Suchergebnisse

The field of medical geographic information systems (Medical GIS) has become extremely useful in understanding the bigger picture of public health. The discipline holds a substantial capacity to understand not only differences, but also similarities in population health all over the world. The main goal of marrying the disciplines of medical geography, public health and informatics is to understand how countless health issues impact populations, and the trends by which these populations are affected. From the 1990s to today, this practical approach has become a valued and progressive system in analyzing medical and epidemiological phenomena ranging from cholera to cancer. The instruments supporting this field include geographic information systems (GIS), disease surveillance, big data, and analytical approaches like the Geographical Analysis Machine (GAM), Dynamic Continuous Area Space Time Analysis (DYCAST), cellular automata, agent-based modeling, spatial statistics and self-organizing maps. The positive effects on disease mapping have proven to be tremendous as these instruments continue to have a great impact on the mission to improve worldwide health care. While traditional uses of GIS in public health are static and lacking real-time components, implementing a space-time animation in these instruments will be monumental as technology and data continue to grow.

Pathological Internet use (but only with respect to gaming) is classified as mental disorder in the ICD-11. However, there is a large group of adolescents showing excessive Internet use, which may rather be considered adolescent risk-behavior. The aim was to test whether pathological and excessive Internet use should be considered as "psychopathology" or "risk-behavior". A representative, cross-sectional sample of 11.110 students from 10 European Union countries was analyzed. Structural equation models, including the factors "risk-behavior" and "psychopathology" and the variables excessive and pathological Internet use, were tested against each other. "Risk-behavior" was operationalized by several risk-behaviors (e.g. drug abuse, truancy, etc). "Psychopathology" included measures of several mental disorders (e.g. depression, hyperactivity, etc). Excessive Internet use was assessed as the duration and frequency of Internet use. Pathological Internet use was assessed with the Young Diagnostic Questionnaire (i.e., presence of addiction criteria). Excessive Internet use loaded on "risk-behavior" (λ = 0.484, p < .001) and on "psychopathology" (λ = 0.071, p < .007). Pathological Internet use loaded on "risk-behavior" (λ = 0.333, p < .001) and on "psychopathology" (λ = 0.852, p < .001). Chi-square tests determined that the loadings of excessive Internet use (χ2 (1) = 81.98, p < .001) were significantly stronger on "risk-behavior" than "psychopathology". Vice versa, pathological Internet use loaded significantly stronger on "psychopathology" (χ2 (1) = 107.10, p < .001). The results indicate that pathological Internet use should rather be considered as psychopathology. Excessive Internet use on the other hand, should be classified as adolescent risk-behavior.

Rising global rates of pathological Internet use (PIU) and related psychological impairments have gained considerable attention in recent years. In an effort to acquire evidence-based knowledge of this relationship, the main objective of this study was to investigate the association between PIU, psychopathology and self-destructive behaviours among school-based adolescents in eleven European countries. This cross-sectional study was implemented within the framework of the European Union project: Saving and Empowering Young Lives in Europe. A representative sample of 11,356 school-based adolescents (M/F: 4,856/6,500; mean age: 14.9) was included in the analyses. PIU was assessed using the Young's Diagnostic Questionnaire. Psychopathology was measured using the Beck Depression Inventory-II, Zung Self-Rating Anxiety Scale and Strengths and Difficulties Questionnaire. Self-destructive behaviours were evaluated by the Deliberate Self-Harm Inventory and Paykel Suicide Scale. Results showed that suicidal behaviours (suicidal ideation and suicide attempts), depression, anxiety, conduct problems and hyperactivity/inattention were significant and independent predictors of PIU. The correlation between PIU, conduct problems and hyperactivity/inattention was stronger among females, while the link between PIU and symptoms of depression, anxiety and peer relationship problems was stronger among males. The association between PIU, psychopathology and self-destructive behaviours was stronger in countries with a higher prevalence of PIU and suicide rates. These findings ascertain that psychopathology and suicidal behaviours are strongly related to PIU. This association is significantly influenced by gender and country suggesting socio-cultural influences. At the clinical and public health levels, targeting PIU among adolescents in the early stages could potentially lead to improvements of psychological well-being and a reduction of suicidal behaviours.