Emily G. Lattie

IntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety

Background Digital mental health tools have tended to use psychoeducational strategies based on treatment orientations developed and validated outside of digital health. These features do not map well to the brief but frequent ways that people use mobile phones and mobile phone apps today. To address these challenges, we developed a suite of apps for depression and anxiety called IntelliCare, each developed with a focused goal and interactional style. IntelliCare apps prioritize interactive skills training over education and are designed for frequent but short interactions. Objective The overall objective of this study was to pilot a coach-assisted version of IntelliCare and evaluate its use and efficacy at reducing symptoms of depression and anxiety. Methods Participants, recruited through a health care system, Web-based and community advertising, and clinical research registries, were included in this single-arm trial if they had elevated symptoms of depression or anxiety. Participants had access to the 14 IntelliCare apps from Google Play and received 8 weeks of coaching on the use of IntelliCare. Coaching included an initial phone call plus 2 or more texts per week over the 8 weeks, with some participants receiving an additional brief phone call. Primary outcomes included the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder-7 (GAD-7) for anxiety. Participants were compensated up to US

Stress management skills, neuroimmune processes and fatigue levels in persons with chronic fatigue syndrome

90 for completing all assessments; compensation was not for app use or treatment engagement. Results Of the 99 participants who initiated treatment, 90.1% (90/99) completed 8 weeks. Participants showed substantial reductions in the PHQ-9 and GAD-7 (P<.001). Participants used the apps an average of 195.4 (SD 141) times over the 8 weeks. The average length of use was 1.1 (SD 2.1) minutes, and 95% of participants downloaded 5 or more of the IntelliCare apps. Conclusions This study supports the IntelliCare framework of providing a suite of skills-focused apps that can be used frequently and briefly to reduce symptoms of depression and anxiety. The IntelliCare system is elemental, allowing individual apps to be used or not used based on their effectiveness and utility, and it is eclectic, viewing treatment strategies as elements that can be applied as needed rather than adhering to a singular, overarching, theoretical model. Trial Registration Clinicaltrials.gov NCT02176226; http://clinicaltrials.gov/ct2/show/NCT02176226 (Archived by WebCite at http://www.webcitation/6mQZuBGk1)

The relationship between mobile phone location sensor data and depressive symptom severity

OBJECTIVES Stressors and emotional distress responses impact chronic fatigue syndrome (CFS) symptoms, including fatigue. Having better stress management skills might mitigate fatigue by decreasing emotional distress. Because CFS patients comprise a heterogeneous population, we hypothesized that the role of stress management skills in decreasing fatigue may be most pronounced in the subgroup manifesting the greatest neuroimmune dysfunction. METHODS In total, 117 individuals with CFS provided blood and saliva samples, and self-report measures of emotional distress, perceived stress management skills (PSMS), and fatigue. Plasma interleukin-1-beta (IL-1β, IL-2, IL-6, IL-10, and tumor necrosis factor-alpha (TNF-α), and diurnal salivary cortisol were analyzed. We examined relations among PSMS, emotional distress, and fatigue in CFS patients who did and did not evidence neuroimmune abnormalities. RESULTS Having greater PSMS related to less fatigue (p=.019) and emotional distress (p<.001), greater diurnal cortisol slope (p=.023) and lower IL-2 levels (p=.043). PSMS and emotional distress related to fatigue levels most strongly in CFS patients in the top tercile of IL-6, and emotional distress mediated the relationship between PSMS and fatigue most strongly in patients with the greatest circulating levels of IL-6 and a greater inflammatory (IL-6):anti-inflammatory (IL-10) cytokine ratio. DISCUSSION CFS patients having greater PSMS show less emotional distress and fatigue, and the influence of stress management skills on distress and fatigue appear greatest among patients who have elevated IL-6 levels. These findings support the need for research examining the impact of stress management interventions in subgroups of CFS patients showing neuroimmune dysfunction.

Stress management skills, cortisol awakening response, and post-exertional malaise in Chronic Fatigue Syndrome.

Background Smartphones offer the hope that depression can be detected using passively collected data from the phone sensors. The aim of this study was to replicate and extend previous work using geographic location (GPS) sensors to identify depressive symptom severity. Methods We used a dataset collected from 48 college students over a 10-week period, which included GPS phone sensor data and the Patient Health Questionnaire 9-item (PHQ-9) to evaluate depressive symptom severity at baseline and end-of-study. GPS features were calculated over the entire study, for weekdays and weekends, and in 2-week blocks. Results The results of this study replicated our previous findings that a number of GPS features, including location variance, entropy, and circadian movement, were significantly correlated with PHQ-9 scores (r’s ranging from −0.43 to −0.46, p-values < .05). We also found that these relationships were stronger when GPS features were calculated from weekend, compared to weekday, data. Although the correlation between baseline PHQ-9 scores with 2-week GPS features diminished as we moved further from baseline, correlations with the end-of-study scores remained significant regardless of the time point used to calculate the features. Discussion Our findings were consistent with past research demonstrating that GPS features may be an important and reliable predictor of depressive symptom severity. The varying strength of these relationships on weekends and weekdays suggests the role of weekend/weekday as a moderating variable. The finding that GPS features predict depressive symptom severity up to 10 weeks prior to assessment suggests that GPS features may have the potential as early warning signals of depression.

Uptake and Usage of IntelliCare: A Publicly Available Suite of Mental Health and Well-Being Apps.

Chronic Fatigue Syndrome (CFS) is characterized in part by debilitating fatigue typically exacerbated by cognitive and/or physical exertion, referred to as post-exertional malaise (PEM). In a variety of populations, the cortisol awakening response (CAR) has stood out as a marker of endocrine dysregulation relevant to the experience of fatigue, and may therefore be particularly relevant in CFS. This is the first study to examine PEM and the CAR in a sample of individuals with CFS. The CAR has also been established as a stress-sensitive measure of HPA axis functioning. It follows that better management of stress could modulate the CAR, and in turn PEM. In this cross-sectional study, we hypothesized that greater Perceived Stress Management Skills (PSMS) would relate to lower reports of PEM, via the impact of PSMS on the CAR. A total of 117 adults (72% female) with a CFS diagnosis completed self-report measures of PSMS and PEM symptomatology and a two-day protocol of saliva collection. Cortisol values from awakening and 30 min post-awakening were used to compute the CAR. Regression analyses revealed that greater PSMS related to greater CAR and greater CAR related to less PEM severity. Bootstrapped analyses revealed an indirect effect of PSMS on PEM via the CAR, such that greater PSMS related to less PEM, via a greater CAR. Future research should examine these trends longitudinally and whether interventions directed at improving stress management skills are accompanied by improved cortisol regulation and less PEM in individuals with CFS.

Translation of the Diabetes Prevention Program to Ethnic Communities in the United States

Background Treatments for depression and anxiety have several behavioral and psychological targets and rely on varied strategies. Digital mental health treatments often employ feature-rich approaches addressing several targets and strategies. These treatments, often optimized for desktop computer use, are at odds with the ways people use smartphone applications. Smartphone use tends to focus on singular functions with easy navigation to desired tools. The IntelliCare suite of apps was developed to address the discrepancy between need for diverse behavioral strategies and constraints imposed by typical app use. Each app focuses on one strategy for a limited subset of clinical aims all pertinent to depression and anxiety. This study presents the uptake and usage of apps from the IntelliCare suite following an open deployment on a large app marketplace. Methods Thirteen lightweight apps, including 12 interactive apps and one Hub app that coordinates use across those interactive apps, were developed and made free to download on the Google Play store. De-identified app usage data from the first year of IntelliCare suite deployment were analyzed for this study. Results In the first year of public availability, 5210 individuals downloaded one or more of the IntelliCare apps, for a total of 10,131 downloads. Nearly a third of these individuals (31.8%) downloaded more than one of these apps. The modal number of launches for each of the apps was 1, however the mean number of app launches per app ranged from 3.10 to 16.98, reflecting considerable variability in the use of each app. Conclusions The use rate of the IntelliCare suite of apps is higher than public deployments of other comparable digital resources. Our findings suggest that people will use multiple apps and provides support for the concept of app suites as a useful strategy for providing diverse behavioral strategies.

Accelerating digital mental health research from early design and creation to successful implementation and sustainment

The Diabetes Prevention Program (DPP), an evidenced-based lifestyle intervention for type 2 diabetes (T2D), has been translated for use with ethnic minority communities throughout the United States that are disproportionately at-risk for T2D. The present paper sought to critically review ethnic translation studies of the DPP with respect to translation methods utilized, the success of these methods, and alternative or supplemental methodologies for future translation efforts. Manuscripts reviewed were found by searching PubMed and PsycINFO, using the terms: “diabetes prevention program” AND [“translation” or “ethnic”]. Of 89 papers found, only 6 described ethnic translations of the DPP in the United States, and were included in this review. Translations of the DPP to African American, Hispanic/Latino, Native Hawaiian and Other Pacific Islander, Arab American, and American Indian and Native Alaskan communities were identified and reviewed. The most common translation strategies included group-based delivery and use of bilingual study personnel. Generally, these factors appeared to increase acceptability of the intervention within the ethnic communities reviewed, and should be considered in future efforts to implement and translate the DPP to ethnic communities in the United States.

Millon Behavioral Medicine Diagnostic (MBMD) Predicts Health-Related Quality of Life (HrQoL) Over Time Among Men Treated for Localized Prostate Cancer

Mental health problems are common and pose a tremendous societal burden in terms of cost, morbidity, quality of life, and mortality. The great majority of people experience barriers that prevent access to treatment, aggravated by a lack of mental health specialists. Digital mental health is potentially useful in meeting the treatment needs of large numbers of people. A growing number of efficacy trials have shown strong outcomes for digital mental health treatments. Yet despite their positive findings, there are very few examples of successful implementations and many failures. Although the research-to-practice gap is not unique to digital mental health, the inclusion of technology poses unique challenges. We outline some of the reasons for this gap and propose a collection of methods that can result in sustainable digital mental health interventions. These methods draw from human-computer interaction and implementation science and are integrated into an Accelerated Creation-to-Sustainment (ACTS) model. The ACTS model uses an iterative process that includes 2 basic functions (design and evaluate) across 3 general phases (Create, Trial, and Sustain). The ultimate goal in using the ACTS model is to produce a functioning technology-enabled service (TES) that is sustainable in a real-world treatment setting. We emphasize the importance of the service component because evidence from both research and practice has suggested that human touch is a critical ingredient in the most efficacious and used digital mental health treatments. The Create phase results in at least a minimally viable TES and an implementation blueprint. The Trial phase requires evaluation of both effectiveness and implementation while allowing optimization and continuous quality improvement of the TES and implementation plan. Finally, the Sustainment phase involves the withdrawal of research or donor support, while leaving a functioning, continuously improving TES in place. The ACTS model is a step toward bringing implementation and sustainment into the design and evaluation of TESs, public health into clinical research, research into clinics, and treatment into the lives of our patients.

Poor sleep quality is associated with greater circulating pro-inflammatory cytokines and severity and frequency of chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) symptoms in women

Prostate cancer treatment presents multiple challenges that can negatively affect health-related quality of life (HrQoL), and that can be further compromised by maladaptive personality styles and psychological adjustment difficulties. This study examined the utility of a comprehensive psychosocial screening tool to identify psychosocial traits that prospectively predict HrQoL status among men treated for localized prostate cancer. The Millon Behavioral Medicine Diagnostic (MBMD) was administered to 66 men (M age = 68 years, 59% White) treated by either radical prostatectomy or radiotherapy along with standard measures of general and prostate-cancer-specific quality of life assessed at a 12-month follow-up. Higher scores on both summary MBMD Management Guides (Adjustment Difficulties and Psych Referral) and higher scores on personality styles characterized by avoidance, dependency, depression, passive aggressiveness, and self-denigration predicted lower HrQoL (β range = –.21 to –.50). Additionally, higher scores on the MBMD Depression, Tension-Anxiety, and Future Pessimism scales predicted lower HrQoL. Finally, higher scores on the MBMD Intervention Fragility and Utilization Excess scale also consistently predicted poorer mental and physical health functioning over time. These results point to the utility of the MBMD to help screen for potential impairments in mental and physical health functioning in men undergoing treatment for prostate cancer.

Distress, delay of gratification and preference for palliative care in men with prostate cancer.

OBJECTIVE Poor sleep quality has been linked to inflammatory processes and worse disease outcomes in the context of many chronic illnesses, but less is known in conditions such as chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME). This study examines the relationships between sleep quality, pro-inflammatory cytokines, and CFS/ME symptoms. METHODS Sixty women diagnosed with CFS/ME were assessed using the Pittsburgh Sleep Quality Index (PSQI), Fatigue Symptom Inventory (FSI) and Center for Disease Control and Prevention (CDC)-based CFS/ME symptom questionnaires. Circulating plasma pro-inflammatory cytokine levels were measured by ELISA. Multiple regression analyses examined associations between sleep, cytokines and symptoms, controlling for age, education, and body mass index. RESULTS Poor sleep quality (PSQI global score) was associated with greater pro-inflammatory cytokine levels: interleukin-1β (IL-1β) (β=0.258, p=0.043), IL-6 (β=0.281, p=0.033), and tumor necrosis factor-alpha (TNF-α) (β=0.263, p=0.044). Worse sleep quality related to greater fatigue severity (β=0.395, p=0.003) and fatigue-related interference with daily activities (β=0.464, p<0.001), and more severe and frequent CDC-defined core CFS/ME symptoms (β=0.499, p<0.001, and β=0.556, p<0.001, respectively). CONCLUSIONS Results underscore the importance of managing sleep-related difficulties in this patient population. Further research is needed to identify the etiology of sleep disruptions in CFS/ME and mechanistic factors linking sleep quality to symptom severity and inflammatory processes.