Targeting Anxiety to Improve Sleep Disturbance: A Randomized Clinical Trial of App-Based Mindfulness Training.

OBJECTIVE: Sleep disturbance is experienced by nearly 20% of Americans and is highly comorbid with anxiety. Sleep disturbances may predict the development of anxiety disorders. Mindfulness training (MT) has shown efficacy for anxiety yet remains limited by in-person-based delivery. Digitally delivered MT may target habitual worry processes, yet its effects on sleep have not been studied. This study tested if app-based MT for anxiety could reduce worry and improve sleep and examined the underlying mechanisms. METHODS: Individuals reporting worry interfering with sleep were randomized to treatment as usual (TAU; n = 40) or TAU + app-based MT (n = 40). Treatment-related changes in worry-related sleep disturbances (WRSDs), worry, nonreactivity, and anxiety were evaluated via self-report questionnaires at 1 and 2 months after treatment initiation. Fitbit devices were used to record total sleep time and estimate sleep efficiency. At 2 months, TAU received access to app-based MT, and both groups were reassessed at 4 months. RESULTS: In a modified intent-to-treat analysis, WRSD scores decreased by 27% in TAU + MT (n = 36) and 6% in TAU (n = 35) at 2 months (median [IQR] change = 11 [4.3] versus 15 [5.0], p = .001). These WRSD reductions were mediated by decreased worry, particularly improved nonreactivity (p values < .001). At 4 months, TAU reported a significant 29% reduction after beginning app-based MT at 2 months and TAU + MT maintained its gains. No significant between-group differences in average estimated total sleep time or sleep efficiency were found after 2 months of using the app. CONCLUSIONS: Few mindfulness-related apps have been evaluated for clinical efficacy and/or mechanism. Results from this study demonstrate a mechanistic link between MT and increased emotional nonreactivity, decreased worry, and reduction in reported sleep disturbances, suggesting that app-based MT may be a viable option to help individuals who report that worry interferes with their sleep.Trial Registration: ClinicalTrials.gov identifier: NCT03684057.

App-Based Mindfulness Training Predicts Reductions in Smoking Behavior by Engaging Reinforcement Learning Mechanisms: A Preliminary Naturalistic Single-Arm Study.

Mindfulness training (MT) has been shown to influence smoking behavior, yet the involvement of reinforcement learning processes as underlying mechanisms remains unclear. This naturalistic, single-arm study aimed to examine slope trajectories of smoking behavior across uses of our app-based MT craving tool for smoking cessation, and whether this relationship would be mediated by the attenuating impact of MT on expected reward values of smoking. Our craving tool embedded in our MT app-based smoking cessation program was used by 108 participants upon the experience of cigarette cravings in real-world contexts. Each use of the tool involved mindful awareness to the experience of cigarette craving, a decision as to whether the participant wanted to smoke or ride out their craving with a mindfulness exercise, and paying mindful attention to the choice behavior and its outcome (contentment levels felt from engaging in the behavior). Expected reward values were computed using contentment levels experienced from the choice behavior as the reward signal in a Rescorla−Wagner reinforcement learning model. Multi-level mediation analysis revealed a significant decreasing trajectory of smoking frequency across MT craving tool uses and that this relationship was mediated by the negative relationship between MT and expected reward values (all ps < 0.001). After controlling for the mediator, the predictive relationship between MT and smoking was no longer significant (p < 0.001 before and p = 0.357 after controlling for the mediator). Results indicate that the use of our app-based MT craving tool is associated with negative slope trajectories of smoking behavior across uses, mediated by reward learning mechanisms. This single-arm naturalistic study provides preliminary support for further RCT studies examining the involvement of reward learning mechanisms underlying app-based mindfulness training for smoking cessation.

Mindfulness-based interventions among people of color: A systematic review and meta-analysis.

Objective In the United States, people of color (POC) are disproportionately affected by various sources of stress and prevalent mental and physical health issues that may benefit from Mindfulness-based Interventions (MBIs). However, effects of MBIs for POC are unclear. This meta-analysis examines the efficacy of MBIs through randomized controlled trials (RCTs) that included predominately POC (≥75% of the sample). Method: Random effects models were used to synthesize effect sizes. A total of 24 RCT samples were analyzed. Results: Samples were on average 94.4% POC and predominantly from low-income backgrounds (total N = 2,156). At post-treatment, MBIs yielded small but statistically superior outcomes to active controls (Hedges' g = 0.11) and inactive controls (g = 0.26). Compared to active controls, MBIs' effects on well-being were smaller than their effects on other outcome types. Compared to inactive controls, MBIs that focused on non-clinical populations and had higher proportion of POC had larger effect sizes. Attrition rates of MBIs did not differ from other active conditions in outpatient settings. Conclusion: Findings provide modest, preliminary empirical support for MBIs among POC. We discuss main findings, limitations, and implications for future MBI research for health promotion among POC.

Clinical Efficacy and Psychological Mechanisms of an App-Based Digital Therapeutic for Generalized Anxiety Disorder: Randomized Controlled Trial.

BACKGROUND: Current treatments for generalized anxiety disorder (GAD) often yield suboptimal outcomes, partly because of insufficient targeting of underlying psychological mechanisms (eg, avoidance reinforcement learning). Mindfulness training (MT) has shown efficacy for anxiety; yet, widespread adoption has been limited, partly because of the difficulty in scaling in-person-based delivery. Digital therapeutics are emerging as potentially viable treatments; however, very few have been empirically validated. OBJECTIVE: The aim of this study is to test the efficacy and mechanism of an app-delivered MT that was designed to target a potential mechanism of anxiety (reinforcement learning), based on which previous studies have shown concern regarding feedback and the perpetuation of anxiety through negative reinforcement. METHODS: Individuals with GAD were recruited using social media advertisements and randomized during an in-person visit to receive treatment as usual (n=33) or treatment as usual+app-delivered MT (Unwinding Anxiety; n=32). The latter was composed of 30 modules to be completed over a 2-month period. Associated changes in outcomes were assessed using self-report questionnaires 1 and 2 months after treatment initiation. RESULTS: We randomized 65 participants in this study, and a modified intent-to-treat approach was used for analysis. The median number of modules completed by the MT group was 25.5 (IQR 17) out of 30; 46% (13/28) of the participants completed the program. In addition, the MT group demonstrated a significant reduction in anxiety (GAD-7) compared with the control group at 2 months (67% vs 14%; median change in GAD-7: -8.5 [IQR 6.5] vs -1.0 [IQR 5.0]; P<.001; 95% CI 6-10). Increases in mindfulness at 1 month (nonreactivity subscale) mediated decreases in worry at 2 months (Penn State Worry Questionnaire; P=.02) and decreases in worry at 1 month mediated reductions in anxiety at 2 months (P=.03). CONCLUSIONS: To our knowledge, this is the first report on the efficacy and mechanism of an app-delivered MT for GAD. These findings demonstrate the clinical efficacy of MT as a digital therapeutic for individuals with anxiety (number needed to treat=1.6). These results also link recent advances in our mechanistic understanding of anxiety with treatment development, showing that app-delivered MT targets key reinforcement learning pathways, resulting in tangible, clinically meaningful reductions in worry and anxiety. Evidence-based, mechanistically targeted digital therapeutics have the potential to improve health at a population level at a low cost. TRIAL REGISTRATION: ClinicalTrials.gov NCT03683472; https://clinicaltrials.gov/ct2/show/NCT03683472.

Craving to Quit: A Randomized Controlled Trial of Smartphone App-Based Mindfulness Training for Smoking Cessation.

INTRODUCTION: Mindfulness training may reduce smoking rates and lessen the association between craving and smoking. This trial tested the efficacy of mindfulness training via smartphone app to reduce smoking. Experience sampling (ES) was used to measure real-time craving, smoking, and mindfulness. METHODS: A researcher-blind, parallel randomized controlled trial compared the efficacy of mobile mindfulness training with experience sampling (MMT-ES; Craving to Quit) versus experience sampling only (ES) to (1) increase 1-week point-prevalence abstinence rates at 6 months, and (2) lessen the association between craving and smoking. A modified intent-to-treat approach was used for treatment starters (MMT-ES n = 143; ES n = 182; 72% female, 81% white, age 41 ± 12 year). RESULTS: No group difference was found in smoking abstinence at 6 months (overall, 11.1%; MMT-ES, 9.8%; ES, 12.1%; χ2(1) = 0.43, p = .51). From baseline to 6 months, both groups showed a reduction in cigarettes per day (p < .0001), craving strength (p < .0001) and frequency (p < .0001), and an increase in mindfulness (p < .05). Using ES data, a craving by group interaction was observed (F(1,3785) = 3.71, p = .05) driven by a stronger positive association between craving and cigarettes per day for ES (t = 4.96, p < .0001) versus MMT-ES (t = 2.03, p = .04). Within MMT-ES, the relationship between craving and cigarettes per day decreased as treatment completion increased (F(1,104) = 4.44, p = .04). CONCLUSIONS: Although mindfulness training via smartphone app did not lead to reduced smoking rates compared with control, our findings provide preliminary evidence that mindfulness training via smartphone app may help lessen the association between craving and smoking, an effect that may be meaningful to support quitting in the longer term. IMPLICATIONS: This is the first reported full-scale randomized controlled trial of any smartphone app for smoking cessation. Findings provide preliminary evidence that smartphone app-based MMT-ES may lessen the association between craving and smoking. TRIAL REGISTRATION: Clinicaltrials.gov NCT02134509.

Mapping complex mind states: EEG neural substrates of meditative unified compassionate awareness.

Specific mental training cultivates diminished self-reference, encompassing non-duality, emptiness, awakened-awareness, and compassionate experiences. We aimed to elucidate the neural substrates of four distinct, interdependent Essence-of-Mind states: (1) timelessness, (2) non-preference, non-duality, non-conceptualization, (3) the view of luminosity and limitlessness, (4) unified compassionate experience of oneness (stable awakened-awareness). EEG data were collected from 30 advanced meditators concomitant to eyes-open/eyes-closed resting baseline, followed by 60-min of instructed practice. Alpha, beta, and gamma, frequency-spatial EEG-dimensions were analyzed. The results revealed that compared to baseline, current density across frequencies significantly decreased upon meditation onset in self-referential, and executive-control regions. During meditation, gamma-band current density significantly increased from state-1 compared to state-4, within the ACC, precuneus, and superior parietal lobule, whereas beta-band activity increased within the insula. These findings suggest a dissociation between brain regions regulating self-referential vs. executive-control processing, during non-dual, compassionate states, characterized by brilliantly awake awareness, free from conceptual thought and "doing".

Testing a mobile mindful eating intervention targeting craving-related eating: feasibility and proof of concept.

Theoretically driven smartphone-delivered behavioral interventions that target mechanisms underlying eating behavior are lacking. In this study, we administered a 28-day self-paced smartphone-delivered intervention rooted in an operant conditioning theoretical framework that targets craving-related eating using mindful eating practices. At pre-intervention and 1-month post-intervention, we assessed food cravings among adult overweight or obese women (N = 104; M age = 46.2 ± 14.1 years; M BMI = 31.5 ± 4.5) using ecological momentary assessment via text message (SMS), self-reported eating behavior (e.g., trait food craving), and in-person weight. Seventy-eight participants (75.0%) completed the intervention within 7 months ('all completers'), and of these, 64 completed the intervention within 3 months ('timely completers'). Participants experienced significant reductions in craving-related eating (40.21% reduction; p < .001) and self-reported overeating behavior (trait food craving, p < .001; other measures ps < .01). Reductions in trait food craving were significantly correlated with weight loss for timely completers (r = .30, p = .020), this pattern of results was also evident in all completers (r = .22, p = .065). Taken together, results suggest that smartphone-delivered mindful eating training targeting craving-related eating may (1) target behavior that impacts a relative metabolic pathway, and (2) represent a low-burden and highly disseminable method to reduce problematic overeating among overweight individuals. ClinicalTrials.gov registration: NCT02694731.

Neural stress reactivity relates to smoking outcomes and differentiates between mindfulness and cognitive-behavioral treatments.

Stress and negative affect are known contributors to drug use and relapse, and several known treatments for addictions include strategies for managing them. In the current study, we administered a well-established stress provocation during functional magnetic resonance imaging (fMRI) to 23 participants who completed either mindfulness training (MT; N=11) or the American Lung Association's Freedom From Smoking (FFS; N=12), which is a cognitive-behavioral treatment (CBT) for smoking cessation. Across the entire sample, we found that stress reactivity in several brain regions including the amygdala and anterior/mid insula was related to reductions in smoking after treatment, as well as at 3-month post-treatment follow-up. Moreover, conjunction analysis revealed that these same regions also differentiated between treatment groups such that the MT group showed lower stress-reactivity compared to the FFS/CBT group. This suggests that reduction in stress reactivity may be one of the mechanisms that underlie the efficacy of MT in reducing smoking over time. The findings have important implications for our understanding of stress, the neural and psychological mechanisms that underlie mindfulness-based treatments, and for smoking cessation treatments more broadly.

Source-space EEG neurofeedback links subjective experience with brain activity during effortless awareness meditation.

BACKGROUND: Meditation is increasingly showing beneficial effects for psychiatric disorders. However, learning to meditate is not straightforward as there are no easily discernible outward signs of performance and thus no direct feedback is possible. As meditation has been found to correlate with posterior cingulate cortex (PCC) activity, we tested whether source-space EEG neurofeedback from the PCC followed the subjective experience of effortless awareness (a major component of meditation), and whether participants could volitionally control the signal. METHODS: Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators were briefly trained to perform a basic meditation practice to induce the subjective experience of effortless awareness in a progressively more challenging neurofeedback test-battery. Experienced meditators performed a self-selected meditation practice to induce this state in the same test-battery. Neurofeedback was provided based on gamma-band (40-57Hz) PCC activity extracted using a beamformer algorithm. Associations between PCC activity and the subjective experience of effortless awareness were assessed by verbal probes. RESULTS: Both groups reported that decreased PCC activity corresponded with effortless awareness (P<0.0025 for each group), with high median confidence ratings (novices: 8 on a 0-10 Likert scale; experienced: 9). Both groups showed high moment-to-moment median correspondence ratings between PCC activity and subjective experience of effortless awareness (novices: 8, experienced: 9). Both groups were able to volitionally control the PCC signal in the direction associated with effortless awareness by practicing effortless awareness meditation (novices: median % of time=77.97, P=0.001; experienced: 89.83, P<0.0005). CONCLUSIONS: These findings support the feasibility of using EEG neurofeedback to link an objective measure of brain activity with the subjective experience of effortless awareness, and suggest potential utility of this paradigm as a tool for meditation training.

Meditation leads to reduced default mode network activity beyond an active task.

Meditation has been associated with relatively reduced activity in the default mode network, a brain network implicated in self-related thinking and mind wandering. However, previous imaging studies have typically compared meditation to rest, despite other studies having reported differences in brain activation patterns between meditators and controls at rest. Moreover, rest is associated with a range of brain activation patterns across individuals that has only recently begun to be better characterized. Therefore, in this study we compared meditation to another active cognitive task, both to replicate the findings that meditation is associated with relatively reduced default mode network activity and to extend these findings by testing whether default mode activity was reduced during meditation, beyond the typical reductions observed during effortful tasks. In addition, prior studies had used small groups, whereas in the present study we tested these hypotheses in a larger group. The results indicated that meditation is associated with reduced activations in the default mode network, relative to an active task, for meditators as compared to controls. Regions of the default mode network showing a Group × Task interaction included the posterior cingulate/precuneus and anterior cingulate cortex. These findings replicate and extend prior work indicating that the suppression of default mode processing may represent a central neural process in long-term meditation, and they suggest that meditation leads to relatively reduced default mode processing beyond that observed during another active cognitive task.

A randomized controlled trial of smartphone-based mindfulness training for smoking cessation: a study protocol.

BACKGROUND: Tobacco use is responsible for the death of about 1 in 10 individuals worldwide. Mindfulness training has shown preliminary efficacy as a behavioral treatment for smoking cessation. Recent advances in mobile health suggest advantages to smartphone-based smoking cessation treatment including smartphone-based mindfulness training. This study evaluates the efficacy of a smartphone app-based mindfulness training program for improving smoking cessation rates at 6-months follow-up. METHODS/DESIGN: A two-group parallel-randomized clinical trial with allocation concealment will be conducted. Group assignment will be concealed from study researchers through to follow-up. The study will be conducted by smartphone and online. Daily smokers who are interested in quitting smoking and own a smartphone (n = 140) will be recruited through study advertisements posted online. After completion of a baseline survey, participants will be allocated randomly to the control or intervention group. Participants in both groups will receive a 22-day smartphone-based treatment program for smoking. Participants in the intervention group will receive mobile mindfulness training plus experience sampling. Participants in the control group will receive experience sampling-only. The primary outcome measure will be one-week point prevalence abstinence from smoking (at 6-months follow-up) assessed using carbon monoxide breath monitoring, which will be validated through smartphone-based video chat. DISCUSSION: This is the first intervention study to evaluate smartphone-based delivery of mindfulness training for smoking cessation. Such an intervention may provide treatment in-hand, in real-world contexts, to help individuals quit smoking. TRIAL REGISTRATION: Clinicaltrials.gov NCT02134509 . Registered 7 May 2014.

Mindfulness and Cardiovascular Disease Risk: State of the Evidence, Plausible Mechanisms, and Theoretical Framework.

The purpose of this review is to provide (1) a synopsis on relations of mindfulness with cardiovascular disease (CVD) and major CVD risk factors, and (2) an initial consensus-based overview of mechanisms and theoretical framework by which mindfulness might influence CVD. Initial evidence, often of limited methodological quality, suggests possible impacts of mindfulness on CVD risk factors including physical activity, smoking, diet, obesity, blood pressure, and diabetes regulation. Plausible mechanisms include (1) improved attention control (e.g., ability to hold attention on experiences related to CVD risk, such as smoking, diet, physical activity, and medication adherence), (2) emotion regulation (e.g., improved stress response, self-efficacy, and skills to manage craving for cigarettes, palatable foods, and sedentary activities), and (3) self-awareness (e.g., self-referential processing and awareness of physical sensations due to CVD risk factors). Understanding mechanisms and theoretical framework should improve etiologic knowledge, providing customized mindfulness intervention targets that could enable greater mindfulness intervention efficacy.

Meditation experience is associated with differences in default mode network activity and connectivity.

Many philosophical and contemplative traditions teach that "living in the moment" increases happiness. However, the default mode of humans appears to be that of mind-wandering, which correlates with unhappiness, and with activation in a network of brain areas associated with self-referential processing. We investigated brain activity in experienced meditators and matched meditation-naive controls as they performed several different meditations (Concentration, Loving-Kindness, Choiceless Awareness). We found that the main nodes of the default-mode network (medial prefrontal and posterior cingulate cortices) were relatively deactivated in experienced meditators across all meditation types. Furthermore, functional connectivity analysis revealed stronger coupling in experienced meditators between the posterior cingulate, dorsal anterior cingulate, and dorsolateral prefrontal cortices (regions previously implicated in self-monitoring and cognitive control), both at baseline and during meditation. Our findings demonstrate differences in the default-mode network that are consistent with decreased mind-wandering. As such, these provide a unique understanding of possible neural mechanisms of meditation.

Finding the right match: mindfulness training may potentiate the therapeutic effect of nonjudgment of inner experience on smoking cessation.

Mindfulness training (MT) is an emerging therapeutic modality for addictive disorders. Nonjudgment of inner experience, a component of mindfulness, may influence addiction treatment response. To test whether this component influences smoking cessation, tobacco smokers (n = 85) in a randomized control trial of MT vs. Freedom from Smoking (FFS), a standard cognitive-behaviorally-oriented treatment, were divided into split-half subgroups based on baseline Five Facet Mindfulness Questionnaire nonjudgment subscale. Smokers who rarely judge inner experience (nonjudgment > 30.5) smoked less during follow-up when randomized to MT (3.9 cigs/d) vs. FFS (11.1 cigs/d), p < .01. Measuring trait nonjudgment may help personalize treatment assignments, improving outcomes.

Smartband-based smoking detection and real-time brief mindfulness intervention: findings from a feasibility clinical trial.

BACKGROUND: Smartbands can be used to detect cigarette smoking and deliver real time smoking interventions. Brief mindfulness interventions have been found to reduce smoking. OBJECTIVE: This single arm feasibility trial used a smartband to detect smoking and deliver brief mindfulness exercises. METHODS: Daily smokers who were motivated to reduce their smoking wore a smartband for 60 days. For 21 days, the smartband monitored, detected and notified the user of smoking in real time. After 21 days, a 'mindful smoking' exercise was triggered by detected smoking. After 28 days, a 'RAIN' (recognize, allow, investigate, nonidentify) exercise was delivered to predicted smoking. Participants received mindfulness exercises by text message and online mindfulness training. Feasibility measures included treatment fidelity, adherence and acceptability. RESULTS: Participants (N=155) were 54% female, 76% white non-Hispanic, and treatment starters (n=115) were analyzed. Treatment fidelity cutoffs were met, including for detecting smoking and delivering mindfulness exercises. Adherence was mixed, including moderate smartband use and low completion of mindfulness exercises. Acceptability was mixed, including high helpfulness ratings and mixed user experiences data. Retention of treatment starters was high (81.9%). CONCLUSIONS: Findings demonstrate the feasibility of using a smartband to track smoking and deliver quit smoking interventions contingent on smoking.

Optimizing the Implementation of a Lifestyle Dementia Prevention Intervention for Older Patients in an Academic Healthcare System.

Background: Interventions that promote healthy lifestyles are critical for the prevention of Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD). However, knowledge of the best practices for implementing AD/ADRD prevention in healthcare settings remains limited. Objective: We aimed to qualitatively identify barriers and facilitators to implementing a clinical trial of a novel lifestyle intervention (My Healthy Brain) in our medical center for older patients with subjective cognitive decline who are at-risk for AD/ADRD. Methods: We conducted focus groups with 26 healthcare professionals (e.g., physicians, psychology, nursing) from 5 clinics that treat older patients (e.g., memory care, psychiatry). Our qualitative analysis integrated two implementation frameworks to systematically capture barriers and facilitators to AD/ADRD prevention (Consolidated Framework for Implementation Science Research) that impact implementation outcomes of acceptability, appropriateness, and feasibility (Proctor's framework). Results: We found widespread support for an RCT of My Healthy Brain and AD/ADRD prevention. Participants identified barriers related to patients (stigma, technological skills), providers (dismissiveness of "worried well," doubting capacity for behavior change), clinics (limited time and resources), and the larger healthcare system (underemphasis on prevention). Implementation strategies guided by Expert Recommendations for Implementing Change (ERIC) included: developing tailored materials, training staff, obtaining buy-in from leadership, addressing stigmatized language and practices, identifying "champions," and integrating with workflows and resources. Conclusions: The results will inform our recruitment, enrollment, and retention procedures to implement the first randomized clinical trial of My Healthy Brain. Our study provides a blueprint for addressing multi-level barriers to the implementation of AD/ADRD prevention for older patients in medical settings.

Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review.

Importance: In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers. Objective: To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts. Evidence Review: The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders. Findings: There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes. Conclusions and Relevance: Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.

Real-time fMRI links subjective experience with brain activity during focused attention.

Recent advances in brain imaging have improved the measure of neural processes related to perceptual, cognitive and affective functions, yet the relation between brain activity and subjective experience remains poorly characterized. In part, it is a challenge to obtain reliable accounts of participant's experience in such studies. Here we addressed this limitation by utilizing experienced meditators who are expert in introspection. We tested a novel method to link objective and subjective data, using real-time fMRI (rt-fMRI) to provide participants with feedback of their own brain activity during an ongoing task. We provided real-time feedback during a focused attention task from the posterior cingulate cortex, a hub of the default mode network shown to be activated during mind-wandering and deactivated during meditation. In a first experiment, both meditators and non-meditators reported significant correspondence between the feedback graph and their subjective experience of focused attention and mind-wandering. When instructed to volitionally decrease the feedback graph, meditators, but not non-meditators, showed significant deactivation of the posterior cingulate cortex. We were able to replicate these results in a separate group of meditators using a novel step-wise rt-fMRI discovery protocol in which participants were not provided with prior knowledge of the expected relationship between their experience and the feedback graph (i.e., focused attention versus mind-wandering). These findings support the feasibility of using rt-fMRI to link objective measures of brain activity with reports of ongoing subjective experience in cognitive neuroscience research, and demonstrate the generalization of expertise in introspective awareness to novel contexts.

Cluster-based psychological phenotyping and differences in anxiety treatment outcomes.

The identification of markers of mental health illness treatment response and susceptibility using personalized medicine has been elusive. In the context of psychological treatment for anxiety, we conducted two studies to identify psychological phenotypes with distinct characteristics related to: psychological intervention modalities (mindfulness training/awareness), mechanism of action (worry), and clinical outcome (generalized anxiety disorder scale scores). We also examined whether phenotype membership interacted with treatment response (Study 1) and mental health illness diagnosis (Studies 1-2). Interoceptive awareness, emotional reactivity, worry, and anxiety were assessed at baseline in treatment-seeking individuals (Study 1, n = 63) and from the general population (Study 2, n = 14,010). In Study 1, participants were randomly assigned to an app-delivered mindfulness program for anxiety for two months or treatment as usual. Changes in anxiety were assessed 1 and 2 months post-treatment initiation. In studies 1-2, three phenotypes were identified: 'severely anxious with body/emotional awareness' (cluster 1), 'body/emotionally unaware' (cluster 2), and 'non-reactive and aware' (cluster 3). Study 1's results revealed a significant treatment response relative to controls (ps < 0.001) for clusters 1 and 3, but not for cluster 2. Chi-square analyses revealed that phenotypes exhibited significantly different proportions of participants with mental health diagnoses (studies 1-2). These results suggest that psychological phenotyping can bring the application of personalized medicine into clinical settings.Registry name and URL: Developing a novel digital therapeutic for the treatment of generalized anxiety disorder https://clinicaltrials.gov/ct2/show/NCT03683472?term=judson+brewer&draw=1&rank=1 .Trial registration: Registered at clinicaltrials.gov (NCT03683472) on 25/09/2018.

App-Delivered Mindfulness Training to Reduce Anxiety in People with HIV Who Smoke: A One-Armed Feasibility Trial.

INTRODUCTION: People with HIV (PWH) who smoke have reported that managing anxiety is a barrier to making a quit attempt and maintaining abstinence post-quit. This study examined the feasibility and acceptability of an app-based mindfulness intervention, Unwinding Anxiety, to reduce anxiety prior to a quit attempt in PWH who were not planning to quit in the next 30 days. METHODS: Sixteen PWH (mean age 51.5 [SD = 13.2]; mean cigarettes per day 11.4 [SD = 5.4]) were enrolled and followed for eight weeks. A smartphone-based app with 30 modules designed to reduce anxiety was introduced at baseline; participants were encouraged to complete one module daily for four weeks. Symptoms of anxiety and readiness to quit smoking were measured at baseline and weeks 4 and 8. The mean number of modules completed, session attendance, and number of study completers were examined. Generalized estimating equations (GEE) were used to examine changes in self-reported anxiety and readiness to quit at baseline, week 4, and week 8. A brief qualitative interview was conducted at week 4 to explore the acceptability of the app. RESULTS: Feasibility was high, with 93% of participants completing the study. The mean number of study sessions completed was 2.7 (SD = 0.59), and the mean number of modules completed was 16.0 (SD 16.8). Anxiety was high at baseline (M = 14.4, SD = 3.9), but lower at week 4 (b = -5.5; CI: [-9.4, -1.7]; p = 0.004) and week 8 (b = -5.1; CI: [-8.8, -1.3]; p = 0.008), and stable between weeks 4 and 8 (b = 0.48; CI: [-2.0, 3.0]; p = 0.706). Readiness to quit significantly increased from baseline M = 5.5 (SD = 1.6) to week 4 (b = 0.56; CI: [0.20, 0.91]; p = 0.002) but was not significantly different from baseline at week 8 (b = 0.34; CI: [-0.30, 1.0]; p = 0.30). Ad-hoc moderation analyses found that anxiety had a small significantly positive association with readiness to quit at baseline (main effect: b = 0.10; SE = 0.03; p < 0.001) and significantly attenuated the increase in readiness to quit observed at week 4 (anxiety by week 4 interaction: b = -0.08; SE = 0.03; p = 0.009). CONCLUSIONS: App-based mindfulness training appears to be feasible and acceptable for PWH who smoke and report baseline anxiety. At week 4, anxiety was reduced and readiness to quit was increased, perhaps a key time point for a smoking cessation attempt.