Coping styles for sexual dysfunction and stress among married women of reproductive age: a cross-sectional study from Turkiye.

Objectives: To identify sexual dysfunction in married women of reproductive age, and to examine its relationship with stress coping styles. METHODS: The cross-sectional, descriptive study was conducted between February and June 2019 at the obstetrics and gynaecology outpatient clinic of Gulhane Training and Research Hospital in Ankara, Turkiye. The sample comprised married women aged 18-49 years who had an active sexual life over the preceding month, and were neither pregnant nor in the postpartum phase. Data was collected using the Female Sexual Function Index, and the Stress Coping Styles Scale. Data was analysed using SPSS 22. RESULTS: There were 216 women with mean age 33.58±6.77 years. The mean Female Sexual Function Index score was 22.29±6.08. The mean Stress Coping Styles Scale subscale scores were: self-confident 20.71±3.53, helpless 18.07±4.27, submissive 12.13±3.00, optimistic 13.70±2.35, and seeking social support 11.89±2.01. The total Female Sexual Function Index score had a positive, significant correlation with self-confidence (r=0.15; p=0.03) and seeking social support subscales (r=0.18; p=0.01) and a negative, significant correlation with submissive subscale (r=-0.17; p=0.02) of the Stress Coping Styles Scale. CONCLUSIONS: Establishing awareness among women about sexual dysfunction and improving effective coping styles may contribute to improved sexual health among women.

Machine Learning for Health: Algorithm Auditing & Quality Control.

Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 screening show. We envision an integrated framework of algorithm auditing and quality control that provides a path towards the effective and reliable application of ML systems in healthcare. In this editorial, we give a summary of ongoing work towards that vision and announce a call for participation to the special issue  Machine Learning for Health: Algorithm Auditing & Quality Control in this journal to advance the practice of ML4H auditing.

Effect of education and counselling on reducing pain and anxiety in women undergoing hysterosalpingography: A randomised controlled trial.

AIMS AND OBJECTIVES: To investigate the effects of education and counselling on anxiety and pain in women undergoing hysterosalpingography (HSG) as part of infertility treatment. BACKGROUND: The hysterosalpingography has an important diagnostic role in finding the cause of infertility and making a decision on management of treatment. In addition, it is considered a feared procedure in the infertility process and the one about which very little is known. Women often experience anxiety and pain during the HSG procedure. DESIGN: A randomised controlled trial. METHODS: The CONSORT guidelines have been used to describe the methods. Women who were diagnosed with infertility between February-October 2016 were included in the study. The participants were randomised and divided into intervention (52) and control (53) groups. The sociodemographic and obstetric data collection form, the State-Trait Anxiety Inventory and a visual analogue scale were used before the procedure. After the questionnaires were applied to the intervention group, individual learning and counselling sessions were given about the hysterosalpingography process. Brochures were also distributed to the patients for their reference after the learning session. The control group received standard care. RESULTS: When the intervention and control groups were compared, it was found that the education and counselling given before the HSG procedure significantly decreased the level of pain and anxiety felt by women. In addition, a significant positive correlation was found between pain and anxiety after the training in the intervention group. CONCLUSIONS: This study indicates that the education and counselling given to women before the HSG procedure are effective interventions for reducing pain and anxiety in women undergoing HSG. RELEVANCE TO CLINICAL PRACTICE: With the application of HSG education and counselling, and the distribution of brochures to each patient, pain and anxiety can be reduced during the HSG procedure.

Unicornuate uterus with a rudimentary horn diagnosed at scheduled third Cesarean Section.

A unicornuate uterus with a rudimentary horn is an anomaly caused by defective fusion of the Müllerian duct, estimated to occur in one in 76,000 pregnancies. Life threateningly heavy bleeding is a highly expected clinical consequence of such pregnancies. According to the known literature, only two living twins and few living singleton pregnancies have been reported up to now. Here we report on an incidentally diagnosed unicornuate uterus with a communicating rudimentary horn, found during a cesarean section of a gravida 3, parity 2 (G3 P2) patient. This case is rather unique since the patient has had three full term pregnancies and three cesarean sections without significant fetal compromise. This delivery and the existing literature showed us that extensive uterine correction surgeries need not be automatically proposed when a unicornuate uterus is diagnosed in the preconception period. Such deliveries indicate that women with this uterine anomaly may have the potential to carry pregnancies to full term.

Cytohistological discrepancies of cervico-vaginal smears and HPV status.

OBJECTIVES: Discrepancies between abnormal cervical cytology or high-risk human papillomavirus (HR-HPV) status (cytolo-gy negative/HPV positive) and subsequent histological findings are a common occurrence. After using co-testing, the dis-crepancies between the HR-HPV status and cervical cytology have become an issue. In this study, we aimed to determine the characteristics of women with a discrepancy between histology and cytology/HR-HPV status, in terms of diagnosis, review and identification. MATERIAL AND METHODS: A total of 52 women, patients of the University Hospital between 2013-2015, with cytohistologi-cal or HR-HPV status discrepancy were recruited for the study and retrospectively analyzed. The cytological samples were liquid-based Pap smears, classified according to the 2001 Bethesda system. The HR-HPV status was identified using the Hybrid Capture 2 HR-HPV DNA assay. The histological samples were obtained by cervical biopsy as well as large loop exci-sion of the transformation zone (LLETZ). RESULTS: A cytohistological discrepancy was demonstrated in patients with (-)cytology/HR-HPV(+), ASCUS, LSIL, ASC-H, HSIL, AGC-NOS: 17.3%, 23.07%, 26.9%, 9.5%, 17.3% and 5.7%, respectively. When the degree of atypia in cytology increases, the concurrency of cervical cytology with biopsy also increases. A positive HR-HPV co-test result (19/24, 79.1%) was observed in nearly all CIN2 ≥ (+) cases. Our study emphasizes the significance of HR-HPV testing to determine CIN2 ≥ (+) cases, even in the presence of a normal cytological result. CONCLUSIONS: In case of cytohistological or HR-HPV discrepancies, a careful review of the HR-HPV status and the degree of cytological atypia should be performed before further intervention.

Prenatal diagnosis of the acute meconium peritonitis secondary to ileum volvulus perforation: a case report.

This is an unusual case in comparison to other sonographically described prenatal cases due to very early diagnosis and surgical intervention following prompt delivery. A 40-year-old pregnant, ultrasonography showed presence of cystic structure in the fetal abdomen that was consistent with intestinal dilatation. At 32 weeks' of gestation, repeat ultrasound showed collapse of the bowel dilatation along with the presence of hyperechogenic fluid in the fetal abdominal cavity. Cesarean section was performed. The clinical utility of this report is the recognition that meconium peritonitis (MP) may be diagnosed in the acute phase with typical ultrasound features, and should be considered in the differential diagnoses of cases presented with reduced fetal movements. Although it appears that morbidity and mortality in MP cases depend upon gestational age, this case report may help to manage similar cases for defining the appropriate delivery time and treatment modality after prenatal identification of the problem.

Towards algorithm auditing: managing legal, ethical and technological risks of AI, ML and associated algorithms.

-Business reliance on algorithms is becoming ubiquitous, and companies are increasingly concerned about their algorithms causing major financial or reputational damage. High-profile cases include Google's AI algorithm for photo classification mistakenly labelling a black couple as gorillas in 2015 (Gebru 2020 In The Oxford handbook of ethics of AI, pp. 251-269), Microsoft's AI chatbot Tay that spread racist, sexist and antisemitic speech on Twitter (now X) (Wolf et al. 2017 ACM Sigcas Comput. Soc. 47, 54-64 (doi:10.1145/3144592.3144598)), and Amazon's AI recruiting tool being scrapped after showing bias against women. In response, governments are legislating and imposing bans, regulators fining companies and the judiciary discussing potentially making algorithms artificial 'persons' in law. As with financial audits, governments, business and society will require algorithm audits; formal assurance that algorithms are legal, ethical and safe. A new industry is envisaged: Auditing and Assurance of Algorithms (cf. data privacy), with the remit to professionalize and industrialize AI, ML and associated algorithms. The stakeholders range from those working on policy/regulation to industry practitioners and developers. We also anticipate the nature and scope of the auditing levels and framework presented will inform those interested in systems of governance and compliance with regulation/standards. Our goal in this article is to survey the key areas necessary to perform auditing and assurance and instigate the debate in this novel area of research and practice.

Neopterin: a promising marker for the inflammation in polycystic ovary syndrome.

BACKGROUND: Several markers of low-grade chronic inflammation are altered in women with polycystic ovary syndrome (PCOS). Neopterin (NEO) is a marker of celullar immunity, and oxidative stress, mainly produced by activated macrophages. We aimed to evaluate the NEO levels in PCOS patients and correlate them with antropometric and biochemical parameters. METHODS: The study groups consisted of 69 women with PCOS and 46 healthy controls. Both groups were divided into two subgroups according to their body mass index (BMI): <25 = normoweight, >25 = overweight. The clinical and biochemical parameters and serum NEO levels were analyzed. RESULTS: Circulating levels of NEO were significantly (p < 0.001) higher in women with PCOS (normoweight: 15.9 ± 4.7 nmol/l; overweight 13.3 ± 8.1 nmol/l) compared to controls (normoweight: 8.6 ± 2.0 nmol/l; overweight 9.2 ± 1.8 nmol/l) regardless of their weight classes. Waist-to-hip ratio (WHR) (p < 0.05), free and total testosterone (p < 0.001) were significantly elevated in women with PCOS compared to controls after controlling for the effect of obesity. CONCLUSION: Circulating NEO level s are elevated in PCOS independent of body mass index supporting the suggestion of PCOS is a low-grade chronic inflammatory state.

Chitotriosidase, interleukin-1 beta and tumor necrosis factor alpha levels in mild preeclampsia.

OBJECTIVE: Chitotriosidase (ChT) is an activated macrophage marker. Tumor necrosis factor alpha (TNF-α) and interleukin 1 beta (IL-1ß) are mainly produced macrophages. The aim of the present study was to evaluate the relationship between serum ChT activity, levels of TNF-α and IL-1ß in patients with mild preeclampsia and normal pregnancy. METHODS: An overall 64 cases, 32 healthy pregnant control women (control group) and 32 women with mild preeclamptic patients (study group), were enrolled in this study. At the beginning of the study, all study participants were matched for age and gestational age. Serum ChT activity was measured by fluorometer; TNF-α and IL-1ß levels were measured by enzyme-linked immunosorbent assay. RESULTS: The mean age, gestational week, parity and gravida were similar in the two groups (p > 0.05). Serum ChT activity was significantly higher in the preeclampsia group compared to the control group (p < 0.05). Levels of TNF-α and IL-1ß in patients with mild preeclampsia were similar compared to the control group (p > 0.05). In the PE group, serum ChT activity was not correlated with TNF-α and IL-1ß. CONCLUSION: Mild preeclampsia is found associated with higher ChT activity. This result suggests that activated macrophages play a role in the pathogenesis of preeclampsia. This suggestion needs to be confirmed in future studies with larger populations.

Combined approach in a large placental chorioangioma case with intratumoral alcohol injection, cordocentesis, IU transfusion, and amnioreduction.

Large placental chorioangiomas (LPCs) are rare complications of pregnancy and these tumors are associated with increased risk of pregnancy complications. We presented a LPC case at 25th week of gestation, complicated by polyhydramnios and preterm labor in which intratumoral alcohol injection was performed succesfully. Cordocentesis, fetal intrauterine transfusion, and amnioreduction were performed at the same session, as a combined approach. The safety of the procedure was shown by the lack of alcohol in the fetal cord blood sample. Intratumoral alcohol injection is a reliable and effective treatment modality in the management of LPCs and may be combined with other invasive procedures.

Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021.

In the past few decades, technology has completely transformed the world around us. Indeed, experts believe that the next big digital transformation in how we live, communicate, work, trade and learn will be driven by Artificial Intelligence (AI) [83]. This paper presents a high-level industrial and academic overview of AI in Education (AIEd). It presents the focus of latest research in AIEd on reducing teachers' workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd's research and practice. The intended readership of this article is policy makers and institutional leaders who are looking for an introductory state of play in AIEd.

The role of the African value of Ubuntu in global AI inclusion discourse: A normative ethics perspective.

Historically, Sub-Saharan Africa (SSA) has been excluded from the benefits of the previous industrial revolutions, as its people and their resources and aspirations have been objectified through foreign domination, and its culture has either been fragmented or appropriated. While artificial intelligence (AI) is poised to generate vast amounts of wealth, its application could lead to further social and economic exclusion of SSA due to a lack of access to technological advancements and the historical injustice and exclusion based on protected characteristics. Through an examination of the concept of inclusion, this paper explores how to improve the terms on which African populations and subpopulations and their concerns are included in the global AI ethics discourses. Specifically, it is argued that the SSA value of Ubuntu could be of immense value in AI applied normative ethics, particularly toward an inclusive approach for the implementation of the universal AI ethics principles and guidelines.

Scoring a forced-choice image-based assessment of personality: A comparison of machine learning, regression, and summative approaches.

Recent years have seen rapid advancements in the way that personality is measured, resulting in a number of innovative predictive measures being proposed, including using features extracted from videos and social media profiles. In the context of selection, game- and image-based assessments of personality are emerging, which can overcome issues like social desirability bias, lack of engagement and low response rates that are associated with traditional self-report measures. Forced-choice formats, where respondents are asked to rank responses, can also mitigate issues such as acquiescence and social desirability bias. Previously, we reported on the development of a gamified forced-choice image-based assessment of the Big Five personality traits created for use in selection, using Lasso regression for the scoring algorithms. In this study, we compare the machine-learning-based Lasso approach to ordinary least squares regression, as well as the summative approach that is typical of forced-choice formats. We find that the Lasso approach performs best in terms of generalisability and convergent validity, although the other methods have greater discriminate validity. We recommend the use of predictive Lasso regression models for scoring forced-choice image-based measures of personality over the other approaches. Potential further studies are suggested.

Measuring Personality through Images: Validating a Forced-Choice Image-Based Assessment of the Big Five Personality Traits.

Selection methods are commonly used in talent acquisition to predict future job performance and to find the best candidates, but questionnaire-based assessments can be lengthy and lead to candidate fatigue and poor engagement, affecting completion rates and producing poor data. Gamification can mitigate some of these issues through greater engagement and shorter testing times. One avenue of gamification is image-based tests. Although such assessments are starting to gain traction in personnel selection, few studies describing their validity and psychometric properties exist. The current study explores the potential of a five-minute, forced-choice, image-based assessment of the Big Five personality traits to be used in selection. Study 1 describes the creation of the image pairs and the selection of the 150 best-performing items based on a sample of 300 respondents. Study 2 describes the creation of machine-learning-based scoring algorithms and tests of their convergent and discriminate validity and adverse impact based on a sample of 431 respondents. All models showed good levels of convergent validity with the IPIP-NEO-120 (openness r = 0.71, conscientiousness r = 0.70, extraversion r = 0.78, agreeableness r = 0.60, and emotional stability r = 0.70) and were largely free from potential adverse impact. The implications for recruitment policy and practice and the need for further validation are discussed.

A critical review of the Online Safety Bill.

The UK Parliament has tabled the Online Safety Bill to make the internet safer for users by requiring providers to regulate legal but harmful content on their platform. This paper critically assesses the draft legislation, surveying its rationale; its scope in terms of lawful and unlawful harms it intends to regulate; and the mechanisms through which it will be enforced. We argue that it requires further refinement if it is to protect free speech and innovation in the digital sphere. We propose four conclusions: further evidence is required to substantiate the necessity and proportionality of the Bill's interventions; the Bill risks a democratic deficit by limiting the opportunity for parliamentary scrutiny; the duties of the bill may be too wide (in terms of burdening providers); and that enforcement of a Code of Practice will likely be insufficient.

Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem.

In recent years, the field of ethical artificial intelligence (AI), or AI ethics, has gained traction and aims to develop guidelines and best practices for the responsible and ethical use of AI across sectors. As part of this, nations have proposed AI strategies, with the UK releasing both national AI and data strategies, as well as a transparency standard. Extending these efforts, the Centre for Data Ethics and Innovation (CDEI) has published an AI Assurance Roadmap, which is the first of its kind and provides guidance on how to manage the risks that come from the use of AI. In this article, we provide an overview of the document's vision for a "mature AI assurance ecosystem" and how the CDEI will work with other organizations for the development of regulation, industry standards, and the creation of AI assurance practitioners. We also provide a commentary of some key themes identified in the CDEI's roadmap in relation to (i) the complexities of building "justified trust", (ii) the role of research in AI assurance, (iii) the current developments in the AI assurance industry, and (iv) convergence with international regulation.

On the sui generis value capture of new digital technologies: The case of AI.

Much of the academic interest surrounding the emergence of new digital technologies has focused on forwarding the engineering literature, concentrating on the potential opportunities (economic, innovation, etc.) and harms (ethics, climate, etc.), with less focus on the foundational and theoretical shifts brought about by these technologies (e.g., what are "digital things"? What is the ontological nature and state of phenomena produced by and expressed in terms of digital products? Are there distinctions between the traditional conceptions of digital and non-digital technologies?. We investigate the question of what value is being expressed by an algorithm, which we conceptualize in terms of a digital asset, defining a digital asset as a valued digital thing that is derived from a particular digital technology (in this case, an algorithmic system). Our main takeaway is to invite the reader to consider artificial intelligence as a representation of the capture of value sui generis and that this may be a step change in the capture of value vis à vis the emergence of digital technologies.