Background: Many disorders in childhood and adolescence were already present in the preschool years. However, there is little empirical research on the prevalence of psychiatric disorders in young children. A true community study using structured diagnostic tools has yet to be published.

Methods:  All children born in 2003 or 2004 in the city of Trondheim, Norway, who attended the regular community health check-up for 4-year-olds (97.2% of eligible children) whose parents consented to take part in the study (N = 2,475, 82.0%) were screened for behavioral and emotional problems with the Strengths and Difficulties Questionnaire (SDQ). A screen-stratified subsample of 1,250 children took part in a furthermore comprehensive study including a structured diagnostic interview (the Preschool Age Psychiatric Assessment, PAPA), which 995 parents (79.6%) completed.

Results:  The estimated population rate for any psychiatric disorder (excluding encopresis – 6.4%) was 7.1%. The most common disorders were attention deficit hyperactivity disorder (1.9%), oppositional defiant disorder (1.8%), conduct disorder (0.7%), anxiety disorders (1.5%), and depressive disorders (2.0%). Comorbidity among disorders was common. More emotional and behavioral disorders were seen in children whose parents did not live together and in those of low socioeconomic status. Boys more often had attention-deficit/hyperactivity disorder (ADHD) and depressive disorders than girls.

Conclusions:  The prevalence of disorders among preschoolers was lower than in previous studies from the USA. Comorbidity was frequent and there was a male preponderance in ADHD and depression at this early age. These results underscore the fact that the most common disorders of childhood can already be diagnosed in preschoolers. However, rates of disorder in Norway may be lower than in the USA.

Prevalence of psychiatric disorders in preschoolers

OBJECTIVE: To develop a method enabling human-like, flexible supervisory control via delegation to automation. BACKGROUND: Real-time supervisory relationships with automation are rarely as flexible as human task delegation to other humans. Flexibility in human-adaptable automation can provide important benefits, including improved situation awareness, more accurate automation usage, more balanced mental workload, increased user acceptance, and improved overall performance. METHOD: We review problems with static and adaptive (as opposed to "adaptable") automation; contrast these approaches with human-human task delegation, which can mitigate many of the problems; and revise the concept of a "level of automation" as a pattern of task-based roles and authorizations. We argue that delegation requires a shared hierarchical task model between supervisor and subordinates, used to delegate tasks at various levels, and offer instruction on performing them. A prototype implementation called Playbook is described. RESULTS: On the basis of these analyses, we propose methods for supporting human-machine delegation interactions that parallel human-human delegation in important respects. We develop an architecture for machine-based delegation systems based on the metaphor of a sports team's "playbook." Finally, we describe a prototype implementation of this architecture, with an accompanying user interface and usage scenario, for mission planning for uninhabited air vehicles. CONCLUSION: Delegation offers a viable method for flexible, multilevel human-automation interaction to enhance system performance while maintaining user workload at a manageable level. APPLICATION: Most applications of adaptive automation (aviation, air traffic control, robotics, process control, etc.) are potential avenues for the adaptable, delegation approach we advocate. We present an extended example for uninhabited air vehicle mission planning. Language: en

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Designing for flexible interaction between humans and automation: delegation interfaces for supervisory control.

Public stigma is a pervasive barrier that prevents many individuals in the U.S. from engaging in mental health care. This systematic literature review aims to: (1) evaluate methods used to study the public’s stigma toward mental disorders, (2) summarize stigma findings focused on the public’s stigmatizing beliefs and actions and attitudes toward mental health treatment for children and adults with mental illness, and (3) draw recommendations for reducing stigma towards individuals with mental disorders and advance research in this area. Public stigma of mental illness in the U.S. was widespread. Findings can inform interventions to reduce the public’s stigma of mental illness.

Public Stigma of Mental Illness in the United States: A Systematic Literature Review

OBJECTIVE: The authors discuss empirical studies of human-automation interaction and their implications for automation design. BACKGROUND: Automation is prevalent in safety-critical systems and increasingly in everyday life. Many studies of human performance in automated systems have been conducted over the past 30 years. METHODS: Developments in three areas are examined: levels and stages of automation, reliance on and compliance with automation, and adaptive automation. RESULTS: Automation applied to information analysis or decision-making functions leads to differential system performance benefits and costs that must be considered in choosing appropriate levels and stages of automation. Human user dependence on automated alerts and advisories reflects two components of operator trust, reliance and compliance, which are in turn determined by the threshold designers use to balance automation misses and false alarms. Finally, adaptive automation can provide additional benefits in balancing workload and maintaining the user's situation awareness, although more research is required to identify when adaptation should be user controlled or system driven. CONCLUSIONS: The past three decades of empirical research on humans and automation has provided a strong science base that can be used to guide the design of automated systems. APPLICATION: This research can be applied to most current and future automated systems. Language: en

Humans : Still Vital After All These Years of Automation

Automation does not mean humans are replaced; quite the opposite. Increasingly, humans are asked to interact with automation in complex and typically large-scale systems, including aircraft and air traffic control, nuclear power, manufacturing plants, military systems, homes, and hospitals. This is not an easy or error-free task for either the system designer or the human operator/automation supervisor, especially as computer technology becomes ever more sophisticated. This review outlines recent research and challenges in the area, including taxonomies and qualitative models of human-automation interaction; descriptions of automation-related accidents and studies of adaptive automation; and social, political, and ethical issues. Keywords: Driver distraction; Language: en

Human-Automation Interaction

Objective To estimate the magnitude of stigmatizing attitudes toward peers with depression or attention-deficit/hyperactivity disorder (ADHD) in a national sample of children ages 8 to 18 and to examine variation in level of stigma by school location, region of the United States, grade level, race/ethnicity, or sex. Method Surveys were administered to 1,318 children and adolescents. Respondents were randomly assigned to depression, ADHD, or asthma conditions and were presented with a vignette about a peer with one of the conditions. Participants responded to items assessing positive and negative attributions, social distance, and family attitudes. Mean differences were tested for statistical significance and effect sizes were computed. Results Respondents were more likely to make negative attributions about peers with ADHD and depression versus asthma, particularly regarding the likelihood of antisocial behavior and violence (Cohen d range 0.78-1.35, large effect sizes). Moderate effect sizes were found for preferences for social distance from peers with ADHD ( d = 0.37) and depression ( d = 0.45). Effects were found for perceptions of negative family attitudes toward both mental health conditions, with depression ( d = 0.78) seen as even more stigmatized than ADHD ( d = 0.47). The level of stigmatization was relatively constant across demographic variables, with the exception of greater stigmatization evident in Asian/Pacific Islander youths. Conclusions Across most items, both depression and ADHD were more stigmatized than asthma, with depression more stigmatized than ADHD. The perception of likelihood of violence and antisocial behavior was particularly high for both ADHD and depression, greatly exceeding the real-world association for depression. J. Am. Acad. Child Adolesc. Psychiatry , 2008;47(8):912-920.

Children's Stigmatization of Childhood Depression and ADHD: Magnitude and Demographic Variation in a National Sample

Three experiments and a computational analysis were conducted to investigate the effects of a delegation-type interface on human supervision of simulated multiple unmanned vehicles. Participants supervised up to eight robots using automated behaviors ("plays"), manual (waypoint) control, or both to capture the flag of an opponent with an equal number of robots, using a simple form of a delegation-type interface, Playbook. Experiment 1 showed that the delegation interface increased mission success rate and reduced mission completion time when the opponent "posture" was unpredictably offensive or defensive. Experiment 2 showed that performance was superior when operators could flexibly use both automated behaviors and manual control, although there was a small increase in subjective workload. Experiment 3 investigated additional dimensions of flexibility by comparing delegation interfaces to restricted interfaces. Eight interfaces were tested, varying in the level of abstraction at which robot behavior could be tasked and the level of aggregation (single or multiple robots) to which plays could be assigned. Performance was superior with flexible interfaces for four robots, but this benefit was eliminated when eight robots had to be supervised. Finally, a computational analysis using task-network modeling and Monte Carlo simulation gave results that closely paralleled the empirical data on changes in workload across interface type. The results provide initial empirical evidence for the efficacy of delegation-type interfaces in human supervision of a team of multiple autonomous robots.

A flexible delegation-type interface enhances system performance in human supervision of multiple robots: empirical studies with RoboFlag

The number and type of unmanned vehicles sought in military operations continues to grow. A critical consideration in designing these systems is identifying interface types or interaction schemes that enhance an operator's ability to supervise multiple unmanned vehicles. Past research has explored how interface types impact overall performance measures (e.g. mission execution time), but has not extensively examined other human performance factors that might influence human-robot interaction. Within a dynamic military environment, it is particularly important to assess how interfaces impact an operator's ability to quickly adapt and alter the unmanned vehicle's tasking. To assess an operator's ability to confront this changing environment, we explored the impact of interface type on task switching. Research has shown performance costs (i.e. increased time response) when individuals switch between different tasks. Results from this study suggest that this task switching effect is also seen when participants controlling multiple unmanned vehicles switch between different strategies. Results also indicate that when utilizing a flexible delegation interface, participants did not incur as large a switch cost effect as they did when using an interface that allowed only the use of fixed automated control of the unmanned vehicles.

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Human control of multiple unmanned vehicles: effects of interface type on execution and task switching times

When and where perceptual load interacts with voluntary visuospatial attention: an event-related potential and dipole modeling study.

Objective: Children’s causal attributions about childhood mental health problems were examined in a national sample for prevalence; relative stigmatization; variation by age, race and ethnicity, and gender; and self-report of a diagnosis of depression or attention-deficit hyperactivity disorder (ADHD). Methods: A national sample of 1,091 children were randomly assigned to read vignettes about a peer with depression, ADHD, or asthma and respond to an online survey. Causal attributions and social distance were assessed, and correlations were examined. Logistic regression models for each causal item tested main effects and interaction terms for conditions, demographic characteristics, and self-reported diagnosis. Results: The beliefs that parenting, substance abuse, and low effort caused the condition were all strongly intercorrelated and were moderately correlated with social distance. The depression condition was the strongest predictor of endorsement of the most stigmatizing causal beliefs. Stigmatizing causal beliefs were evident for ADHD, but with more modest effects. Children who reported a diagnosis were more likely to endorse parenting and substance abuse as causes (attenuated for ADHD). Modest to moderate effects were found for variation in causal beliefs across ethnic groups. Conclusions: This study demonstrated a consistent presence of stigmatization in children’s beliefs about the causes of childhood mental health problems. Low effort, parenting, and substance abuse together tapped a moralistic and blaming view of mental health problems. The results reinforce the need to address stigmatization of mental disorders and the relative stigmatization of different causal beliefs. The findings of variation by ethnicity and diagnosis can inform and target antistigmatization efforts. (Psychiatric Services 60:950–957, 2009)

https://ps.psychiatryonline.org/doi/pdf/10.1176/ps.2009.60.7.950

Peter Squire

Papers

Children's Stigmatization of Childhood Depression and ADHD: Magnitude and Demographic Variation in a National Sample

A flexible delegation-type interface enhances system performance in human supervision of multiple robots: empirical studies with RoboFlag

Human control of multiple unmanned vehicles: effects of interface type on execution and task switching times

When and where perceptual load interacts with voluntary visuospatial attention: an event-related potential and dipole modeling study.

Children's beliefs about causes of childhood depression and ADHD: a study of stigmatization.