IMPORTANCESuicide prediction models have the potential to improve the identification of patients at heightened suicide risk by using predictive algorithms on large-scale data sources. Suicide prediction models are being developed for use across enterprise-level health care systems including the US Department of Defense, US Department of Veterans Affairs, and Kaiser Permanente.OBJECTIVES To evaluate the diagnostic accuracy of suicide prediction models in predicting suicide and suicide attempts and to simulate the effects of implementing suicide prediction models using population-level estimates of suicide rates.EVIDENCE REVIEW A systematic literature search was conducted in MEDLINE, PsycINFO, Embase, and the Cochrane Library to identify research evaluating the predictive accuracy of suicide prediction models in identifying patients at high risk for a suicide attempt or death by suicide. Each database was searched from inception to August 21, 2018. The search strategy included search terms for suicidal behavior, risk prediction, and predictive modeling. Reference lists of included studies were also screened. Two reviewers independently screened and evaluated eligible studies.FINDINGS From a total of 7306 abstracts reviewed, 17 cohort studies met the inclusion criteria, representing 64 unique prediction models across 5 countries with more than 14 million participants. The research quality of the included studies was generally high. Global classification accuracy was good (Ն0.80 in most models), while the predictive validity associated with a positive result for suicide mortality was extremely low (Յ0.01 in most models). Simulations of the results suggest very low positive predictive values across a variety of population assessment characteristics.CONCLUSIONS AND RELEVANCE To date, suicide prediction models produce accurate overall classification models, but their accuracy of predicting a future event is near 0. Several critical concerns remain unaddressed, precluding their readiness for clinical applications across health systems.

IMPORTANCE It is often difficult for members of the US military to access high-quality care for posttraumatic stress disorder (PTSD) and depression.OBJECTIVE To determine effectiveness of a centrally assisted collaborative telecare (CACT) intervention for PTSD and depression in military primary care. DESIGN, SETTING, AND PARTICIPANTSThe STEPS-UP study (Stepped Enhancement of PTSD Services Using Primary Care) is a randomized trial comparing CACT with usual integrated mental health care for PTSD or depression. Patients, mostly men in their 20s, were enrolled from 18 primary care clinics at 6 military installations from February 2012 to August 2013 with 12-month follow-up completed in October 2014.INTERVENTIONS Randomization was to CACT (n = 332) or usual care (n = 334). The CACT patients received 12 months of stepped psychosocial and pharmacologic treatment with nurse telecare management of caseloads, symptoms, and treatment. MAIN OUTCOMES AND MEASURESPrimary outcomes were severity scores on the PTSD Diagnostic Scale (PDS; scored 0-51) and Symptom Checklist depression items (SCL-20; scored 0-4). Secondary outcomes were somatic symptoms, pain severity, health-related function, and mental health service use. RESULTSOf 666 patients, 81% were male and the mean (SD) age was 31.1 (7.7) years. The CACT and usual care patients had similar baseline mean (SD) PDS PTSD (29.4 [9.4] vs 28.9 [8.9]) and SCL-20 depression (2.1 [0.6] vs 2.0 [0.7]) scores. Compared with usual care, CACT patients reported significantly greater mean (SE) 12-month decrease in PDS PTSD scores (−6.07 [0.68] vs −3.54 [0.72]) and SCL-20 depression scores −0.56 [0.05] vs −0.31 [0.05]). In the CACT group, significantly more participants had 50% improvement at 12 months compared with usual care for both PTSD (73 [25%] vs 49 [17%]; relative risk, 1.6 [95% CI, 1.1-2.4]) and depression (86 [30%] vs 59 [21%]; relative risk, 1, with a number needed to treat for a 50% improvement of 12.5 (95% CI, 6.9-71.9) and 11.1 (95% CI, 6.2-50.5), respectively. The CACT patients had significant improvements in somatic symptoms (difference between mean 12-month Patient Health Questionnaire 15 changes, −1.37 [95% CI, −2.26 to −0.47]) and mental health-related functioning (difference between mean 12-month Short Form-12 Mental Component Summary changes, 3.17 [95% CI, 0.91 to 5.42]), as well as increases in telephone health contacts and appropriate medication use. CONCLUSIONS AND RELEVANCECentral assistance for collaborative telecare with stepped psychosocial management modestly improved outcomes of PTSD and depression among military personnel attending primary care. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01492348

Previous investigations have identified individuals who meet criteria for DSM-IV-TR substance dependence as applied to caffeine, but there is little research on treatments for caffeine dependence. This study aimed to thoroughly characterize individuals who are seeking treatment for problematic caffeine use. Ninety-four individuals who identified as being psychologically or physically dependent on caffeine, or who had tried unsuccessfully to modify caffeine consumption participated in a face-to-face diagnostic clinical interview. They also completed measures concerning caffeine use and quitting history, reasons for seeking treatment, and standardized self-report measures of psychological functioning. Caffeine treatment seekers (mean age 41 yrs, 55% women) consumed an average of 548 mg caffeine per day. The primary source of caffeine was coffee for 50% of the sample and soft drinks for 37%. Eighty-eight percent reported prior serious attempts to modify caffeine use (mean 2.7 prior attempts) and 43% reported being advised by a medical professional to reduce or eliminate caffeine. Ninety-three percent met criteria for caffeine dependence when generic DSM-IV-TR substance dependence criteria were applied to caffeine use. The most commonly endorsed criteria were withdrawal (96%), persistent desire or unsuccessful efforts to control use (89%), and use despite knowledge of physical or psychological problems caused by caffeine (87%). The most common reasons for wanting to modify caffeine use were health-related (59%) and not wanting to be dependent on caffeine (35%). This investigation reveals that there are individuals with problematic caffeine use who are seeking treatment, and suggests that there is a need for effective caffeine dependence treatments.

Among chronic smokers, individual differences in subjective reactions to smoking may characterize important facets of nicotine dependence that relate to abstinence-induced craving, withdrawal symptom profiles, and risk for relapse. Although the negative reinforcing properties of smoking have achieved prominent positions in models of relapse (Baker, Brandon, & Chassin, 2004), vulnerability to relapse risk may also arise from seeking positive reinforcement from smoking (Shiffman & Kirchner, 2009). In this study, 183 cessation-motivated smokers provided subjective craving, positive and negative reactions to standardized cigarettes following overnight abstinence. Level of craving, negative mood, and positive mood after overnight abstinence were significantly predictive of withdrawal on quit-day. Increased positive reactions to smoking were uniquely predictive of relapse after quitting (Hazard Ratio = 1.22, p < .001). Individual differences in positive reactions to smoking may be important markers of neurobiological systems that promote dependence and interfere with cessation efforts.