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Measures of adolescents' HIV/AIDS knowledge that cover only the basic facts may fail to assess underlying misunderstandings in need of intervention. We developed and evaluated a measure covering the broad domain of HIV/AIDS knowledge, emphasizing misunderstandings revealed in semi-structured qualitative interviews. These included the cumulative and relative risks of unsafe behaviors, proper condom use, needle cleaning, HIV test procedures, and disease progression. Reliability was satisfactory; a correlation between test performance and condom use among sexually active teens provided predictive validity. [ABSTRACT FROM AUTHOR]

We examine whether adolescents' probability judgments for significant life events are predictive and accurate. We find significant correlations with actual experiences, reported on successive waves of a national survey. Mean probability judgments approximated observed outcome rates, or were optimistic, except that adolescents greatly overestimated their probability of dying prematurely. [ABSTRACT FROM AUTHOR]

A longitudinal randomized design was used to evaluate the impact of a theoretically based, stand-alone interactive video intervention on 300 urban adolescent girls' (a) knowledge about sexually transmitted diseases (STDs), (b) self-reported sexual risk behavior, and (c) STD acquisition. It was compared to two controls, representing high-quality informational interventions. One used the same content in book form; the other used commercially available brochures. Following randomization, the interventions were administered at baseline, with booster sessions at 1, 3, and 6 months. Self-reports revealed that those assigned to the interactive video were significantly more likely to be abstinent in the first 3 months following initial exposure to the intervention, and experienced fewer condom failures in the following 3 months, compared to controls. Six months after enrollment, participants in the video condition were significantly less likely to report having been diagnosed with an STD. A non-significant trend in data from a clinical PCR assay of Chlamydia trachomatis was consistent with that finding. [ABSTRACT FROM AUTHOR]

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research., (© 2024. The Author(s).)

Background: Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting., Methods: Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier., Results: Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82-0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers ( N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70-0.73 AUC)., Conclusions: These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.

Objective: Electroconvulsive therapy (ECT) is effective for major depressive episodes. Understanding of underlying mechanisms has been increased by examining changes of brain connectivity but studies often do not correct for test-retest variability in healthy controls (HC). In this study, we investigated changes in resting-state networks after ECT in a multicenter study., Methods: Functional resting-state magnetic resonance imaging data, acquired before start and within one week after ECT, from 90 depressed patients were analyzed, as well as longitudinal data of 24 HC. Group-information guided independent component analysis (GIG-ICA) was used to spatially restrict decomposition to twelve canonical resting-state networks. Selected networks of interest were the default mode network (DMN), salience network (SN), and left and right frontoparietal network (LFPN, and RFPN). Whole-brain voxel-wise analyses were used to assess group differences at baseline, group by time interactions, and correlations with treatment effectiveness. In addition, between-network connectivity and within-network strengths were computed., Results: Within-network strength of the DMN was lower at baseline in ECT patients which increased after ECT compared to HC, after which no differences were detected. At baseline, ECT patients showed lower whole-brain voxel-wise DMN connectivity in the precuneus. Increase of within-network strength of the LFPN was correlated with treatment effectiveness. We did not find whole-brain voxel-wise or between-network changes., Conclusion: DMN within-network connectivity normalized after ECT. Within-network increase of the LFPN in ECT patients was correlated with higher treatment effectiveness. In contrast to earlier studies, we found no whole-brain voxel-wise changes, which highlights the necessity to account for test-retest effects., Competing Interests: Declaration of competing interest O.O. and L.O. receive grant support from Western Norway Health Authorities. C.A. receives grant support from National Institutes of Health., (Copyright © 2024. Published by Elsevier Inc.)

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohen's d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohen's d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level., (© 2023. The Author(s).)

Background: Electroconvulsive therapy (ECT) is an effective treatment for severe depression and induces gray matter (GM) increases in the brain. Small-scale studies suggest that ECT also leads to changes in brain functioning, but findings are inconsistent. In this study, we investigated the influence of ECT on changes in both brain structure and function and their relation to clinical improvement using multicenter neuroimaging data from the Global ECT-MRI Research Collaboration (GEMRIC)., Methods: We analyzed T1-weighted structural magnetic resonance imaging (MRI) and functional resting-state MRI data of 88 individuals (49 male) with depressive episodes before and within one week after ECT. We performed voxel-based morphometry on the structural data and calculated fractional amplitudes of low-frequency fluctuations, regional homogeneity, degree centrality, functional connectomics, and hippocampus connectivity for the functional data in both unimodal and multimodal analyses. Longitudinal effects in the ECT group were compared to repeated measures of healthy controls (n = 27)., Results: Wide-spread increases in GM volume were found in patients following ECT. In contrast, no changes in any of the functional measures were observed, and there were no significant differences in structural or functional changes between ECT responders and non-responders. Multimodal analysis revealed that volume increases in the striatum, supplementary motor area and fusiform gyrus were associated with local changes in brain function., Conclusion: These results confirm wide-spread increases in GM volume, but suggest that this is not accompanied by functional changes or associated with clinical response. Instead, focal changes in brain function appear related to individual differences in brain volume increases., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Currently, one of the most pressing public health challenges is encouraging people to get vaccinated against COVID-19. Due to limited supplies, some people have had to wait for the COVID-19 vaccine. Consumer research has suggested that people who are overlooked in initial distribution of desired goods may no longer be interested. Here, we therefore examined people's preferences for proposed vaccine allocation strategies, as well as their anticipated responses to being overlooked. After health-care workers, most participants preferred prioritizing vaccines for high-risk individuals living in group-settings (49%) or with families (29%). We also found evidence of reluctance if passed over. After random assignment to vaccine allocation strategies that would initially overlook them, 37% of participants indicated that they would refuse the vaccine. The refusal rate rose to 42% when the vaccine allocation strategy prioritized people in areas with more COVID-19 - policies that were implemented in many areas. Even among participants who did not self-identify as vaccine hesitant, 22% said they would not want to vaccine in that case. Logistic regressions confirmed that vaccine refusal would be largest if vaccine allocation strategies targeted people who live in areas with more COVID-19 infections. In sum, once people are overlooked by vaccine allocation, they may no longer want to get vaccinated, even if they were not originally vaccine hesitant. Vaccine allocation strategies that prioritize high-infection areas and high-risk individuals in group-settings may enhance these concerns.

No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Background: Serotonin transporter blockers, like citalopram, dose-dependently bind to the serotonin transporter. Pharmacological magnetic resonance imaging (phMRI) can be used to non-invasively monitor effects of serotonergic medication. Although previous studies showed that phMRI can measure the effect of a single dose of serotoninergic medication, it is currently unclear whether it can also detect dose-dependent effects., Aims: To investigate the dose-dependent phMRI response to citalopram and compared this with serotonin transporter occupancy, measured with single photon emission computed tomography (SPECT)., Methods: Forty-five healthy females were randomized to pre-treatment with placebo, a low (4 mg) or clinically standard (16 mg) oral citalopram dose. Prior to citalopram, and 3 h after, subjects underwent SPECT scanning. Subsequently, a phMRI scan with a citalopram challenge (7.5 mg intravenously) was conducted. Change in cerebral blood flow in response to the citalopram challenge was assessed in the thalamus and occipital cortex (control region)., Results: Citalopram dose-dependently affected serotonin transporter occupancy, as measured with SPECT. In addition, citalopram dose-dependently affected the phMRI response to intravenous citalopram in the thalamus (but not occipital cortex), but phMRI was less sensitive in distinguishing between groups than SPECT. Serotonin transporter occupancy showed a trend-significant correlation to thalamic cerebral blood flow change., Conclusion: These results suggest that phMRI likely suffers from higher variation than SPECT, but that these techniques probably also assess different functional aspects of the serotonergic synapse; therefore phMRI could complement positron emission tomography/SPECT for measuring effects of serotonergic medication.

Background: Patients with behavioral variant of frontotemporal dementia (bvFTD) initially may only show behavioral and/or cognitive symptoms that overlap with other neurological and psychiatric disorders. The diagnostic accuracy is dependent on progressive symptoms worsening and frontotemporal abnormalities on neuroimaging findings. Predictive biomarkers could facilitate the early detection of bvFTD., Objective: To determine the prognostic accuracy of clinical and structural MRI data using a support vector machine (SVM) classification to predict the 2-year clinical follow-up diagnosis in a group of patients presenting late-onset behavioral changes., Methods: Data from 73 patients were included and divided into probable/definite bvFTD (n = 18), neurological (n = 28), and psychiatric (n = 27) groups based on 2-year follow-up diagnosis. Grey-matter volumes were extracted from baseline structural MRI scans. SVM classifiers were used to perform three binary classifications: bvFTD versus neurological and psychiatric, bvFTD versus neurological, and bvFTD versus psychiatric group(s), and one multi-class classification. Classification performance was determined for clinical and neuroimaging data separately and their combination using 5-fold cross-validation., Results: Accuracy of the binary classification tasks ranged from 72-82% (p < 0.001) with adequate sensitivity (67-79%), specificity (77-88%), and area-under-the-receiver-operator-curve (0.80-0.9). Multi-class accuracy ranged between 55-59% (p < 0.001). The combination of clinical and voxel-wise whole brain data showed the best performance overall., Conclusion: These results show the potential for automated early confirmation of diagnosis for bvFTD using machine learning analysis of clinical and neuroimaging data in a diverse and clinically relevant sample of patients.

Decision-making competence is the ability to follow normative principles when making decisions. In a longitudinal analysis, we examine the robustness of decision-making competence over time, as measured by two batteries of paper-and-pencil tasks. Participants completed the youth version (Y-DMC) at age 19 and/or the adult version (A-DMC) eleven years later at age 30, as part of a larger longitudinal study. Both measures are comprised of tasks adapted from ones used in experimental studies of decision-making skills. Results supported the robustness of these measures and the usefulness of the construct. Response patterns for Y-DMC were similar to those observed with a smaller initial sample drawn from the same population. Response patterns for A-DMC were similar to those observed with an earlier community sample. Y-DMC and A-DMC were significantly correlated, for participants who completed both measures, 11 years apart, even after controlling for measures of cognitive ability. Nomological validity was observed in correlations of scores on both tests with measures of cognitive ability, cognitive style, and environmental factors with predicted relationships to decision-making competence, including household SES, neighborhood disadvantage, and paternal substance abuse. Higher Y-DMC and A-DMC scores were also associated with lower rates of potentially risky and antisocial behaviors, including adolescent delinquency, cannabis use, and early sexual behavior. Thus, the Y-DMC and A-DMC measures appear to capture a relatively stable, measurable construct that increases with supportive environmental factors and is associated with constructive behaviors.

Background: Policy makers and program managers need to better understand consumers' perceptions of their energy use and savings to design effective strategies for promoting energy savings., Methods: We reviewed 14 studies from the emerging interdisciplinary literature examining consumers' perceptions electricity use by specific appliances, and potential savings., Results: We find that: (1) electricity use is often overestimated for low-energy consuming appliances, and underestimated for high-energy consuming appliances; (2) curtailment strategies are typically preferred over energy efficiency strategies; (3) consumers lack information about how much electricity can be saved through specific strategies; (4) consumers use heuristics for assessing the electricity use of specific appliances, with some indication that more accurate judgments are made among consumers with higher numeracy and stronger pro-environmental attitudes. However, design differences between studies, such as variations in reference points, reporting units and assessed time periods, may affect consumers' reported perceptions. Moreover, studies differ with regard to whether accuracy of perceptions was evaluated through comparisons with general estimates of actual use, self-reported use, household-level meter readings, or real-time smart meter readings., Conclusion: Although emerging findings are promising, systematic variations in the measurement of perceived and actual electricity use are potential cause for concern. We propose avenues for future research, so as to better understand, and possibly inform, consumers' perceptions of their electricity use. Ultimately, this literature will have implications for the design of effective electricity feedback for consumers, and related policies.

Suicide rates are highest in adults of middle and older age. Research with psychiatric patients has shown that proneness to feel regret about past decisions can grow so intense that suicide becomes a tempting escape. Here, we examine the additional role of individual differences in maximizing, or the tendency to strive for the best decision, rather than one that is good enough. We provided individual-differences measures of maximizing, regret proneness, and negative life decision outcomes (as reported on the Decision Outcome Inventory or DOI) to a non-psychiatric control group, as well as three groups of psychiatric patients in treatment for suicide attempts, suicidal ideation, or non-suicidal depression. We found that scores on the three individual-differences measures were worse for psychiatric patients than for non-psychiatric controls, and were correlated to clinical assessments of depression, hopelessness, and suicidal ideation. More importantly, maximizing was associated with these clinical assessments, even after taking into account maximizers' worse life decision outcomes. Regret proneness significantly mediated those relationships, suggesting that maximizers could be at risk for clinical depression because of their proneness to regret. We discuss the theoretical relevance of our findings and their promise for clinical practice. Ultimately, late-life depression and suicidal ideation may be treated with interventions that promote better decision making and regret regulation.

Across Europe, organizations in different sectors are sensitive to climate variability and change, at a range of temporal scales from the seasonal to the interannual to the multi-decadal. Climate forecast providers face the challenge of communicating the uncertainty inherent in these forecasts to these decision-makers in a way that is transparent, understandable and does not lead to a false sense of certainty. This article reports the findings of a user-needs survey, conducted with 50 representatives of organizations in Europe from a variety of sectors (e.g. water management, forestry, energy, tourism, health) interested in seasonal and interannual climate forecasts. We find that while many participating organizations perform their own 'in house' risk analysis most require some form of processing and interpretation by forecast providers. However, we also find that while users tend to perceive seasonal and interannual forecasts to be useful, they often find them difficult to understand, highlighting the need for communication formats suitable for both expert and non-expert users. In addition, our results show that people tend to prefer familiar formats for receiving information about uncertainty. The implications of these findings for both the providers and users of climate information are discussed., (© 2015 The Authors.)

Using cluster-analysis, we investigated whether rational, intuitive, spontaneous, dependent, and avoidant styles of decision making (Scott & Bruce, 1995) combined to form distinct decision-making profiles that differed by age and gender. Self-report survey data were collected from 1,075 members of RAND's American Life Panel (56.2% female, 18-93 years, M age = 53.49). Three decision-making profiles were identified: affective/experiential, independent/self-controlled, and an interpersonally-oriented dependent profile. Older people were less likely to be in the affective/experiential profile and more likely to be in the independent/self-controlled profile. Women were less likely to be in the affective/experiential profile and more likely to be in the interpersonally-oriented dependent profile. Interpersonally-oriented profiles are discussed as an overlooked but important dimension of how people make important decisions.

Background: The Heatwave Plan for England provides guidance for personal and home protection measures during heatwaves. Although studies in the USA, Australia and Europe have surveyed heat-related behaviours during heatwaves, few have been conducted in the UK. This study assesses personal and housing (at-home) behaviour and housing characteristics of the UK population during the 2013 heatwave., Methods: This paper analyses data from 1497 respondents of an online survey on heat protection measures and behaviour. Participants were asked questions about their behaviour during the 2013 heatwave, the characteristics of their current housing as well as about any negative health outcomes experienced due to the hot weather. We used multinomial logit regression to analyse personal and home heat protection behaviour and logistic regression to analyse characteristics of participants' current home (installed air conditioner, curtains etc.). We stratified the outcomes by age, sex, ethnicity, income, education and regional location., Results: In 2013, for all heat-related illness (except tiredness), a higher proportion of those in the younger age groups reported symptoms compared with those in the older age groups. Women, higher income groups and those with higher education levels were found to be more likely to report always/often taking personal heat protective measures. The elderly were less likely to take some personal and home protective measures but were more likely to live in insulated homes and open windows at night to keep their home cool., Conclusion: Our study has found a high level of awareness of the actions to take during heatwaves in the UK, and has identified important demographic indicators of sections of the UK population that might benefit from additional or more targeted information. The health agencies should attempt to provide better information about heatwaves to those vulnerable (elderly, those at risk living in London, low income earners) or identify any barriers that might be preventing them from undertaking protective behaviour.

Decision-making competence in later adulthood is affected by declines in cognitive skills, and age-related changes in affect and experience can sometimes compensate. However, recent findings suggest that age-related changes in motivation also affect the extent to which adults draw from experience, affect, and deliberative skills when making decisions. To date, relatively little attention has been given to strategies for addressing age-related changes in motivation to promote better decisions in older adults. To address this limitation, we draw from diverse literatures to suggest promising intervention strategies for motivating older recipients' motivation to make better decisions. We start by reviewing the life-span developmental literature, which suggests that older adults' motivation to put effort into decisions depends on the perceived personal relevance of decisions as well as their self-efficacy (i.e., confidence in applying their ability and knowledge). Next, we discuss two approaches from the health intervention design literature, the mental models approach and the patient activation approach, which aim to improve motivation for decision making by improving personal relevance or by building self-efficacy or confidence to use new information and skills. Using examples from these literatures, we discuss how to construct interventions to motivate good decisions in later adulthood.

Financial decisions about investing and saving for retirement are increasingly complex, requiring financial knowledge and confidence in that knowledge. Few studies have examined whether direct assessments of individuals' confidence are related to the outcomes of their financial decisions. Here, we analyzed data from a national sample recruited through RAND's American Life Panel (ALP), an internet panel of U.S. adults aged 18 to 88. We examined the relationship of confidence with self-reported and actual financial decisions, using four different tasks, each performed by overlapping samples of ALP participants. The four tasks were designed by different researchers for different purposes, using different methods to assess confidence. Yet, measures of confidence were correlated across tasks, and results were consistent across methodologies. Confidence and knowledge showed only modest positive correlations. However, even after controlling for actual knowledge, individuals with greater confidence were more likely to report financial planning for retirement and to successfully minimize fees on a hypothetical investment task. Implications for the role of confidence (even if it is unjustified) in investment behavior is discussed.

Feelings of unwarranted invulnerability, seen in judgments of 0% risk, can reflect misunderstandings of risk and risk behaviors, suggesting increased need for risk communication. However, judgments of 0% risk may be given by individuals who feel invulnerable, and by individuals who are rounding from small non-zero probabilities. We examined the effect of allowing participants to give more precise responses in the 0-1% range on the validity of reported probability judgments. Participants assessed probabilities for getting H1N1 influenza and dying from it conditional on infection, using a 0-100% visual linear scale. Those responding in the 0-1% range received a follow-up question with more options in that range. This two-step procedure reduced the use of 0% and increased the resolution of responses in the 0-1% range. Moreover, revised probability responses improved predictions of attitudes and self-reported behaviors. Hence, our two-step procedure allows for more precise and more valid measurement of perceived invulnerability.

Purpose: The purpose of this article was to summarize scientific knowledge from an expert panel on reproductive health among adolescents with type 2 diabetes (T2D)., Methods: Using a mental model approach, a panel of experts--representing perspectives on diabetes, adolescents, preconception counseling, and reproductive health--was convened to discuss reproductive health issues for female adolescents with T2D., Results: Several critical issues emerged. Compared with adolescents with type 1 diabetes, (1) adolescents with T2D may perceive their disease as less severe and have less experience managing it, putting them at risk for complications; (2) T2D is more prevalent among African Americans, who may be less trusting of the medical establishment; (3) T2D is associated with obesity, and it is often difficult to change one's lifestyle within family environments practicing sedentary and dietary behaviors leading to obesity; (4) teens with T2D could be more fertile, because obesity is related to earlier puberty; (5) although obese teens with T2D have a higher risk of polycystic ovary syndrome, which is associated with infertility, treatment with metformin can increase fertility; and (6) women with type 2 diabetes are routinely transferred to insulin before or during pregnancy to allow more intensive management., Conclusions: Findings from the expert panel provide compelling reasons to provide early, developmentally appropriate, culturally sensitive preconception counseling for teens with T2D.

Public perceptions of carbon capture and sequestration (CCS) and other low-carbon electricity-generating technologies may affect the feasibility of their widespread deployment. We asked a diverse sample of 60 participants recruited from community groups in Pittsburgh, Pennsylvania to rank 10 technologies (e.g., coal with CCS, natural gas, nuclear, various renewables, and energy efficiency), and seven realistic low-carbon portfolios composed of these technologies, after receiving comprehensive and carefully balanced materials that explained the costs and benefits of each technology. Rankings were obtained in small group settings as well as individually before and after the group discussions. The ranking exercise asked participants to assume that the U.S. Congress had mandated a reduction in carbon dioxide emissions from power plants to be built in the future. Overall, rankings suggest that participants favored energy efficiency, followed by nuclear power, integrated gasification combined-cycle coal with CCS and wind. The most preferred portfolio also included these technologies. We find that these informed members of the general public preferred diverse portfolios that contained CCS and nuclear over alternatives once they fully understood the benefits, cost, and limitations of each. The materials and approach developed for this study may also have value in educating members of the general public about the challenges of achieving a low-carbon energy future., (© 2010 Society for Risk Analysis.)

Xenotransplantation entails using organs from genetically modified animals as a way to solve the shortage of human organs for transplantation. As with other novel technologies, if xenotransplantation is to be judged fairly, proponents must explain its complex, uncertain, and unfamiliar risks and benefits. Xenotransplantation's risks include the possibility of a recombinant virus infecting human transplant recipients, potentially causing an epidemic of an unfamiliar disease. Using materials vetted by scientific experts, we communicated the variables and relationships determining this risk in three formally equivalent formats: (a) a graphic model, (b) scenarios structured by the graphic model, and (c) both the model and the scenarios. Participants were randomly assigned to receiving one set of materials. They rated them as equally clear and studied them equally long, suggesting similar ease of cognitive processing. Compared to participants receiving the scenarios, those who received the graphic model better identified causes and effects of the risk, and saw less risk of xenotransplantation. Participants who received both the model and the scenarios generally showed intermediate responses. The study demonstrates a general procedure for developing and evaluating formally equivalent graphic and scenario communications regarding highly uncertain risks. In this application to xenotransplantation, presenting a graphic representation improved people's understanding of the risk.

We report on 30 in-depth mental models interviews with parents discussing vaccination for their children, both in general terms and in response to communications drawn from sources supporting and opposing vaccines. We found that even parents favourable to vaccination can be confused by the ongoing debate, leading them to question their choices. Many parents lack basic knowledge of how vaccines work, and do not find the standard information provided to them to be particularly helpful in explaining it. Those with the greatest need to know about vaccination seem most vulnerable to confusing information. Opportunities for education may be missed if paediatricians do not appreciate parents' specific information needs.

Shortly after the 2002 terrorist attacks in Bali, readers of Conde Nast Traveler magazine were surveyed regarding their views on the risks of travel to various destinations. Their risk estimates were highest for Israel, and lowest for Canada. Estimates for the different destinations correlated positively with (1) one another, (2) concern over aspects of travel that can make one feel at risk (e.g., sticking out as an American), (3) worries about other travel problems (e.g., contracting an infectious disease), and (4) attitudes toward risk. Respondents' willingness to travel to a destination was predicted well by whether their estimate of its risk was above or below their general threshold for the acceptability of travel risks. Overall, the responses suggest orderly choices, based on highly uncertain judgments of risks. Worry played a significant role in these choices, even after controlling for cognitive considerations, thereby supporting the recently proposed "risk as feelings" hypothesis. Thus, even among people who have generally consistent and defensible beliefs, emotions may affect choices. These results emerged with people selected for their interest in and experience with the decision domain (travel), but challenged to incorporate a new concern (terror).

Twenty-five women with breast implants participated in semistructured interviews designed to reveal their "mental models" of the processes potentially causing local (i.e., nonsystemic) problems. The authors analyzed their responses in terms of an "expert model," circumscribing scientifically relevant information. Most of the women interviewed had something to say about most elements in the expert model. Nonetheless, gaps in their mental models undermined decision making about their implants. One woman misunderstood the terms used by the medical community to describe implant failure (e.g., rupture, leak, and bleed). Another exaggerated the implants' vulnerability to direct impacts, such as car accidents. Participants also overestimated their ability to detect localized problems and to select medical remedies. Although they were generally satisfied with their own implants, many participants were dissatisfied with the decision-making processes that lead to their choice. Their interviews are interpreted by the form and content of communications that women with implants need to help them manage their health decisions better.

This study examines the effect of question format on HIV/AIDS knowledge assessed in teens in a detention center, public high school students, and adults. Multiple-choice items were taken from a Red Cross questionnaire and were transformed into open-ended and true/false/don't know formats. Each respondent received an open-ended and a structured version of the test (consisting of multiple-choice and true/false/don't know items). Format effects varied by group and order of presentation: High school students and adults performed better on the open-ended questions if they had answered the structured versions first-suggesting that the structured questions provided these respondents with unintended cues. Detention center youths did not benefit from having answered the structured items, and scored especially low on the open-ended questions. However, they did almost as well as the other groups with the true/false/don't know format. Implications are discussed for measuring HIV/AIDS knowledge and evaluating educational programs for different target audiences.

When estimating risks, people may use "50" as an expression of the verbal phrase "fifty-fifty chance," without intending the associated number of 50%. The result is an excess of 50s in the response distribution. The present study examined factors determining the magnitude of such a "50 blip," using a large sample of adolescents and adults. We found that phrasing probability questions in a distributional format (asking about risks as a percentage in a population) rather than in a singular format (asking about risks to an individual) reduced the use of "50." Less numerate respondents, children, and less educated adults were more likely to say "50." Finally, events that evoked feelings of less perceived control led to more 50s. The results are discussed in terms of what they reveal about how people express epistemic uncertainty. Copyright 2000 Academic Press.