Cognitive-behavioral therapies (CBTs) are the most widely studied form of psychotherapy for disorders like depression and anxiety. Nonetheless, there is heterogeneity in response to CBTs vs. other treatments. Researchers have become increasingly interested in using pre-treatment individual differences (i.e., moderators) to match patients to the most effective treatments for them. Several methods to combine multiple variables to create precision treatment rules (PTRs) that identify subgroups have been proposed. We review the rationale behind multivariable PTRs as well as the findings of studies that have used different PTRs. We identify conceptual and methodological issues in the literature. Multivariable treatment assignment is a promising avenue of research. Nonetheless, effect sizes appear to be small and most of the samples that have been used to study these questions have been grossly underpowered to detect small effects. We recommend researchers explore multivariable treatment selection strategies, particularly those resembling risk-stratification, in heterogeneous samples of patients undergoing low-intensity CBTs vs. realistic minimal controls.

Despite the research attention that has been paid to the public and self-stigma of mental illness, much less attention has been given to stigma and physical disabilities, particularly compared with psychological disabilities. Participants were 243 workers on Amazon's Mechanical Turk, an online crowd-sourcing tool, who completed measures of public stigma, self-stigma, stigma consciousness, as well as outcome measures of self-esteem, social anxiety, depression, and ostracism. Compared with physically disabled individuals, psychologically disabled participants reported significantly higher scores on public stigma, the awareness component of self-stigma, stigma consciousness, and all four outcome measures. Of particular import, however, is that persons with physical disabilities, though reporting lower levels of stigma than individuals with psychological disabilities, still evidenced both public and self-stigma. The results highlight the need for additional research examining stigma and physical disabilities, specifically, and research comparing these experiences with those of individuals with psychological disabilities. Implications of the findings for reducing stigma are discussed.

Background Common mental disorders, including depression and anxiety, are leading causes of disability worldwide. Digital mental health interventions, such as web-based self-help and other low-intensity treatments (LITs) that are not digital (eg, bibliotherapy), have the potential to reach many individuals by circumventing common barriers present in traditional mental health care. It is unclear how often LITs are used in clinical practice, or whether providers would be interested in their use for treatment waiting lists. Objective The aims of this study were to (1) describe current practices for treatment waiting lists, (2) describe providers’ attitudes toward digital and nondigital LITs for patients on a waiting list, and (3) explore providers’ willingness to use digital and nondigital LITs and their decisions to learn about them. Methods We surveyed 141 practicing mental health care providers (eg, therapists and psychologists) and provided an opportunity for them to learn about LITs. Results Most participants reported keeping a waiting list. Few participants reported currently recommending digital or nondigital LITs, though most were willing to use at least one for patients on their waiting list. Attitudes toward digital and nondigital LITs were neutral to positive. Guided digital and nondigital LITs were generally perceived to be more effective but less accessible, and unguided interventions were perceived to be less effective but more accessible. Most participants selected to access additional information on LITs, with the most popular being web-based self-help. Conclusions Results suggest providers are currently not recommending LITs for patients on treatment waiting lists but would be willing to recommend them. Future work should explore barriers and facilitators to implementing digital and nondigital LITs for patients on treatment waiting lists.

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