Adjustment Disorders Are Uniquely Suited for eHealth Interventions: Concept and Case Study

Background: Adjustment disorders (also known as mental distress in response to a stressor) are among the most frequently diagnosed mental disorders in psychiatry and clinical psychology worldwide. They are also commonly diagnosed in clients engaging in deliberate self-harm and in those consulting general practitioners. However, their reputation in research-oriented mental health remains weak since they are largely underresearched. This may change when the International Statistical Classification of Diseases-11 (ICD-11) by the World Health Organization is introduced, including a new conceptualization of adjustment disorders as a stress-response disorder with positively defined core symptoms. Objective: This paper provides an overview of evidence-based interventions for adjustment disorders. Methods: We reviewed the new ICD-11 concept of adjustment disorder and discuss the the rationale and case study of an unguided self-help protocol for burglary victims with adjustment disorder, and its possible implementation as an eHealth intervention. Results: Overall, the treatment with the self-help manual reduced symptoms of adjustment disorder, namely preoccupation and failure to adapt, as well as symptoms of depression, anxiety, and stress. Conclusions: E-mental health options are considered uniquely suited for offering early intervention after the experiences of stressful life events that potentially trigger adjustment disorders.

Differences Between Monetary and Multidimensional Poverty in the Lao PDR: Implications for Targeting of Poverty Reduction Policies and Interventions

This study compares monetary and multidimensional poverty measures for the Lao People’s Democratic Republic. Using household data of 2007/2008, we compare the empirical outcomes of the country’s current official monetary poverty measure with those of a multidimensional poverty measure. We analyze which population subgroups are identified as poor by both measures and thus belong to the category of the poorest of the poor; and we look at which subgroups are identified as poor by only one of the measures and belong either to the category of the income-poor (identified as poor only by the monetary measure) or to that of the overlooked poor (identified as poor only by the multidimensional poverty measure). Furthermore, we examined drivers of these differences using a multinomial regression model and found that monetary poverty does not capture the multiple deprivations of ethnic minorities, who are only identified as poor when using a multidimensional poverty measure. We conclude that complementing the monetary poverty measure with a multidimensional poverty index would enable more effective targeting of poverty reduction efforts.