Avoidance and fear day by day in social anxiety disorder.

OBJECTIVE: Theories assert that avoidance maintains maladaptive anxiety over time, yet a clear prospective test of this effect in the day-by-day lives of people with social anxiety disorder (SAD) is lacking. METHOD: We used intensive longitudinal data to test prospective relationships between social fear and social avoidance in 32 participants with SAD who reported on a total of 4256 time points. RESULTS: Results suggested that avoidance strongly predicted future anxiety, but only in a minority of people with SAD. Relationships between anxiety and avoidance varied considerably across individuals. Pre-registered tests found that the strength of autocorrelation for social fear is a good target for future testing of prediction of exposure response. Participants with lower autocorrelations were less likely to show between-session habituation. CONCLUSIONS: Overall, results suggest avoidance maintains fear in SAD for at least some individuals, but also indicates considerable variability. Further intensive longitudinal data is needed to examine individuals with SAD across varying time courses.

Feasibility and utility of idiographic models in the clinic: A pilot study.

AbstractIntroduction: Idiographic, or individual-level, methodology has been touted for its potential clinical utility. Empirically modeling relationships between symptoms for a single individual may offer both the client and therapist information that is useful for case conceptualization and treatment planning. However, few studies have investigated the feasibility and utility of integrating idiographic models in a clinical setting.Methods: Clients (n = 12) completed ecological momentary assessment regarding psychological symptoms five times per day for three weeks. Clients also generated predictions about the associative and directed relationships in their networks. Graphical vector autoregression was used to generate contemporaneous and directed networks from each client's data, and both clients and therapists completed self-report questionnaires regarding the feasibility and utility of these methods.Results: Results indicated that the idiographic model structures varied widely across participants and differed markedly from the client's own predictions. Clients found the models useful, whereas their therapists demonstrated a more tempered response.Discussion: These results echo previous findings suggesting that clients are willing to complete intensive data collection and are interested in the output, whereas therapists may be less open to idiographic methods. We provide recommendations for future implementation of personalized models in clinical settings.

mHealth Assessment and Intervention of Depression and Anxiety in Older Adults.

Mobile technology is increasingly being used to enhance health and wellness, including in the assessment and treatment of psychiatric disorders. Such applications have been referred to collectively as mHealth, and this article provides a comprehensive review and clinical perspective of research regarding mHealth in late-life mood and anxiety disorders. The novel data collection offered by mHealth has contributed to a broader understanding of psychopathology, to an increased diversity of psychological interventions, and to novel methods of assessment that may ultimately provide individually adaptive mental health care for this population. Older adults face challenges (e.g., transportation, mobility) that limit their ability to receive medical and mental health care services, and mHealth may improve the capacity to reach this population. Although several mobile interventions exist for health-related issues in older adults (e.g., balance, diabetes, medication management), mHealth targeting psychiatric disorders is limited and most often focuses on problems related to dementia, cognitive dysfunction, and memory loss. Given that depression and anxiety are two of the most common mental health concerns among this population, mHealth has strong potential for broad public health interventions that may improve effectiveness of mental health care via individualized assessments and treatments.

Blunts versus joints: Cannabis use characteristics and consequences among treatment-seeking adults.

BACKGROUND: Despite the high prevalence of blunt smoking among cannabis users, very few studies examine the clinical profile of blunt smokers relative to those using more common methods of cannabis use, such as joints. METHODS: The current study uses baseline data from the ACCENT (Achieving Cannabis Cessation-Evaluating N-acetylcysteine Treatment) study, a multi-site randomized pharmacotherapy clinical trial within the National Drug Abuse Treatment Clinical Trials Network, to predict the association between blunt and joint use frequency and cannabis use characteristics (e.g., grams of cannabis used) and consequences (e.g., withdrawal) among past-month cannabis users (N = 377) who were screened for study participation. RESULTS: After controlling for race, age, gender, other forms of cannabis use (including joint use) and nicotine dependence, multivariable linear regression models indicated that the number of days of blunt use in the past month was a significant predictor of the average amount of cannabis per using day (t = 3.04, p < .01), the estimated average cost of cannabis (t = 2.28, p < .05) and Cannabis Withdrawal Scale scores (t = 1.94, p < .05). Frequency of joint use did not significantly predict any of the cannabis use characteristics or consequences. CONCLUSIONS: Blunt smokers may present to treatment with greater amounts of cannabis smoked and more intense withdrawal symptoms, which may adversely impact their likelihood of successful abstinence. Cannabis-dependent blunt smokers may be more likely to benefit from treatment that targets physiological and mood-related withdrawal symptoms.