Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data

AI tools intend to transform mental healthcare by providing remote estimates of depression risk using behavioral data collected by sensors embedded in smartphones. While these tools accurately predict elevated depression symptoms in small, homogenous populations, recent studies show that these tools are less accurate in larger, more diverse populations. In this work, we show that accuracy is reduced because sensed-behaviors are unreliable predictors of depression across individuals: sensed-behaviors that predict depression risk are inconsistent across demographic and socioeconomic subgroups. We first identified subgroups where a developed AI tool underperformed by measuring algorithmic bias, where subgroups with depression were incorrectly predicted to be at lower risk than healthier subgroups. We then found inconsistencies between sensed-behaviors predictive of depression across these subgroups. Our findings suggest that researchers developing AI tools predicting mental health from sensed-behaviors should think critically about the generalizability of these tools, and consider tailored solutions for targeted populations.

Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health

Digital mental health (DMH) interventions, such as text-message-based lessons and activities, offer immense potential for accessible mental health support. While these interventions can be effective, real-world experimental testing can further enhance their design and impact. Adaptive experimentation, utilizing algorithms like Thompson Sampling for (contextual) multi-armed bandit (MAB) problems, can lead to continuous improvement and personalization. However, it remains unclear when these algorithms can simultaneously increase user experience rewards and facilitate appropriate data collection for social-behavioral scientists to analyze with sufficient statistical confidence. Although a growing body of research addresses the practical and statistical aspects of MAB and other adaptive algorithms, further exploration is needed to assess their impact across diverse real-world contexts. This paper presents a software system developed over two years that allows text-messaging intervention components to be adapted using bandit and other algorithms while collecting data for side-by-side comparison with traditional uniform random non-adaptive experiments. We evaluate the system by deploying a text-message-based DMH intervention to 1100 users, recruited through a large mental health non-profit organization, and share the path forward for deploying this system at scale. This system not only enables applications in mental health but could also serve as a model testbed for adaptive experimentation algorithms in other domains.

Small Steps over time: A longitudinal usability test of an automated interactive text messaging intervention to support self-management of depression and anxiety symptoms

BACKGROUND

Digital mental health interventions (DMHIs) offer potential solutions for addressing mental health care gaps, but often suffer from low engagement. Text messaging is one promising medium for increasing access and sustaining user engagement with DMHIs. This paper examines the Small Steps SMS program, an 8-week, automated, adaptive text message-based intervention for depression and anxiety.

METHODS

We conducted an 8-week longitudinal usability test of the Small Steps SMS program, recruiting 20 participants who met criteria for major depressive disorder and/or generalized anxiety disorder. Participants used the automated intervention for 8 weeks and completed symptom severity and usability self-report surveys after 4 and 8 weeks of intervention use. Participants also completed individual interviews to provide feedback on the intervention.

RESULTS

Participants responded to automated messages on 70 % of study days and with 85 % of participants sending responses to messages in the 8th week of use. Usability surpassed established cutoffs for software that is considered acceptable. Depression symptom severity decreased significantly over the usability test, but reductions in anxiety symptoms were not significant. Participants noted key areas for improvement including addressing message volume, aligning message scheduling to individuals' availability, and increasing the customizability of content.

LIMITATIONS

This study does not contain a control group.

CONCLUSIONS

An 8-week automated interactive text messaging intervention, Small Steps SMS, demonstrates promise with regard to being a feasible, usable, and engaging method to deliver daily mental health support to individuals with symptoms of anxiety and depression.

Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study

While studies show links between smartphone data and affective symptoms, we lack clarity on the temporal scale, specificity (e.g., to depression vs. anxiety), and person-specific (vs. group-level) nature of these associations. We conducted a large-scale (n = 1013) smartphone-based passive sensing study to identify within- and between-person digital markers of depression and anxiety symptoms over time. Participants (74.6% female; M age = 40.9) downloaded the LifeSense app, which facilitated continuous passive data collection (e.g., GPS, app and device use, communication) across 16 weeks. Hierarchical linear regression models tested the within- and between-person associations of 2-week windows of passively sensed data with depression (PHQ-8) or generalized anxiety (GAD-7). We used a shifting window to understand the time scale at which sensed features relate to mental health symptoms, predicting symptoms 2 weeks in the future (distal prediction), 1 week in the future (medial prediction), and 0 weeks in the future (proximal prediction). Spending more time at home relative to one's average was an early signal of PHQ-8 severity (distal β = 0.219, p = 0.012) and continued to relate to PHQ-8 at medial (β = 0.198, p = 0.022) and proximal (β = 0.183, p = 0.045) windows. In contrast, circadian movement was proximally related to (β = -0.131, p = 0.035) but did not predict (distal β = 0.034, p = 0.577; medial β = -0.089, p = 0.138) PHQ-8. Distinct communication features (i.e., call/text or app-based messaging) related to PHQ-8 and GAD-7. Findings have implications for identifying novel treatment targets, personalizing digital mental health interventions, and enhancing traditional patient-provider interactions. Certain features (e.g., circadian movement) may represent correlates but not true prospective indicators of affective symptoms. Conversely, other features like home duration may be such early signals of intra-individual symptom change, indicating the potential utility of prophylactic intervention (e.g., behavioral activation) in response to person-specific increases in these signals.

Specific associations of passively sensed smartphone data with future symptoms of avoidance, fear, and physiological distress in social anxiety

Background

Prior literature links passively sensed information about a person's location, movement, and communication with social anxiety. These findings hold promise for identifying novel treatment targets, informing clinical care, and personalizing digital mental health interventions. However, social anxiety symptoms are heterogeneous; to identify more precise targets and tailor treatments, there is a need for personal sensing studies aimed at understanding differential predictors of the distinct subdomains of social anxiety. Our objective was to conduct a large-scale smartphone-based sensing study of fear, avoidance, and physiological symptoms in the context of trait social anxiety over time.

Methods

Participants (n = 1013; 74.6 % female; M age = 40.9) downloaded the LifeSense app, which collected continuous passive data (e.g., GPS, communication, app and device use) over 16 weeks. We tested a series of multilevel linear regression models to understand within- and between-person associations of 2-week windows of passively sensed smartphone data with fear, avoidance, and physiological distress on the self-reported Social Phobia Inventory (SPIN). A shifting sensor lag was applied to examine how smartphone features related to SPIN subdomains 2 weeks in the future (distal prediction), 1 week in the future (medial prediction), and 0 weeks in the future (proximal prediction).

Results

A decrease in time visiting novel places was a strong between-person predictor of social avoidance over time (distal β = -0.886, p = .002; medial β = -0.647, p = .029; proximal β = -0.818, p = .007). Reductions in call- and text-based communications were associated with social avoidance at both the between- (distal β = -0.882, p = .002; medial β = -0.932, p = .001; proximal β = -0.918, p = .001) and within- (distal β = -0.191, p = .046; medial β = -0.213, p = .028) person levels, as well as between-person fear of social situations (distal β = -0.860, p < .001; medial β = -0.892, p < .001; proximal β = -0.886, p < .001) over time. There were fewer significant associations of sensed data with physiological distress. Across the three subscales, smartphone data explained 9-12 % of the variance in social anxiety.

Conclusion

Findings have implications for understanding how social anxiety manifests in daily life, and for personalizing treatments. For example, a signal that someone is likely to begin avoiding social situations may suggest a need for alternative types of exposure-based interventions compared to a signal that someone is likely to begin experiencing increased physiological distress. Our results suggest that as a prophylactic means of targeting social avoidance, it may be helpful to deploy interventions involving social exposures in response to decreases in time spent visiting novel places.

From formative design to service-ready therapeutic: A pragmatic approach to designing digital mental health interventions across domains

As digital mental health interventions (DMHIs) proliferate, there is a growing need to understand the complexities of moving these tools from concept and design to service-ready products. We highlight five case studies from a center that specializes in the design and evaluation of digital mental health interventions to illustrate pragmatic approaches to the development of digital mental health interventions, and to make transparent some of the key decision points researchers encounter along the design-to-product pipeline. Case studies cover different key points in the design process and focus on partnership building, understanding the problem or opportunity, prototyping the product or service, and testing the product or service. We illustrate lessons learned and offer a series of questions researchers can use to navigate key decision points in the digital mental health intervention (DMHI) development process.

A text messaging intervention to support the mental health of young adults: User engagement and feedback from a field trial of an intervention prototype

Background

Young adults have high rates of mental health conditions, but most do not want or cannot access treatment. By leveraging a medium that young adults routinely use, text messaging programs have potential to keep young adults engaged with content supporting self-management of mental health issues and can be delivered inexpensively at scale. We designed an intervention that imparts strategies for self-managing mental health symptoms through interactive text messaging dialogues and engages users through novelty and variety in strategies (from cognitive behavioral therapy, acceptance and commitment therapy, and positive psychology) and styles of interaction (e.g., prompts, peer stories, writing tasks).

Methods

The aim of this mixed-methods study was to pilot 1- and 2-week versions of an interactive text messaging intervention among young adults (ages 18-25), and to obtain feedback to guide intervention refinements. Young adults were recruited via a mental health advocacy website and snowball sampling at a North American University. We used Wizard-of-Oz methods in which study staff sent messages based on a detailed script. Transcripts of interviews were subject to qualitative analysis to identify aspects of the program that need improvements, and to gather participant perspectives on possible solutions.

Results

Forty-eight individuals ages 18-25 participated in the study (mean age: 22.0). 85 % responded to the program at least once. Among those who ever responded, they replied to messages on 85 % of days, and with engagement sustained over the study period. Participants endorsed the convenience of text messaging, the types of interactive dialogues, and the variety of content. They also identified needed improvements to message volume, scheduling, and content.

Conclusions

Young adults showed high levels of engagement and satisfaction with a texting program supporting mental health self-management. The program may be improved through refining personalization, timing, and message volume, and extending content to support use over a longer timeframe. If shown to be effective in randomized trials, this program has potential to help address a substantial treatment gap in young adults' mental health.

Mental Health Self-Tracking Preferences of Young Adults With Depression and Anxiety Not Engaged in Treatment: Qualitative Analysis

BACKGROUND

Despite the high prevalence of anxiety and depression among young adults, many do not seek formal treatment. Some may turn to digital mental health tools for support instead, including to self-track moods, behaviors, and other variables related to mental health. Researchers have sought to understand processes and motivations involved in self-tracking, but few have considered the specific needs and preferences of young adults who are not engaged in treatment and who seek to use self-tracking to support mental health.

OBJECTIVE

This study seeks to assess the types of experiences young adults not engaged in treatment have had with digital self-tracking for mood and other mental health data and to assess how young adults not seeking treatment want to engage in self-tracking to support their mental health.

METHODS

We conducted 2 online asynchronous discussion groups with 50 young adults aged 18 years to 25 years who were not engaged in treatment. Participants were recruited after indicating moderate to severe symptoms of depression or anxiety on screening surveys hosted on the website of Mental Health America. Participants who enrolled in the study responded anonymously to discussion prompts on a message board, as well as to each other's responses, and 3 coders performed a thematic analysis of their responses.

RESULTS

Participants had mixed experiences with self-tracking in the past, including disliking when tracking highlighted unwanted behaviors and discontinuing tracking for a variety of reasons. They had more positive past experiences tracking behaviors and tasks they wanted to increase, using open-ended journaling, and with gamified elements to increase motivation. Participants highlighted several design considerations they wanted self-tracking tools to address, including building self-understanding; organization, reminders, and structure; and simplifying the self-tracking experience. Participants wanted self-tracking to help them identify their feelings and how their feelings related to other variables like sleep, exercise, and events in their lives. Participants also highlighted self-tracking as useful for motivating and supporting basic activities and tasks of daily living during periods of feeling overwhelmed or low mood and providing a sense of accomplishment and stability. Although self-tracking can be burdensome, participants were interested and provided suggestions for simplifying the process.

CONCLUSIONS

These young adults not engaged in treatment reported interest in using self-tracking to build self-understanding as a goal in and of itself or as a first step in contemplating and preparing for behavior change or treatment-seeking. Alexithymia, amotivation, and feeling overwhelmed may serve both as barriers to self-tracking and opportunities for self-tracking to help.

Analyzing text message linguistic features: Do people with depression communicate differently with their close and non-close contacts?

BACKGROUND

Relatively little is known about how communication changes as a function of depression severity and interpersonal closeness. We examined the linguistic features of outgoing text messages among individuals with depression and their close- and non-close contacts.

METHODS

419 participants were included in this 16-week-long observational study. Participants regularly completed the PHQ-8 and rated subjective closeness to their contacts. Text messages were processed to count frequencies of word usage in the LIWC 2015 libraries. A linear mixed modeling approach was used to estimate linguistic feature scores of outgoing text messages.

RESULTS

Regardless of closeness, people with higher PHQ-8 scores tended to use more differentiation words. When texting with close contacts, individuals with higher PHQ-8 scores used more first-person singular, filler, sexual, anger, and negative emotion words. When texting with non-close contacts these participants used more conjunctions, tentative, and sadness-related words and fewer first-person plural words.

CONCLUSION

Word classes used in text messages, when combined with symptom severity and subjective social closeness data, may be indicative of underlying interpersonal processes. These data may hold promise as potential treatment targets to address interpersonal drivers of depression.

Exploring the Safety of a General Digital Mental Health Intervention to Effect Symptom Reduction among Individuals with and without Suicidal Ideation: A Secondary Analysis

Trials of digital mental health interventions (DMHIs) often exclude individuals with suicide-related thoughts and behaviors precluding an understanding of whether DMHIs for affective disorders are safe for, and perform similarly within, this high-risk group. We explore the safety and performance of a DMHI for depression in participants with and without suicidal ideation (SI) at baseline. Three hundred and one participants were included in this secondary data analysis from a trial of an 8-week DMHI comprising 14 smartphone apps. We found that SI decreased across the study among participants with baseline SI and that baseline SI status did not attenuate depression treatment effects. Through a case study of the IntelliCare platform, we find that DMHIs for general affective disorders can be safe.

Investigating the Role of Context in the Delivery of Text Messages for Supporting Psychological Wellbeing

Without a nuanced understanding of users' perspectives and contexts, text messaging tools for supporting psychological wellbeing risk delivering interventions that are mismatched to users' dynamic needs. We investigated the contextual factors that influence young adults' day-to-day experiences when interacting with such tools. Through interviews and focus group discussions with 36 participants, we identified that people's daily schedules and affective states were dominant factors that shape their messaging preferences. We developed two messaging dialogues centered around these factors, which we deployed to 42 participants to test and extend our initial understanding of users' needs. Across both studies, participants provided diverse opinions of how they could be best supported by messages, particularly around when to engage users in more passive versus active ways. They also proposed ways of adjusting message length and content during periods of low mood. Our findings provide design implications and opportunities for context-aware mental health management systems.

Preparing a Workforce of Care Coordinators to Address Patient Mental Health Needs in the Digital Age: Training and Needs Identification

Introduction

Care coordinators (CCs) are specialized healthcare providers and often the primary point of contact for patients with multiple medical and mental health comorbidities in integrated healthcare settings. Prior work shows CCs have lower comfort addressing mental health than physical health concerns. Digital mental health interventions can support CCs' management of patient mental health needs, but training gaps must be addressed prior to a digital mental health intervention's implementation.

Methods

As part of a quality improvement initiative, a 1-hour training focused on the assessment and management of depression and suicide-related thoughts and behaviors was delivered to CCs within a large midwestern healthcare system's Division of Ambulatory Care Coordination. CCs completed online surveys prior to and following the training.

Conclusion

Training resulted in increased comfort working with clinical populations, including patients who experience suicide-related thoughts and behaviors. Gains around screening for suicide risk were modest. Brief trainings for CCs can address training gaps, however, ongoing training and case consultation may also be indicated.

Prospective associations of text-message-based sentiment with symptoms of depression, generalized anxiety, and social anxiety

OBJECTIVE

Language patterns may elucidate mechanisms of mental health conditions. To inform underlying theory and risk models, we evaluated prospective associations between in vivo text messaging language and differential symptoms of depression, generalized anxiety, and social anxiety.

METHODS

Over 16 weeks, we collected outgoing text messages from 335 adults. Using Linguistic Inquiry and Word Count (LIWC), NRC Emotion Lexicon, and previously established depression and stress dictionaries, we evaluated the degree to which language features predict symptoms of depression, generalized anxiety, or social anxiety the following week using hierarchical linear models. To isolate the specificity of language effects, we also controlled for the effects of the two other symptom types.

RESULTS

We found significant relationships of language features, including personal pronouns, negative emotion, cognitive and biological processes, and informal language, with common mental health conditions, including depression, generalized anxiety, and social anxiety (ps < .05). There was substantial overlap between language features and the three mental health outcomes. However, after controlling for other symptoms in the models, depressive symptoms were uniquely negatively associated with language about anticipation, trust, social processes, and affiliation (βs: -.10 to -.09, ps < .05), whereas generalized anxiety symptoms were positively linked with these same language features (βs: .12-.13, ps < .001). Social anxiety symptoms were uniquely associated with anger, sexual language, and swearing (βs: .12-.13, ps < .05).

CONCLUSION

Language that confers both common (e.g., personal pronouns and negative emotion) and specific (e.g., affiliation, anticipation, trust, and anger) risk for affective disorders is perceptible in prior week text messages, holding promise for understanding cognitive-behavioral mechanisms and tailoring digital interventions.

Social media-based interventions for adolescent and young adult mental health: A scoping review

Background

Mental health conditions are common among adolescents and young adults, yet few receive adequate mental health treatment. Many young people seek support and information online through social media, and report preferences for digital interventions. Thus, digital interventions deployed through social media have promise to reach a population not yet engaged in treatment, and at risk of worsening symptoms.

Objective

In this scoping review, we aimed to identify and review empirical research on social media-based interventions aimed at improving adolescent and young adult mental health. A secondary objective was to identify the features and functionalities of platforms described as social media.

Methods

Adhering to the PRISMA-ScR guidelines for scoping reviews, the search was conducted in PubMed MEDLINE; Embase Central Register of Controlled Trials (Wiley); PsycINFO (Ebsco); Scopus; Web of Science; IEEE Xplore; ACM Digital Library; and ClinicalTrials.gov from inception until November 2021. Studies were included if they involved adolescents or young adults (10-26 years of age) that meet clinical, or subclinical, levels of a mental health condition and include a pre- and post-assessment of mental health outcomes.

Results

Among the 18,380 references identified, 15 met full inclusion criteria and were published between 2017 and 2021-this included four randomized controlled trials, seven non-randomized pre-post trials, and four were experimental or quasi-experimental designs. Just five studies were delivered through an existing social media site (Facebook or Pixtori), with the remainder focused on purpose-built networks. Three studies involved adolescents or young adults who self-reported a mental health condition, seven involved young people diagnosed with a mental health condition by a clinician or who scored above a clinical threshold on valid clinical measure, three involved college students without a mental health inclusion criterion, and two studies focused on young people with a cancer diagnosis.

Conclusions

The review highlights innovations in the delivery of mental health interventions, provides preliminary evidence of the ability of social media interventions to improve mental health outcomes, and underscores the need for, and merit of, future work in this area. We discuss opportunities and challenges for future research, including the potential to leveragei existing peer networks, the use of just-in-time interventions, and scaling interventions to meet need.

"I Kind of Bounce off It": Translating Mental Health Principles into Real Life Through Story-Based Text Messages

Adopting new psychological strategies to improve mental wellness can be challenging since people are often unable to anticipate how new habits are applicable to their circumstances. Narrative-based interventions have the potential to alleviate this burden by illustrating psychological principles in an applied context. In this work, we explore how stories can be delivered via the ubiquitous and scalable medium of text messaging. Through formative work consisting of interviews and focus group discussions with 15 participants, we identified desirable elements of stories about mental health, including authenticity and relatability. We then deployed story-based text messages to 42 participants to explore challenges regarding both the stories' content (e.g., specific versus generalized) and format (e.g., story length). We observed that our stories helped participants reflect on and identify flaws in their thinking patterns. Our findings highlight design implications and opportunities for mental wellness interventions that utilize stories in text messaging services.

Meeting Young Adults' Social Support Needs across the Health Behavior Change Journey: Implications for Digital Mental Health Tools

In pursuit of mental wellness, many find that behavioral change is necessary. This process can often be difficult but is facilitated by strong social support. This paper explores the role of social support across behavioral change journeys among young adults, a group at high risk for mental health challenges, but with the lowest rates of mental health treatment utilization. Given that digital mental health tools are effective for treating mental health conditions, they hold particular promise for bridging the treatment gap among young adults, many of whom, are not interested in - or cannot access - traditional mental healthcare. We recruited a sample of young adults with depression who were seeking information about their symptoms online to participate in an Asynchronous Remote Community (ARC) elicitation workshop. Participants detailed the changing nature of social interactions across their behavior change journeys. They noted that both directed and undirected support are necessary early in behavioral change and certain needs such as informational support are particularly pronounced, while healthy coping partnerships and accountability are more important later in the change process. We discuss the conceptual and design implications of our findings for the next generation of digital mental health tools.

The association of language style matching in text messages with mood and anxiety symptoms

Context

Impairment in social functioning is a feature and consequence of depression and anxiety disorders. For example, in depression, anhedonia and negative feelings about the self may impact relationships; in anxiety, fear of negative evaluation may interfere with getting close to others. It is unknown whether social impairment associated with depression and anxiety symptoms is reflected in day-to-day language exchanges with others, such as through reduced language style matching (LSM).

Methods

Over 16 weeks, we collected text message data from 458 adults and evaluated differences in LSM between people with average scores above/below the clinical cutoff for depression, generalized anxiety, and social anxiety in text message conversations. Text message sentiment scores were computed across 73 Linguistic Inquiry and Word Count (LIWC) categories for each participant. T-tests were used to compare LSM across two groups (average scores above/below clinical cutoff) for each of the 3 diagnostic categories (depression, generalized anxiety, social anxiety), and each of the 73 LIWC categories, with correction for multiple comparisons.

Results

We found reduced LSM of function words (namely, prepositions [t=-2.82, p=.032], articles [t=-5.26, p<.001], and auxiliary verbs [t=-2.64, p=.046]) in people with average scores above the clinical cutoff for generalized anxiety, and reduced LSM of prepositions (t=-4.26, p<.001) and articles (t=-3.39, p=.010) in people with average scores above the clinical cutoff for social anxiety. There were no significant differences in LSM of function words between people with average scores above and below the clinical cutoff for depression. Across all symptom categories, elevated affective psychopathology was associated with being more likely to style match on formality, including netspeak (generalized anxiety, t=5.77, p<.001; social anxiety, t=4.14, p<.001; depression, t=3.13, p=.021) and informal language (generalized anxiety, t=6.65, p<.001; social anxiety, t=5.14, p>.001; depression, t=3.20, p=.020).We also observed content-specific LSM differences across the three groups.

Conclusions

Reduced LSM of function words among patients reporting elevated anxiety symptoms suggests that anxiety-related psychosocial difficulties may be perceptible in subtle cues from day-to-day language. Conversely, the absence of differences in the LSM of function words among people with average scores above and below the clinical cutoff for depression indicates a potentially distinct mechanism of social impairment.

Implications

Results point to potential markers of psychosocial difficulties in daily conversations, particularly among those experiencing heightened anxiety symptoms. Future studies may consider the degree to which LSM is associated with self-reported psychosocial impairment, with the promise of informing cognitive-behavioral mechanisms and tailoring digital interventions for social skills.

System design of a text messaging program to support the mental health needs of non-treatment seeking young adults

Young adults (ages 18-25) experience the highest levels of mental health problems of any adult age group, but have the lowest mental health treatment rates. Text messages are the most used feature on the mobile phone and provide an opportunity to reach non-treatment engaged users throughout the day in a conversational manner. We present the design of an automated text message-based intervention for symptom self-management. The intervention comprises: (1) psychological strategies (i.e., types of evidence-based techniques leveraged to achieve symptom reduction) and (2) interaction types or the form that intervention content takes as it is delivered to and elicited from users.

Involving Crowdworkers with Lived Experience in Content-Development for Push-Based Digital Mental Health Tools: Lessons Learned from Crowdsourcing Mental Health Messages

Digital tools can support individuals managing mental health concerns, but delivering sufficiently engaging content is challenging. This paper seeks to clarify how individuals with mental health concerns can contribute content to improve push-based mental health messaging tools. We recruited crowdworkers with mental health symptoms to evaluate and revise expert-composed content for an automated messaging tool, and to generate new topics and messages. A second wave of crowdworkers evaluated expert and crowdsourced content. Crowdworkers generated topics for messages that had not been prioritized by experts, including self-care, positive thinking, inspiration, relaxation, and reassurance. Peer evaluators rated messages written by experts and peers similarly. Our findings also suggest the importance of personalization, particularly when content adaptation occurs over time as users interact with example messages. These findings demonstrate the potential of crowdsourcing for generating diverse and engaging content for push-based tools, and suggest the need to support users in meaningful content customization.

Meeting Users Where They Are: User-centered Design of an Automated Text Messaging Tool to Support the Mental Health of Young Adults

Young adults have high rates of mental health conditions, but most do not want or cannot access formal treatment. We therefore recruited young adults with depression or anxiety symptoms to co-design a digital tool for self-managing their mental health concerns. Through study activities-consisting of an online discussion group and a series of design workshops-participants highlighted the importance of easy-to-use digital tools that allow them to exercise independence in their self-management. They described ways that an automated messaging tool might benefit them by: facilitating experimentation with diverse concepts and experiences; allowing variable depth of engagement based on preferences, availability, and mood; and collecting feedback to personalize the tool. While participants wanted to feel supported by an automated tool, they cautioned against incorporating an overtly human-like motivational tone. We discuss ways to apply these findings to improve the design and dissemination of digital mental health tools for young adults.

The relationship between text message sentiment and self-reported depression

BACKGROUND

Personal sensing has shown promise for detecting behavioral correlates of depression, but there is little work examining personal sensing of cognitive and affective states. Digital language, particularly through personal text messages, is one source that can measure these markers.

METHODS

We correlated privacy-preserving sentiment analysis of text messages with self-reported depression symptom severity. We enrolled 219 U.S. adults in a 16 week longitudinal observational study. Participants installed a personal sensing app on their phones, which administered self-report PHQ-8 assessments of their depression severity, collected phone sensor data, and computed anonymized language sentiment scores from their text messages. We also trained machine learning models for predicting end-of-study self-reported depression status using on blocks of phone sensor and text features.

RESULTS

In correlation analyses, we find that degrees of depression, emotional, and personal pronoun language categories correlate most strongly with self-reported depression, validating prior literature. Our classification models which predict binary depression status achieve a leave-one-out AUC of 0.72 when only considering text features and 0.76 when combining text with other networked smartphone sensors.

LIMITATIONS

Participants were recruited from a panel that over-represented women, caucasians, and individuals with self-reported depression at baseline. As language use differs across demographic factors, generalizability beyond this population may be limited. The study period also coincided with the initial COVID-19 outbreak in the United States, which may have affected smartphone sensor data quality.

CONCLUSIONS

Effective depression prediction through text message sentiment, especially when combined with other personal sensors, could enable comprehensive mental health monitoring and intervention.

"I Wanted to See How Bad it Was": Online Self-screening as a Critical Transition Point Among Young Adults with Common Mental Health Conditions

Young adults have high rates of mental health conditions, yet they are the age group least likely to seek traditional treatment. They do, however, seek information about their mental health online, including by filling out online mental health screeners. To better understand online self-screening, and its role in help-seeking, we conducted focus groups with 50 young adults who voluntarily completed a mental health screener hosted on an advocacy website. We explored (1) catalysts for taking the screener, (2) anticipated outcomes, (3) reactions to the results, and (4) desired next steps. For many participants, the screener results validated their lived experiences of symptoms, but they were nevertheless unsure how to use the information to improve their mental health moving forward. Our findings suggest that online screeners can serve as a transition point in young people's mental health journeys. We discuss design implications for online screeners, post-screener feedback, and digital interventions broadly.

Centering Lived Experience in Developing Digital Interventions for Suicide and Self-injurious Behaviors: User-Centered Design Approach

BACKGROUND

The prevalence of self-injurious thoughts and behaviors (SITB) signals a growing public health crisis. Despite a recognized need for improved and scalable interventions, the field of SITB intervention faces several challenges: existing interventions are often time and resource intensive, most individuals with SITB do not seek formal mental health care, and efficacious treatments are characterized by small effects. Combined, these challenges indicate a need for improved SITB interventions for individuals in formal treatment and those who are not treatment engaged but are at high risk of worsening mental health and future suicide attempts.

OBJECTIVE

We present a methodological approach and set of techniques that may address these challenges by centering the lived experience of individuals with SITB in the process of developing needed services: user-centered design (UCD).

METHODS

We highlight the value of UCD in the context of digital interventions for SITB by describing the UCD approach and explicating how it can be leveraged to include lived experience throughout the development and evaluation process. We provide a detailed case example highlighting 3 phases of the early development process that can be used to design an intervention that is engaging and meets end-user needs. In addition, we point to novel applications of UCD to complement new directions in SITB research.

RESULTS

In this paper, we offer a 2-pronged approach to meet these challenges. First, in terms of addressing access to effective interventions, digital interventions hold promise to extend the reach of evidence-based treatments outside of brick-and-mortar health care settings. Second, to address challenges related to treatment targets and engagement, we propose involving individuals with lived experience in the design and research process.

CONCLUSIONS

UCD offers a well-developed and systematic process to center the unique needs, preferences, and perceived barriers of individuals with lived SITB experience in the development and evaluation of digital interventions.

The effect of depression and anxiety symptom severity on clinical outcomes and app use in digital mental health treatments: Meta-regression of three trials

A large number of trials have consistently shown that guided digital mental health treatments (DMHTs) are effective for depression and anxiety. As DMHTs are adopted by healthcare organizations, payers, and employers, they are often considered most appropriate for people with mild-to-moderate levels of symptom severity. Thus, the aim of this study was to examine the effects of symptom severity on depression and anxiety outcomes and app use across three trials of a guided DMHT, IntelliCare. Participants were categorized into mild, moderate, moderately severe, and severe symptom severity groups on depression and anxiety. All symptom severity groups showed significant reductions in depression and anxiety in a clear ordinal pattern, with the mild symptom severity group showing the smallest changes and the severe symptom group showing the largest improvements. Those with the lowest levels of educational attainment showed the largest symptom improvement. Baseline symptom severity was not significantly related to app use. App use was significantly related to depression and anxiety outcomes. These findings suggest that depression and anxiety symptom severity is not useful in determining who should be referred to a guided DMHT.

Evaluation of Changes in Depression, Anxiety, and Social Anxiety Using Smartphone Sensor Features: Longitudinal Cohort Study

BACKGROUND

The assessment of behaviors related to mental health typically relies on self-report data. Networked sensors embedded in smartphones can measure some behaviors objectively and continuously, with no ongoing effort.

OBJECTIVE

This study aims to evaluate whether changes in phone sensor-derived behavioral features were associated with subsequent changes in mental health symptoms.

METHODS

This longitudinal cohort study examined continuously collected phone sensor data and symptom severity data, collected every 3 weeks, over 16 weeks. The participants were recruited through national research registries. Primary outcomes included depression (8-item Patient Health Questionnaire), generalized anxiety (Generalized Anxiety Disorder 7-item scale), and social anxiety (Social Phobia Inventory) severity. Participants were adults who owned Android smartphones. Participants clustered into 4 groups: multiple comorbidities, depression and generalized anxiety, depression and social anxiety, and minimal symptoms.

RESULTS

A total of 282 participants were aged 19-69 years (mean 38.9, SD 11.9 years), and the majority were female (223/282, 79.1%) and White participants (226/282, 80.1%). Among the multiple comorbidities group, depression changes were preceded by changes in GPS features (Time: r=-0.23, P=.02; Locations: r=-0.36, P<.001), exercise duration (r=0.39; P=.03) and use of active apps (r=-0.31; P<.001). Among the depression and anxiety groups, changes in depression were preceded by changes in GPS features for Locations (r=-0.20; P=.03) and Transitions (r=-0.21; P=.03). Depression changes were not related to subsequent sensor-derived features. The minimal symptoms group showed no significant relationships. There were no associations between sensor-based features and anxiety and minimal associations between sensor-based features and social anxiety.

CONCLUSIONS

Changes in sensor-derived behavioral features are associated with subsequent depression changes, but not vice versa, suggesting a directional relationship in which changes in sensed behaviors are associated with subsequent changes in symptoms.

A qualitative study of perceptions of risk and protective factors for suicide among Bhutanese refugees

Over 100,000 ethnically Nepalese, "Lhotshampa," people experienced systematic oppression, disenfranchisement, and violence during the latter part of the 20th century. The Lhotshampa people were forced to flee their homes in southern Bhutan and enter refugee camps in Nepal for over 20 years. As of this writing, most Bhutanese refugees have been resettled in other countries (primarily the United States, Canada, and Australia). As the two remaining Nepalese refugee camps prepare to close, a growing suicide crisis is developing among many Bhutanese refugees. Bhutanese refugees resettled in the United States are dying by suicide at approximately twice the rate of the general U.S. population. It is crucial to examine, qualitatively, the nature of both risk and protective factors from the perspective of Bhutanese refugees, themselves. Our study included 15 Bhutanese refugees (8 men, 7 women) recruited from a community sample as part of a parent project examining culturally responsive suicide risk assessment. Mean age across both genders was 38.4 years (range of 22-55 years). Participants in our study were asked open-ended questions about suicide risk and prevention. We conducted a thematic analysis, synthesized risk and protective themes, and applied a socio-ecological framework to the data. We found risk themes included psychological distress and vulnerability, substance use, social and familial discord, interpersonal violence, isolation, and postmigration stressors. Protective themes included low levels of substance use, de-stigmatization of mental health concerns, strong social connections, reduced postmigration stressors, increased access to mental health care, and strong awareness within the host community of migration-related challenges.

The Supportive Accountability Inventory: Psychometric properties of a measure of supportive accountability in coached digital interventions

BACKGROUND

One of the most widely used coaching models is Supportive Accountability (SA) which aims to provide intervention users with clear expectations for intervention use, regular monitoring, and a sense that coaches are trustworthy, benevolent, and have domain expertise. However, few measures exist to study the role of the SA model on coached digital interventions. We developed the Supportive Accountability Inventory (SAI) and evaluated the underlying factor structure and psychometric properties of this brief self-report measure.

METHOD

Using data from a two-arm randomized trial of a remote intervention for major depressive disorder (telephone CBT [tCBT] or a stepped care model of web-based CBT [iCBT] and tCBT), we conducted an Exploratory Factor Analysis on the SAI item pool and explored the final SAI's relationship to iCBT engagement as well as to depression outcomes. Participants in our analyses (n = 52) included those randomized to a receive iCBT, but were not stepped up to tCBT due to insufficient response to iCBT, had not remitted prior to the 10-week assessment point, and completed the pool of 8 potential SAI items.

RESULTS

The best fitting EFA model included only 6 items from the original pool of 8 and contained two factors: Monitoring and Expectation. Final model fit was mixed, but acceptable (χ ² (4) = 5.24, p = 0.26; RMSR = 0.03; RMSEA = 0.091; TLI = 0.967). Internal consistency was acceptable at α = 0.68. The SAI demonstrated good convergent and divergent validity. The SAI at the 10-week/mid-treatment mark was significantly associated with the number of days of iCBT use (r = 0.29, p = .037), but, contrary to expectations, was not predictive of either PHQ-9 scores (F(2,46) = 0.14, p = .89) or QIDS-C scores (F(2,46) = 0.84, p = .44) at post-treatment.

CONCLUSION

The SAI is a brief measure of the SA framework constructs. Continued development to improve the SAI and expand the constructs it assesses is necessary, but the SAI represents the first step towards a measure of a coaching protocol that can support both coached digital mental health intervention adherence and improved outcomes.

Predictive validity of the Seasonal Beliefs Questionnaire for discriminating between seasonal and nonseasonal major depressive disorder

The Seasonal Beliefs Questionnaire (SBQ) is a 26-item self-report measure of a winter seasonal affective disorder (SAD)-specific cognitive vulnerability consisting of maladaptive thoughts about the seasons, light availability, and weather conditions. In a known groups comparison, currently depressed adults with SAD had significantly higher SBQ scores than currently depressed adults with nonseasonal major depressive disorder (MDD) and healthy controls, and the MDD group had significantly higher SBQ scores than controls. Using that database, this study explored the predictive validity of using an SBQ cutoff score to differentiate SAD from MDD. Receiver operator characteristic curve analyses used SBQ total score to predict SAD versus MDD, SAD versus control, and MDD versus control status. The SBQ subscale combined score, derived from multivariable logistic regression with SBQ subscales, was examined as an alternative predictor. SBQ total score with a cutpoint of 132 had good predictive ability for distinguishing SAD from MDD (C-statistic = .792, sensitivity = .798, specificity = .794). The SBQ subscale combination score slightly improved predictive ability for the SAD/MDD distinction (C-statistic = .813), with better sensitivity (.930) but worse specificity (.571). In contrast, the score on a generic measure of depressogenic cognitive vulnerability, the Dysfunctional Attitudes Scale, was poor for differentiating SAD from MDD. SBQ total score was excellent in discriminating SAD cases from controls with a cutpoint of 121 (C-statistic = .962, sensitivity = .939, specificity .873), but had poor sensitivity for discriminating MDD cases from controls. Results support using the SBQ to screen for probable SAD in practice settings. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Detecting Critical Decision Points during Cognitive-Behavioral Therapy and Light Therapy for Winter Depression Nonremission and Recurrence

Using data from a clinical trial comparing cognitive-behavioral therapy (CBT-SAD) and light therapy (LT) for winter seasonal affective disorder (SAD; N = 177), we explored critical decision points, or treatment weeks, that predict likelihood of nonremission at post-treatment and depression recurrence following treatment. In receiver operator characteristic (ROC) curve analyses, we used weekly Structured Clinical Interview for the Hamilton Rating Scale for Depression-SAD Version (SIGH-SAD) scores during treatment to predict nonremission at post-treatment (Week 6) and recurrence one winter later (Winter 1), two winters later (Winter 2), and any recurrence. Although several C-statistics of ≥ .70 were found, only Week 4 SIGH-SAD scores in CBT-SAD for nonremission had enough predictive ability to inform clinical decision-making (C-statistic = .80; sensitivity = .91; specificity = .68). Week 4 of CBT-SAD may be a critical time point to identify likely nonremitters who need tailoring of intervention, based on SIGH-SAD cutpoint score ≥ 13. This study illustrates how clinical trial data can inform detecting optimal decision points in treatment for identifying patients unlikely to remit, a critical first step to developing adaptive treatment strategies using decision rules to operationalize when and for whom treatment should change to maximize clinical benefit.

Applying experimental therapeutics to examine cognitive and chronological vulnerabilities as mediators of acute outcomes in cognitive-behavioral therapy and light therapy for winter depression

OBJECTIVE

We applied the experimental therapeutics approach to test whether acute treatment outcomes for winter seasonal affective disorder (SAD) are mediated by a cognitive mechanism in cognitive-behavioral therapy (CBT-SAD) versus a chronobiologic mechanism in light therapy (LT).

METHOD

Currently depressed adults with major depression, recurrent with seasonal pattern (N = 177; 83.6% female, 92.1% non-Hispanic White, M age = 45.6) were randomized to 6 weeks of LT or group CBT-SAD. SAD symptoms were assessed weekly on the Structured Clinical Interview for the Hamilton Rating Scale for Depression-SAD Version. At pre-, mid-, and posttreatment, participants completed measures of general depressogenic cognitions (Dysfunctional Attitudes Scale; DAS); SAD-specific negative cognitions (Seasonal Beliefs Questionnaire; SBQ); chronotype (Morningness-Eveningness Questionnaire; MEQ); and depressive symptoms (Beck Depression Inventory-Second Edition).

RESULTS

Parallel-process growth models showed evidence for hypothesized mechanisms. For SAD-specific negative cognitions (SBQ), both symptom measures showed (1) an effect of treatment group on the slope of the mediator, with CBT-SAD demonstrating greater decreases, and (2) an effect of the slope of the mediator on the slope of the outcome. These effects held for the SBQ but not the broader measure of depressogenic cognitions (DAS). For the chronotype measure (MEQ), treatment assignment affected change, whereby LT was associated with reduced "eveningness," but this was unrelated to change in symptoms.

CONCLUSIONS

CBT-SAD promoted decreases in SAD-specific negative cognitions, and these changes were related to decreases in symptoms. Consistent with the theory that LT corrects misaligned circadian rhythms, LT reduced eveningness, but this did not correspond to symptom improvement. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

COVID-19 pandemic: every day feels like a weekday to most

The COVID-19 outbreak has clear clinical and economic impacts, but also affects behaviors e.g. through social distancing, and may increase stress and anxiety. However, while case numbers are tracked daily, we know little about the psychological effects of the outbreak on individuals in the moment. Here we examine the psychological and behavioral shifts over the initial stages of the outbreak in the United States in an observational longitudinal study. Through GPS phone data we find that homestay is increasing, while being at work dropped precipitously. Using regular real-time experiential surveys we observe an overall increase in stress and mood levels which is similar in size to the weekend vs. weekday differences. As there is a significant difference between weekday and weekend mood and stress levels, this is an important decrease in wellbeing. For some, especially those affected by job loss, the mental health impact is severe.

286Predictors of atrial fibrillation in patients with embolic stroke of undetermined source: an analysis of the RE-SPECT ESUS trial

Background

A proportion of patients with embolic stroke of undetermined source (ESUS) may have silent atrial fibrillation (AF) or develop AF after the initial evaluation. Better understanding of risk for identification is critical to implement optimal monitoring strategies with the goal of preventing recurrent stroke. The RE-SPECT ESUS trial provides an opportunity to assess predictors for developing AF and associated recurrent stroke.

Methods

RE-SPECT ESUS was a randomized, controlled trial (564 sites, 42 countries) assessing dabigatran versus aspirin for the prevention of recurrent stroke in patients with ESUS. Of 5390 patients enrolled and followed for a median of 19 months, 403 (7.5%) were found to develop AF reported as an adverse event or using cardiac monitoring per standard clinical care. Univariable and multivariable regression analyses for predictors of AF were conducted.

Results

In a multivariable analysis, clinical predictors for developing AF were: older age, history of heart failure, lower heart rate, hypertension, higher body mass index, and being from Western Europe (Table). Using several published predictive models, including HAVOC, C2HEST, AS5F, ARIC, and CHA2DS2-VASc, high scores were associated with increased rates of AF. In patients who developed AF, recurrent stroke occurred in 7.0% per year, versus 4.2% per year in patients who did not develop AF (hazard ratio 1.75; 95% CI 1.30–2.35, p=0.0002).

Conclusion

Besides age as the most important variable, several other factors, including lower heart rate, higher body mass index, and hypertension, are independent predictors of AF after ESUS. Understanding who is at higher risk of developing AF may help identify patients requiring more intense, long-term cardiac monitoring.

Acknowledgement/Funding

Funded by Boehringer Ingelheim

The desire to be dead among Bhutanese refugees resettled in the United States: Assessing risk

Bhutanese refugees are at elevated risk for suicide, but culturally inflexible suicide risk models may hinder accurate risk detection in this population. This cross-sectional study aimed to use a theoretical model based on the interpersonal psychological theory of suicide and the cultural model of suicide to improve suicide risk-assessment among Bhutanese refugees. Participants included 60 Bhutanese refugees (31 males and 29 females), aged 18 to 65, resettled in Vermont. Suicidal ideation (n = 4, 6.7%) was low, but a substantial minority (n = 29, 48.3%) endorsed some desire to be dead. Perceived burdensomeness, but not thwarted belongingness, was significantly associated with both suicidal ideation and the desire to be dead. Neither desire to be dead nor suicidal ideation was significantly related to suicide attempt history. Results highlight that including assessments of desire to be dead in addition to assessments of suicidal ideation may address the problem of underidentification of Bhutanese refugees at risk for suicidal behavior, particularly those who do not present with suicidal ideation. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

A measure of cognitions specific to seasonal depression: Development and validation of the Seasonal Beliefs Questionnaire

We introduce the Seasonal Beliefs Questionnaire (SBQ), a self-report inventory of maladaptive thoughts about the seasons, light availability, and weather conditions, proposed to constitute a unique cognitive vulnerability to winter seasonal affective disorder (SAD; Rohan, Roecklein, & Haaga, 2009). Potential items were derived from a qualitative analysis of self-reported thoughts during SAD-tailored cognitive-behavioral therapy (CBT-SAD) and subsequently refined based on qualitative feedback from 48 SAD patients. In the psychometric study (N = 536 college students), exploratory and confirmatory factor analyses pruned the items to a 26-item scale with a 5-factor solution, demonstrating good internal consistency, convergent and divergent validity, and 2-week test-retest reliability. In a known groups comparison, the SBQ discriminated SAD patients (n = 86) from both nonseasonal major depressive disorder (MDD) patients (n = 30) and healthy controls (n = 110), whereas a generic measure of depressogenic cognitive vulnerability (the Dysfunctional Attitudes Scale [DAS]) discriminated MDD patients from the other groups. In a randomized clinical trial comparing CBT-SAD with light therapy (N = 177), SBQ scores improved at twice the rate in CBT-SAD than in light therapy. Greater change in SBQ scores during CBT-SAD, but not during light therapy, was associated with a lower risk of depression recurrence 2 winters later. In contrast, DAS scores improved comparably during CBT-SAD and light therapy, and DAS change was unrelated to recurrence following either treatment. These results support using the SBQ as a brief assessment tool for a SAD-specific cognitive vulnerability and as a treatment target in CBT-SAD. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Suicide and Suicide-related Behavior among Bhutanese Refugees Resettled in the United States

Suicidal behavior and death by suicide are significant and pressing problems in the Bhutanese refugee community. Currently, Bhutanese refugees are dying by suicide at a rate nearly two times that of the general U.S. population. Proper identification of risk factors for suicide saves lives; however, if risk is underestimated due to culturally inflexible risk assessments, preventable deaths may continue to occur. In this review, we examine specific cultural factors related to psychopathology and suicide among Bhutanese refugees. To contextualize the current suicide crisis among Bhutanese refugees, we propose an integration of the interpersonal psychological theory of suicide (Joiner, 2005) and the cultural model of suicide (Chu, Goldblum, Floyd, & Bongar, 2010). We provide recommendations for preventing suicide from a systems framework and discuss practical lessons from a preliminary study designed to test a culturally-responsive model of suicide in Bhutanese refugees.

Patterns of depressive symptom remission during the treatment of seasonal affective disorder with cognitive-behavioral therapy or light therapy

BACKGROUND

To elucidate mechanisms related to remission in winter seasonal affective disorder (SAD), we explored the course of individual depressive symptom offset across two distinct treatment modalities that show comparable outcomes at treatment endpoint: cognitive-behavioral therapy for SAD (CBT-SAD) and light therapy (LT).

METHOD

One hundred seventy-seven adults with SAD in a depressive episode were randomized to 6-weeks of CBT-SAD (n = 88) or LT (n = 89). Symptoms were assessed via the 29-item Structured Interview Guide for the Hamilton Rating Scale for Depression-SAD Version (SIGH-SAD) at pretreatment and weekly during treatment. Survival analyses were conducted for the 17 SIGH-SAD items endorsed by more than 40 participants at pretreatment. Within each of the included symptoms, data from participants who endorsed the symptom at pretreatment and who had 3 or fewer weeks missing were included.

RESULTS

For most (13/17; 76%) symptoms, CBT-SAD and LT did not differ in time to remission. However, for four symptoms (early insomnia, psychic anxiety, hypersomnia, and social withdrawal), LT led to symptom remission more quickly than CBT-SAD.

CONCLUSIONS

Symptom remission progressed comparably across CBT-SAD and LT for most symptoms. Despite the fact that the two treatments led to similar remission rates and improvements at treatment endpoint, for early insomnia, psychic anxiety, hypersomnia, and social withdrawal, LT led to symptom remission faster than CBT-SAD. These results suggest different mechanisms and pathways to the same therapeutic end. Speedier remission of early insomnia and hypersomnia is consistent with the theory that SAD is related to a pathological circadian phase-shift that can be corrected with LT.

Molecular indicators of stress-induced neuroinflammation in a mouse model simulating features of post-traumatic stress disorder

A social-stress mouse model was used to simulate features of post-traumatic stress disorder (PTSD). The model involved exposure of an intruder (male C57BL/6) mouse to a resident aggressor (male SJL) mouse for 5 or 10 consecutive days. Transcriptome changes in brain regions (hippocampus, amygdala, medial prefrontal cortex and hemibrain), blood and spleen as well as epigenome changes in the hemibrain were assayed after 1- and 10-day intervals following the 5-day trauma or after 1- and 42-day intervals following the 10-day trauma. Analyses of differentially expressed genes (common among brain, blood and spleen) and differentially methylated promoter regions revealed that neurogenesis and synaptic plasticity pathways were activated during the early responses but were inhibited after the later post-trauma intervals. However, inflammatory pathways were activated throughout the observation periods, except in the amygdala in which they were inhibited only at the later post-trauma intervals. Phenotypically, inhibition of neurogenesis was corroborated by impaired Y-maze behavioral responses. Sustained neuroinflammation appears to drive the development and maintenance of behavioral manifestations of PTSD, potentially via its inhibitory effect on neurogenesis and synaptic plasticity. By contrast, peripheral inflammation seems to be directly responsible for tissue damage underpinning somatic comorbid pathologies. Identification of overlapping, differentially regulated genes and pathways between blood and brain suggests that blood could be a useful and accessible brain surrogate specimen for clinical translation.

Treatment expectations for cognitive-behavioral therapy and light therapy for seasonal affective disorder: Change across treatment and relation to outcome

OBJECTIVE

To examine the dynamic relationship between treatment expectations and treatment outcome over the course of a clinical trial for winter seasonal affective disorder (SAD).

METHOD

Currently depressed adults with Major Depression, Recurrent with Seasonal Pattern (N = 177) were randomized to 6 weeks of group-delivered cognitive-behavioral therapy for SAD (CBT-SAD) or light therapy (LT). The majority were female (83.6%) and white (92.1%), with a mean age of 45.6 years. Treatment expectations for CBT-SAD and LT were assessed using a modification of the Treatment Expectancy and Credibility Survey (Borkovec & Nau, 1972). Depression severity was assessed using the Beck Depression Inventory-Second Edition (Beck, Steer, & Brown, 1996). All measures were administered at pretreatment, midtreatment, and posttreatment.

RESULTS

As treatment progressed, expectations for the treatment received increased across time steeply in CBT-SAD patients and moderately in LT patients. Collapsing across time, patients with higher treatment expectations had lower depression severity than those with lower treatment expectations. In a cross-lagged panel path analysis, there was a significant effect of treatment expectations at midtreatment on depression severity at posttreatment among CBT-SAD patients.

CONCLUSIONS

Treatment expectations changed across treatment, affected outcome, and should be assessed and monitored repeatedly throughout treatment. Findings suggest that treatment expectations at midtreatment are a mechanism by which CBT-SAD reduces depression, which should be replicated in SAD samples and examined for generalizability to nonseasonal depression. These findings underscore the importance of further research examining treatment expectations in mediating CBT's effects in depression and other types of psychopathology. (PsycINFO Database Record

A protocol for the Hamilton Rating Scale for Depression: Item scoring rules, Rater training, and outcome accuracy with data on its application in a clinical trial

BACKGROUND

We present a fully articulated protocol for the Hamilton Rating Scale for Depression (HAM-D), including item scoring rules, rater training procedures, and a data management algorithm to increase accuracy of scores prior to outcome analyses. The latter involves identifying potentially inaccurate scores as interviews with discrepancies between two independent raters on the basis of either scores >=5-point difference) or meeting threshold for depression recurrence status, a long-term treatment outcome with public health significance. Discrepancies are resolved by assigning two new raters, identifying items with disagreement per an algorithm, and reaching consensus on the most accurate scores for those items.

METHODS

These methods were applied in a clinical trial where the primary outcome was the Structured Interview Guide for the Hamilton Rating Scale for Depression-Seasonal Affective Disorder version (SIGH-SAD), which includes the 21-item HAM-D and 8 items assessing atypical symptoms. 177 seasonally depressed adult patients were enrolled and interviewed at 10 time points across treatment and the 2-year followup interval for a total of 1589 completed interviews with 1535 (96.6%) archived.

RESULTS

Inter-rater reliability ranged from ICCs of .923-.967. Only 86 (5.6%) interviews met criteria for a between-rater discrepancy. HAM-D items "Depressed Mood", "Work and Activities", "Middle Insomnia", and "Hypochondriasis" and Atypical items "Fatigability" and "Hypersomnia" contributed most to discrepancies.

LIMITATIONS

Generalizability beyond well-trained, experienced raters in a clinical trial is unknown.

CONCLUSIONS

Researchers might want to consider adopting this protocol in part or full. Clinicians might want to tailor it to their needs.

Outcomes One and Two Winters Following Cognitive-Behavioral Therapy or Light Therapy for Seasonal Affective Disorder

OBJECTIVE

The central public health challenge for winter seasonal affective disorder (SAD) is recurrence prevention. Preliminary studies suggest better long-term outcomes following cognitive-behavioral therapy tailored for SAD (CBT-SAD) than light therapy. The present study is a large, randomized head-to-head comparison of these treatments on outcomes one and two winters after acute treatment.

METHOD

Community adults with major depression, recurrent with seasonal pattern (N=177) were followed one and two winters after a randomized trial of 6 weeks of CBT-SAD (N=88) or light therapy (N=89). Prospective follow-up visits occurred in January or February of each year, and major depression status was assessed by telephone in October and December of the first year. The primary outcome was winter depression recurrence status on the Structured Interview Guide for the Hamilton Depression Rating Scale-Seasonal Affective Disorder Version (SIGH-SAD). Other outcomes were depression severity on the SIGH-SAD and the Beck Depression Inventory-Second Edition (BDI-II), remission status based on severity cutoff scores, and major depression status from tracking calls.

RESULTS

The treatments did not differ on any outcome during the first year of follow-up. At the second winter, CBT-SAD was associated with a smaller proportion of SIGH-SAD recurrences (27.3% compared with 45.6%), less severe symptoms on both measures, and a larger proportion of remissions defined as a BDI-II score ≤8 (68.3% compared with 44.5%) compared with light therapy. Nonrecurrence at the next winter was more highly associated with nonrecurrence at the second winter among CBT-SAD participants (relative risk=5.12) compared with light therapy participants (relative risk=1.92).

CONCLUSIONS

CBT-SAD was superior to light therapy two winters following acute treatment, suggesting greater durability for CBT-SAD.

Randomized Trial of Cognitive-Behavioral Therapy Versus Light Therapy for Seasonal Affective Disorder: Acute Outcomes

OBJECTIVE

Whereas considerable evidence supports light therapy for winter seasonal affective disorder (SAD), data on cognitive-behavioral therapy for SAD (CBT-SAD) are promising but preliminary. This study estimated the difference between CBT-SAD and light therapy outcomes in a large, more definitive test.

METHOD

The participants were 177 adults with a current episode of major depression that was recurrent with a seasonal pattern. The randomized clinical trial compared 6 weeks of CBT-SAD (N=88) and light therapy (N=89). Light therapy consisted of 10,000-lux cool-white florescent light, initiated at 30 minutes each morning and adjusted according to a treatment algorithm based on response and side effects. CBT-SAD comprised 12 sessions of the authors' SAD-tailored protocol in a group format and was administered by Ph.D. psychologists in two 90-minute sessions per week. Outcomes were continuous scores on the Structured Interview Guide for the Hamilton Rating Scale for Depression-SAD Version (SIGH-SAD, administered weekly) and Beck Depression Inventory-Second Edition (BDI-II, administered before treatment, at week 3, and after treatment) and posttreatment remission status based on cut points.

RESULTS

Depression severity measured with the SIGH-SAD and BDI-II improved significantly and comparably with CBT-SAD and light therapy. Having a baseline comorbid diagnosis was associated with higher depression scores across all time points in both treatments. CBT-SAD and light therapy did not differ in remission rates based on the SIGH-SAD (47.6% and 47.2%, respectively) or the BDI-II (56.0% and 63.6%).

CONCLUSIONS

CBT-SAD and light therapy are comparably effective for SAD during an acute episode, and both may be considered as treatment options.

Intermittent Explosive Disorder and aversive parental care

Parental bonding has been shown to have lasting impacts on the psychological development of children. Despite a growing body of research examining trauma as it relates to Intermittent Explosive Disorder (IED), no prior research has examined the relationship between parental bonding and IED. Six hundred fifty eight subjects were studied and categorized into one of three groups: Normal Control (no history of current or lifetime Axis I or Axis II disorder), Psychiatric Control (current and/or lifetime Axis I and/or Axis II disorders without IED), and IED (met current and/or lifetime criteria for IED). Self-reported parental care was assessed using the Parental Bonding Inventory (PBI). PBI Care scores were lowest among IED subjects, which were lower than among Psychiatric Control subjects, which were lower than among Normal Control subjects. PBI Control scores were highest among IED and Psychiatric Control subjects, which were higher than among Normal Control subjects. The diagnostic group differences in PBI Care/PBI Control scores were not impacted by the number of Axis I/II diagnoses. The findings in this study expand the link between childhood trauma exposure, violent behavior, and IED. This is the first report of an association of IED with an aversive childhood parenting environment.

Species-specific preferences of German recreational anglers for freshwater fishing experiences, with emphasis on the intrinsic utilities of fish stocking and wild fishes

To answer the question, whether anglers have an intrinsic preference for stocking or a preference for catch outcomes (e.g. catch rates) believed to be maintained by stocking, a discrete choice experiment was conducted among a sample of anglers (n = 1335) in Lower Saxony, Germany. After controlling for catch aspects of the fishing experience, no significant influence of two stocking attributes (stocking frequency and composition of the catch in terms of wild v. hatchery fishes) on the utility gained from fishing was found for any of the freshwater species that were studied. It was concluded that the previously documented large appreciation of fish stocking by anglers may be indicative of an underlying preference for sufficiently high catches rather than reflect an intrinsic preference for stocking or the catching of wild fishes per se.

Attack priming in female Syrian golden hamsters is associated with a c-fos-coupled process within the corticomedial amygdala

Allowing a resident hamster a single "priming" attack on a conspecific induces a transient aggressive arousal as indicated by a reduction in the latency and increase in the probability of attack on a second intruder presented within the next 30 min. We present two lines of evidence identifying the corticomedial amygdala as an important locus mediating this effect. (1) Attack priming significantly increases the number of neurons expressing immunocytochemically identified Fos protein in the corticomedial amygdala, but not elsewhere. Pursuit and biting of an inanimate object does not induce corticomedial amygdala c-fos expression of the same pattern or magnitude. The corticomedial amygdala contribution to the priming effect involves more than a non-specific arousal, since corticomedial amygdala c-fos expression does not correlate with locomotor activity, a standard indicator of such arousal. (2) Radiofrequency lesions of the corticomedial amygdala reduce aggression, the greatest reduction occurring with the more anterior lesions. Other behaviors, including a priming-like locomotor practice effect in a running wheel, are unaffected by corticomedial amygdala lesions. These findings suggest that attack priming is an aggression-specific effect resulting from a Fos-coupled change within neural circuitry of which the corticomedial amygdala is a part. From a theoretical point of view, these experiments suggest a new approach to the analysis of the mechanisms underlying aggressive behavior and the persistence of aggressive arousal. We present a sketch of a quantitative neurobehavioral model which relates attack probability to neural activation within the corticomedial amygdala. From a methodological viewpoint, these experiments extend the utility of mapping c-fos expression as a technique for localizing endogenous, behavior-specific processes within the central nervous system.