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Abstract Background Artificial intelligence (AI) is a rapidly advancing field that is beginning to enter the practice of medicine. Primary care is a cornerstone of medicine and deals with challenges such as physician shortage and burnout which impact patient care. AI and its application via digital health is increasingly presented as a possible solution. However, there is a scarcity of research focusing on primary care physician (PCP) attitudes toward AI. This study examines PCP views on AI in primary care. We explore its potential impact on topics pertinent to primary care such as the doctor-patient relationship and clinical workflow. By doing so, we aim to inform primary care stakeholders to encourage successful, equitable uptake of future AI tools. Our study is the first to our knowledge to explore PCP attitudes using specific primary care AI use cases rather than discussing AI in medicine in general terms. Methods From June to August 2023, we conducted a survey among 47 primary care physicians affiliated with a large academic health system in Southern California. The survey quantified attitudes toward AI in general as well as concerning two specific AI use cases. Additionally, we conducted interviews with 15 survey respondents. Results Our findings suggest that PCPs have largely positive views of AI. However, attitudes often hinged on the context of adoption. While some concerns reported by PCPs regarding AI in primary care focused on technology (accuracy, safety, bias), many focused on people-and-process factors (workflow, equity, reimbursement, doctor-patient relationship). Conclusion Our study offers nuanced insights into PCP attitudes towards AI in primary care and highlights the need for primary care stakeholder alignment on key issues raised by PCPs. AI initiatives that fail to address both the technological and people-and-process concerns raised by PCPs may struggle to make an impact.

Low vaginal self-sampling has been pioneered as an important development to improve uptake of cervical screening globally. Limited research is available in specific patient groups in the UK exploring views around self-sampling to detect high-risk human papillomavirus (hrHPV) DNA. Therefore, we explored patient views to support development of a novel point-of-care self-sampling cervical cancer screening device, by undertaking a cross-sectional semi-structured questionnaire survey to explore preferences, acceptability, barriers and facilitators around self-sampling. Patients attending a colposcopy clinic, 25-64 years old, were invited to participate after having carried out a low vaginal self-sample using a regular flocked swab. Participants self-completed an anonymous 12-point questionnaire. Quantitative data were analysed in MS Excel and Graphpad Prism, and qualitative data with Nvivo. We recruited 274 patients with a questionnaire response rate of 76%. Acceptability of self-sampling was high (95%, n = 187/197; Cronbachs-α = 0.778). Participants were asked their choice of future screening method: a) low vaginal self-sampling, b) healthcare professional collected vaginal swab, c) cervical brush sample with healthcare professional speculum examination, or d) no preference. Preferences were: a) 37% (n = 74/198), b) 19% (n = 37/198); c) 9% (n = 17/198), and d) 35% (n = 70/198), showing no single option as a strong preference. Key motivators were: Test simplicity (90%, n = 170/190), speed (81%, n = 153/190) and less pain (65%, n = 123/190). Barriers included lack of confidence taking the sample (53%, n = 10/19), resulting in preference for a healthcare professional sample (47%, n = 9/19). Whilst self-sampling showed high acceptability, lack of strong preference for screening method may reflect that respondents attending colposcopy are already engaged with screening and have differing perception of cervical cancer risk. This group appear less likely to 'switch' to self-sampling, and it may be better targeted within primary and community care, focusing on under-screened populations. Any shift in this paradigm in the UK requires comprehensive education and support for patients and providers.

This article uses critical discourse analysis to interrogate Covid-19 vaccine allocation frameworks created by Johns Hopkins and the National Academies to understand how the authors of these frameworks conceptualized the problem of vaccine hesitancy among people of colour. This article argues these frameworks represent an institutional discourse about vaccine-hesitant racialized people that casts people of colour as mistrustful, conspiracy-prone and unwilling to engage with public health efforts and that this stereotyping undermined the anti-racist potential of these frameworks to address vaccine hesitancy among racialized people by failing to consider how vaccine hesitancy in people of colour can be an attempt to mitigate the untrustworthy nature of US public health institutions. There will undoubtedly be another situation in the future where there are not enough critical health resources for all, and priorities will have to be set. Public health officials need to learn from the Covid-19 experience and will need a far better understanding of the issue of vaccine hesitancy among people of colour.

In "Diagnosing Desire," Alyson K. Spurgas examines female sexual dysfunction, specifically low desire in women, and refuses to take anything for granted. One part history of modern sexology and one part feminist critique of the biopolitics engendered by sex research, Spurgas uses anti-racist, queer, disability studies, and trauma-informed theories to argue that the apolitical and atheoretical approach used in much of the modern science of sexuality confines women's sexual desire to a purely receptive model. Spurgas problematizes essentialist, anti-intersectional, and hetero- and cisnormative frameworks through which women's sexual desire has become a problem to be solved through self-improvement and by learning to push through feelings of low desire. Instead, Spurgas offers insights into the lives of women with low desire by attending to their experiences with inequality and trauma, and proposes a new understanding of women's sexuality—and of femininity more generally—based on prudent and critical attention to power.

A large sample of autistic and non-autistic adults was recruited to investigate whether self-reported beliefs about their own and other people's mindreading abilities were in line with either mindreading deficit accounts of autism or the double empathy problem (DEP) (which proposes mindreading difficulties are relational in autism). Three hundred and forty-eight (139 autistic) participants completed an online questionnaire which asked about autism identification and diagnostic status and their beliefs about their own mindreading abilities in relation to autistic and non-autistic others, and about autistic and non-autistic others' abilities to read their (the participant's) own minds. While autistic participants did report weaker mindreading abilities, this was only true in relation to non-autistic others. Both groups reported better mindreading abilities in same- than other-neurotype interactions, with autistic participants reporting mindreading abilities commensurate with non-autistic participants in relation to autistic targets. The same pattern was found when participants were asked about other people's mindreading abilities. The findings were more consistent with the DEP than deficit theories, as the target reference group strongly impacted participants' perceived mindreading abilities. While self-reported beliefs do not necessarily reflect actual mindreading abilities, they may still have important consequences for intergroup relations and social outcomes for autistic people.

Vertebrates are recognized as sentient beings. Consequently, urgent priority is now being given to understanding the needs and maximizing the welfare of animals under human care. The general health of animals is most commonly determined by physiological indices e.g., blood sampling, but may also be assessed by documenting behavior. Physiological health assessments, although powerful, may be stressful for animals, time-consuming and costly, while assessments of behavior can also be time-consuming, subject to bias and suffer from a poorly defined link between behavior and health. However, behavior is recognized as having the potential to code for stress and well-being and could, therefore, be used as an indicator of health, particularly if the process of quantifying behavior could be objective, formalized and streamlined to be time efficient. This study used Daily Diaries (DDs) (motion-sensitive tags containing tri-axial accelerometers and magnetometers), to examine aspects of the behavior of bycaught loggerhead turtles, Caretta caretta in various states of health. Although sample size limited statistical analysis, significant behavioral differences (in terms of activity level and turn rate) were found between “healthy” turtles and those with external injuries to the flippers and carapace. Furthermore, data visualization (spherical plots) clearly showed atypical orientation behavior in individuals suffering gas emboli and intestinal gas, without complex data analysis. Consequently, we propose that the use of motion-sensitive tags could aid diagnosis and inform follow-up treatment, thus facilitating the rehabilitation process. This is particularly relevant given the numerous rehabilitation programs for bycatch sea turtles in operation. In time, tag-derived behavioral biomarkers, TDBBs for health could be established for other species with more complex behavioral repertoires such as cetaceans and pinnipeds which also require rehabilitation and release. Furthermore, motion-sensitive data from animals under human care and wild conspecifics could be compared in order to define a set of objective behavioral states (including activity levels) for numerous species housed in zoos and aquaria and/or wild species to help maximize their welfare.

The developed world has pledged to mobilize at least US $100 billion per year of ‘new’ and ‘additional’ funds by 2020 to help the developing world respond to climate change. Tracking this finance is particularly problematic for climate change adaptation, as there is no clear definition of what separates adaptation aid from standard development aid. Here we use a historical database of overseas development assistance projects to test the effect of different accounting assumptions on the delivery of adaptation finance to the developing countries of Oceania, using machine algorithms developed from a manual pilot study. The results show that explicit adaptation finance grew to 3%–4% of all development aid to Oceania by the 2008–2012 period, but that total adaptation finance could be as high as 37% of all aid, depending on potentially politically motivated assumptions about what counts as adaptation. There was also an uneven distribution of adaptation aid between countries facing similar challenges like Kiribati, the Marshall Islands, and the Federated States of Micronesia. The analysis indicates that data allowing individual projects to be weighted by their climate change relevance is needed. A robust and mandatory metadata system for all aid projects would allow multilateral aid agencies and independent third parties to perform their own analyses using different assumptions and definitions, and serve as a key check on international climate aid promises.