Psychopathy, intelligence and conviction history.

The current study examined the relationship between psychopathy, intelligence and two variables describing the conviction history (length of conviction and number of prior convictions). It was hypothesized that psychopathy factors (interpersonal and antisocial factors assuming a 2-factor model or interpersonal, affective, lifestyle and antisocial factors assuming a 4-factor model) would be related in different ways to IQ scores, length of conviction and number of prior convictions. Psychopathy and IQ were assessed using the PCL:SV and the CFT 20-R respectively. Results indicated no association between interpersonal psychopathy features (Factor 1, two-factor model), IQ and the number of prior convictions but a positive association between Factor 1 and the length of conviction. Antisocial features (Factor 2, two-factor model) were negatively related to IQ and the length of conviction and positively related to the number of prior convictions. Results were further differentiated for the four-factor model of psychopathy. The relationship between IQ and psychopathy features was further assessed by statistically isolating the effects of the two factors of psychopathy. It was found that individuals scoring high on interpersonal features of psychopathy are more intelligent than those scoring high on antisocial features, but less intelligent than those scoring low on both psychopathy features. The results underpin the importance of allocating psychopathic individuals to subgroups on the basis of personality characteristics and criminological features. These subgroups may identify different types of offenders and may be highly valuable for defining treatment needs and risk of future violence

A scattered landscape: assessment of the evidence base for 71 patient decision aids developed in a hospital setting

Background Recent publications reveal shortcomings in evidence review and summarization methods for patient decision aids. In the large-scale "Share to Care (S2C)" Shared Decision Making (SDM) project at the University Hospital Kiel, Germany, one of 4 SDM interventions was to develop up to 80 decision aids for patients. Best available evidence on the treatments' impact on patient-relevant outcomes was systematically appraised to feed this information into the decision aids. Aims of this paper were to (1) describe how PtDAs are developed and how S2C evidence reviews for each PtDA are conducted, (2) appraise the quality of the best available evidence identified and (3) identify challenges associated with identified evidence. Methods The quality of the identified evidence was assessed based on GRADE quality criteria and categorized into high-, moderate-, low-, very low-quality evidence. Evidence appraisal was conducted across all outcomes assessed in an evidence review and for specific groups of outcomes, namely mortality, morbidity, quality of life, and treatment harms. Challenges in evidence interpretation and summarization resulting from the characteristics of decision aids and the type and quality of evidence are identified and discussed. Conclusions Evidence reviews in this project were carefully conducted and summarized. However, the evidence identified for our decision aids was indeed a "scattered landscape" and often poor quality. Facing a high prevalence of low-quality, non-directly comparative evidence for treatment alternatives doesn't mean it is not necessary to choose an evidence-based approach to inform patients. While there is an urgent need for high quality comparative trials, best available evidence nevertheless has to be appraised and transparently communicated to patients

Making shared decision-making (SDM) a reality: protocol of a large-scale long-term SDM implementation programme at a Northern German University Hospital

Introduction: Shared decision-making (SDM) is not yet widely used when making decisions in German hospitals. Making SDM a reality is a complex task. It involves training healthcare professionals in SDM communication and enabling patients to actively participate in communication, in addition to providing sound, easy to understand information on treatment alternatives in the form of evidence-based patient decision aids (EbPDAs). This project funded by the German Innovation Fund aims at designing, implementing and evaluating a multicomponent, large-scale and integrative SDM programme-called SHARE TO CARE (S2C)-at all clinical departments of a University Hospital Campus in Northern Germany within a 4-year time period. Methods and analysis S2C tackles the aforementioned components of SDM: (1) training physicians in SDM communication, (2) activating and empowering patients, (3) developing EbPDAs in the most common/relevant diseases and (4) training other healthcare professionals in SDM coaching. S2C is designed together with patients and providers. The physicians' training programme entails an online and an in situ training module. The decision coach training is based on a similar but less comprehensive approach. The development of online EbPDAs follows the International Patient Decision Aid Standards and includes written, graphical and video-based information. Validated outcomes of SDM implementation are measured in a preintervention and postintervention evaluation design. Process evaluation accompanies programme implementation. Health economic impact of the intervention is investigated using a propensity-score-matched approach based on potentially preference-sensitive hospital decisions. Ethics and dissemination Ethics committee review approval has been obtained from Medical Ethics Committee of the Medical Faculty of the Christian-Albrechts-University Kiel. Project information and results will be disseminated at conferences, on project-hosted websites at University Hospital Medical Center Schleswig Holstein and by S2C as well as in peer-reviewed and professional journals

Investigating a training supporting shared decision making (IT'S SDM 2011): study protocol for a randomized controlled trial

<p/> <p>Background</p> <p>Shared Decision Making (SDM) is regarded as the best practice model for the communicative challenge of decision making about treatment or diagnostic options. However, randomized controlled trials focusing the effectiveness of SDM trainings are rare and existing measures of SDM are increasingly challenged by the latest research findings. This study will 1) evaluate a new physicians' communication training regarding patient involvement in terms of SDM, 2) validate SDM_MASS, a new compound measure of SDM, and 3) evaluate the effects of SDM on the perceived quality of the decision process and on the elaboration of the decision.</p> <p>Methods</p> <p>In a multi-center randomized controlled trial with a waiting control group, 40 physicians from 7 medical fields are enrolled. Each physician contributes a sequence of four medical consultations including a diagnostic or treatment decision.</p> <p>The intervention consists of two condensed video-based individual coaching sessions (15min.) supported by a manual and a DVD. The interventions alternate with three measurement points plus follow up (6 months).</p> <p>Realized patient involvement is measured using the coefficient SDM_MASSdrawn from the Multifocal Approach to the Sharing in SDM (MAPPIN'SDM) which includes objective involvement, involvement as perceived by the patient, and the doctor-patient concordance regarding their judges of the involvement. For validation purposes, all three components of SDM_MASSare supplemented by similar measures, the OPTION observer scale, the Shared Decision Making Questionnaire (SDM-Q) and the dyadic application of the Decisional Conflict Scale (DCS). Training effects are analyzed using t-tests. Spearman correlation coefficients are used to determine convergent validities, the influence of involvement (SDM_MASS) on the perceived decision quality (DCS) and on the elaboration of the decision. The latter is operationalised by the ELAB coefficient from the UP24 (Uncertainty Profile, 24 items version).</p> <p>Discussion</p> <p>Due to the rigorous blinded randomized controlled design, the current trial promises valid and reliable results. On the one hand, we expect this condensed time-saving training to be adopted in clinical routine more likely than previous trainings. On the other hand, the exhaustivity of the MAPPIN'SDM measurement system qualifies it as a reference measure for simpler instruments and to deepen understanding of decision-making processes.</p> <p>Trial registration</p> <p>Current Controlled Trials <a href="http://www.controlled-trials.com/ISRCTN78716079">ISRCTN78716079</a></p

The Relationship Between DSM-IV Cluster B Personality Disorders and Psychopathy According to Hare&apos;s Criteria: Clarification and Resolution of Previous Contradictions

This study examines the relationship between DSM-cluster B personality disorders (PDs) and psychopaths according to Hare&apos;s criteria as detected by the Psychopathy Checklist (PCL:SV) in 299 violent offenders. To clarify some contradictions among several previous studies on this issue, individual cluster B PDs were looked at alone, excluding any cases of comorbidity with other PDs of this cluster. We found highly significant relationships between antisocial and borderline PD and Factor II of the PCL and a highly significant correlation between narcissistic PD and Factor I of the PCL. These results were to be expected from the theoretical basis of the development of the PCL and provide a contribution to the construct validity of the PCL, which until now has not been validated on such a large sample in Germany

MAPPIN'SDM – The Multifocal Approach to Sharing in Shared Decision Making

BACKGROUND: The wide scale permeation of health care by the shared decision making concept (SDM) reflects its relevance and advanced stage of development. An increasing number of studies evaluating the efficacy of SDM use instruments based on various sub-constructs administered from different viewpoints. However, as the concept has never been captured in operable core definition it is quite difficult to link these parts of evidence. This study aims at investigating interrelations of SDM indicators administered from different perspectives. METHOD: A comprehensive inventory was developed mapping judgements from different perspectives (observer, doctor, patient) and constructs (behavior, perception) referring to three units (doctor, patient, doctor-patient-dyad) and an identical set of SDM-indicators. The inventory adopted the existing approaches, but added additional observer foci (patient and doctor-patient-dyad) and relevant indicators hitherto neglected by existing instruments. The complete inventory comprising a doctor-patient-questionnaire and an observer-instrument was applied to 40 decision consultations from 10 physicians from different medical fields. Convergent validities were calculated on the basis of Pearson correlation coefficients. RESULTS: Reliabilities for all scales were high to excellent. No correlations were found between observer and patients or physicians neither for means nor for single items. Judgements of doctors and patients were moderately related. Correlations between the observer scales and within the subjective perspectives were high. Inter-perspective agreement was not related to SDM performance or patient activity. CONCLUSION: The study demonstrates the contribution to involvement made by each of the relevant perspectives and emphasizes the need for an inter-subjective approach regarding SDM measurement

Patients' and Observers' Perceptions of Involvement Differ. Validation Study on Inter-Relating Measures for Shared Decision Making

OBJECTIVE: Patient involvement into medical decisions as conceived in the shared decision making method (SDM) is essential in evidence based medicine. However, it is not conclusively evident how best to define, realize and evaluate involvement to enable patients making informed choices. We aimed at investigating the ability of four measures to indicate patient involvement. While use and reporting of these instruments might imply wide overlap regarding the addressed constructs this assumption seems questionable with respect to the diversity of the perspectives from which the assessments are administered. METHODS: The study investigated a nested cohort (N = 79) of a randomized trial evaluating a patient decision aid on immunotherapy for multiple sclerosis. Convergent validities were calculated between observer ratings of videotaped physician-patient consultations (OPTION) and patients' perceptions of the communication (Shared Decision Making Questionnaire, Control Preference Scale & Decisional Conflict Scale). RESULTS: OPTION reliability was high to excellent. Communication performance was low according to OPTION and high according to the three patient administered measures. No correlations were found between observer and patient judges, neither for means nor for single items. Patient report measures showed some moderate correlations. CONCLUSION: Existing SDM measures do not refer to a single construct. A gold standard is missing to decide whether any of these measures has the potential to indicate patient involvement. PRACTICE IMPLICATIONS: Pronounced heterogeneity of the underpinning constructs implies difficulties regarding the interpretation of existing evidence on the efficacy of SDM. Consideration of communication theory and basic definitions of SDM would recommend an inter-subjective focus of measurement. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN25267500

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

The general fault in our fault lines

Pervading global narratives suggest that political polarization is increasing, yet the accuracy of such group meta-perceptions has been drawn into question. A recent US study suggests that these beliefs are inaccurate and drive polarized beliefs about out-groups. However, it also found that informing people of inaccuracies reduces those negative beliefs. In this work, we explore whether these results generalize to other countries. To achieve this, we replicate two of the original experiments with 10,207 participants across 26 countries. We focus on local group divisions, which we refer to as fault lines. We find broad generalizability for both inaccurate meta-perceptions and reduced negative motive attribution through a simple disclosure intervention. We conclude that inaccurate and negative group meta-perceptions are exhibited in myriad contexts and that informing individuals of their misperceptions can yield positive benefits for intergroup relations. Such generalizability highlights a robust phenomenon with implications for political discourse worldwide

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions 1, with behavioural science increasingly part of this process 2. In April 2020, an influential paper 3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization