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Additional work is needed to determine whether the observed adolescent cannabis administration patterns are similar across different samples and sampling methods as well as how these trends change over time with extended exposure to new products and methods. The combined knowledge gained via diverse sampling strategies will have important implications for the development of regulatory policy and prevention and intervention efforts.

Background User engagement is key to the effectiveness of digital mental health interventions. Considerable research has examined the clinical outcomes of overall engagement with mental health apps (eg, frequency and duration of app use). However, few studies have examined how specific app use behaviors can drive change in outcomes. Understanding the clinical outcomes of more nuanced app use could inform the design of mental health apps that are more clinically effective to users. Objective This study aimed to classify user behaviors in a suite of mental health apps and examine how different types of app use are related to depression and anxiety outcomes. We also compare the clinical outcomes of specific types of app use with those of generic app use (ie, intensity and duration of app use) to understand what aspects of app use may drive symptom improvement. Methods We conducted a secondary analysis of system use data from an 8-week randomized trial of a suite of 13 mental health apps. We categorized app use behaviors through a mixed methods analysis combining qualitative content analysis and principal component analysis. Regression analyses were used to assess the association between app use and levels of depression and anxiety at the end of treatment. Results A total of 3 distinct clusters of app use behaviors were identified: learning, goal setting, and self-tracking. Each specific behavior had varied effects on outcomes. Participants who engaged in self-tracking experienced reduced depression symptoms, and those who engaged with learning and goal setting at a moderate level (ie, not too much or not too little) also had an improvement in depression. Notably, the combination of these 3 types of behaviors, what we termed “clinically meaningful use,” accounted for roughly the same amount of variance as explained by the overall intensity of app use (ie, total number of app use sessions). This suggests that our categorization of app use behaviors succeeded in capturing app use associated with better outcomes. However, anxiety outcomes were neither associated with specific behaviors nor generic app use. Conclusions This study presents the first granular examination of user interactions with mental health apps and their effects on mental health outcomes. It has important implications for the design of mobile health interventions that aim to achieve greater user engagement and improved clinical efficacy.

Technology-enabled mental health services have the potential to expand the reach of care and reduce clinician demand. While the efficacy of technology-enabled mental health services is well established, there have been few successful implementations of such services into community care settings.Using mixed methods, 89 clinicians and supervisors at a mental health service organization shared attitudes toward and interest in using a variety of technologies in their work. Participants discussed several challenges and opportunities for technology-enabled mental health services. Whilst clinicians saw potential for technology to engage individuals both in and outside the clinical environment, the range of therapeutic techniques used by clinicians presented a challenge in implementing a tool to meet their needs. Client technology access was a concern, and although text messaging would facilitate communication, current HIPAA and payment structures restrict this ability. With these considerations, we offer recommendations for implementing technological services in community mental health organizations.Terms of use and reuse: academic research for non-commercial purposes, see here for full terms. https://www.springer.com/aamterms-v1

Internet-based cognitive behavioral therapy (iCBT) may overcome barriers to mental health care and has proven efficacious. However, this approach currently exists outside the existing mental health care delivery system. Stepped care is a proposed framework for integrating digital mental health (DMH) into health systems by initiating iCBT and “stepping up” care to a more intensive intervention should iCBT prove ineffective. This study explores pre-treatment factors associated with reaching stepping criteria among patients receiving iCBT. This exploratory analysis of a stepped care arm of a larger randomized trial examined participants who were stepped to a more intensive intervention if they did not respond to iCBT. The association of pre-treatment factors on stepping were examined using Kruskal–Wallis and Chi-square tests. One-fifth of the 151 participants met criteria for stepping within the 20-week treatment period. Only pre-treatment depression severity and treatment preference were associated with increased likelihood of stepping (p = 0.049 and 0.048, respectively). The low number of individuals who stepped provides support for iCBT as an effective, low intensity treatment for depression. The modest association of pre-treatment depression and preference to not receive iCBT may be useful in identifying patients who are less likely to respond.

Independent lines of evidence have linked posttraumatic stress symptomatology to both peritraumatic disgust (i.e., disgust experienced during a traumatic event) and posttraumatic disgust reactivity in response to traumatic event cues among individuals exposed to traumatic events. Much of this work suggests disgust, defined as a rejection/revulsion response aimed at distancing oneself from a potential source of contamination, may be important in understanding the nature of posttraumatic stress reactions even after accounting for the more frequently studied affective states of fear and anxiety. The current investigation provided a preliminary test of a model of disgust in posttraumatic stress among a sample of 54 community-recruited women with a history sexual victimization. Both peritraumatic disgust and posttraumatic disgust reactivity in response to an ideographic traumatic event script were significantly associated with posttraumatic stress symptom severity. After accounting for variability associated peritraumatic fear and posttraumatic anxious reactivity, an indirect effect of peritraumatic disgust through posttraumatic disgust reactivity also was found, suggesting that one mechanism through which peritraumatic disgust relates to posttraumatic stress is through its relation with increased posttraumatic disgust reactivity. These findings highlight the importance of further elucidating the nature of disgust in relation to traumatic events and subsequent posttraumatic stress reactions.

Background This article provides a generalizable method, rooted in co-design and stakeholder engagement, to identify, specify, and prioritize implementation strategies. To illustrate this method, we present a case example focused on identifying strategies to promote pediatric hypertension (pHTN) Clinical Practice Guideline (CPG) implementation in community health center-based primary care practices that involved meaningful engagement of pediatric clinicians, clinic staff, and patients/caregivers. This example was chosen based on the difficulty clinicians and organizations experience in implementing the pHTN CPG, as evidenced by low rates of guideline-adherent pHTN diagnosis and treatment. Methods We convened a Stakeholder Advisory Panel (SAP), comprising 6 pediatricians and 5 academic partners, for 8 meetings (~12 h total) to rigorously identify determinants of pHTN CPG adherence and to ultimately develop a testable multilevel, multicomponent implementation strategy. Our approach expanded upon the Expert Recommendations for Implementation Change (ERIC) protocol by incorporating a modified Delphi approach, user-centered design methods, and the Implementation Research Logic Model (IRLM). At the recommendation of our SAP, we gathered further input from youth with or at-risk for pHTN and their caregivers, as well as clinic staff who would be responsible for carrying out facets of the implementation strategy. Results First, the SAP identified 17 determinants, and 18 discrete strategies were prioritized for inclusion. The strategies primarily targeted determinants in the domains of intervention characteristics, inner setting, and characteristics of the implementers. Based on SAP ratings of strategy effectiveness, feasibility, and priority, three tiers of strategies emerged, with 7 strategies comprising the top tier implementation strategy package. Next, input from caregivers and clinic staff confirmed the feasibility and acceptability of the implementation strategies and provided further detail in the definition and specification of those strategies. Conclusions This method—an adaptation of the ERIC protocol—provided a pragmatic structure to work with stakeholders to efficiently identify implementation strategies, particularly when supplemented with user-centered design activities and the intuitive organizing framework of the IRLM. This generalizable method can help researchers identify and prioritize strategies that align with the implementation context with an increased likelihood of adoption and sustained use.

Background: Self-regulation deficits expressed through a decreased ability to value future rewards (delay discounting (DD)) and impaired emotion regulation (negative urgency (NU), cannabis coping motives (CCM), and anxiety sensitivity (AS)) relate to more frequent or problematic cannabis use. However, there is a need to better understand how self-regulation and emotion regulation constructs reflect competition between deliberative and reactive systems that drive individual differences in cannabis use patterns. Further, few studies assess frequency of cannabis use within and across days of use, which may obscure differentiation of individual differences. Methods:In a large national sample of 2545 cannabis users, Latent Class Analysis was used to derive participant sub-classes based on two frequency indices, self-reported cannabis use days and times cannabis was used per day. Three classes emerged: Low (1-9 days/month, 1 time/day; 23 %), moderate (10-29 days/month, 2-3 times/day; 41 %), and high (30 days/month, ≥4 times/day; 36 %). Relationships among frequency classes and emotional regulation and impulsivity were assessed with a multinomial logistic regression.Results: Higher frequency use was associated with greater DD (χ 2 = 6.0, p = .05), greater CCM (χ 2 = 73.3, p < .001), and lower cognitive AS (χ 2 = 12.1, p = .002), when controlling for *