An Exploratory Randomized Controlled Trial of Personalized Lifestyle Advice and Tandem Skydives as a Means to Reduce Anhedonia

A simulation-based network analysis of intervention targets for comorbid symptoms of depression and anxiety in Chinese healthcare workers in the post-dynamic zero-COVID policy era

BACKGROUND

After the official end of the dynamic zero-COVID policy in China, healthcare workers continued to heavy workloads and psychological stress. In this new phase, concerns related to work and family, rather than infection, may have become new sources of psychological issues such as depression and anxiety among healthcare workers, leading to new patterns of comorbidity. However, few studies have addressed these issues. To fill this gap, this study used network analysis to examine new features and mechanisms of comorbidity between depression and anxiety symptoms, and simulated symptom-specific interventions to identify effective targets for intervention.

METHODS

A total of 708 Chinese healthcare workers (71.2% females; Age: M = 37.55, SD = 9.37) were recruited and completed the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7). This study first calculated the incidence rates of anxiety, depression, and their comorbidity, and then constructed the comorbid Ising network. Central and bridge symptoms were identified with expected influence (EI) and bridge EI, respectively. The NodeIdentifyR algorithm (NIRA) was then used to simulate interventions within the network, examining the effects of alleviating or aggravating specific symptoms on the network's severity.

RESULTS

48.2% of Chinese healthcare workers reported experiencing depression (19.8%), anxiety (11.7%), or both (16.2%). In the anxiety-depression network, "guilt" and "appetite changes" were identified as the central symptoms, and "guilt" and "excessive worry" were identified as the bridge symptoms. Simulated interventions suggested that alleviating "Anhedonia" can the most reduce the overall severity of the network, while aggravating "guilt" can the most increase the overall severity. These two symptoms were considered the key target for treatment and prevention, respectively.

CONCLUSIONS

Chinese healthcare workers still face high risk of depression, anxiety, and comorbidity in the post-dynamic zero-COVID policy era. Our findings highlight the key roles of guilt, appetite changes, and excessive worry in the network of depression and anxiety symptoms. Future research should apply the results of the simulated interventions, develop intervention strategies targeting anhedonia, and focus on preventing guilt to improve the healthcare workers' mental health.

TRIAL REGISTRATION

Not applicable.

Using ecological momentary assessment and machine learning techniques to predict depressive symptoms in emerging adults

The objective of this study was to predict the level of depressive symptoms in emerging adults by analyzing sociodemographic variables, affect, and emotion regulation strategies. Participants were 33 emerging adults (M = 24.43; SD = 2.80; 56.3 % women). They were asked to assess their current emotional state (positive or negative affect), recent events that may relate to that state, and emotion regulation strategies through ecological momentary assessment. Participants were prompted randomly by an app 6 times per day between 10 am and 10 pm for a seven-day period. They answered 1233 of the 2058 surveys (beeps), collectively. The analysis of observations, using Machine Learning (ML) techniques, showed that the Random Forest algorithm yields significantly better predictions than other models. The algorithm used 13 out of the 36 variables adopted in the study. Furthermore, the study revealed that age, emotion of worried and a specific emotion regulation strategy related to social exchange were the most accurate predictors of severe depressive symptoms. By carefully selecting predictors and utilizing appropriate sorting techniques, these findings may provide valuable supplementary information to traditional diagnostic methods and psychological assessments.

The dynamics of social activation and suspiciousness in individuals at ultra-high risk for psychosis

INTRODUCTION

Social functioning is often impaired during the ultra-high risk (UHR) phase for psychosis, but group-level studies regarding the role of social functioning in transition to psychosis are inconsistent. Exploring the inter-individual differences which underlie the association between social functioning and psychotic symptoms in this phase could yield new insights.

OBJECTIVE

To examine the idiographic and dynamic association between social activation and suspiciousness in individuals at UHR for psychosis using time-series analysis.

METHODS

Twenty individuals at UHR for psychosis completed a diary application every evening for 90 days. Two items on social activation (quantity: 'time spent alone' and quality: 'feeling supported') and two items on suspiciousness ('feeling suspicious' and 'feeling disliked') were used. Time series (T = 90) of each individual were analyzed using vector auto regression analysis (VAR), to estimate the lagged (over 1 day) effect of social activation on suspiciousness, and vice versa, as well as their contemporaneous associations.

RESULTS

Heterogeneous person-specific associations between social activation and suspiciousness were found in terms of strength, direction and temporal aspects.

CONCLUSIONS

The association between social activation and suspiciousness differs amongst individuals who are at UHR for psychosis. These findings underline the importance of tailoring psychosocial interventions to the individual. Future studies may examine whether using results of single-subject studies in clinical practice to personalize treatment goals leads to better treatment outcomes.

Sensitivity to intrinsic rewards is domain general and related to mental health

Humans frequently engage in intrinsically rewarding activities (for example, consuming art, reading). Despite such activities seeming diverse, we show that sensitivity to intrinsic rewards is domain general and associated with mental health. In this cross-sectional study, participants online (N = 483) were presented with putative visual, cognitive and social intrinsic rewards as well as monetary rewards and neutral stimuli. All rewards elicited positive feelings (were 'liked'), generated consummatory behaviour (were 'wanted') and increased the likelihood of the action leading to them (were 'reinforcing'). Factor analysis revealed that ~40% of response variance across stimuli was explained by a general sensitivity to all rewards, but not to neutral stimuli. Affective aspects of mental health were associated with sensitivity to intrinsic, but not monetary, rewards. These results may help explain thriving and suffering: individuals with high reward sensitivity will engage in a variety of intrinsically rewarding activities, eventually finding those they excel at, whereas low sensitivity individuals will not.

How to explore within-person and between-person measurement model differences in intensive longitudinal data with the R package lmfa

Intensive longitudinal data (ILD) have become popular for studying within-person dynamics in psychological constructs (or between-person differences therein). Before investigating the dynamics, it is crucial to examine whether the measurement model (MM) is the same across subjects and time and, thus, whether the measured constructs have the same meaning. If the MM differs (e.g., because of changes in item interpretation or response styles), observations cannot be validly compared. Exploring differences in the MM for ILD can be done with latent Markov factor analysis (LMFA), which classifies observations based on the underlying MM (for many subjects and time points simultaneously) and thus shows which observations are comparable. However, the complexity of the method or the fact that no open-source software for LMFA existed until now may have hindered researchers from applying the method in practice. In this article, we provide a step-by-step tutorial for the new user-friendly software package lmfa, which allows researchers to easily perform the analysis LMFA in the freely available software R to investigate MM differences in their own ILD.

Evaluating Covariate Effects on ESM Measurement Model Changes with Latent Markov Factor Analysis: A Three-Step Approach

Invariance of the measurement model (MM) between subjects and within subjects over time is a prerequisite for drawing valid inferences when studying dynamics of psychological factors in intensive longitudinal data. To conveniently evaluate this invariance, latent Markov factor analysis (LMFA) was proposed. LMFA combines a latent Markov model with mixture factor analysis: The Markov model captures changes in MMs over time by clustering subjects' observations into a few states and state-specific factor analyses reveal what the MMs look like. However, to estimate the model, Vogelsmeier, Vermunt, van Roekel, and De Roover (2019) introduced a one-step (full information maximum likelihood; FIML) approach that is counterintuitive for applied researchers and entails cumbersome model selection procedures in the presence of many covariates. In this paper, we simplify the complex LMFA estimation and facilitate the exploration of covariate effects on state memberships by splitting the estimation in three intuitive steps: (1) obtain states with mixture factor analysis while treating repeated measures as independent, (2) assign observations to the states, and (3) use these states in a discrete- or continuous-time latent Markov model taking into account classification errors. A real data example demonstrates the empirical value.

Practitioner and researcher perspectives on the utility of ecological momentary assessment in mental health care: A survey study

BACKGROUND

Ecological momentary assessment (EMA) is a scientific self-monitoring method to capture individuals' daily life experiences. Early on, EMA has been suggested to have the potential to improve mental health care. However, it remains unclear if and how EMA should be implemented. This requires an in-depth investigation of how practitioners and researchers view the implementation of EMA.

OBJECTIVE

Explore the perspectives of mental health practitioners and EMA researchers on the utility of EMA for mental health care.

METHODS

Practitioners (n = 89; psychiatrists, psychologists, psychiatric nurses) and EMA researchers (n = 62) completed a survey about EMA in clinical practice. This survey addressed EMA goals for practitioner and patient, requirements regarding clinical use of EMA, and (dis)advantages of EMA compared to treatment-as-usual. t-Tests were used to determine agreement with each statement and whether practitioners' and researchers' views differed significantly. Linear regression was used to explore predictors of goals and preferences (e.g., EMA experience).

RESULTS

Practitioners and researchers considered EMA to be a useful clinical tool for diverse stages of care. They indicated EMA to be most useful for gaining insight into the context specificity of symptoms (55.0 %), whereas receiving alerts when symptoms increase was rated the least useful (11.3 %, alerts is in 95 % of bootstrap iterations between rank 8 and 10). Compared to treatment-as-usual, EMA was considered easier to use (M = 4.87, t = 5.30, p < .001) and interpret (M = 4.52, t = 3.61, p < .001), but also more burdensome for the patient (M = 4.48, t = 3.17, p < .001). Although participants preferred personalization of the EMA diary, they also suggested that EMA should cost practitioners and patients limited time. The preference for creating personalized EMA was related to the level of experience with EMA. Finally, they highlighted the need for practitioner training and patient full-time access to the EMA feedback.

CONCLUSIONS

This survey study demonstrated that practitioners and researchers expect EMA to have added value for mental health care. Concrete recommendations for implementation of EMA are formulated. This may inform the development of specific clinical applications and user-friendly EMA software.

A Web-Based Application for Personalized Ecological Momentary Assessment in Psychiatric Care: User-Centered Development of the PETRA Application

BACKGROUND

Smartphone self-monitoring of mood, symptoms, and contextual factors through ecological momentary assessment (EMA) provides insights into the daily lives of people undergoing psychiatric treatment. Therefore, EMA has the potential to improve their care. To integrate EMA into treatment, a clinical tool that helps clients and clinicians create personalized EMA diaries and interpret the gathered data is needed.

OBJECTIVE

This study aimed to develop a web-based application for personalized EMA in specialized psychiatric care in close collaboration with all stakeholders (ie, clients, clinicians, researchers, and software developers).

METHODS

The participants were 52 clients with mood, anxiety, and psychotic disorders and 45 clinicians (psychiatrists, psychologists, and psychiatric nurses). We engaged them in interviews, focus groups, and usability sessions to determine the requirements for an EMA web application and repeatedly obtained feedback on iteratively improved high-fidelity EMA web application prototypes. We used human-centered design principles to determine important requirements for the web application and designed high-fidelity prototypes that were continuously re-evaluated and adapted.

RESULTS

The iterative development process resulted in Personalized Treatment by Real-time Assessment (PETRA), which is a scientifically grounded web application for the integration of personalized EMA in Dutch clinical care. PETRA includes a decision aid to support clients and clinicians with constructing personalized EMA diaries, an EMA diary item repository, an SMS text message-based diary delivery system, and a feedback module for visualizing the gathered EMA data. PETRA is integrated into electronic health record systems to ensure ease of use and sustainable integration in clinical care and adheres to privacy regulations.

CONCLUSIONS

PETRA was built to fulfill the needs of clients and clinicians for a user-friendly and personalized EMA tool embedded in routine psychiatric care. PETRA is unique in this codevelopment process, its extensive but user-friendly personalization options, its integration into electronic health record systems, its transdiagnostic focus, and its strong scientific foundation in the design of EMA diaries and feedback. The clinical effectiveness of integrating personalized diaries via PETRA into care requires further research. As such, PETRA paves the way for a systematic investigation of the utility of personalized EMA for routine mental health care.

Feasibility, usability and clinical value of intensive longitudinal diary assessments in older persons with cognitive impairment and depressive symptoms

OBJECTIVES

To evaluate the feasibility, usability and clinical value of daily diary assessments combined with actigraphy in older persons with cognitive impairment.

METHODS

For 63 days, patients ≥60 years with cognitive impairments filled out a daily diary (including standardized questionnaires and cognitive test battery), and wore an actiwatch (sleep). After the study, participants and clinicians received personal feedback about patterns and daily triggers of depressive symptoms, sleep and cognitive performance. We assessed feasibility (participation rate, compliance and subjective burden), usability (variability and floor- or ceiling effects) and clinical value for patients and their clinicians (questionnaires).

RESULTS

Of 96 eligible patients, 13 agreed to participate (13.5%). One patient dropped out after 2 days, another after 37 days, and another did not complete the cognitive test battery. Compliance rate was high (6.7-10% missing values). Subjective burden was relatively low. Time-series data showed sufficient variability and no floor- or ceiling effects, except for one relevant ceiling effect on the One Back task. The personal feedback report was considered insightful by 4 out of 11 participants and 5 out of 7 clinicians.

CONCLUSION

Daily assessments are suitable for a minority of cognitively impaired older persons, but is helpful to increase insight into their symptoms.

Temporal dynamics of depression, cognitive performance and sleep in older persons with depressive symptoms and cognitive impairments: a series of eight single-subject studies

OBJECTIVES

To investigate the presence, nature and direction of the daily temporal association between depressive symptoms, cognitive performance and sleep in older individuals.

DESIGN, SETTING, PARTICIPANTS

Single-subject study design in eight older adults with cognitive impairments and depressive symptoms.

MEASUREMENTS

For 63 consecutive days, depressive symptoms, working memory performance and night-time sleep duration were daily assessed with an electronic diary and actigraphy. The temporal associations of depressive symptoms, working memory and total sleep time were evaluated for each participant separately with time-series analysis (vector autoregressive modeling).

RESULTS

For seven out of eight participants we found a temporal association between depressive symptoms and/or sleep and/or working memory performance. More depressive symptoms were preceded by longer sleep duration in one person (r = 0.39; p < .001), by longer or shorter sleep duration than usual in one other person (B = 0.49; p < .001), by worse working memory in one person (B = -0.45; p = .007), and by better working memory performance in one other person (B = 0.35; p = .009). Worse working memory performance was preceded by longer sleep duration (r = -.35; p = .005) in one person, by shorter or longer sleep duration in three other persons (B = -0.76; p = .005, B = -0.61; p < .001; B = -0.34; p = .002), and by more depressive symptoms in one person (B = -0.25; p = .009).

CONCLUSION

The presence, nature and direction of the temporal associations between depressive symptoms, cognitive performance and sleep differed between individuals. Knowledge of personal temporal associations may be valuable for the development of personalized intervention strategies in order to maintain their health, quality of life, functional outcomes and independence.

A Review of Explicit and Implicit Assumptions When Providing Personalized Feedback Based on Self-Report EMA Data

Ecological Momentary Assessment (EMA) in which participants report on their moment-to-moment experiences in their natural environment, is a hot topic. An emerging field in clinical psychology based on either EMA, or what we term Ecological Retrospective Assessment (ERA) as it requires retrospectivity, is the field of personalized feedback. In this field, EMA/ERA-data-driven summaries are presented to participants with the goal of promoting their insight in their experiences. Underlying this procedure are some fundamental assumptions about (i) the relation between true moment-to-moment experiences and retrospective evaluations of those experiences, (ii) the translation of these experiences and evaluations to different types of data, (iii) the comparison of these different types of data, and (iv) the impact of a summary of moment-to-moment experiences on retrospective evaluations of those experiences. We argue that these assumptions deserve further exploration, in order to create a strong evidence-based foundation for the personalized feedback procedure.

Measuring parent-adolescent interactions in natural habitats. The potential, status, and challenges of ecological momentary assessment

Few people are as important for an adolescent's development as their parents. However, most research on parent-adolescent relationships describes long-term population-wide effects. Therefore, little is known about everyday interactions between adolescents and parents in individual families. Ecological momentary assessment (EMA) measures families several times a day as they go through daily life. This approach provides ecologically valid insights into which interactions took place and how they were experienced. State-of-the-art EMA studies suggest that within-family fluctuations in parenting may trigger changes in an adolescent's well-being and behaviors. In practice, moreover, EMA may strengthen family support and intervention research. This article reviews recent empirical work, highlights the (un)used theoretical and practical promise of EMA and identifies key-challenges to unlock this full potential.

Personalizing Psychological Care for Chronic Cancer-Related Fatigue: A Case Study on Symptom Dynamics

Approximately 25% of cancer patients suffer from chronic cancer-related fatigue (CCRF), which is a complex, multifactorial condition. While there are evidence-based interventions, it remains unclear what treatment works best for the individual patient. Psychological network models can offer a schematic representation of interrelations among fatigue and protective and perpetuating factors for the individual patient. We explored whether feedback based on these individual fatigue networks can help personalize psychological care for CCRF. A 34-year old woman with CCRF was referred to our mental healthcare institute for psycho-oncology. During the waitlist period, she filled out an experience sampling app for 101 days, including five daily assessments of fatigue, pain, mood, activity and fatigue coping. The interplay between items was visualized in network graphs at the moment-level and day-level, which were discussed with the patient. For example, acceptance of fatigue in the past three hours was associated with less hopelessness and less fatigue in the following moment. At the day-level, acceptance was also being associated with less fatigue, less hopelessness, a better mood, and more motivation to do things. The patient recognized these patterns and explained how unexpected waves of fatigue can make her feel hopeless. This started a dialogue on how cultivating acceptance could potentially help her handle the fatigue. The patient would discuss this with her therapist. Feedback based on individual fatigue networks can provide direct insight into how one copes with CCRF and subsequently offer directions for treatment. Further research is needed in order to implement this in clinical practice.

Personalized lifestyle advice alters affective reactivity to negative events in anhedonic young adults

BACKGROUND

Anhedonia is a common symptom of several disorders, but cost-effective treatments that focus on anhedonia specifically have been lacking. Therefore, personalized lifestyle advice has recently been investigated as a suitable means of enhancing pleasure and positive affect (PA) in young adults with anhedonia. This intervention provided individuals with a personalized lifestyle advice which was based on observed individual patterns of lifestyle behaviors and experienced pleasure in daily life. The present study extends this previous work by examining a potential mechanism of treatment success, affective reactivity.

METHODS

We explored changes in affective reactivity to events in daily life from pre- to post-intervention in a subclinical sample of young adults with anhedonia (N = 69). Using the Experience Sampling Method (ESM), participants answered questions on their activities, their pleasure levels, PA and negative affect (NA) before and after the intervention.

RESULTS

Multilevel analysis revealed that participants did not experience an altered affective reactivity to positive events after the intervention. The affective reactivity to negative events depended on the level of improvement in mean-PA after the lifestyle advice intervention.

LIMITATIONS

The present study used a subclinical sample with the majority of participants being female which limited the generalizability of the findings.

CONCLUSION

This study suggests that an altered affective reactivity to negative events is an underlying mechanism of the effectiveness of a personalized lifestyle advice.

Universal and Selective Interventions to Prevent Poor Mental Health Outcomes in Young People: Systematic Review and Meta-analysis

BACKGROUND

Much is not known about the efficacy of interventions to prevent poor mental health outcomes in young people by targeting either the general population (universal prevention) or asymptomatic individuals with high risk of developing a mental disorder (selective prevention).

METHODS

We conducted a PRISMA/MOOSE-compliant systematic review and meta-analysis of Web of Science to identify studies comparing post-test efficacy (effect size [ES]; Hedges' g) of universal or selective interventions for poor mental health outcomes versus control groups, in samples with mean age <35 years (PROSPERO: CRD42018102143). Measurements included random-effects models, I2 statistics, publication bias, meta-regression, sensitivity analyses, quality assessments, number needed to treat, and population impact number.

RESULTS

295 articles (447,206 individuals; mean age = 15.4) appraising 17 poor mental health outcomes were included. Compared to control conditions, universal and selective interventions improved (in descending magnitude order) interpersonal violence, general psychological distress, alcohol use, anxiety features, affective symptoms, other emotional and behavioral problems, consequences of alcohol use, posttraumatic stress disorder features, conduct problems, tobacco use, externalizing behaviors, attention-deficit/hyperactivity disorder features, and cannabis use, but not eating-related problems, impaired functioning, internalizing behavior, or sleep-related problems. Psychoeducation had the highest effect size for ADHD features, affective symptoms, and interpersonal violence. Psychotherapy had the highest effect size for anxiety features.

CONCLUSION

Universal and selective preventive interventions for young individuals are feasible and can improve poor mental health outcomes.

Internet and smartphone-based ecological momentary assessment and personalized advice (PROfeel) in adolescents with chronic conditions: A feasibility study

OBJECTIVE

Growing up with a chronic disease comes with challenges, such as coping with fatigue. Many adolescents are severely fatigued, though its associated factors exhibit considerable interpersonal and longitudinal variation. We assessed whether PROfeel, a combination of a smartphone-based ecological momentary assessment (EMA) method using the internet, followed by a face-to-face dialogue and personalized advice for improvement of symptoms or tailor treatment based on a dynamic network analysis report, was feasible and useful.

STUDY DESIGN

Feasibility study in fatigued outpatient adolescents 12-18 years of age with cystic fibrosis, autoimmune disease, post-cancer treatment, or with medically unexplained fatigue. Participants were assessed at baseline to personalize EMA questions. EMA was conducted via smartphone notifications five times per day for approximately six weeks. Hereby, data was collected via the internet. The EMA results were translated into a personalized report, discussed with the participant, and subsequently translated into a personalized advice. Afterwards, semi-structured interviews on feasibility and usefulness were held.

RESULTS

Fifty-seven adolescents were assessed (mean age 16.2 y ± 1.6, 16% male). Adolescents deemed the smartphone-based EMA feasible, with the app being used for an average of 49 days. Forty-two percent of the notifications were answered and 85% of the participants would recommend the app to other adolescents. The personalized report was deemed useful and comprehensible and 95% recognized themselves in the personalized report, with 64% rating improved insight in their symptoms and subsequent steps towards an approach to reduce one's fatigue as good or very good.

CONCLUSIONS

PROfeel was found to be highly feasible and useful for fatigued adolescents with a chronic condition. This innovative method has clinical relevance through bringing a patient's daily life into the clinical conversation.

Latent Markov Latent Trait Analysis for Exploring Measurement Model Changes in Intensive Longitudinal Data

Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requires the measurement model (MM)-indicating how items relate to constructs-to be invariant across subjects and time-points. When assessing subjects in their daily life, however, there may be multiple MMs, for instance, because subjects differ in their item interpretation or because the response style of (some) subjects changes over time. The recently proposed "latent Markov factor analysis" (LMFA) evaluates (violations of) measurement invariance by classifying observations into latent "states" according to the MM underlying these observations such that MMs differ between states but are invariant within one state. However, LMFA is limited to normally distributed continuous data and estimates may be inaccurate when applying the method to ordinal data (e.g., from Likert items) with skewed responses or few response categories. To enable researchers and health professionals with ordinal data to evaluate measurement invariance, we present "latent Markov latent trait analysis" (LMLTA), which builds upon LMFA but treats responses as ordinal. Our application shows differences in MMs of adolescents' affective well-being in different social contexts, highlighting the importance of studying measurement invariance for drawing accurate inferences for psychological science and practice and for further understanding dynamics of psychological constructs.

The Link between Parental Support and Adolescent Negative Mood in Daily Life: between-Person Heterogeneity in within-Person Processes

Lack of parental support is related to more adolescent negative mood. However, little is known about how fluctuations of parental support relate to fluctuations of negative mood within adolescents in daily life. The current study aimed to elucidate these processes at a day to day micro-level and examined to which extent adolescents would differ in the association between perceived parental support and adolescent negative mood. The sample consisted of 242 Dutch adolescents (Mage = 13.82, 63.2% female) who completed ecological momentary assessments of 3 weeks 3 months apart. Results from the multilevel regression analyses showed that, on average, adolescents experienced higher levels of negative mood on days when they perceived their parents to be less supportive. Substantial individual differences were found in this association, however, these were partially explained by the level of depressive symptoms and perceived parental intrusiveness. These findings suggest that advice on parental support should be tailored to the unique characteristics of the adolescent.

ESMvis: a tool for visualizing individual Experience Sampling Method (ESM) data

Purpose

The experience sampling method (ESM) is used for intensive longitudinal time-series data collection during normal daily life. ESM data give information on momentary affect, activities and (social) context of, for example, patients suffering from mental disorders, and allows for person-specific feedback reports. However, current personalized feedback reports only display a selection of measured variables, and typically involve only summary statistics, thus not reflecting the dynamic fluctuations in affect and its influencing factors. To address this shortcoming, we developed a tool for dynamically visualizing ESM data.

Methods

We introduce a new framework, ESMvis, for giving descriptive feedback, focusing on direct visualization of the dynamic nature of raw data. In this ESM feedback approach, raw ESM data are visualized using R software. We applied ESMvis to data collected for over 52 weeks on a patient diagnosed with an obsessive–compulsive disorder with comorbid depression.

Results

We provided personalized feedback, in which both the overall trajectory and specific time moments were captured in a movie format. Two relapses during the study period could be visually determined, and subsequently confirmed by the therapist. The therapist and patient evaluated ESMvis as an insightful add-on tool to care-as-usual.

Conclusion

ESMvis is a showcase on providing personalized feedback by dynamic visualization of ESM time-series data. Our tool is freely available and adjustable, making it widely applicable. In addition to potential applications in clinical practice, ESMvis can work as an exploratory tool that can lead to new hypotheses and inform more complex statistical techniques.

Electronic supplementary material

The online version of this article (10.1007/s11136-020-02701-4) contains supplementary material, which is available to authorized users.

Single-Subject Research in Psychiatry: Facts and Fictions

Scientific evidence in the field of psychiatry is mainly derived from group-based ("nomothetic") studies that yield group-aggregated results, while often the need is to answer questions that apply to individuals. Particularly in the presence of great inter-individual differences and temporal complexities, information at the individual-person level may be valuable for personalized treatment decisions, individual predictions and diagnostics. The single-subject study design can be used to make inferences about individual persons. Yet, the single-subject study is not often used in the field of psychiatry. We believe that this is because of a lack of awareness of its value rather than a lack of usefulness or feasibility. In the present paper, we aimed to resolve some common misconceptions and beliefs about single-subject studies by discussing some commonly heard "facts and fictions." We also discuss some situations in which the single-subject study is more or less appropriate, and the potential of combining single-subject and group-based study designs into one study. While not intending to plea for single-subject studies at the expense of group-based studies, we hope to increase awareness of the value of single-subject research by informing the reader about several aspects of this design, resolving misunderstanding, and providing references for further reading.

Measuring psychopathology as it unfolds in daily life: addressing key assumptions of intensive longitudinal methods in the TRAILS TRANS-ID study

BACKGROUND

Intensive longitudinal (IL) designs provide the potential to study symptoms as they evolve in real-time within individuals. This has promising clinical implications, potentially allowing conclusions at the level of specific individuals. The current study aimed to establish the feasibility of IL designs, as indicated by self-rated burden and attrition, in the context of psychiatry. Additionally, we evaluated three core assumptions about the instruments (diary items) used in IL designs. These assumptions are: diary items (1) reflect experiences that change over time within individuals (indicated by item variability), (2) are interpreted consistently over time, and (3) correspond to retrospective assessments of psychopathology.

METHODS

TRAILS TRANS-ID is an add-on IL study in the clinical cohort of the TRAILS study. Daily diaries on psychopathological symptoms for six consecutive months were completed by 134 at risk young adults (age 22.6 ± 0.6 years). At baseline, immediately after the diary period, and one year after the diary period, participants completed a diagnostic interview.

RESULTS

Excellent compliance (88.5% of the diaries completed), low participant burden (M = 3.21; SD = 1.42; range 1-10), and low attrition (8.2%) supported the feasibility of six-month IL designs. Diary items differed in their variability over time. Evaluation of the consistency of diary item interpretations showed that within-individual variability in scores could not be attributed to changing interpretations over time. Further, daily symptom reports reasonably correlated with retrospective assessments (over a six month period) of psychopathology obtained with the diagnostic interview, suggesting that both measures might complement each other.

CONCLUSION

The current study is the first to show that IL designs over extensive periods (i.e., multiple months) in psychiatry are feasible, and meet three core assumptions to study change in psychopathology. This might allow for addressing novel and promising hypotheses in our field, and might substantially alter how we treat and study mental ill-health.

Personalized eHealth Program for Life-style Change: Results From the "Do Cardiac Health Advanced New Generated Ecosystem (Do CHANGE 2)" Randomized Controlled Trial

OBJECTIVE

Unhealthy life-style factors have adverse outcomes in cardiac patients. However, only a minority of patients succeed to change unhealthy habits. Personalization of interventions may result in critical improvements. The current randomized controlled trial provides a proof of concept of the personalized Do Cardiac Health Advanced New Generation Ecosystem (Do CHANGE) 2 intervention and evaluates effects on a) life-style and b) quality of life over time.

METHODS

Cardiac patients (n = 150; mean age = 61.97 ± 11.61 years; 28.7% women; heart failure, n = 33; coronary artery disease, n = 50; hypertension, n = 67) recruited from Spain and the Netherlands were randomized to either the "Do CHANGE 2" or "care as usual" group. The Do CHANGE 2 group received ambulatory health-behavior assessment technologies for 6 months combined with a 3-month behavioral intervention program. Linear mixed-model analysis was used to evaluate the intervention effects, and latent class analysis was used for secondary subgroup analysis.

RESULTS

Linear mixed-model analysis showed significant intervention effects for life-style behavior (Finteraction(2,138.5) = 5.97, p = .003), with improvement of life-style behavior in the intervention group. For quality of life, no significant main effect (F(1,138.18) = .58, p = .447) or interaction effect (F(2,133.1) = 0.41, p = .67) was found. Secondary latent class analysis revealed different subgroups of patients per outcome measure. The intervention was experienced as useful and feasible.

CONCLUSIONS

The personalized eHealth intervention resulted in significant improvements in life-style. Cardiac patients and health care providers were also willing to engage in this personalized digital behavioral intervention program. Incorporating eHealth life-style programs as part of secondary prevention would be particularly useful when taking into account which patients are most likely to benefit.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT03178305.

Personalized Models of Psychopathology

The personalized approach to psychopathology conceptualizes mental disorder as a complex system of contextualized dynamic processes that is nontrivially specific to each individual, and it seeks to develop formal idiographic statistical models to represent these individual processes. Although the personalized approach draws on long-standing influences in clinical psychology, there has been an explosion of research in recent years following the development of intensive longitudinal data capture and statistical techniques that facilitate modeling of the dynamic processes of each individual's pathology. Advances are also making idiographic analyses scalable and generalizable. We review emerging research using the personalized approach in descriptive psychopathology, precision assessment, and treatment selection and tailoring, and we identify future challenges and areas in need of additional research. The personalized approach to psychopathology holds promise to resolve thorny diagnostic issues, generate novel insights, and improve the timing and efficacy of interventions.

Applied ambulatory assessment: Integrating idiographic and nomothetic principles of measurement

Ambulatory assessment (AA; also known as ecological momentary assessment) has enjoyed enthusiastic implementation in psychological research. The ability to assess thoughts, feelings, behavior, physiology, and context intensively and repeatedly in the moment in an individual's natural ecology affords access to data that can answer exciting questions about sequences of events and dynamic processes in daily life. AA also holds unique promise for developing personalized models of individuals (i.e., precision or person-specific assessment) that might be transformative for applied settings such as clinical practice. However, successfully translating AA from bench to bedside is challenging because of the inherent tension between idiographic and nomothetic principles of measurement. We argue that the value of applied AA will be most fully realized by balancing the ability to develop personalized models with ensuring comparability among individuals. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A Review of Current Ambulatory Assessment Studies in Adolescent Samples and Practical Recommendations

The use of ambulatory assessment (AA) and related methods (experience sampling, ecological momentary assessment) has greatly increased within the field of adolescent psychology. In this guide, we describe important practices for conducting AA studies in adolescent samples. To better understand how researchers have been implementing AA study designs, we present a review of 23 AA studies that were conducted in adolescent samples from 2017. Results suggest that there is heterogeneity in how AA studies in youth are conducted and reported. Based on these insights, we provide recommendations with regard to participant recruitment, sampling scheme, item selection, power analysis, and software choice. Further, we provide a checklist for reporting on AA studies in adolescent samples that can be used as a guideline for future studies.

Keeping secrets from parents: on galloping horses, prancing ponies and pink unicorns

We identify the need for a new wave of research on adolescent secrecy in their relationship with parents that relinquishes the focus on the nomothetic objective of finding general principles. This third wave builds on novel insights on three fallacies committed in previous waves of research: (1) between-person effects do not necessarily provide insights into within-family processes (the ecological fallacy), (2) within-family processes are not necessarily homogeneous across adolescents and families (the one size fits all fallacy), and (3) longer-term effects are not necessarily identical to short-term processes (the galloping horse fallacy). This approach promises to provide us with a more person-specific understanding of adolescent secrecy from parents, which enables more tailored insights as to when and for whom secrecy is bad versus good.

The dynamical signature of anhedonia in major depressive disorder: positive emotion dynamics, reactivity, and recovery

BACKGROUND

Major Depressive Disorder (MDD) is the leading cause of disability worldwide. The cardinal features of MDD are depressed mood and anhedonia. Anhedonia is defined as a "markedly diminished interest or pleasure in all, or almost all, activities of the day", and has generally been investigated on group-level using retrospective data (e.g. via questionnaire/interview). However, inferences based on group-level findings not necessarily generalize to daily life experiences within individuals.

METHODS

We repeatedly sampled pleasurable experiences within individuals' daily lives by means of Experience Sampling Methods, and compared how positive affect unfolded in the daily life of healthy controls versus patients diagnosed with MDD and anhedonia. We sampled Positive Affect (PA) and reward experiences on 10 semi-random time points a day, for seven days in the daily lives of 47 MDD patients with anhedonia, and 40 controls.

RESULTS

Multilevel models showed that anhedonia was associated with low PA, but not to differences in PA dynamics, nor reward frequency in daily life. In reaction to rewards, MDD patients with anhedonia showed no difference in their increase in PA (i.e., PA reactivity), and showed no signs of a faster return to baseline thereafter (i.e., PA recovery).

CONCLUSIONS

Our results suggest that the dynamical signature of anhedonia in MDD can be described best as a lower average level of PA, and "normal" in terms of PA dynamics, daily reward reactivity and reward recovery. Preregistration: https://osf.io/gmfsc/register/565fb3678c5e4a66b5582f67 . Preprint: https://osf.io/cfkts.

The Efficacy of Vortioxetine on Anhedonia in Patients With Major Depressive Disorder

Background: Anhedonia is a common, persistent, and disabling phenomenon in treated adults with Major Depressive Disorder (MDD). Hitherto, relatively few antidepressant agents have been evaluated with respect to their effect on anhedonia in MDD. Methods: This is a post-hoc analysis of a primary study that sought to evaluate the sensitivity to change of the THINC-integrated tool (THINC-it) in MDD (ClinicalTrials.gov Identifier: NCT03053362). Adults meeting DSM-5 criteria for MDD with at least moderate depressive symptom severity [i.e., Montgomery Åsberg Depression Rating Scale (MADRS) total score ≥20] were eligible. Subjects were recruited between October 2017 and August 2018 in Toronto, Ontario at the Brain and Cognition Discovery Foundation. All subjects received open-label vortioxetine (10-20 mg/day, flexibly-dosed) for 8 weeks. Herein, the primary outcome of interest was the change from baseline to endpoint in the Snaith-Hamilton Pleasure Scale (SHAPS) total score, as well as the MADRS anhedonia factor. The mediational effects of improvements in anhedonia on general function and quality of life, as measured by the Sheehan Disability Scale (SDS) and the 5-Item World Health Organization Well-Being Index (WHO-5), were secondarily assessed. Results: A total of 100 subjects with MDD were enrolled in the primary study and began treatment with vortioxetine. Vortioxetine significantly improved anhedonia as evidenced by significant baseline to endpoint improvements in SHAPS and MADRS anhedonia factor scores (p < 0.0001). Improvements in the SHAPS and the MADRS anhedonia factor correlated with improvements in general function (i.e., SDS) and quality of life (i.e., WHO-5) (p < 0.0001). Notably, improvements in anhedonia were found to mediate the association between improvements in overall depressive symptom severity (i.e., MADRS total score) and social functioning (i.e., social life component of the SDS) (p = 0.026). Conclusion: The unmet need in depression is to improve patient functioning and other patient-reported outcomes (e.g., quality of life). Antidepressant interventions capable of attenuating anhedonia as well as cognitive dysfunction in MDD may help in this regard, as improvement in these domains have been associated with improvement in psychosocial function and quality of life.

Constructing a Reward-Related Quality of Life Statistic in Daily Life-a Proof of Concept Study Using Positive Affect

Background: Mental healthcare needs person-tailored interventions. Experience Sampling Method (ESM) can provide daily life monitoring of personal experiences. This study aims to operationalize and test a measure of momentary reward-related Quality of Life (rQoL). Intuitively, quality of life improves by spending more time on rewarding experiences. ESM clinical interventions can use this information to coach patients to find a realistic, optimal balance of positive experiences (maximize reward) in daily life. rQoL combines the frequency of engaging in a relevant context (a 'behavior setting') with concurrent (positive) affect. High rQoL occurs when the most frequent behavior settings are combined with positive affect or infrequent behavior settings co-occur with low positive affect. Methods: Resampling procedures (Monte Carlo experiments) were applied to assess the reliability of rQoL using various behavior setting definitions under different sampling circumstances, for real or virtual subjects with low-, average- and high contextual variability. Furthermore, resampling was used to assess whether rQoL is a distinct concept from positive affect. Virtual ESM beep datasets were extracted from 1,058 valid ESM observations for virtual and real subjects. Results: Behavior settings defined by Who-What contextual information were most informative. Simulations of at least 100 ESM observations are needed for reliable assessment. Virtual ESM beep datasets of a real subject can be defined by Who-What-Where behavior setting combinations. Large sample sizes are necessary for reliable rQoL assessments, except for subjects with low contextual variability. rQoL is distinct from positive affect. Conclusion: rQoL is a feasible concept. Monte Carlo experiments should be used to assess the reliable implementation of an ESM statistic. Future research in ESM should asses the behavior of summary statistics under different sampling situations. This exploration is especially relevant in clinical implementation, where often only small datasets are available.