Attitudes and expectations about treatment have been associated with symptomatic outcomes, adherence and utilization in patients with psychiatric disorders. No measure of patients' anticipated benefits of treatment on domains of everyday functioning has previously been available.

The Anticipated Benefits of Care (ABC) is a new, 10-item questionnaire used to measure patient expectations about the impact of treatment on domains of everyday functioning. The ABC was collected at baseline in adult out-patients with major depressive disorder (MDD) (n=528), bipolar disorder (n=395) and schizophrenia (n=447) in the Texas Medication Algorithm Project (TMAP). Psychometric properties of the ABC were assessed, and the association of ABC scores with treatment response at 3 months was evaluated.

Evaluation of the ABC's internal consistency yielded Cronbach's α of 0.90–0.92 for patients across disorders. Factor analysis showed that the ABC was unidimensional for all patients and for patients with each disorder. For patients with MDD, lower anticipated benefits of treatment was associated with less symptom improvement and lower odds of treatment response [odds ratio (OR) 0.72, 95% confidence interval (CI) 0.57–0.87, p=0.0011]. There was no association between ABC and symptom improvement or treatment response for patients with bipolar disorder or schizophrenia, possibly because these patients had modest benefits with treatment.

The ABC is the first self-report that measures patient expectations about the benefits of treatment on everyday functioning, filling an important gap in available assessments of attitudes and expectations about treatment. The ABC is simple, easy to use, and has acceptable psychometric properties for use in research or clinical settings.

Despite abundant research on the potential causal influence of childhood maltreatment (CM) on psychological maladaptation in adulthood, almost none has implemented the discordant twin design as a means of examining the role of such experiences in later disordered gambling (DG) while accounting for genetic and family environmental confounds. The present study implemented such an approach to disentangle the potential causal and familial factors that may account for the association between CM and DG.

Participants were 3750 twins from the Australian Twin Registry [Mage = 37.60 (s.d. = 2.31); 58% female]. CM and DG were assessed separately via two semi-structured telephone interviews. Random-intercept generalized linear mixed models were fit to the data; zygosity, sex, educational attainment, childhood psychiatric disorder, adult antisocial behavior, and alcohol use disorder (AUD) were included as covariates.

Neither quasi-causal nor familial effects of CM predicted DG after adjusting for covariates. Educational attainment appeared to reduce the risk of DG while AUD appeared to increase risk; evidence also emerged for familial effects of antisocial behavior on DG. Post-hoc analyses revealed a familial effect of CM on antisocial behavior, indicating that the association between CM and DG identified in unadjusted models and in prior studies may be accounted for by genetic and shared family environmental effects of antisociality.

These findings add to the meager literature showing that CM does not exert a causal effect on DG, and present novel evidence that familial effects of antisocial behavior may account for the association between CM and DG identified in extant non-twin research.

Only a few studies have analyzed the effects of physical and psychiatric conditions on the risk of chronic fatigue syndrome (CFS). Therefore, the goal of this exploratory case-control study was to investigate the associations of physical and psychiatric conditions with CFS in almost 19 800 adults from Germany.

This study included patients diagnosed for the first time with CFS in one of 1238 general practices in Germany between 2010 and 2017 (index date). Controls without CFS were matched (1:1) to cases with CFS by sex, age, index year, and practice. Physical and psychiatric conditions diagnosed in the year prior to the index date were included if they were present in at least 3% of patients with CFS. Associations between physical and psychiatric conditions (33 potential independent variables) and CFS (dependent variable) were analyzed in an adjusted conditional logistic regression model, and physical and psychiatric disorders were included in the model using forward stepwise selection.

This study included 9896 cases with CFS and 9896 controls without CFS [65.1% women; mean (standard deviation) age 49.5 (18.3) years]. Seven conditions were associated with CFS in the adjusted regression model. The disorders displaying the strongest relationship with CFS were cancer [odds ratio (OR) = 2.57, 95% confidence interval (CI) = 2.24–2.95], sleep disorders (OR = 1.88, 95% CI = 1.66–2.12) and depression (OR = 1.77, 95% CI = 1.61–1.95).

Cancer, sleep disorders, and depression were strongly and positively associated with CFS. Additional studies are needed to gain a better understanding of the mechanisms underlying these relationships.