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.

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.

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.

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.

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.

Reliability and Validity of a Turkish Version of Multi-Factor Attitude Toward Condoms Scale: A Methodological Study.

ABSTRACT: This study tested the validity and reliability of the Turkish translation of the Multi-Factor Attitude toward Condoms Scale in a sample of Turkish outpatient clients ( N = 336). Internal consistency reliability was demonstrated by a Cronbach α of .82, and test-retest reliability was supported by a positive correlation between initial and retest scores ( p < .05). Construct validity was supported by results of an exploratory factor analysis that yielded a three-factor solution, explaining 71.0% of the variance. The Turkish version of the scale was found to be valid and reliable.

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.

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.

Road map for research on responsible artificial intelligence for development (AI4D) in African countries: The case study of agriculture.

Individuals from a diverse range of backgrounds are increasingly engaging in research and development in the field of artificial intelligence (AI). The main activities, although still nascent, are coalescing around three core activities: innovation, policy, and capacity building. Within agriculture, which is the focus of this paper, AI is working with converging technologies, particularly data optimization, to add value along the entire agricultural value chain, including procurement, farm automation, and market access. Our key takeaway is that, despite the promising opportunities for development, there are actual and potential challenges that African countries need to consider in deciding whether to scale up or down the application of AI in agriculture. Input from African innovators, policymakers, and academics is essential to ensure that AI solutions are aligned with African needs and priorities. This paper proposes questions that can be used to form a road map to inform research and development in this area.

Philosophical foundations for digital ethics and AI Ethics: a dignitarian approach.

AI Ethics is a burgeoning and relatively new field that has emerged in response to growing concerns about the impact of artificial intelligence (AI) on human individuals and their social institutions. In turn, AI ethics is a part of the broader field of digital ethics, which addresses similar concerns generated by the development and deployment of new digital technologies. Here, we tackle the important worry that digital ethics in general, and AI ethics in particular, lack adequate philosophical foundations. In direct response to that worry, we formulate and rationally justify some basic concepts and principles for digital ethics/AI ethics, all drawn from a broadly Kantian theory of human dignity. Our argument, which is designed to be relatively compact and easily accessible, is presented in ten distinct steps: (1) what "digital ethics" and "AI ethics" mean, (2) refuting the dignity-skeptic, (3) the metaphysics of human dignity, (4) human happiness or flourishing, true human needs, and human dignity, (5) our moral obligations with respect to all human real persons, (6) what a natural automaton or natural machine is, (7) why human real persons are not natural automata/natural machines: because consciousness is a form of life, (8) our moral obligations with respect to the design and use of artificial automata or artificial machines, aka computers, and digital technology more generally, (9) what privacy is, why invasions of digital privacy are morally impermissible, whereas consensual entrances into digital privacy are either morally permissible or even obligatory, and finally (10) dignitarian morality versus legality, and digital ethics/AI ethics. We conclude by asserting our strongly-held belief that a well-founded and generally-accepted dignitarian digital ethics/AI ethics is of global existential importance for humanity.

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.

The Effect of an Education and Counseling Program on Maternal/Neonatal Outcomes in Pregnant Women at Risk of Preeclampsia.

OBJECTIVE: To evaluate, in pregnant women at risk for preeclampsia, the effect of an education and counseling program on healthy lifestyle behaviors, self-efficacy, and maternal/neonatal outcomes. METHODS: This study had a randomized controlled trial design and was conducted with 132 pregnant women at risk of preeclampsia and attending an antenatal clinic for routine care. The intervention group received education and counseling focused on preventing preeclampsia and were given a preeclampsia booklet; the control group received standard prenatal care. The members of the 2 groups were seen 4 times during their pregnancies, and once after giving birth. Data were gathered with the Health Promoting Lifestyle Profile-II, the Self-Efficacy Scale (SES), pregnant woman and fetal follow-up forms, and a postpartum data collection form. Permission from the ethics committee was obtained for the study. RESULTS: Education and counseling about preeclampsia had a statistically significant effect on healthy lifestyle behaviors (P < .008). However, we found no statistically significant differences in the total SES scores (P > .0125), systolic and diastolic blood pressure averages, edema status, or feeling the baby move (P > .05). We found differences in terms of physical activity in the first and third follow-ups, and in terms of breathing exercises in the first, second, and third follow-ups (P < .05). Preeclampsia developed in 4 of the pregnant women (7.6%) in the control group but not at all in the intervention group. CONCLUSION: A preeclampsia education and counseling program could help to develop healthy lifestyle behaviors in pregnant women at risk of preeclampsia.

A high-level overview of AI ethics.

Artificial intelligence (AI) ethics is a field that has emerged as a response to the growing concern regarding the impact of AI. It can be read as a nascent field and as a subset of the wider field of digital ethics, which addresses concerns raised by the development and deployment of new digital technologies, such as AI, big data analytics, and blockchain technologies. The principle aim of this article is to provide a high-level conceptual discussion of the field by way of introducing basic concepts and sketching approaches and central themes in AI ethics. The first part introduces concepts by noting what is being referred to by "AI" and "ethics", etc.; the second part explores some predecessors to AI ethics, namely engineering ethics, philosophy of technology, and science and technology studies; the third part discusses three current approaches to AI ethics namely, principles, processes, and ethical consciousness; and finally, the fourth part discusses central themes in translating ethics in to engineering practice. We conclude by summarizing and noting the inherent interdisciplinary future directions and debates in AI ethics.

Systematizing Audit in Algorithmic Recruitment.

Business psychologists study and assess relevant individual differences, such as intelligence and personality, in the context of work. Such studies have informed the development of artificial intelligence systems (AI) designed to measure individual differences. This has been capitalized on by companies who have developed AI-driven recruitment solutions that include aggregation of appropriate candidates (Hiretual), interviewing through a chatbot (Paradox), video interview assessment (MyInterview), and CV-analysis (Textio), as well as estimation of psychometric characteristics through image-(Traitify) and game-based assessments (HireVue) and video interviews (Cammio). However, driven by concern that such high-impact technology must be used responsibly due to the potential for unfair hiring to result from the algorithms used by these tools, there is an active effort towards proving mechanisms of governance for such automation. In this article, we apply a systematic algorithm audit framework in the context of the ethically critical industry of algorithmic recruitment systems, exploring how audit assessments on AI-driven systems can be used to assure that such systems are being responsibly deployed in a fair and well-governed manner. We outline sources of risk for the use of algorithmic hiring tools, suggest the most appropriate opportunities for audits to take place, recommend ways to measure bias in algorithms, and discuss the transparency of algorithms.

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.

Analysis of community-based studies related with knowledge, awareness, attitude, and behaviors towards HPV and HPV vaccine published in Turkey: A systematic review

Human papilloma virus (HPV) vaccine is a proven method for preventing HPV-related cancers and genital warts, especially preventing cervical cancer. It is aimed to systematically review and synthesize conclusions in detail from community-based studies published in Turkey between 2009 and 2019, which evaluate the knowledge, awareness, attitude, and behaviors of individuals towards HPV and HPV vaccination. This systematic review is conducted based on the PRISMA reporting method and includes community-based, descriptive cross-sectional and cross-sectional studies published between 2009 and 2019. In this systematic review, 5132 studies from six databases were scanned in total. It was determined that there were 23 studies that met the eligibility criteria for this systematic review. In the reviewed studies, it was determined that the rate of "Hearing of HPV before" was 3.8% at the lowest and 57.0% at the highest, and the rate of "Hearing of HPV vaccine before" was 2.2% at the lowest and 74.7% at the highest. In the reviewed studies, it was reported that although parents' willingness to have their daughters vaccinated with HPV vaccine varied between 14.4% and 68.0%, their willingness to have their sons vaccinated with HPV vaccine varied between 11.0% and 62.0%. In addition, it was reported that the lowest rate of vaccination with HPV vaccine among participants was 0.3% at the lowest and 6.0% at the highest. Consequently, it is considered that conducting common, systematic, and continuous health education programs aimed at both sexes and including both parents, which will increase the knowledge and awareness on HPV and its vaccine, would provide positive attitudes, and will be effective in protecting against HPV-related cancers.