BackgroundResearch has shown high rates of suicidality in autism spectrum conditions (ASC), but there is lack of research into why this is the case. Many common experiences of autistic adults, such as depression or unemployment, overlap with known risk markers for suicide in the general population. However, it is unknown whether there are risk markers unique to ASC that require new tailored suicide prevention strategies.MethodsThrough consultation with a steering group of autistic adults, a survey was developed aiming to identify unique risk markers for suicidality in this group. The survey measured suicidality (SBQ-R), non-suicidal self-injury (NSSI-AT), mental health problems, unmet support needs, employment, satisfaction with living arrangements, self-reported autistic traits (AQ), delay in ASC diagnosis, and ‘camouflaging’ ASC. One hundred sixty-four autistic adults (65 male, 99 female) and 169 general population adults (54 males, 115 females) completed the survey online.ResultsA majority of autistic adults (72%) scored above the recommended psychiatric cut-off for suicide risk on the SBQ-R; significantly higher than general population (GP) adults (33%). After statistically controlling for a range of demographics and diagnoses, ASC diagnosis and self-reported autistic traits in the general population significantly predicted suicidality. In autistic adults, non-suicidal self-injury, camouflaging, and number of unmet support needs significantly predicted suicidality.ConclusionsResults confirm previously reported high rates of suicidality in ASC, and demonstrate that ASC diagnosis, and self-reported autistic traits in the general population are independent risk markers for suicidality. This suggests there are unique factors associated with autism and autistic traits that increase risk of suicidality. Camouflaging and unmet support needs appear to be risk markers for suicidality unique to ASC. Non-suicidal self-injury, employment, and mental health problems appear to be risk markers shared with the general population that are significantly more prevalent in the autistic community. Implications for understanding and prevention of suicide in ASC are discussed.

SummaryIn cost-utility analysis, the numbers of quality-adjusted life years (QALYs) gained are aggregated according to the sum-ranking (or QALY maximisation) rule. This requires that the social value from health improvements is a simple product of gains in quality of life, length of life and the number of persons treated. The results from a systematic review of the literature suggest that QALY maximisation is descriptively flawed. Rather than being linear in quality and length of life, it would seem that social value diminishes in marginal increments of both. And rather than being neutral to the characteristics of people other than their propensity to generate QALYs, the social value of a health improvement seems to be higher if the person has worse lifetime health prospects and higher if that person has dependents. In addition, there is a desire to reduce inequalities in health. However, there are some uncertainties surrounding the results, particularly in relation to what might be affecting the responses, and there is the need for more studies of the general public that attempt to highlight the relative importance of various key factors. Copyright

Autistic people are at high risk of mental health problems, self-injury and suicidality. However, no studies have explored autistic peoples’ experiences of treatment and support for these difficulties. In partnership with a steering group of autistic adults, an online survey was developed to explore these individuals’ experiences of treatment and support for mental health problems, self-injury and suicidality for the first time. A total of 200 autistic adults (122 females, 77 males and 1 unreported) aged 18–67 (mean = 38.9 years, standard deviation = 11.5), without co-occurring intellectual disability, completed the online survey. Thematic analysis of open-ended questions resulted in an overarching theme that individually tailored treatment and support was both beneficial and desirable, which consisted of three underlying themes: (1) difficulties in accessing treatment and support; (2) lack of understanding and knowledge of autistic people with co-occurring mental health difficulties and (3) appropriate treatment and support, or lack of, impacted autistic people’s well-being and likelihood of seeing suicide as their future. Findings demonstrate an urgent need for autism treatment pathways in mental health services.

In this paper, we outline the three main concepts of 'ageism'; health maximisation ageism, productivity ageism, and fair innings ageism. We provide a methodological overview of the existing empirical literature on people's preferences regarding age and classify these studies according to the types of questions that have been asked. We consider some of the methodological issues involved in eliciting preferences regarding ageism and propose using a fixed duration of benefit rather than, as some studies have done, a benefit that lasts for a full lifetime. Informed by this discussion, we present the results from our own empirical study, carried out in the UK, which combines qualitative and quantitative methods to explore the reasons people have for choosing one age over another. In so doing, we are able to consider the extent to which respondents might bring extraneous factors to bear on their responses and/or disregard relevant information (such as that relating to the fixed nature of the benefit). The results suggest that people are broadly in favour of giving priority to younger over older people, based on arguments relating to both productivity ageism and fair innings ageism. However, respondents appear to assume that a benefit would last for a full lifetime (even if they are told to assume a fixed benefit), unless they are asked to consider a 'full-life' benefit first. This particular framing effect has important implications for preference elicitation studies, suggesting that if you want people to answer the question you have in mind, first ask them the question you think they may have in mind.

This article compares two practices for initiating treatment decision-making, evident in audio-recorded consultations between a neurologist and 13 patients in two hospital clinics in the UK. We call these 'recommending' and 'option-listing'. The former entails making a proposal to do something; the latter entails the construction of a list of options. Using conversation analysis (CA), we illustrate each, showing that the distinction between these two practices matters to participants. Our analysis centres on two distinctions between the practices: epistemic differences and differences in the slots each creates for the patient's response. Considering the implications of our findings for understanding medical authority, we argue that option-listing -relative to recommending -is a practice whereby clinicians work to relinquish a little of their authority. This article contributes, then, to a growing body of CA work that offers a more nuanced, tempered account of medical authority than is typically portrayed in the sociological literature. We argue that future CA studies should map out the range of ways -in addition to recommending -in which treatment decision-making is initiated by clinicians. This will allow for further evidence-based contributions to debates on the related concepts of patient participation, choice, shared decisionmaking and medical authority.

Background.Physical activity can positively influence health for older adults. Primary care is a good setting for physical activity promotion.Objective.To assess the feasibility of a pedometer-based walking programme in combination with physical activity consultations.Methods.Design: Two-arm (intervention/control) 12-week randomized controlled trial with a 12-week follow-up for the intervention group. Setting: One general practice in Glasgow, UK. Participants: Participants were aged ≥65 years. The intervention group received two 30-minute physical activity consultations from a trained practice nurse, a pedometer and a walking programme. The control group continued as normal for 12 weeks and then received the intervention. Both groups were followed up at 12 and 24 weeks. Outcome measures: Step counts were measured by sealed pedometers and an activPALTM monitor. Psychosocial variables were assessed and focus groups conducted.Results.The response rate was 66% (187/284), and 90% of those randomized (37/41) completed the study. Qualitative data suggested that the pedometer and nurse were helpful to the intervention. Step counts (activPAL) showed a significant increase from baseline to week 12 for the intervention group, while the control group showed no change. Between weeks 12 and 24, step counts were maintained in the intervention group, and increased for the control group after receiving the intervention. The intervention was associated with improved quality of life and reduced sedentary time.Conclusions.It is feasible to recruit and retain older adults from primary care and help them increase walking. A larger trial is necessary to confirm findings and consider cost-effectiveness.

Previous research shows that autistic people have high levels of co-occurring mental health conditions. Yet, a number of case reports have revealed that mental health conditions are often misdiagnosed in autistic individuals. A total of 420 adults who identified as autistic, possibly autistic or non-autistic completed an online survey consisting of questions regarding mental health diagnoses they received, whether they agreed with those diagnoses and if not why. Autistic and possibly autistic participants were more likely to report receiving mental health diagnoses compared to non-autistic participants, but were less likely to agree with those diagnoses. Thematic analysis revealed the participants’ main reasons for disagreement were that (1) they felt their autism characteristics were being confused with mental health conditions by healthcare professionals and (2) they perceived their own mental health difficulties to be resultant of ASC. Participants attributed these to the clinical barriers they experienced, including healthcare professionals’ lack of autism awareness and lack of communication, which in turn prevented them from receiving appropriate support. This study highlights the need for autism awareness training for healthcare professionals and the need to develop tools and interventions to accurately diagnose and effectively treat mental health conditions in autistic individuals.

Using Conversation Analysis (CA), we studied conversations between one UK-based epilepsy specialist and thirteen seizure patients in whom there was uncertainty about the diagnosis, and for whom different treatment and investigational options were being considered. In line with recent communication guidance, the specialist offered some form of choice to all patients: in eight cases, a course of action was proposed, to be accepted or rejected, and in the remaining five a "menu" of options was offered. Even when presenting a menu, the specialist sometimes conveyed his own preferences in how he described the options, and in some cases the menu was used for reasons other than offering choice (e.g. to address patient resistance). Close linguistic and interactional analysis of clinical encounters can show why doctors may feel they are offering choices when patients report that the decision was clinician-dominated.