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ObjectiveContinuity of care is a long-standing feature of healthcare, especially of general practice. It is associated with increased patient satisfaction, increased take-up of health promotion, greater adherence to medical advice and decreased use of hospital services. This review aims to examine whether there is a relationship between the receipt of continuity of doctor care and mortality.DesignSystematic review without meta-analysis.Data sourcesMEDLINE, Embase and the Web of Science, from 1996 to 2017.Eligibility criteria for selecting studiesPeer-reviewed primary research articles, published in English which reported measured continuity of care received by patients from any kind of doctor, in any setting, in any country, related to measured mortality of those patients.ResultsOf the 726 articles identified in searches, 22 fulfilled the eligibility criteria. The studies were all cohort or cross-sectional and most adjusted for multiple potential confounding factors. These studies came from nine countries with very different cultures and health systems. We found such heterogeneity of continuity and mortality measurement methods and time frames that it was not possible to combine the results of studies. However, 18 (81.8%) high-quality studies reported statistically significant reductions in mortality, with increased continuity of care. 16 of these were with all-cause mortality. Three others showed no association and one demonstrated mixed results. These significant protective effects occurred with both generalist and specialist doctors.ConclusionsThis first systematic review reveals that increased continuity of care by doctors is associated with lower mortality rates. Although all the evidence is observational, patients across cultural boundaries appear to benefit from continuity of care with both generalist and specialist doctors. Many of these articles called for continuity to be given a higher priority in healthcare planning. Despite substantial, successive, technical advances in medicine, interpersonal factors remain important.PROSPERO registration numberCRD42016042091.

Adoption of legal technology within law firms has seen a significant increase in recent years with the current necessity for seemingly indefinite remote working only adding to the need for technology solutions to keep legal workflows running. In light of this, legal technology purchases will undoubtedly see a further increase and a well conducted proof of value is crucial to making the right investment decision. This article is based on a talk given by Eleanor White at the BIALL Knowledge Management SIG in November 2018. It establishes the difference between a proof of concept and proof of value and elaborates on some key principles to consider during each phase of the latter. From the preparation and planning through to the running of the evaluation and the resulting decision-making process, this article addresses how to get the most out of the proof of value opportunity.

To explore COVID-19 vaccination uptake, facilitators and barriers in ethnically-diverse pregnant women. An anonymous quality improvement questionnaire survey exploring COVID-19 vaccination uptake, causes of vaccine hesitancy and trusted sources of information among pregnant women in two acute district general hospitals in England (Berkshire and Surrey) between 1.9.21 and 28.2.22. 441 pregnant women attending routine antenatal clinic appointments. Consented pregnant women completed the survey either electronically using a QR code or on paper. Descriptive data were summarised and free text responses were thematically analysed. 441 pregnant women, mean age 32 years (range 17-44), completed the survey. Twenty-six percent were from ethnic minority groups, and 31% had a co-morbid health condition. Most respondents (66.2%) had been vaccinated against COVID-19 with at least one dose (White British 71.9%, Asian 67.9%, White-other 63.6%, Black 33%). The most common reasons for not being vaccinated were concerns about effects on the unborn baby and future pregnancies, anxiety about possible adverse impact on the mother, not enough known about the vaccine, and lack of trust in vaccines. Comments included: \"I'd rather not risk injecting the unknown into my body\", and \"I don't trust it.\" Although 23% used social media for information on COVID-19 vaccination, the most trusted sources were the patient's GP and midwife (43%) and official health-related websites such as NHS (39%). A third of these pregnant women had not been vaccinated against COVID-19. Trusted health professionals like midwives and GPs could have a crucial role in increasing vaccination uptake.

Loneliness is a global issue which is particularly prevalent among college students, where it poses risks to mental health and academic success. Chronic loneliness can manifest in two primary forms: social loneliness, which is defined by a lack of belonging or a social network, and emotional loneliness, which comes from the absence of deep, meaningful connections. Differentiating between these forms is crucial for designing personalized and targeted interventions. Passive sensing technology offers a promising, unobtrusive approach to detecting loneliness by using behavioural data collected from smartphones and wearables. This study investigates behavioural patterns associated with social and emotional loneliness using passively sensed data from a student population. Our objectives were to (1) identify behavioural patterns linked to social and emotional loneliness, (2) evaluate the predictive power of these patterns for classifying loneliness types, and (3) determine the most significant digital markers used by machine learning models in loneliness prediction. Using statistical analysis, machine learning, and SHAP-based feature importance methods, we identified significant differences in behaviours between socially and Emotionally Lonely students. Specifically, there were distinct differences in phone use and location-based features. Our machine learning analysis shows a strong ability to classify types of loneliness accurately. The XGBoost model achieved the highest accuracy (78.48%) in predicting loneliness. Feature importance analysis found the critical role of phone usage and location-based features in distinguishing between social and emotional loneliness.

Ayahuasca is a psychedelic plant brew originating from the Amazon rainforest. It is formed from two basic components, the Banisteriopsis caapi vine and a plant containing the potent psychedelic dimethyltryptamine (DMT), usually Psychotria viridis. Here we review the history of ayahuasca and describe recent work on its pharmacology, phenomenological responses, and clinical applications. There has been a significant increase in interest in ayahuasca since the turn of the millennium. Anecdotal evidence varies significantly, ranging from evangelical accounts to horror stories involving physical and psychological harm. The effects of the brew on personality and mental health outcomes are discussed in this review. Furthermore, phenomenological analyses of the ayahuasca experience are explored. Ayahuasca is a promising psychedelic agent that warrants greater empirical attention regarding its basic neurochemical mechanisms of action and potential therapeutic application.

Background Opportunities for nurses, midwives, allied health professionals and healthcare scientists (NMAHP+s) to engage in research are increasing but still lag behind opportunities for medical staff.Iinitiatives to identify, support and develop NMAHP+s considering and pursuing clinical academic roles are key to growing an NMAHP+ clinical academic workforce. We describe and evaluate the impact of the Interdisciplinary Clinical Academic health Research Excellence facilitated research career pathway (iCAhRE ™ programme) on NMAHP+ participants in one National Health Service Trust in England. Methods The study used a mixed methods approach informed by the Kirkpatrick Model of Training/Evaluation. Quantitative data related to uptake, progression through programme stages and key demographics of participants in the programme. Twenty-nine participants participated in a survey which assessed experiences of the programme, learning and impact from the programme, career trajectories, and barriers and enablers to pursuing a clinical academic career. Experiences of the programme were captured in greater depth in 12 interviews. Results Since 2016, participants were able to engage with the programme appropriate to their needs and research careers. Responses to the programme were highly positive and participants had increased their research knowledge and skills, initiated new research-related activities, improved their practice and increased their confidence. A high number had progressed to a role with a higher banding compared to when they started the programme (37.9%) and had research as part of their current role (55.2%). However, significant challenges to pursuing a clinical academic career for NMAHP+s included: unsupportive managers, lack of dedicated time for research engagement in a context of clinical pressures, a lack of clinical academic posts and limited progression opportunities. Conclusions This NHS Trust-supported high-quality facilitated research career pathway has lasting effects, increasing research knowledge and skills, informing and changing participants’ clinical practice, building confidence, increasing research-related activities undertaken and career progression. The programme’s range of opportunities across the whole pathway, the strong collaborative partnership between the NHS Trust and partner Higher Education Institute (HEI) and visible support for research are important contributors to the programme’s impact. However, challenges to pursuing a clinical academic career for NMAHP+s persist and require further attention.

Loneliness and social isolation are associated with multiple health problems, including depression, functional impairment, and death. Mobile sensing using smartphones and wearable devices, such as fitness trackers or smartwatches, as well as ambient sensors, can be used to acquire data remotely on individuals and their daily routines and behaviors in real time. This has opened new possibilities for the early detection of health and social problems, including loneliness and social isolation. This scoping review aimed to identify and synthesize recent scientific studies that used passive sensing techniques, such as the use of in-home ambient sensors, smartphones, and wearable device sensors, to collect data on device users' daily routines and behaviors to detect loneliness or social isolation. This review also aimed to examine various aspects of these studies, especially target populations, privacy, and validation issues. A scoping review was undertaken, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Studies on the topic under investigation were identified through 6 databases (IEEE Xplore, Scopus, ACM, PubMed, Web of Science, and Embase). The identified studies were screened for the type of passive sensing detection methods for loneliness and social isolation, targeted population, reliability of the detection systems, challenges, and limitations of these detection systems. After conducting the initial search, a total of 40,071 papers were identified. After screening for inclusion and exclusion criteria, 29 (0.07%) studies were included in this scoping review. Most studies (20/29, 69%) used smartphone and wearable technology to detect loneliness or social isolation, and 72% (21/29) of the studies used a validated reference standard to assess the accuracy of passively collected data for detecting loneliness or social isolation. Despite the growing use of passive sensing technologies for detecting loneliness and social isolation, some substantial gaps still remain in this domain. A population heterogeneity issue exists among several studies, indicating that different demographic characteristics, such as age and differences in participants' behaviors, can affect loneliness and social isolation. In addition, despite extensive personal data collection, relatively few studies have addressed privacy and ethical issues. This review provides uncertain evidence regarding the use of passive sensing to detect loneliness and social isolation. Future research is needed using robust study designs, measures, and examinations of privacy and ethical concerns.

Background While there is recognition of the relationship between loneliness and depression, specific behavioural patterns distinguishing both are still not well understood. Objectives Our objective is to identify distinct behavioural patterns of loneliness and depression from a passively collected dataset of college students, understand their similarities and interrelationships and assess their effectiveness in identifying loneliness and depression. Methods Utilizing the StudentLife dataset, we applied regression analysis to determine associations with self-reported loneliness and depression. Mediation analysis interprets the relationship between the two conditions, and machine learning models predict loneliness and depression based on behavioural indicators. Results Distinct behavioural patterns emerged: high evening screen time (OR = 1.45, p = 0.002) and high overall phone usage (OR = 1.50, p = 0.003) were associated with more loneliness, whereas depression was significantly associated with fewer screen unlocks (OR = 0.75, p = 0.044) and visits to fewer unique places (OR = 0.85, p = 0.023). Longer durations of physical activity (OR = 0.72, p = 0.014) and sleep (OR = 0.46, p = 0.002) are linked to a lower risk of both loneliness and depression. Mediation analysis revealed that loneliness significantly increases the likelihood of depression by 48%. The prediction accuracy of our XGBoost-based machine learning approach was 82.43% for loneliness and 79.43% for depression. Conclusion Our findings show that high evening screen time and overall phone usage are significantly associated with increased loneliness, while fewer screen unlocks and visits to fewer unique places are significantly related to depression. The findings can help in developing targeted interventions to promote well-being and mental health in students.

Foster carers require high-quality training to support them in caring for children with trauma-related difficulties. This paper describes a mixed methods approach that was applied to evaluate the complex intervention Fostering Connections: The Trauma-Informed Foster Care Programme, a recently developed trauma-informed psychoeducational intervention for foster carers in Ireland. A quantitative outcome evaluation and a qualitative process evaluation were integrated to capture a comprehensive understanding of the effects of this complex intervention. A convergent mixed methods model with data integration was used. Coding matrix methods were employed to integrate data. There was convergence among component studies for: programme acceptability, increased trauma-informed foster caring, improvement in child regulation and peer problems, and the need for ongoing support for foster carers. This research provides support for the intervention suggesting the importance of its implementation in Ireland. The integrative findings are discussed in relation to effects and future implementation.