ObjectiveThis study aims at evaluating the cost-effectiveness and cost-utility of a guided and unguided internet-based intervention for chronic pain patients (ACTonPainguidedand ACTonPainunguided) compared with a waitlist control group (CG) as well as the comparative cost-effectiveness of the guided and the unguided version.DesignThis is a health economic evaluation alongside a three-arm randomised controlled trial from a societal perspective. Assessments were conducted at baseline, 9 weeks and 6 months after randomisation.SettingParticipants were recruited through online and offline strategies and in collaboration with a health insurance company.Participants302 adults (≥18 years, pain for at least 6 months) were randomly allocated to one of the three groups (ACTonPainguided, ACTonPainunguided, CG).InterventionsACTonPain consists of seven modules and is based on Acceptance and Commitment Therapy. ACTonPainguidedand ACTonPainunguidedonly differ in provision of human support.Primary and secondary outcome measuresMain outcomes of the cost-effectiveness and the cost-utility analyses were meaningful change in pain interference (treatment response) and quality-adjusted life years (QALYs), respectively. Economic evaluation estimates were the incremental cost-effectiveness and cost-utility ratio (ICER/ICUR).ResultsAt 6-month follow-up, treatment response and QALYs were highest in ACTonPainguided(44% and 0.280; mean costs = €6,945), followed by ACTonPainunguided(28% and 0.266; mean costs = €6,560) and the CG (16% and 0.244; mean costs = €6,908). ACTonPainguidedvs CG revealed an ICER of €45 and an ICUR of €604.ACTonPainunguideddominated CG. At a willingness-to-pay of €0 the probability of being cost-effective was 50% for ACTonPainguided(vs CG, for both treatment response and QALY gained) and 67% for ACTonPainunguided(vs CG, for both treatment response and QALY gained). These probabilities rose to 95% when society’s willingness-to-pay is €91,000 (ACTonPainguided) and €127,000 (ACTonPainunguided) per QALY gained. ACTonPainguidedvs ACTonPainunguidedrevealed an ICER of €2,374 and an ICUR of €45,993.ConclusionsDepending on society’s willingness-to-pay, ACTonPain is a potentially cost-effective adjunct to established pain treatment. ACTonPainunguided(vs CG) revealed lower costs at better health outcomes. However, uncertainty has to be considered. Direct comparison of the two interventions does not indicate a preference for ACTonPainguided.Trial registration numberDRKS00006183.
Zusammenfassung Ziel der Studie Der Artikel beschreibt Evaluationsergebnisse eines Modellprojekts zur Unterstützung psychisch belasteter Geflüchteter durch geschulte Laien. Ziel der Evaluation war eine Beurteilung hinsichtlich Notwendigkeit, Nützlichkeit und Effektivität des Projekts. Methodik Es wurden involvierte und außenstehende Akteure mittels validierter sowie selbst entworfener Instrumente befragt und die Ergebnisse durch statistische Datenanalyse ausgewertet. Bei den Stichproben handelte es sich um 197 in Sammelunterkünften lebende Geflüchtete, 18 im Projekt arbeitende Laienhelfer (LH) sowie 16 Sozialarbeiter und Verwalter aus zwölf Flüchtlingsunterkünften. Ergebnisse Mehr als die Hälfte der befragten Geflüchteten gaben eine psychisch auffällige Belastung an. Die Laienhilfe, die primär aus individualisierten Einzelangeboten bestand, wurde von den Geflüchteten positiv bewertet. 58,5 % der Klienten der LH wurden in die Regelversorgung weitervermittelt. Schulung, Koordination und Supervision wurden von den LH als gut bewertet. Im Projektverlauf änderte sich die Belastung der LH nicht. Sozialarbeiter und Verwalter der Flüchtlingsunterkünfte sahen die Arbeit der LH als hilfreich an. Schlussfolgerung Das Konzept des Modellprojekts erweist sich als notwendig und sinnvoll. Psychisch belastete Geflüchtete profitieren von dem niedrigschwelligen Angebot in den Flüchtlingsunterkünften, und die LH leisten eine wertvolle muttersprachliche Hilfestellung. Gute Schulung, Koordination und Supervision als Rahmenbedingungen ermöglichen den erfolgreichen Einsatz von Laien zur effektiven Unterstützung von psychisch belasteten Geflüchteten.
Despite compelling evidence that victimization and offending co-occur, it remains unclear what types of victimization are linked to specific forms of perpetration. Here we examined the relationship between physical, psychological, and sexual violence with respect to influencing variables including mental health, risk-taking behaviors, and coping strategies. Data from 5385 men were collected as part of an epidemiological study on violence experience. A classification and regression tree analysis identified the main predictors of violence perpetration and classified violent offending into high-and low-risk groups.Results indicate that violence is best predicted by previous exposure to violence and polyvictimization. Physical violence is best predicted by prior exposure to physical violence and this is further influenced by the frequency of and the age at which violence was experienced. Drug use was a strong predictor of physical and psychological violence. The latter is best predicted by a history of polyvictimization, the severity and the originator of violence. Sexual violence is strongly predicted by one's sexual violence experience. Other factors such as demographic characteristics are less predictive. Our results may contribute to the development of early prevention and intervention approaches that account for different risk factors. The significance of violence exposure suggest that intervention measures must focus on victims of early and prolonged experience of violence. On the strength of the link between drug use and violence, exposure to violence should be considered in drug prevention and intervention and vice versa. K E Y W O R D S classification and regression tree analysis, exposure to violence, perpetration, polyvictimization, risk factors, violent offending This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Violence is a known risk factor for health problems. In this epidemiological study across 5,385 male patients, we investigate the prevalence of perpetrated violence, exposure to violence, their overlap and the relationship between violence, mental, and psychosomatic health, as well as adverse health behaviors, such as self-harming behavior and the consumption of drugs. Participants completed an anonymous questionnaire addressing violence experience (i.e., both expose and perpetration), age of victimization/perpetration, frequency, and perceived severity of violence exposure. We considered physical, psychological as well as sexual violence. Information on health status and adverse health behaviors complemented the data. Results showed that 48.4% of the sample reported having experienced violence (perpetration, victimization, or both). The victim-perpetrator overlap formed the largest group, in which the incidence of having experienced multiple types of violence was significantly higher compared to victims and perpetrators. The age-crime curve flattened more slowly with increasing age in this group. Although the perceived severity of exposure to violence is lower in the overlap group, its health status and adverse health behaviors were worse. Interventions should focus on this group since they constitute a burden for the healthcare system.
Despite compelling evidence that victimization and offending co-occur, it remains unclear what types of victimization are linked to specific forms of perpetration. Here we examined the relationship between physical, psychological, and sexual violence with respect to influencing variables including mental health, risk-taking behaviors, and coping strategies. Data from 5,385 men were collected as part of an epidemiological study on violence experience. A classi-fication and regression tree analysis identified the main predictors of violence perpetration and classified violent offending into high- and low risk groups. Results indicate that violence is best predicted by previous exposure to violence and polyvictimization. Physical violence is best predicted by prior exposure to physical violence and this is further influenced by the fre-quency of and the age at which violence was experienced. Drug use was a strong predictor of physical and psychological violence. The latter is best predicted by a history of polyvictimiza-tion, the severity and the originator of violence. Sexual violence is strongly predicted by one´s sexual violence experience. Other factors such as demographic characteristics are less predic-tive. Our results may contribute to the development of early prevention and intervention ap-proaches that account for different risk factors. The significance of violence exposure suggest that intervention measures must focus on victims of early and prolonged experience of vio-lence. On the strength of the link between drug use and violence, exposure to violence should be considered in drug prevention and intervention and vice versa.
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