Evaluation of suicide risk among youths in community settings

Identifying youths in imminent danger of suicide and in need of emergency psychiatric services is a difficult task. Although clinicians have often described the psychiatric profile of youths at risk for suicide, there is little empirical evidence of successful strategies for identifying suicidal risk. Researchers are faced with a number of problems when attempting to validate risk evaluation procedures: Suicide risk profiles vary with age and developmental stage; there appear to be several patterns or subtypes of suicidal patterns; suicidality depends on one's current emotional state; evaluators are likely to be biased in the direction of over-estimating risk and are not likely to have extensive clinical training; imminent danger for suicide is time-limited; and a youth's risk will depend on surrounding environmental stressors and supports. These considerations force researchers to assume a strategic approach in defining levels of suicide risk and imminent danger of suicide. An example of a potential strategy for identifying risk among youths is outlined in this chapter. Although this strategic approach appears useful, researchers continue to be faced with major problems in validating such procedures. Determining the predictive validity of potential suicide screening procedures requires researchers to evaluate and to follow longitudinally a large sample of youths, while deliberately refraining from intervening to help those youths who appear to be in crisis.     

Heterosexual risk behaviors in at-risk young men from early adolescence to young adulthood: prevalence,prediction, and association with STD contraction

Health-compromising lifestyles involve stable patterns of behavior and are associated with high-risk social environments and accelerated developmental trajectories. Developmentally, antisocial behavior is associated with such lifestyles. Mediational models predicting a measure of lifetime average sexual risk behavior assessed over a 10-year period (from ages 13-14 to 22-23 years) were examined for a sample of at-risk young men. The measure included years of abstinence from intercourse as well as levels of 3 key heterosexual indicators of risk: frequency of intercourse, number of intercourse partners, and condom use. Predictors included lifetime average measures of contextual, family, and peer process variables and individual behaviors. In addition, similar models for prediction of STD contraction were assessed. A younger age of onset of intercourse was associated with higher numbers of intercourse partners after onset. As hypothesized, findings indicated mediational associations of socioeconomic status, parental monitoring, deviant-peer association, antisocial behavior, and substance use in the prediction of sexual risk behavior. Lower condom use also predicted STD contraction.     

Developmental changes in effects of risk and valence on adolescent decision-making

Recent research on risky decision-making in adults has shown that both the risk in potential outcomes and their valence (i.e., whether those outcomes involve gains or losses) exert dissociable influences on decisions. We hypothesised that the influences of these two crucial decision variables (risk and valence) on decision-making would vary developmentally during adolescence. We adapted a risk-taking paradigm that provides precise metrics for the impacts of risk and valence. Decision-making in 11–16 year old female adolescents was influenced by both risk and valence. However, their influences assumed different developmental patterns: the impact of valence diminished with age, while there was no developmental change in the impact of risk. These different developmental patterns provide further evidence that risk and valence are fundamentally dissociable constructs and have different influences on decisions across adolescence.     

Illness perceptions and distress in women at increased risk of breast cancer

Variation in the levels of distress in women at increased risk of breast cancer has been reported, yet there is limited understanding of the factors that are associated with heightened distress in this population. This study took a theoretical approach using Leventhal's Self Regulatory Model (SRM) to understand variation in distress levels. The study examined the associations between perceptions of breast cancer and distress in women at increased risk of breast cancer, and a comparison sample with no experience of the disease in their social environment. Questionnaire data from 117 women at increased risk of breast cancer and 100 comparison women were analysed. Women at increased risk of breast cancer showed comparable levels of general distress but significantly higher levels of cancer specific distress than the comparison group. There were few differences in illness perceptions between the samples, although a number of cognitive perceptions of breast cancer were related to both general and cancer specific distress in the increased risk sample, but not in the comparison sample. The results suggest that the SRM provides a useful framework to explore the psychological response to genetic risk. Further research is required in this population to examine illness perceptions in more detail, validate quantitative measures of illness perceptions, and examine interactions between risk perception and the SRM constructs.     

The implications of age of onset for delinquency risk II: Longitudinal data

The role of age of onset in the level of involvement in delinquent behavior as marked by seriousness and chronicity of involvement continues to draw extensive attention from researchers. This issue bears on some of the key causal contentions about the dynamism of involvement and the validity of a developmental model of antisocial behavior risk. Five waves of the National Youth Survey were utilized here to determine if, among a nationally representative sample, there was evidence of onset age influence on later involvement. Results suggest that early onset (before age 12) relates to higher rates of more serious acts over a longer period of time for boys and girls. Overall, the results suggest support for early onset spurring on later involvement, but the contribution is small once psychosocial predictors are considered. Onset age seems most important in understanding involvement in serious crime over several years. Involvement is explained best by peer variables for males and school and family variables for females. Onset age is explained by a wider range of variables than involvement and there is greater similarity of the psychosocial variables that explain onset for both genders. The interaction of involvement and predictors was noted, suggesting a dynamic model of risk. Implications for prediction and prevention are discussed.This work was conducted with support of an NIJ summer fellowship to the first author and NIMH grants MH48248 and MH48034 awarded the first author.     

Salience network response to changes in emotional expressions of others is heightened during early adolescence: relevance for social functioning

Adolescence is a unique developmental period when the salience of social and emotional information becomes particularly pronounced. Although this increased sensitivity to social and emotional information has frequently been considered with respect to risk behaviors and psychopathology, evidence suggests that increased adolescent sensitivity to social and emotional cues may confer advantages. For example, greater sensitivity to shifts in the emotions of others is likely to promote flexible and adaptive social behavior. In this study, a sample of 54 children and adolescents (age 8–19 years) performed a delayed match‐to‐sample task for emotional faces while undergoing fMRI scanning. Recruitment of the anterior cingulate and anterior insula when the emotion of the probe face did not match the emotion held in memory followed a quadratic developmental pattern that peaked during early adolescence. These findings indicate meaningful developmental variation in the neural mechanisms underlying sensitivity to changes in the emotional expressions. Across all participants, greater activation of this network for changes in emotional expression was associated with less social anxiety and fewer social problems. These results suggest that the heightened salience of social and emotional information during adolescence may confer important advantages for social behavior, providing sensitivity to others’ emotions that facilitates flexible social responding.     

Temporal patterns of variable relationships in person-oriented research: longitudinal models of configural frequency analysis

This article reviews the premises of configural frequency analysis (CFA), including methods of choosing significance tests and base models, as well as protecting alpha, and discusses why CFA is a useful approach when conducting longitudinal person-oriented research. CFA operates at the manifest variable level. Longitudinal CFA seeks to identify those temporal patterns that stand out as more frequent (CFA types) or less frequent (CFA antitypes) than expected with reference to a base model. A base model that has been used frequently in CFA applications, prediction CFA, and a new base model, auto-association CFA, are discussed for analysis of cross-classifications of longitudinal data. The former base model takes the associations among predictors and among criteria into account. The latter takes the auto-associations among repeatedly observed variables into account. Application examples of each are given using data from a longitudinal study of domestic violence. It is demonstrated that CFA results are not redundant with results from log-linear modeling or multinomial regression and that, of these approaches, CFA shows particular utility when conducting person-oriented research.     

Implications of age of onset for delinquency risk

A substantial body of research suggests that age of onset is a viable discriminator of risk for chronic versus transient delinquency. Also, a mullivariate model of psychosocial variables (demographics, individual, school, and family functioning) appears likely to provide a comparatively accurate and useful discriminatory model for prediction. These two findings were applied to a normal sample of male adolescents (N=199, ages 15–18) to study the relationship of age of onset to delinquent behavior (as opposed to use of legal status to denote delinquency) and legal status. Additionally, the efficiency and improvement over chance accuracy of a multivariate model developed as part of a larger research project was tested. Results indicated that age of onset is an important and accurate discriminator of extent of subsequent delinquency. Subjects with an early age of onset reported more delinquent behavior, were more likely to be adjudicated, and showed different patterns of delinquency. A combination of demographic, individual, school, and family variables predicted age of onset.This work was conducted while the author was a Clinical Research Training Fellow in Adolescence (funded by T32 MH 14668) at the Institute for Psychosomatic and Psychiatric Research and Training, Michael Reese Hospital and Medical Center, in a program also sponsored by the Departments of Behavioral Science and Psychiatry, University of Chicago, and the Adolescent Program of the Illinois State Psychiatric Institute. The author is indebted to Ronald Rosenthal, Daniel Offer, and two anonymous reviewers for their advice and comments on an earlier draft of this article.     

Brain activity patterns of phonemic representations are atypical in beginning readers with family risk for dyslexia

There is an ongoing debate whether phonological deficits in dyslexics should be attributed to (a) less specified representations of speech sounds, like suggested by studies in young children with a familial risk for dyslexia, or (b) to an impaired access to these phonemic representations, as suggested by studies in adults with dyslexia. These conflicting findings are rooted in between study differences in sample characteristics and/or testing techniques. The current study uses the same multivariate functional MRI (fMRI) approach as previously used in adults with dyslexia to investigate phonemic representations in 30 beginning readers with a familial risk and 24 beginning readers without a familial risk of dyslexia, of whom 20 were later retrospectively classified as dyslexic. Based on fMRI response patterns evoked by listening to different utterances of /bA/ and /dA/ sounds, multivoxel analyses indicate that the underlying activation patterns of the two phonemes were distinct in children with a low family risk but not in children with high family risk. However, no group differences were observed between children that were later classified as typical versus dyslexic readers, regardless of their family risk status, indicating that poor phonemic representations constitute a risk for dyslexia but are not sufficient to result in reading problems. We hypothesize that poor phonemic representations are trait (family risk) and not state (dyslexia) dependent, and that representational deficits only lead to reading difficulties when they are present in conjunction with other neuroanatomical or—functional deficits.     

Person‐specific versus multilevel autoregressive models: Accuracy in parameter estimates at the population and individual levels

This paper compares the multilevel modelling (MLM) approach and the person‐specific (PS) modelling approach in examining autoregressive (AR) relations with intensive longitudinal data. Two simulation studies are conducted to examine the influences of sample heterogeneity, time series length, sample size, and distribution of individual level AR coefficients on the accuracy of AR estimates, both at the population level and at the individual level. It is found that MLM generally outperforms the PS approach under two conditions: when the sample has a homogeneous AR pattern, namely, when all individuals in the sample are characterized by AR processes with the same order; and when the sample has heterogeneous AR patterns, but a multilevel model with a sufficiently high order (i.e., an order equal to or higher than the maximum order of individual AR patterns in the sample) is fitted and successfully converges. If a lower‐order multilevel model is chosen for heterogeneous samples, the higher‐order lagged effects are misrepresented, resulting in bias at the population level and larger prediction errors at the individual level. In these cases, the PS approach is preferable, given sufficient measurement occasions (T ≥ 50). In addition, sample size and distribution of individual level AR coefficients do not have a large impact on the results. Implications of these findings on model selection and research design are discussed.     

Trajectories of Social Anxiety during Adolescence and Relations with Cognition, Social Competence, and Temperament

This cohort-sequential study examined developmental trajectories of social anxiety in a nonclinical sample (N?=?331, 161 girls) aged 9 to 17 years at initial and 12 to 21 years at final assessment. We tested whether variables assessing cognition, social competence, and temperament discriminated between the trajectories. Variables were collected from different sources: participants, independent observers, parents, and teachers. Using Latent Class Growth Modeling (LCGM) we identified three distinct social anxiety trajectory groups: i) high and changing; ii) moderate and decreasing; and iii) low and decreasing. Multinomial regression analyses showed that the cognition variables, negative interpretations of ambiguous social situations and self-focused attention, differentiated between all three trajectories. A lack of social skills and having social problems at school were specifically related to the chance of following the high trajectory versus the moderate trajectory. Neuroticism differentiated between the low and moderate trajectories. Findings indicate that adolescents at risk of belonging to a high social anxiety trajectory can be discriminated from peers belonging to a less anxious trajectory using both cognition and social competence variables.     

PERSONALITY, INTEGRITY, AND WHITE COLLAR CRIME: A CONSTRUCT VALIDITY STUDY

This study examined the construct validity of personality scales, a personality-based integrity test, and homogenous biodata scales as reflected in their ability to discriminate white collar criminals from other white collar employees. The sample included 365 prison inmates incarcerated in 23 federal correctional institutions for white collar offenses, and 344 individuals employed in upper-level positions of authority. A cross-validated linear discriminant function ( DF ) based on 16 variables selected in the developmental sample produced a large difference (1.83 standard deviation units) between the two sample groups. The pattern of score differences revealed the offenders as having greater tendencies toward irresponsibility, lack of dependability, and disregard of rules and social norms. This study indicates that there are large and measurable psychological differences between white collar offenders and nonoffenders, and that the major construct underlying these differences is "social conscientiousness." The best measure of this difference was a personality-based integrity test.     

Prediction and Intervention in Health-Related Behavior: A Meta-Analytic Review of Protection Motivation Theory

Protection motivation theory (PMT) was introduced by Rogers in 1975 and has since been widely adopted as a framework for the prediction of and intervention in health-related behavior. However. PMT remains the only major cognitive model of behavior not to have been the subject of a meta-analytic review. A quantitative review of PMT is important to assess its overall utility as a predictive model and to establish which of its variables would be most useful to address health-education interventions. The present paper provides a comprehensive introduction to PMT and its application to health-related behavior, together with a quantitative review of the applications of PMT to health-related intentions and behavior. The associations between threat- and coping-appraisal variables and intentions, and all components of the model and behavior were assessed both by meta-analysis and by vote-count procedures. Threat- and coping-appraisal components of PMT were found to be useful in the prediction of health-related intentions. The model was found to be useful in predicting concurrent behavior, but of less utility in predicting future behavior. The coping-appraisal component of the model was found to have greater predictive validity than was the threat-appraisal component. The main findings are discussed in relation to theory and research on social cognition models. The importance of the main findings to health education is also discussed, and future research directions are suggested.     

Order of question presentation and correlation between judgments of comparative and own risk

Unrealistic optimism is often assessed using a single question asking for an estimate of comparative risk. However, it has been proposed that individuals treat such a question essentially as though it were only about their own risk. This proposal leads to the prediction that, when the questions about own risk and comparative risk are asked in sequence, the correlation between the resulting estimates should be lower if the question about own risk comes first than if the question about comparative risk comes first. This prediction was tested using a student sample (N=68). Participants answered the two types of question in sequence, with order of presentation being counterbalanced. Results were in accord with the prediction. Possible reasons are advanced for individuals' answering questions about comparative risk as if the questions concerned their own risk.     

Exposure to Violence,Social Information Processing,and Problem Behavior in Preschool Children

Understanding the mechanisms by which early risk factors for social maladjustment contribute to disruptive behaviors in social settings is vital to developmental research and practice. A major risk factor for social maladjustment is early exposure to violence, which was examined in this short‐term longitudinal study in relation to social information processing (SIP) patterns and externalizing and internalizing behaviors in a sample of 256 preschool children. Data on exposure to violence were obtained via parent report, data on SIP were obtained via child interview, and data on child problem behavior were obtained via teacher report. Findings supported the hypothesis that, compared to children not exposed to violence, children reported to witness and/or experience violence are more likely to attribute hostile intent to peers, generate aggressive responses, and evaluate socially unaccepted responses (aggressive and inept) as socially suitable. The former were also found to exhibit higher levels of externalizing and internalizing behaviors. Finally, SIP mediated the link between exposure to violence and problem behavior thus supporting this study's general approach, which argues that the link between exposure to violence and children's problem behaviors are better understood within the context of their perceptions about social relationships. Aggr. Behav. 38:429‐441, 2012. © 2012 Wiley Periodicals, Inc.     

Neural network modeling of risk assessment in child protective services

The advantages of using neural network methodology for the modeling of complex social science data are demonstrated, and neural network analysis is applied to Washington State Child Protective Services risk assessment data. Neural network modeling of the association between social worker overall assessment of risk and the 37 separate risk factors from the State of Washington Risk Assessment Matrix is shown to provide case classification results superior to linear or logistic multiple regression. The improvement in case prediction and classification accuracy is attributed to the superiority of neural networks for modeling nonlinear relationships between interacting variables; in this respect the mathematical framework of neural networks is a better approximation to the actual process of human decision making than linear, main effects regression. The implications of this modeling advantage for evaluating social science data within the framework of ecological theories are discussed.     

An assessment of community suicide risk

The contributions of several core variables to the white suicide rates in 24 Florida counties were examined, and a prediction equation, using multiple linear regression, was developed. Age was found to be about 50% more important than divorce. With both age and divorce controlled, loneliness and insanity were found to be significant core variables (p less than .05). A prediction equation including age, crime rate, insanity, and alcoholism was found that accounted for 79% of the variation in the suicide rates across counties. The observed rates were divided by predicted rates to yield standardized mortality ratios. It is proposed that these ratios may serve to assess both the need for and the impact of community suicide prevention services by placing suicide rates in the context of relevant social conditions.     

Social information processing in preschool children: Relations to sociodemographic risk and problem behavior

Using a multicomponent, process-oriented approach, the links between social information processing during the preschool years and (a) sociodemographic risk and (b) behavior problems in preschool were examined in a community sample of 196 children. Findings provided support for our initial hypotheses that aspects of social information processing in preschool are related to both sociodemographic risk and behavior problems in preschool. Response evaluation and in particular the positive evaluation of an aggressive response were related to both sociodemographic risk and children’s aggressive behavior and partially mediated the links between sociodemographic risk and aggressive behavior in preschool.     

Studying the Dynamics of Problem Behavior Across Multiple Time Scales: Prospects and Challenges

As a commentary on the Special Issue, this paper discusses recent advances in the study of change across several time scales. It points out the importance of specifying time scales and putative patterns of change when characterizing problem behavior over developmental time scales. Methods for studying risk and protective mechanisms through observation of social interaction are also discussed as a way to study influences that operate in real time. Methods for studying episode-level interaction patterns that result from such real-time influences are also discussed, along with ways to integrate these with longitudinal assessments to study the effects of social interaction on problem behavior across developmental time scales.     

Prediction of foot clearance parameters as a precursor to forecasting the risk of tripping and falling

Tripping and falling is a serious health problem for older citizens due to the high medical costs incurred and the high mortality rates precipitated mostly by hip fractures that do not heal well. Current falls prevention technology encompasses a broad range of interventions; both passive (e.g., safer environments, hip protectors) and active (e.g., sensor-based fall detectors) which attempt to reduce the effects of tripping and falling. However the majority of these interventions minimizes the impact of falls and do not directly reduce the risk of falling. This paper investigates the prediction of gait parameters related to foot-to-ground clearance height during the leg swing phase which have been physically associated with tripping and falling risk in the elderly. The objective is to predict parameters of foot trajectory several walking cycles in advance so that anticipated low foot clearance could be addressed early with more volitional countermeasures, e.g., slowing down or stopping. In this primer study, foot kinematics was recorded with a highly accurate motion capture system for 10 healthy adults (25-32 years) and 11 older adults (65-82 years) with a history of falls who each performed treadmill walking for at least 10 min. Vertical foot displacement during the swing phase has three characteristic inflection points and we used these peak values and their normalized time as the target prediction values. These target variables were paired with features extracted from the corresponding foot acceleration signal (obtained through double differentiation). A generalized regression neural network (GRNN) was used to independently predict the gait variables over a prediction horizon (number of gait cycles ahead) of 1-10 gait cycles. It was found that the GRNN attained 0.32-1.10 cm prediction errors in the peak variables and 2-8% errors in the prediction of normalized peak times, with slightly better accuracies in the healthy group compared to elderly fallers. Prediction accuracy decreased linearly (best fit) at a slow rate with increasing prediction horizon ranging from 0.03 to 0.11 cm per step for peak displacement variables and 0.34 × 10(-3) - 1.81 × 10(-3)% per step for normalized peak time variables. Further time series analysis of the target gait variable revealed high autocorrelations in the faller group indicating the presence of cyclic patterns in elderly walking strategies compared to almost random walking patterns in the healthy group. The results are promising because the technique can be extended to portable sensor-based devices which measure foot accelerations to predict the onset of risky foot clearance, thus leading to a more effective falls prevention technology.