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.

An Adjunctive Internet-Based Intervention to Enhance Treatment for Depression in Adults: Randomized Controlled Trial

Background Internet-based interventions promise to enhance the accessibility of mental health care for a greater number of people and in more remote places. Their effectiveness has been shown for the prevention and treatment of various mental disorders. However, their potential when delivered as add-on to conventional treatment (ie, blended care) is less clear. Objective The aim of this study is to study the effectiveness of an internet intervention (ASCENSO) implemented in addition to face-to-face treatment as usual (TAU) for depression. Methods A 2-arm, parallel-group, randomized controlled trial was conducted in an outpatient private mental health care center in Chile. In all, 167 adults, diagnosed with major depressive disorder, without severe comorbidities, and with internet access, were included. Eighty-four participants were assigned to the intervention group and received medical and psychological TAU from the mental health center plus access to the ASCENSO online platform. The control group (n=83) received only TAU. The ASCENSO platform includes psycho-educational information, depressive symptom monitoring and feedback, and managing emergencies based on the principles of cognitive behavioral therapy. Emergency management was mental health provider–assisted. TAU includes access to primary care physicians and psychiatrists, to a brief individual psychotherapy, and to medication when needed. The baseline questionnaires were administered in person, and 6- and 9-months assessments were conducted online. Depression symptoms and quality of life were measured by self-administered questionnaires, and treatment adherence was determined via the Mental Health Center’s internal records. The usage of ASCENSO was assessed by server logs. Reduction on depressive symptomatology was considered as the primary outcome of the intervention and quality of life as a secondary outcome. Results Of the 84 participants in the intervention group, 5 participants (6%) never accessed the online platform. Of the remaining 79 participants who accessed ASCENSO, 1 (1%, 1/79) did not answer any of the symptom questionnaire, and most participants (72/79, 91%) answered the monitoring questionnaires irregularly. The ASCENSO intervention implemented in addition to face-to-face care did not improve the outcome of the usual care delivered at the mental health center, either in terms of reduction of depressive symptoms (F2,6087= 0.48; P=.62) or in the improvement of quality of life (EQ-5D-3L: F2,7678=0.24; P=.79 and EQ-VAS: F2,6670= 0.13; P=.88). In contrast, for the primary (F2,850=78.25; P<.001) and secondary outcomes (EQ-5D-3L: F2,1067=37.87; EQ-VAS: F2,4390= 51.69; P<.001) in both groups, there was an improvement from baseline to 6 months (P<.001), but there was no change at 9 months. In addition, no effects on adherence to or use of TAU were found. Finally, the dropout rate for the face-to-face treatment component was 54% (45/84) for the intervention group versus 39% (32/83) for the control group (P=.07). Conclusions The fact that the adjunctive access to ASCENSO did not improve outcome could be due to both the rather high effectiveness of TAU and to patients’ limited use of the online platform. Trial Registration ClinicalTrials.gov NCT03093467; https://clinicaltrials.gov/ct2/show/NCT03093467

Evaluation of Repeated Web-Based Screening for Predicting Postpartum Depression: Prospective Cohort Study

Background Postpartum depression (PPD) is a severe mental disorder that often results in poor maternal-infant attachment and negatively impacts infant development. Universal screening has recently been recommended to identify women at risk, but the optimal screening time during pregnancy has not been defined so far. Thus, web-based technologies with widespread use among women of childbearing age create new opportunities to detect pregnancies with a high risk for adverse mental health outcomes at an early stage. Objective The aim of this study was to stratify the risk for PPD and to determine the optimal screening time during pregnancy by using a web-based screening tool collecting electronic patient-reported outcomes (ePROs) as the basis for a screening algorithm. Methods In total, 214 women were repeatedly tested for depressive symptoms 5 times during and 3 times after pregnancy by using the Edinburgh Postnatal Depression Scale (EPDS), accessible on a web-based pregnancy platform, developed by the authors of this study. For each prenatal assessment, the area under the curve (AUC), sensitivity, specificity, and predictive values for PPD were calculated. Multivariate logistic regression analyses were applied to identify further potential predictors, such as age, education, parity, relationship quality, and anxiety, to increase predictive accuracy. Results Digitally collected data from 214 pregnant women were analyzed. The predictive accuracy of depressive symptoms 3 and 6 months postpartum was reasonable to good regarding the screening in the second (AUC=0.85) and third (AUC=0.75) trimester. The multivariate logistic regression analyses resulted in an excellent AUC of 0.93 at 3 months and a good AUC of 0.87 at 6 months postpartum. Conclusions The best predictive accuracy for PPD has been shown for screening between the 24th and the 28th gestational week (GW) and seems to be beneficial for identifying women at risk. In combination with the aforementioned predictive factors, the discriminatory power improved, particularly at 3 months postpartum. Screening for depression during pregnancy, combined with the women’s personal risk profile, can be used as a starting point for developing a digital screening algorithm. Thereby, web-based assessment tools constitute feasible, efficient, and cost-effective approaches. Thus, they seem to be beneficial in detecting high-risk pregnancies in order to improve maternal and infant birth outcomes in the long term.

Effectiveness and Feasibility of Internet-Based Interventions for Grief After Bereavement: Systematic Review and Meta-analysis

Background Although grief and its symptoms constitute a normal reaction to experiences of loss, some of those affected still report elevated levels of distress after an extended period, often termed complicated grief. Beneficial treatment effects of face-to-face therapies, for example, grief counseling or cognitive behavioral therapy against complicated grief, have been reported. Evaluations of internet- and mobile-based interventions targeting symptoms of grief in bereaved individuals with regard to objective quality criteria are currently lacking. Objective We aim to conduct a systematic review and meta-analysis on the effectiveness and feasibility of internet- and mobile-based interventions against symptoms of grief after bereavement. Methods We conducted systematic literature searches of randomized controlled trials or feasibility studies published before January 9, 2020, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, in PubMed, PsycINFO, Web of Science Core Collection, and the Cochrane Library. The quality of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations system. We further assessed aspects of feasibility and rated quality of interventions using criteria suggested by an expert panel on mental health care (German Association for Psychiatry, Psychotherapy, and Psychosomatics). A random-effects meta-analysis was conducted to assess between-group effect sizes. Results In total, 9 trials (N=1349) were included. Of these, 7 studies were analyzed meta-analytically. Significant effects were found for symptoms of grief (g=0.54, 95% CI 0.32-0.77), depression (g=0.44, 95% CI 0.20-0.68), and posttraumatic stress (g=0.82, 95% CI 0.63-1.01). Heterogeneity was moderate for grief and depression (I2=48.75% and 55.19%, respectively) and low for posttraumatic stress symptoms (I2=0%). The overall quality of evidence was graded low (grief and depression) to moderate (posttraumatic stress). User satisfaction with the interventions was high, as was the quality of the interventions assessed using objective quality criteria. Conclusions Internet- or mobile-based interventions might constitute an effective treatment approach against symptoms of grief in bereaved adults. However, the small sample sizes and limited number of studies included in the review warrant further investigation. Trial Registration International Prospective Register of Systematic Reviews (PROSPERO) CRD42012002100; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=131428

Language, Speech, and Facial Expression Features for Artificial Intelligence–Based Detection of Cancer Survivors’ Depression: Scoping Meta-Review

Background Cancer survivors often experience disorders from the depressive spectrum that remain largely unrecognized and overlooked. Even though screening for depression is recognized as essential, several barriers prevent its successful implementation. It is possible that better screening options can be developed. New possibilities have been opening up with advances in artificial intelligence and increasing knowledge on the connection of observable cues and psychological states. Objective The aim of this scoping meta-review was to identify observable features of depression that can be intercepted using artificial intelligence in order to provide a stepping stone toward better recognition of depression among cancer survivors. Methods We followed a methodological framework for scoping reviews. We searched SCOPUS and Web of Science for relevant papers on the topic, and data were extracted from the papers that met inclusion criteria. We used thematic analysis within 3 predefined categories of depression cues (ie, language, speech, and facial expression cues) to analyze the papers. Results The search yielded 1023 papers, of which 9 met the inclusion criteria. Analysis of their findings resulted in several well-supported cues of depression in language, speech, and facial expression domains, which provides a comprehensive list of observable features that are potentially suited to be intercepted by artificial intelligence for early detection of depression. Conclusions This review provides a synthesis of behavioral features of depression while translating this knowledge into the context of artificial intelligence–supported screening for depression in cancer survivors.

Examining the Theoretical Framework of Behavioral Activation for Major Depressive Disorder: Smartphone-Based Ecological Momentary Assessment Study

Background Behavioral activation (BA), either as a stand-alone treatment or as part of cognitive behavioral therapy, has been shown to be effective for treating depression. The theoretical underpinnings of BA derive from Lewinsohn et al’s theory of depression. The central premise of BA is that having patients engage in more pleasant activities leads to them experiencing more pleasure and elevates their mood, which, in turn, leads to further (behavioral) activation. However, there is a dearth of empirical evidence about the theoretical framework of BA. Objective This study aims to examine the assumed (temporal) associations of the 3 constructs in the theoretical framework of BA. Methods Data were collected as part of the “European Comparative Effectiveness Research on Internet-based Depression Treatment versus treatment-as-usual” trial among patients who were randomly assigned to receive blended cognitive behavioral therapy (bCBT). As part of bCBT, patients completed weekly assessments of their level of engagement in pleasant activities, the pleasure they experienced as a result of these activities, and their mood over the course of the treatment using a smartphone-based ecological momentary assessment (EMA) application. Longitudinal cross-lagged and cross-sectional associations of 240 patients were examined using random intercept cross-lagged panel models. Results The analyses did not reveal any statistically significant cross-lagged coefficients (all P>.05). Statistically significant cross-sectional positive associations between activities, pleasure, and mood levels were identified. Moreover, the levels of engagement in activities, pleasure, and mood slightly increased over the duration of the treatment. In addition, mood seemed to carry over, over time, while both levels of engagement in activities and pleasurable experiences did not. Conclusions The results were partially in accordance with the theoretical framework of BA, insofar as the analyses revealed cross-sectional relationships between levels of engagement in activities, pleasurable experiences deriving from these activities, and enhanced mood. However, given that no statistically significant temporal relationships were revealed, no conclusions could be drawn about potential causality. A shorter measurement interval (eg, daily rather than weekly EMA reports) might be more attuned to detecting potential underlying temporal pathways. Future research should use an EMA methodology to further investigate temporal associations, based on theory and how treatments are presented to patients. Trial Registration ClinicalTrials.gov, NCT02542891, https://clinicaltrials.gov/ct2/show/NCT02542891; German Clinical Trials Register, DRKS00006866, https://tinyurl.com/ybja3xz7; Netherlands Trials Register, NTR4962, https://www.trialregister.nl/trial/4838; ClinicalTrials.Gov, NCT02389660, https://clinicaltrials.gov/ct2/show/NCT02389660; ClinicalTrials.gov, NCT02361684, https://clinicaltrials.gov/ct2/show/NCT02361684; ClinicalTrials.gov, NCT02449447, https://clinicaltrials.gov/ct2/show/NCT02449447; ClinicalTrials.gov, NCT02410616, https://clinicaltrials.gov/ct2/show/NCT02410616; ISRCTN registry, ISRCTN12388725, https://www.isrctn.com/ISRCTN12388725

Implementing the Routine Use of Electronic Mental Health Screening for Youth in Primary Care: Systematic Review

Background Adolescents often present at primary care clinics with nonspecific physical symptoms when, in fact, they have at least 1 mental health or risk behavior (psychosocial) issue with which they would like help but do not disclose to their care provider. Despite global recommendations, over 50% of youths are not screened for mental health and risk behavior issues in primary care. Objective This review aimed to examine the implementation, acceptability, feasibility, benefits, and barriers of e-screening tools for mental health and risk behaviors among youth in primary care settings. Methods Electronic databases—MEDLINE, CINAHL, Scopus, and the Cochrane Database of Systematic Reviews—were searched for studies on the routine screening of youth in primary care settings. Screening tools needed to be electronic and screen for at least 1 mental health or risk behavior issue. A total of 11 studies that were reported in 12 articles, of which all were from high-income countries, were reviewed. Results e-Screening was largely proven to be feasible and acceptable to youth and their primary care providers. Preconsultation e-screening facilitated discussions about sensitive issues and increased disclosure by youth. However, barriers such as the lack of time, training, and discomfort in raising sensitive issues with youth continued to be reported. Conclusions To implement e-screening, clinicians need to change their behaviors, and e-screening processes must become normalized into their workflows. Co-designing and tailoring screening implementation frameworks to meet the needs of specific contexts may be required to ensure that clinicians overcome initial resistances and perceived barriers and adopt the required processes in their work.

Opening the Black Box of Daily Life in Nonsuicidal Self-injury Research: With Great Opportunity Comes Great Responsibility

Although nonsuicidal self-injury (NSSI)—deliberate damaging of body tissue without suicidal intent—is a behavior that occurs in interaction with real-world contexts, studying NSSI in the natural environment has historically been impossible. Recent advances in real-time monitoring technologies have revolutionized our ability to do exactly that, providing myriad research and clinical practice opportunities. In this viewpoint paper, we review new research pathways to improve our ability to understand, predict, and prevent NSSI, and provide critical perspectives on the responsibilities inherent to conducting real-time monitoring studies on NSSI. Real-time monitoring brings unique opportunities to advance scientific understanding about (1) the dynamic course of NSSI, (2) the real-time predictors thereof and ability to detect acute risk, (3) the ecological validity of theoretical models, (4) the functional mechanisms and outcomes of NSSI, and (5) the promotion of person-centered care and novel technology-based interventions. By considering the opportunities of real-time monitoring research in the context of the accompanying responsibilities (eg, inclusive recruitment, sound and transparent research practices, participant safety and engagement, measurement reactivity, researcher well-being and training), we provide novel insights and resources to open the black box of daily life in the next decade(s) of NSSI research.

Momentary Manifestations of Negative Symptoms as Predictors of Clinical Outcomes in People at High Risk for Psychosis: Experience Sampling Study

Background Negative symptoms occur in individuals at ultrahigh risk (UHR) for psychosis. Although there is evidence that observer ratings of negative symptoms are associated with level of functioning, the predictive value of subjective experience in daily life for individuals at UHR has not been studied yet. Objective This study therefore aims to investigate the predictive value of momentary manifestations of negative symptoms for clinical outcomes in individuals at UHR. Methods Experience sampling methodology was used to measure momentary manifestations of negative symptoms (blunted affective experience, lack of social drive, anhedonia, and social anhedonia) in the daily lives of 79 individuals at UHR. Clinical outcomes (level of functioning, illness severity, UHR status, and transition status) were assessed at baseline and at 1- and 2-year follow-ups. Results Lack of social drive, operationalized as greater experienced pleasantness of being alone, was associated with poorer functioning at the 2-year follow-up (b=−4.62, P=.01). Higher levels of anhedonia were associated with poorer functioning at the 1-year follow-up (b=5.61, P=.02). Higher levels of social anhedonia were associated with poorer functioning (eg, disability subscale: b=6.36, P=.006) and greater illness severity (b=−0.38, P=.045) at the 1-year follow-up. In exploratory analyses, there was evidence that individuals with greater variability of positive affect (used as a measure of blunted affective experience) experienced a shorter time to remission from UHR status at follow-up (hazard ratio=4.93, P=.005). Conclusions Targeting negative symptoms in individuals at UHR may help to predict clinical outcomes and may be a promising target for interventions in the early stages of psychosis.