does applying an ‘elective freeze-all’ policy work in practice? A matched cohort study of over 9,000 embryo transfers

Abstract Study question Does application of a Freeze All Embryo (FAE) policy achieve superior live birth rates in practice compared to fresh IVF transfer cycles? Summary answer FAE FETs achieved significantly higher LBRs than fresh for both the first ET per cycle and cumulatively per cycle. What is known already The efficacy of vitrification methods has led to segmentation between the ovarian stimulation and embryo transfer cycle becoming increasingly applied. Randomised controlled trials have shown that for high responders, especially those at risk of ovarian hyperstimulation syndrome, the FAE approach is likely to be favourable. However, whether a routine freeze all approach applied in routine clinical practice improves outcomes in a broader group of patients remains unclear. Study design, size, duration This is a retrospective analysis of 7,647 autologous fresh oocyte retrievals and 9,609 subsequent ETs, performed between 2016-2022. The primary study aim was to compare (cumulative) live birth rates between fresh and frozen thawed embryo transfers after FAE IVF cycles. The groups consisted of 3,707 fresh IVF transfers plus 1,533 subsequent FETs derived from those cycles, versus 3940 FAE cycles with 3969 subsequent FETs. Participants/materials, setting, methods 5,808 patients underwent fresh oocyte retrievals (2016-2022) at a single UK-based centre. In total, 4,997 of these patients underwent 9,609 ETs; either fresh or frozen. For analysis, FAE cycles and fresh IVF cycles underwent 1:1 full propensity score matching for age and number of eggs collected, using probit regression of treatments on covariates. Logistic regression analyses were fit including full matching weights in the estimation to compare LBR superiority between groups. Main results and the role of chance Patients undergoing fresh transfers were significantly older and yielded significantly fewer oocytes per retrieval (37 and 36, P < 0.001; 7 ± SE 0.07 and 12 ± SE 0.1, P < 0.001, respectively). After full 1:1 matching for age and oocytes collected, the means for both groups were 36 and 15, respectively. Standardised mean differences after matching was <0.2. The first FET from FAE cycles achieved significantly superior LBRs and was a significant predictor of LB compared to fresh ETs when adjusted for covariates (37% and 26%, respectively, aOR 1.3; 95% CI 1.2-1.5, P < 0.001). Cumulative LBs achieved per cycle were also significantly higher for FAE cycles (56% and 37%, respectively). When stratifying by age, first ET LBRs between groups were comparable for <35s (FAE 42%, fresh 40%). However, with increasing age, FAE first FETs achieved higher live births than fresh transfers (35-37, 36% and 33%; 38-39, 34% and 23%; 40-42, 27% and 14%; 43-45, 15% and 5%, respectively). Limitations, reasons for caution This is a retrospective analysis and, although cohorts underwent full 1:1 matching, inherent bias may be present within the data and must be considered when drawing conclusions. Wider implications of the findings These findings suggest that in clinical practice, FETs after a FAE cycle may achieve superior LBRs compared to fresh ETs, particularly in older patients and for higher responders. Overall, FAE cycles were observed to result in higher cumulative LBRs per cycle than cycles that begin with a fresh transfer. Trial registration number Not applicable

P-782 Are pregnancy complications associated with the method of conception in female same-sex couples? Results of a retrospective, matched cohort study comparing ROPA and IUI

Abstract Study question Are pregnancies in female same-sex couples at a higher risk when using reception of oocytes from partner (ROPA) compared to those following intrauterine insemination (IUI)? Summary answer In female same-sex couples, pregnancies following ROPA demonstrated a higher incidence of preterm birth and first-trimester bleeding. What is known already Reception of Oocytes from PArtner (ROPA) enables both partners to contribute biologically to the desired pregnancy. However, oocyte donation, often performed in case of (premature) ovarian failure, is associated with an increased risk of hypertensive disorders of pregnancy/preeclampsia. Female same-sex couples typically comprising healthy, young women without underlying subfertility problems, are a priori at low absolute risk for pregnancy complications. Few studies have investigated the incidence of pregnancy complications and/or obstetrical outcomes in this specific group of women. Further insights and formal data could guide clinicians and patients in making informed decisions regarding the preferred method of conception. Study design, size, duration A retrospective, single-center, matched cohort study was performed including 577 unique female same-sex couples using donor semen who became pregnant after reproductive treatment (88 pregnancies following ROPA and 489 following IUI). None of the patients who opted for ROPA had (failed) IUI before. The study covered the period from January 2015 to January 2023. Participants/materials, setting, methods Pregnancies following ROPA were matched with pregnancies following IUI for age (+/-4 years), BMI (+/-4 kg/m2), parity (nulliparous vs multiparous) and date of embryo transfer/IUI (+/-1year) in a 1:1 ratio. Statistical Package for Social Sciences (SPSS) v26.0 was used for statistical analysis. Kolmogorov-Smirnov test was used to evaluate the normal distribution of continuous variables. Normally distributed data were analyzed with the student t-test and categorical variables were analyzed with the chi-square test. Main results and the role of chance After matching, 154 pregnancies (77 ROPA versus 77 IUI) were eligible for the study. Age (mean age 31.4±4.0 for ROPA versus 31.2±4.3 years for IUI, p = 0.48) and BMI (24.5±3.9 kg/m2 versus 25.2±4.4 kg/m2, for respectively ROPA versus IUI, p = 0.32) were comparable between groups after matching. Two ROPA pregnancies were excluded from further analysis due to elective termination of pregnancy (radiusaplasia and trisomy 21). Both groups experienced two stillbirths (two unexplained mors in utero, one chorioamnionitis and one intrapartum death). No significant difference in hypertensive disorders of pregnancy (HDP) (10.7% (8/75) versus 13.7% (10/73) for ROPA and IUI respectively, p = 0.53) or preeclampsia rates (11.0% (8/73) and 6.7% (5/75) for ROPA and IUI respectively, p = 0.33) was observed. ROPA-associated preeclampsia cases were often preterm (<37weeks’ gestation) compared to IUI (5/8 versus 1/5). ROPA pregnancies had a higher incidence of preterm birth (15.1% vs 1.3%,p<0.002) and first trimester bleeding was significantly more frequent (12.3% vs 0%,p<0.001). No statistically significant differences were observed between groups in neonatal weight, fetal structural malformations and cesarean section delivery rates. Limitations, reasons for caution The study is limited by its retrospective design and inherent bias. Despite reducing the sample size, matching enhanced study robustness. Recognized risk factors for hypertensive disorder of pregnancy, like the use of donor sperm, may mitigate differences associated with conception methods in this population. Wider implications of the findings The study points out potentially increased obstetrical risks following ROPA. These data are crucial to counsel and guide female same-sex couples in their decision regarding the method of conception. The risk of hypertensive disorders of pregnancy, specifically preterm preeclampsia, associated with ROPA warrants further attention, urging larger prospective studies. Trial registration number not applicable

P-318 Reproductive ageing: the seed, the soil, or both?

Abstract Study question Is it all about the embryo? Can a single euploid blastocyst transfer sustain reproductive outcomes in women with advanced reproductive age? Summary answer Despite euploid embryo transfer, endometrial senescence appears to play a crucial role in determining reproductive success, particularly in older patients undergoing in vitro fertilization (IVF). What is known already Advanced reproductive age significantly impairs oocyte and embryo quality. Effective crosstalk and synchronization between embryo and endometrium are pivotal for successful pregnancies, both in vivo and in vitro. Implantation failure remains a persistent challenge in IVF, exacerbated by delayed family planning trends. The transfer of euploid blastocysts through preimplantation genetic testing for aneuploidy (PGT-A) is a potential strategy to address implantation issues, decrease miscarriages, and shorten time-to-pregnancy. However, a significant proportion of IVF treatments remain unsuccessful, suggesting critical factors beyond the embryo. Study design, size, duration This retrospective study analyzed 457 single euploid blastocyst transfers performed by two doctors at a private IVF center from January to November 2023. Inclusion criteria encompassed cases with PGT-A indications (advanced maternal age, repeated implantation failure, recurrent pregnancy loss, etc.) or cases where embryo biopsy was patient-requested. The primary outcome was ongoing pregnancy rate (OPR), with secondary outcomes including pregnancy rate (PR) and clinical pregnancy rate (CPR). Participants/materials, setting, methods Participants were categorized into four groups: Group 1 (< 35 years old; N = 100), Group 2 (35-37 years old; N = 102), Group 3 (38-40 years old; N = 118), and Group 4 (> 41 years old; N = 87). A control group (oocyte donation; N = 50) with single euploid embryo transfers showed a mean recipient age of 43 years. Donors were always less than 32 years old. Endometrial preparation protocols were consistent across all groups. Chi-square test was used to compare groups. Main results and the role of chance Among the 457 transfers analyzed, with a mean female age of 37 years, the overall PR was 71.3%, CPR was 64.8%, and OPR was 60.2%. Groups showed no differences in demographic variables and cycle parameters. Group 1 demonstrated higher PR (83.3%), CPR (78.4%), and OPR (73.5%) compared to Group 2 (PR 70.9%, p = 0.034; CPR 66%, p = 0.047; OPR 62.1%, p = 0.081), Group 3 (PR 68.2%, p = 0.009; CPR 61.2%, p = 0.005; OPR 56.6%, p = 0.008), and Group 4 (PR 65%, p = 0.002; CPR 56.1%, p < 0.001; OPR 51.2%, p = 0.001). Furthermore, the control group (oocyte recipients) showed significantly lower PR (68%, p = 0.031), CPR (54%, p = 0.002), and OPR (46%, p < 0.001) compared to Group 1, but not with the other groups. These findings demonstrate that even with euploid embryos originating from young donors, older women exhibited lower pregnancy rates than young women transferring single euploid blastocysts from their own oocytes and similar rates compared to those with advanced reproductive age transferring their own euploid blastocysts, implying that endometrial ageing may disproportionately influence IVF treatment outcomes. Limitations, reasons for caution The retrospective design introduces inherent bias, notably selection bias and unmeasured confounders. This preliminary data did not account for male infertility factors and their impact on embryo quality. Wider implications of the findings Reproductive aging appears to be influenced by factors beyond the embryo itself, especially in women above 35 years. Further research is warranted to elucidate the causes and impact of reproductive aging on implantation potential, aiming to refine clinical practices and enhance the success of IVF treatments. Trial registration number not applicable

Rightful Rewards: Refining Equity in Team Resource Allocation through a Data-Driven Optimization Approach

In group management, accurate assessment of individual performance is crucial for the fair allocation of resources such as bonuses. This paper explores the complexities of gauging each participant’s contribution in multi-participant projects, particularly through the lens of self-reporting—a method fraught with the challenges of under-reporting and over-reporting, which can skew resource allocation and undermine fairness. Addressing the limitations of current assessment methods, which often rely solely on self-reported data, this study proposes a novel equitable allocation policy that accounts for inherent biases in self-reporting. By developing a data-driven mathematical optimization model, we aim to more accurately align resource allocation with actual contributions, thus enhancing team efficiency and cohesion. Our computational experiments validate the proposed model’s effectiveness in achieving a more equitable allocation of resources, suggesting significant implications for management practices in team settings.

P-369 DuoStim could be a proper option for women seeking fertility preservation for non-medical reasons

Abstract Study question Is Duostim a suitable option for women who wish to preserve fertility for social reasons? Summary answer Providing the option of DuoStim is an efficient way to expand the cohort of vitrified oocytes in women seeking fertility preservation for non-medical reasons. What is known already A growing number of reproductive-age women are choosing to postpone motherhood, giving rise to the concept of reproductive autonomy. Numerous strategies aim to refine ovarian stimulation protocols. DuoStim, entailing dual ovarian stimulations and retrievals within one menstrual cycle, proves advantageous for those with diminished ovarian reserve or facing cancer. To our knowledge, this is the first study offering DuoStim for social preservation. Study design, size, duration Retrospective controlled case-control study conducted with paired follicular phase stimulation (FPS) and luteal phase stimulation (LPS) derived cohorts of oocytes collected in the same ovarian cycle (DuoStim). The study included 160 patients aged 36.85 ± 3.3 years old, who underwent DuoStim for social egg freezing from October 2018 to September 2023. The primary outcome was the number of MII oocytes retrieved per cycle and secondary outcomes included stimulation duration and gonadotropin dose. Participants/materials, setting, methods FPS and LPS were performed using the same daily dose of recombinant gonadotropins in an antagonist protocol. Oocyte retrieval was performed 36 hours after triggering with gonadotropin-releasing hormone agonist triptorelin acetate (0,2 mg) after the FPS. Luteal phase stimulation protocol began on the 5th day after ovarian puncture using dual trigger, followed by a second oocyte retrieval. Mature oocytes were vitrified 2 hours later following the Kitazato® protocol. Main results and the role of chance Stimulation duration and gonadotropin dose were lower during Follicular Phase Stimulation (FPS) vs. Luteal Phase Stimulation (LPS) (10.8 ± 1.5 days vs. 13.0 ± 2.3, P < 0.05 and 2,487.9 ± 580.8 vs. 3,264.0 ± 942.7, P < 0.05). The number of retrieved oocytes was comparable between the two groups (4.78 ± 3.0 vs. 5.32 ± 3.7; P = 0.15). The mean number of MII oocytes acquired in the LPS group exceeded that in the FPS group (4.16 ± 3.0 vs. 3.58 ± 2.3; P = 0.054), indicating a tendency towards more MII oocytes in the LPS group without achieving statistical significance. A total of 110 patients (69.29%) obtained the same or a greater number of MII during the LPS compared to the FPS. Limitations, reasons for caution Although DuoStim is acknowledged as an option to obtain a greater number of eggs in certain situations, the evidence supporting its utility in social fertility preservation is still limited. It is crucial to recognize the inherent biases in observational retrospective studies. Wider implications of the findings DuoStim could be an advantage for women who live abroad or those who dispose of short periods of time for oocyte vitrification, also potentially reducing the drop-out rate. Trial registration number not applicable

P-186 Embryos developing within the optimal morphokinetic range have a 5% higher chance of leading to a Live birth (LB)

Abstract Study question Is there an optimal range of morphokinetic parameters that have a higher LB rate, if so what is the percentage of LB improvement? Summary answer Optimal embryo development range in morphokinetic parameters was identified in t6, t8, tB, t8-t4 and t8-t2 leading to a 5% improvement in LB. What is known already Achieving LB is the main objective in IVF. Traditional embryo assessment based on morphology has drawbacks, with variability among embryologists and limited predictive ability for a single-day assessment. The emergence of AI in IVF, exemplified by CHLOE-EQ, an embryologist’s tool to register embryo morphokinetics and other parameters, presents a solution. This study investigates whether AI-detected morphokinetic parameters can significantly improve LB rates, providing a more precise and predictive approach to embryo assessment. This study investigates if embryos that lead to LB develop under specific morphokinetic optimal ranges. Study design, size, duration Conducted across multiple centres within a private clinic, this retrospective study investigated 7156 embryos with known birth outcome between January 2021 and January 2023. Participants/materials, setting, methods Absolute (tPNf to tEB) and interim morphokinetic parameters that have been previously been found to impact embryo development (CC1, CC2, CC3, S2, S3, t5-t2, t8-t4, t8-t2, tEB-tSB) were automatically annotated by an AI model (CHLOE-EQ, Fairtility Ltd). The interquartile range (Q1-Q3) of embryos that resulted in live birth was analyzed to identify the optimal range. Chi-square analysis compared live birth rates between embryos within and outside this range. Main results and the role of chance A significant Live birth optimal range was found for t6 (47.8-57.3), t8 (51.8-65.8), tB (100.9-113.6), t8-t4 (15.2-25.5), t8-t2 (26.9-39.2), p < 0.05. The following morphokinetic parameters were associated with higher LB rate when the embryo was within the optimal range hours as compared to outside the optimal range: t6 (38%, n = 1012 vs 35% n = 1007, p < 0.05), t8 (38%, n = 947 vs 35%, n = 941, p < 0.05), tB (33%, n = 548 vs 30%, n = 533, p < 0.05), t8-t4 (38%, n = 926 vs 34%, n = 943, p < 0.05), t8-t2 (38%, n = 938 vs 35% n = 936, p < 0.05). No significant LB rate differences were observed for other morphokinetics. Overall, LB rates improved by 3-5% in embryos developing at the optimal rate, with a slightly higher significance in absolute morphokinetic values over interim ones. Limitations, reasons for caution The study’s retrospective nature entails inherent biases. Additionally, this analysis does not account for oocyte origin and male factor as bias elements, which will be considered in future research. Thus results may not be transferrable to clinics that have other clinical practices and different patient demographics. Wider implications of the findings Certain morphokinetic parameters can be added to the already existing range of available LB evaluation methods. Future studies should explore diverse morphokinetic ranges to identify additional optimal intervals for each parameter. AI tools can facilitate automatic annotation and measurement of embryo morphokinetics, enhancing precision in assessment. Trial registration number Not applicable

BASSA: New software tool reveals hidden details in visualisation of low-frequency animal sounds.

The study of animal sounds in biology and ecology relies heavily upon time-frequency (TF) visualisation, most commonly using the short-time Fourier transform (STFT) spectrogram. This method, however, has inherent bias towards either temporal or spectral details that can lead to misinterpretation of complex animal sounds. An ideal TF visualisation should accurately convey the structure of the sound in terms of both frequency and time, however, the STFT often cannot meet this requirement. We evaluate the accuracy of four TF visualisation methods (superlet transform [SLT], continuous wavelet transform [CWT] and two STFTs) using a synthetic test signal. We then apply these methods to visualise sounds of the Chagos blue whale, Asian elephant, southern cassowary, eastern whipbird, mulloway fish and the American crocodile. We show that the SLT visualises the test signal with 18.48%-28.08% less error than the other methods. A comparison between our visualisations of animal sounds and their literature descriptions indicates that the STFT's bias may have caused misinterpretations in describing pygmy blue whale songs and elephant rumbles. We suggest that use of the SLT to visualise low-frequency animal sounds may prevent such misinterpretations. Finally, we employ the SLT to develop 'BASSA', an open-source, GUI software application that offers a no-code, user-friendly tool for analysing short-duration recordings of low-frequency animal sounds for the Windows platform. The SLT visualises low-frequency animal sounds with improved accuracy, in a user-friendly format, minimising the risk of misinterpretation while requiring less technical expertise than the STFT. Using this method could propel advances in acoustics-driven studies of animal communication, vocal production methods, phonation and species identification.

How debunking biases in research and development decisions could lead to more equitable healthcare?

Decades of research have demonstrated that a variety of cognitive biases can affect our judgment and ability to make rational decisions in personal and professional environments. The lengthy, risky, and costly nature of pharmaceutical research and development (R&D) makes it vulnerable to biased decision-making. Moreover, cognitive biases can play a role in regulatory and clinical decision-making, the latter impacting diagnostic and treatment decisions in the therapeutic use of medicines. These inherent and/or institutionalized biases (e.g., in assumptions, data, or decision-making practices) could conceivably contribute to health inequities. In this mini-review, we provide a broad perspective on how cognitive biases can affect pharmaceutical R&D, regulatory evaluation, and therapeutic decision-making. Example approaches to mitigate the effect of common biases in the development, approval, and use of new therapeutics, such as quantitative decision criteria, multidisciplinary reviews, regulatory and treatment guidelines, and evidence-based clinical decision support systems are illustrated. Mitigating the impact of cognitive biases could increase pharma R&D efficiency, change the perspective and prioritization of unmet medical needs, increase representativeness and quality of evidence generated through clinical trials and real-world research, leading to higher quality insights and more effective medication use, and as such could eventually contribute to more equitable healthcare.

Nonrepresentativeness of Human Mobility Data and its Impact on Modeling Dynamics of the COVID-19 Pandemic: Systematic Evaluation.

In recent years, a range of novel smartphone-derived data streams about human mobility have become available on a near-real-time basis. These data have been used, for example, to perform traffic forecasting and epidemic modeling. During the COVID-19 pandemic in particular, human travel behavior has been considered a key component of epidemiological modeling to provide more reliable estimates about the volumes of the pandemic's importation and transmission routes, or to identify hot spots. However, nearly universally in the literature, the representativeness of these data, how they relate to the underlying real-world human mobility, has been overlooked. This disconnect between data and reality is especially relevant in the case of socially disadvantaged minorities. The objective of this study is to illustrate the nonrepresentativeness of data on human mobility and the impact of this nonrepresentativeness on modeling dynamics of the epidemic. This study systematically evaluates how real-world travel flows differ from census-based estimations, especially in the case of socially disadvantaged minorities, such as older adults and women, and further measures biases introduced by this difference in epidemiological studies. To understand the demographic composition of population movements, a nationwide mobility data set from 318 million mobile phone users in China from January 1 to February 29, 2020, was curated. Specifically, we quantified the disparity in the population composition between actual migrations and resident composition according to census data, and shows how this nonrepresentativeness impacts epidemiological modeling by constructing an age-structured SEIR (Susceptible-Exposed-Infected- Recovered) model of COVID-19 transmission. We found a significant difference in the demographic composition between those who travel and the overall population. In the population flows, 59% (n=20,067,526) of travelers are young and 36% (n=12,210,565) of them are middle-aged (P<.001), which is completely different from the overall adult population composition of China (where 36% of individuals are young and 40% of them are middle-aged). This difference would introduce a striking bias in epidemiological studies: the estimation of maximum daily infections differs nearly 3 times, and the peak time has a large gap of 46 days. The difference between actual migrations and resident composition strongly impacts outcomes of epidemiological forecasts, which typically assume that flows represent underlying demographics. Our findings imply that it is necessary to measure and quantify the inherent biases related to nonrepresentativeness for accurate epidemiological surveillance and forecasting.

Navigating The E-Government Landscape in Zanzibar a Comprehensive Empirical Assessment

The study about Navigating e-government landscape in Zanzibar. This investigation emphasizes the interplay among human and financial resource capitals, governmental policies, and Information Communication Technology (ICT) infrastructure. Significantly, technological readiness is explored as a potential mediator, with digital literacy proposed as a moderating influence. Through an empirical lens, the study employs a comprehensive survey targeting diverse respondents, including public sector employees and citizens, capturing their e-government service interactions and perceptions. Employing a blend of statistical tools, the research unveils that human resource capital, aligned with digital knowledge, amplifies e-government efficacy. Strategic financial investments, especially in areas like training and ICT infrastructure, enhance service adoption. Furthermore, progressive government policies fostering transparency and inclusivity create a fertile ground for e-government growth. ICT, being central, further substantiates the call for robust digital infrastructures to support and expedite adoption. However, the mediating role of technological readiness underscores that simply possessing resources isn't sufficient; their strategic application is vital. Still, the study's scope, defined by its geographical focus on Zanzibar and potential inherent biases, necessitates caution when extrapolating results. In essence, this study provides a distilled perspective on e-government adoption in Zanzibar, offering insights potentially applicable to similar global contexts, urging stakeholders to rethink digital strategies.

Islam In Everyday Culture And “Wandering Mullahs” In Kazakhstan in the 1950s–1960s

This article explores the role of Islam in the daily culture of the Muslim communities in Soviet Kazakhstan during the 1950s and 1960s. Drawing from a diverse range of materials, including memos, reports, secret communications of party officials, and accounts from commissioners of the Council for Religious Cults, the research sheds light on various facets of religious life among the local population. These documents, compiled from firsthand observations during official trips, consistently underscore the profound impact of Islam on the everyday culture of the faithful in Kazakhstan. The authors highlight a noteworthy discrepancy in the influence of Islam, emphasizing its markedly greater sway on the daily culture of Tatars, Uzbeks, Chechens, and Ingush as compared to Kazakhs. The findings suggest a discernible shift of Islam from mainstream cultural life into a “parallel world,” where pre-Islamic rituals and practices persist in society. Notable among these are fortune-telling based on the Quran and healing rituals performed by “wandering mullahs” employing ushyktau, ushkyru, and the recitation of Quranic surahs. Despite the inherent ideological bias and partiality evident in official documents, the authors argue that these sources remain invaluable for comprehending the impact of Islam on the everyday culture of the Soviet Kazakh population during the 1950s–1960s.

Tracing participants for longitudinal environmental health research using social networking sites: a pilot study

Aim: Longitudinal cohort study designs are considered the gold standard for investigating associations between environmental exposures and human health yet they are characterized by limitations including participant attrition, and the resource implications associated with cohort recruitment and follow-up. Attrition compromises the integrity of research by threatening both the internal and external validity of empirical results, weakening the accuracy of statistical inferences and the generalizability of findings. This pilot study aimed to trace participants from a historical cohort study, the Hamilton Child Cohort Study (HCC) (n = 3,202), (1976–1986, 2003–2008) which was originally designed to examine the relative contribution of indoor and outdoor exposure to air pollution on respiratory health. Methods: Original participants were traced through social networking sites (SNS) by leveraging personal identifying data (name, age, sex, educational affiliation, and geographical locations) from the HCC entered into SNS search engines. Results: Of the original cohort (n = 3,166), 21% (n = 665) were identified as having social media presence (SMP) on a single social media platform, with 15% (n = 479) found on Facebook, 6% (n = 185) on LinkedIn, &lt; 1% (n = 9) on Instagram, and n = 1 participant on Twitter. However, 68% (n = 2,168) of the cohort were associated with multiple SNS with the same features (matching names, ages, and locations), making conclusive identification challenging. The remaining 11% (n = 334) of the cohort had no SMP (NSMP). Statistical differences in sample characteristics of each cohort were analyzed using the Pearson chi-square test. Significant differences between the SMP and NSMP cohorts were found in relation to sex (p &lt; 0.001), and childhood neighborhood of residence (p &lt; 0.05). Conclusions: This study underscores social media’s potential for tracing participants in longitudinal studies while advising a multi-faceted approach to overcome inherent limitations and biases. A full-scale study is necessary to determine whether utilizing SNS to trace participants for longitudinal research is an effective tool for re-engaging research participants lost to attrition.

What Culture is ChatGPT’s AI?

Artificial intelligence (AI) is increasingly used in many fields. It is widely perceived as an intelligent system that does not just follow algorithms but can demonstrate independent judgment. AI is especially important in handling complex tasks. The responses from the most popular AI chat interface, Chat Generative Pre-Trained Transformer (ChatGPT), are used for guiding decision-making processes and can provide informative answers or recommendations for a wide variety of scenarios. Such scenarios can include job applicants screening or planning for military strategizing. However, similar to human intelligence, which is characterized by cultural biases affecting thought processes and interactions, AI's outputs may also be influenced by inherent cultural biases, whether programmed or incidental, potentially leading to inappropriate outcomes. Given that AI is often used to assist or replace human decision-making, it is particularly important to examine its potential cultural biases. This study aims to assess the cultural bias of ChatGPT by comparing the responses of ChatGPT with established cultural indices, employing the cultural parameters defined by House et al. (2004) and Hofstede (2001). The methodology involves selecting specific cultural parameters, formulating a set of questions representative of these parameters, and analyzing ChatGPT's responses. By using appropriate statistical methods, this study intends to compare ChatGPT's manifested culture with the known values of existing cultures as defined by the GLOBE and Hofstede parameters.

Navigating the ethical terrain of AI in higher education: Strategies for mitigating bias and promoting fairness

Artificial intelligence (AI) and machine learning (ML) are transforming higher education by enhancing personalized learning and academic support, yet they pose significant ethical challenges, particularly in terms of inherent biases. This review critically examines the integration of AI in higher education, underscoring the dual aspects of its potential to innovate educational paradigms and the essential need to address ethical implications to avoid perpetuating existing inequalities. The researchers employed a methodological approach that analyzed case studies and literature as primary data collection methods, focusing on strategies to mitigate biases through technical solutions, diverse datasets, and strict adherence to ethical guidelines. Their findings indicate that establishing an ethical AI environment in higher education is imperative and involves comprehensive efforts across policy regulation, governance, and education. The study emphasizes the significance of interdisciplinary collaboration in addressing the complexities of AI bias, highlighting how policy, regulation, governance, and education play pivotal roles in creating an ethical AI framework. Ultimately, the paper advocates for continuous vigilance and proactive strategies to ensure that AI contributes positively to educational settings, stressing the need for robust frameworks that integrate ethical considerations throughout the lifecycle of AI systems to ensure their responsible and equitable use.

Previous radiotherapy increases the efficacy of cemiplimab in the treatment of locally advanced and metastatic cutaneous squamous cell carcinoma: A retrospective analysis

BackgroundCemiplimab, a PD-1 inhibitor approved in 2018 for patients with locally advanced or metastatic cutaneous squamous cell carcinoma (cSCC) who are ineligible for curative therapies, lacks clarity regarding the optimal patient selection despite its known efficacy. ObjectiveThis retrospective study aims to assess the real-world treatment patterns and outcomes in patients with cSCC at our institution. MethodsA retrospective analysis of consecutively treated patients with cemiplimab for cSCC was conducted. Progression-Free Survival (PFS) and Overall Survival (OS) were evaluated alongside clinical-pathologic characteristics. Results45 patients were included, of which 73.3% were male with a median age of 77 years. After 18 months of median follow-up median PFS and OS were not reached with a mean of 21.3 months ± 2.2 months and 25.3 ± 2.1 months, respectively. Univariate and multivariate analyses revealed significant correlations only between PFS and previous radiotherapy (p-values: 0.043 and 0.046, respectively).Limitations: limitations include its retrospective nature, the low number of patients analyzed and the potential for inherent biases. ConclusionsThe study reveals a significant association between prior radiotherapy and improved PFS in cemiplimab-treated cSCC, suggesting the potential for combining radiotherapy with cemiplimab. Further exploration of this combined approach is warranted.

Towards effective implementation of the energy efficiency first principle: a theory-based classification and analysis of policy instruments

The energy efficiency first (EE1st) principle, embedded in the European Union's (EU) recast Energy Efficiency Directive, aims to prioritise cost-effective energy efficiency solutions over new energy supply infrastructure. These solutions encompass not only end-use energy efficiency, but also, notably, demand-side flexibility. This research bridges the gap between the theoretical underpinnings of the principle and practical policy implementation. Drawing on market failure theory, it identifies an inherent bias in EU energy markets in favour of energy supply infrastructure. By highlighting the correction of market failures – from externalities to transaction costs – through targeted policy instruments, it presents a theoretical policy intervention logic for EE1st. Based on this, it offers a set of twenty-nine established and emerging policy instruments linked to specific market failures, thus providing a systematic roadmap for EE1st application. The study concludes that levelling the playing field between energy efficiency and energy supply requires a broad policy response. This extends beyond traditional energy efficiency policy of standards and public financing, and includes instruments such as electricity market design, remuneration schemes for network operators, and emissions pricing.

Dual-Tower Counterfactual Session-Aware Recommender System.

In the complex dynamics of modern information systems such as e-commerce and streaming services, managing uncertainty and leveraging information theory are crucial in enhancing session-aware recommender systems (SARSs). This paper presents an innovative approach to SARSs that combines static long-term and dynamic short-term preferences within a counterfactual causal framework. Our method addresses the shortcomings of current prediction models that tend to capture spurious correlations, leading to biased recommendations. By incorporating a counterfactual viewpoint, we aim to elucidate the causal influences of static long-term preferences on next-item selections and enhance the overall robustness of predictive models. We introduce a dual-tower architecture with a novel data augmentation process and a self-supervised training strategy, tailored to tackle inherent biases and unreliable correlations. Extensive experiments demonstrate the effectiveness of our approach, outperforming existing benchmarks and paving the way for more accurate and reliable session-based recommendations.

Consideration of student evaluations of teaching (SET) and learning: perspectives of learning and teaching leaders through the ethical lens of “first, do no harm”

This paper explores institutional leaders’ perceptions of learning and teaching involved in facilitating and assessing Student Evaluations of Teaching (SET) survey instruments across Australian regional universities. It focuses on how they understand the function of SET, strategies used to mitigate bias, and potential residual harm. Through adopting a combination of inductive and deductive research processes and a thematic analysis through the ethical lens of nonmaleficence (first, do no harm), we report that leaders in learning and teaching perceive SET as a form of surveillance and Quality Assurance ‘performance’, recognise inherent biases inhabited in SET reports, and identify how these biases negatively impact academics through a lack of systematic harm mitigation strategies. The paper’s critical – and novel – contributions include an increased understanding of how SET inflicts harm towards women and other marginalised academic groups through systematic and authorised microaggressions and how SET contravenes universities’ duty of care to employees. It recommends an expansion of the principle of nonmaleficence beyond potential harm to research subjects, including those who undertake research or evaluation (such as academics), particularly if these impact them.

A Novel Privacy Preservation Scheme by Matrix Factorized Deep Autoencoder

Data transport entails substantial security to avoid unauthorized snooping as data mining yields important and quite often sensitive information that must be and can be secured using one of the myriad Data Privacy Preservation methods. This study aspires to provide new knowledge to the study of protecting personal information. The key contributions of the work are an imputation method for filling in missing data before learning item profiles and the optimization of the Deep Auto-encoded NMF with a customizable learning rate. We used Bayesian inference to assess imputation for data with 13%, 26%, and 52% missing at random. By correcting any inherent biases, the results of decomposition problems may be enhanced. As the statistical analysis tool, MAPE is used. The proposed approach is evaluated on the Wiki dataset and the traffic dataset, against state-of-the-art techniques including BATF, BGCP, BCPF, and modified PARAFAC, all of which use a Bayesian Gaussian tensor factorization. Using this approach, the MAPE index is decreased for data which avails privacy safeguards than its corresponding original forms.