Evidence for mood instability in patients with bipolar disorder: Applying multilevel hidden Markov modeling to intensive longitudinal ecological momentary assessment data.

Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment data in 20 patients with BD, yielding ∼9,820 assessments in total. Ecological momentary assessment data comprised self-report questionnaires (5 × daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model. HMM uncovered four mood states: neutral, elevated, mixed, and lowered, which aligned with weekly symptom scores. On average, patients remained < 25 hr in one state. In almost half of the patients, mood instability was observed. Switching between mood states, three patterns were identified: patients switching predominantly between (a) neutral and lowered states, (b) neutral and elevated states, and (c) mixed, elevated, and lowered states. In all, elevated and lowered mood states were interspersed by mixed states. The results indicate that chronic mood instability is a key feature of BD, even in "relatively" euthymic periods. This should be considered in theoretical and clinical conceptualizations of the disorder. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The temporal order of emotional, cognitive, and behavioral gains in daily life during treatment of depression.

OBJECTIVE: Despite the importance for understanding mechanisms of change, little is known about the order of change in daily life emotions, cognitions, and behaviors during treatment of depression. This study examined the within-person temporal order of emotional, cognitive, and behavioral improvements using ecological momentary assessment data. METHOD: Thirty-two individuals with diagnosed depression completed ecological momentary assessment questions on emotions (sad mood, happy mood), behaviors (social interaction, number of activities), and cognitive variables (worrying, negative self-thoughts) 5 times a day during a 4-month period in which they underwent psychotherapy for depression. Nonparametric change-point analyses were used to determine the timing of gains (i.e., improvements in the mean of each variable) for each individual. We then established whether the first (i.e., earliest) gains in emotions preceded, followed, or occurred in the same week as cognitive and behavioral gains for each individual. RESULTS: Contrary to our hypotheses, first gains in behaviors did not precede first emotional gains (3 times, 8%) more often than they followed them (26 times, 70%). Cognitive gains often occurred in the same week as first emotional gains (43 times, 58%) and less often preceded (13 times, 18%) or followed emotional gains (18 times, 24%). CONCLUSION: The first improvements in behaviors did not tend to precede the first improvements in emotions likely because fewer behavioral gains were found. The finding that cognitive variables tend to improve around the same time as sad mood may explain why many studies failed to find that cognitive change predicts later change in depressive symptoms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Monitoring emotional intensity and variability to forecast depression recurrence in real time in remitted adults.

OBJECTIVE: Recurrent depressive episodes are preceded by changing mean levels of repeatedly assessed emotions (e.g., feeling restless), which can be detected in real time using statistical process control (SPC). This study investigated whether monitoring changes in the standard deviation (SD) of emotions and negative thinking improves the early detection of recurrent depression. METHOD: Formerly depressed adults (N = 41) monitored their emotions five times a day for 4 consecutive months. During the study, 22 individuals experienced recurrent depression. We used SPC to detect warning signs (i.e., changing means and SDs) of four emotions (positive and negative affect with high or low arousal) and negative thinking. RESULTS: SD-based warning signs only preceded 23%-36% of recurrences, but almost never reflected a false alarm (0%-16%). Correspondingly, SD-based warnings had a high specificity (at the cost of sensitivity), while mean-based warnings had a higher sensitivity (but lower specificity). There was little overlap in mean- and SD-based warning signs. For the majority of emotions, monitoring for high SDs alongside monitoring changes in mean levels improved the detection of depression (p < .015) compared to when only monitoring for changing mean levels. CONCLUSIONS: Warning signs for depression manifest not only in changing mean levels of emotions and cognitions but also in increasing SDs. These warnings could eventually be used to detect not just who is at increased risk for depression but also when risk is rising. Further research is needed to evaluate the clinical utility of depression SPC. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Predicting recurrence of depression using cardiac complexity in individuals tapering antidepressants.

It is currently unknown whether the complexity and variability of cardiac dynamics predicts future depression and whether within-subject change herein precedes the recurrence of depression. We tested this in an innovative repeated single-subject study in individuals who had a history of depression and were tapering their antidepressants. In 50 individuals, electrocardiogram (ECG) derived Interbeat-interval (IBI) time-series data were collected for 5 min every morning and evening, for 4 months. Usable data were obtained from 14 participants who experienced a transition (i.e., a clinically significant increase in depressive symptoms) and 14 who did not. The mean, standard deviation, Higuchi dimension and multiscale entropy, calculated from IBIs, were examined for time trends. These quantifiers were also averaged over a baseline period and compared between the groups. No consistent trends were observed in any quantifier before increases in depressive symptoms within individuals. The entropy baseline levels significantly differed between the two groups (morning: P value < 0.001, Cohen's d = -2.185; evening: P value < 0.001, Cohen's d = -1.797) and predicted the recurrence of depressive symptoms, in the current sample. Moreover, higher mean IBIs and Higuchi dimensions were observed in individuals who experienced transitions. While we found little evidence to support the existence of within- individual warning signals in IBI time-series data preceding an upcoming depressive transition, our results indicate that individuals who taper antidepressants and showed lower entropy of cardiac dynamics exhibited a higher chance of recurrence of depression. Hence, entropy could be a potential digital phenotype for assessing the risk of recurrence of depression in the short term while tapering antidepressants.

Recurrence of depression can be foreseen by monitoring mental states with statistical process control.

Detecting early signs of recurrence of psychopathology is key for prevention and treatment. Personalized risk assessment is especially relevant for formerly depressed patients, for whom recurrence is common. We aimed to examine whether recurrence of depression can be accurately foreseen by applying Exponentially Weighted Moving Average (EWMA) statistical process control charts to Ecological Momentary Assessment (EMA) data. Participants were formerly depressed patients (n = 41) in remission who (gradually) discontinued antidepressants. Participants completed five smartphone-based EMA questionnaires a day for 4 months. EWMA control charts were used to prospectively detect structural mean shifts in high and low arousal negative affect (NA), high and low arousal positive affect (PA), and repetitive negative thinking in each individual. A significant increase in repetitive negative thinking (worry, negative thoughts about the self) was the most sensitive early sign of recurrence: this was detected in 18 out of 22 patients (82%) before recurrence and in 8 out of 19 patients (42%) who stayed in remission. A significant increase in NA high arousal (stress, irritation, restlessness) was the most specific early sign of recurrence: this was detected in 10 out of 22 patients (45%) before recurrence and in 2 out of 19 patients (11%) who stayed in remission. These mean changes were detected at least a month before recurrence in the majority of the participants. The outcomes were robust across EWMA parameter choices, but not when using fewer observations per day. The findings demonstrate the value of monitoring EMA data with EWMA charts for detecting prodromal symptoms of depression in real-time. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Real-time monitoring of increases in restlessness to assess idiographic risk of recurrence of depressive symptoms.

BACKGROUND: This confirmatory study aimed to examine whether we can foresee recurrence of depressive symptoms using personalized modeling of rises in restlessness. METHODS: Participants were formerly depressed patients (N = 41) in remission who (gradually) discontinued antidepressants. Participants completed five smartphone-based Ecological Momentary Assessments (EMA) a day, for a period of 4 months, yielding a total of 21 180 observations. Statistical Process Control by means of Exponentially Weighted Moving Average (EWMA) control charts was used to detect rises in the EMA item 'I feel restless', for each individual separately. RESULTS: An increase in restlessness was detected in 68.3% of the participants with recurring depressive symptoms, and in 26.3% of those who stayed in remission (Fisher's exact test p = 0.01, sensitivity was 68.3%, specificity was 73.7%). In the participants with a recurrence and an increase in restlessness, this increase could be detected in the prodromal phase of depression in 93.3% of the cases and at least a month before the onset of the core symptoms of depression in 66.7% of the cases. CONCLUSIONS: Restlessness is a common prodromal symptom of depression. The sensitivity and specificity of the EWMA charts was at least as good as prognostic models based on cross-sectional patient characteristics. An advantage of the current idiographic method is that the EWMA charts provide real-time personalized insight in a within-person increase in early signs of depression, which is key to alert the right patient at the right time.

Transitions in depression: if, how, and when depressive symptoms return during and after discontinuing antidepressants.

PURPOSE: The aim of the current study is to provide insight into if, how, and when meaningful changes occur in individual patients who discontinue antidepressant medication. Agreement between macro-level quantitative symptom data, qualitative ratings, and micro-level Ecological Momentary Assessments is examined. METHODS: During and shortly after antidepressant discontinuation, depressive symptoms and 'feeling down' were measured in 56 participants, using the SCL-90 depression subscale weekly (macro-level) for 6 months, and 5 Ecological Momentary Assessments daily (micro-level) for 4 months (30.404 quantitative measurements in total). Qualitative information was also obtained, providing additional information to verify that changes were clinically meaningful. RESULTS: At the macro-level, an increase in depressive symptoms was found in 58.9% of participants that (a) was statistically reliable, (b) persisted for 3 weeks and/or required intervention, and (c) was clinically meaningful to patients. Of these increases, 30.3% happened suddenly, 42.4% gradually, and for 27.3% criteria were inconclusive. Quantitative and qualitative criteria showed a very high agreement (Cohen's κ = 0.85) regarding if a participant experienced a recurrence of depression, but a moderate agreement (Cohen's κ = 0.49) regarding how that change occurred. At the micro-level, 41.1% of participants experienced only sudden increases in depressed mood, 12.5% only gradual, 30.4% experienced both types of increase, and 16.1% neither. CONCLUSION: Meaningful change is common in patients discontinuing antidepressants, and there is substantial heterogeneity in how and when these changes occur. Depressive symptom change at the macro-level is not the same as depressive symptom change at the micro-level.

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.

Daily dynamics of negative affect: indicators of rate of response to treatment and remission from depression?

More instability (MSSD) and variability (SD) of negative affect (NA) have been related to current and future depressive symptoms. We investigated whether NA instability and variability were predictive of the rate of symptom improvement during treatment and of reaching remission status. Forty-six individuals with major depressive disorder completed six days of ecological momentary assessments (10 beeps/day) before starting a combination of pharmacotherapy and supportive therapy. During and after treatment, the Hamilton Depression Rating Scale (HDRS) diagnostic interview was performed monthly for 18 months. The rate of change in HDRS scores over five months (during treatment) and remission status (HDRS ≤ 7) over eighteen months were predicted by the SD, MSSD and Mean of NA, and relevant baseline predictors. Higher Mean NA and baseline symptom severity, but not NA variability or instability, predicted stronger depressive symptom reduction during treatment. Higher odds of remitting were only associated with lower Mean NA. Higher mean NA may indicate more room for improvement and thus for a steeper rate of symptom change, while lower mean NA levels may imply that remission status is more readily reached. To resolve the inconclusive findings for instability and variability as predictors of symptom improvement replication in larger samples is required.

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.

Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals.

BACKGROUND: In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. The present study investigated whether EWS can anticipate manic and depressive transitions in individual patients with bipolar disorder. METHODS: Twenty bipolar type I/II patients (with ≥ 2 episodes in the previous year) participated in ecological momentary assessment (EMA), completing five questionnaires a day for four months (Mean = 491 observations per person). Transitions were determined by weekly completed questionnaires on depressive (Quick Inventory for Depressive Symptomatology Self-Report) and manic (Altman Self-Rating Mania Scale) symptoms. EWS (rises in autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective and symptomatic EMA states. Positive and negative predictive values were calculated to determine clinical utility. RESULTS: Eleven patients reported 1-2 transitions. The presence of EWS increased the probability of impending depressive and manic transitions from 32-36% to 46-48% (autocorrelation) and 29-41% (standard deviation). However, the absence of EWS could not be taken as a sign that no transition would occur in the near future. The momentary states that indicated nearby transitions most accurately (predictive values: 65-100%) were full of ideas, worry, and agitation. Large individual differences in the utility of EWS were found. CONCLUSIONS: EWS show theoretical promise in anticipating manic and depressive transitions in bipolar disorder, but the level of false positives and negatives, as well as the heterogeneity within and between individuals and preprocessing methods currently limit clinical utility.

A Narrative Review of Network Studies in Depression: What Different Methodological Approaches Tell Us About Depression.

The network theory of psychopathology proposes that mental disorders arise from direct interactions between symptoms. This theory provides a promising framework to understand the development and maintenance of mental disorders such as depression. In this narrative review, we summarize the literature on network studies in the field of depression. Four methodological network approaches are distinguished: (i) studies focusing on symptoms at the macro-level vs. (ii) on momentary states at the micro-level, and (iii) studies based on cross-sectional vs. (iv) time-series (dynamic) data. Fifty-six studies were identified. We found that different methodological approaches to network theory yielded largely inconsistent findings on depression. Centrality is a notable exception: the majority of studies identified either positive affect or anhedonia as central nodes. To aid future research in this field, we outline a novel complementary network theory, the momentary affect dynamics (MAD) network theory, to understand the development of depression. Furthermore, we provide directions for future research and discuss if and how networks might be used in clinical practice. We conclude that more empirical network studies are needed to determine whether the network theory of psychopathology can indeed enhance our understanding of the underlying structure of depression and advance clinical treatment.

Individual and common patterns in the order of symptom improvement during outpatient treatment for major depression.

BACKGROUND: Research so far provided few clues on the order in which depressive symptoms typically remit during treatment. This study examined which depressive symptoms improve first, and whether symptoms changed before, simultaneous with, or after the core symptoms of depression (i.e., sad mood, loss of pleasure, and loss of interest). METHODS: Participants were 176 patients with Major Depressive Disorder (MDD) receiving outpatient treatment (a combination of pharmacotherapy and psychological interventions) for depression. Participants filled out the Inventory of Depressive Symptomatology - Self Report (IDS-SR) for 16 to 20 consecutive weeks. For each symptom, the timing of onset of a persistent improvement was determined for each single-subject separately. RESULTS: Which symptoms improved first differed markedly across patients. The core depression symptoms improved 1.5 to 2 times more often before (48% - 60%) than after (19% -28%) depressive cognitions ('view of myself' and 'view of the future'), anxiety symptoms ('feeling irritable' and 'feeling anxious / tense') and vegetative symptoms ('loss of energy', 'slowed down', and 'physical energy'). Only improvements in suicidal thoughts were more likely to occur before (46% - 48%) than after (29%) improvements in the depression core symptoms. LIMITATIONS: Not all 'core depression-non-core symptom' combinations could be tested because some symptoms did not improve in a sufficient number of patients. CONCLUSIONS: Which improvements mark the start of symptom remission differed between patients. Improvements in the core depression symptoms 'sad mood', 'loss of interest', and 'loss of pleasure' were more likely to occur before than after improvements in non-core symptoms.

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.

Recommendations for the use of long-term experience sampling in bipolar disorder care: a qualitative study of patient and clinician experiences.

BACKGROUND: Self-monitoring has been shown to improve the self-management and treatment of patients with bipolar disorder. However, current self-monitoring methods are limited to once-daily retrospectively assessed mood, which may not suit the rapid mood fluctuations in bipolar disorder. The experience sampling method (ESM), which assesses mood in real-time several times a day, may overcome these limitations. This study set out to assess the experiences of patients and clinicians with the addition of ESM monitoring, real-time alerts, and personalized feedback to clinical care. Participants were twenty patients with bipolar disorder type I/II and their clinicians. For four months, patients completed five ESM assessments per day on mood, symptoms, and activities. Weekly symptom questionnaires alerted patients and clinicians to potential episodes. After the monitoring, a personalized feedback report based on the patient's data was discussed between patient and clinician. Three months later, patient and clinician were both interviewed. RESULTS: Thematic analysis of the transcripts resulted in four themes: perceived effects of the monitoring, alerts, and feedback, and recommendations for implementation of ESM. ESM was perceived as helping patients to cope better with their disorder by increasing awareness, offering new insights, and encouraging life style adjustments. ESM was further believed to facilitate communication between patient and clinician and to lead to new treatment directions. However, high assessment burden and pre-occupation with negative mood and having a disorder were also described. Patients and clinicians advocated for increased personalization and embedding of ESM in care. CONCLUSIONS: This study demonstrates that long-term ESM monitoring, alerts, and personalized feedback are perceived as beneficial to the treatment and self-management of patients with bipolar disorder. Future research should further test the clinical utility of ESM. Clinically relevant feedback and technology need to be developed to enable personalized integration of ESM in clinical care.

Correction to: Feasibility and predictors of change of narrative exposure therapy for displaced populations: a repeated measures design.

[This corrects the article DOI: 10.1186/s40814-020-00613-1.].

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology.

OBJECTIVE: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual's emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient's ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0-16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation.

Virtual reality based cognitive behavioral therapy for paranoia: Effects on mental states and the dynamics among them.

BACKGROUND: Negative affective processes may contribute to maintenance of paranoia in patients with psychosis, and vice versa. Successful treatment may break these pathological symptom networks. This study examined whether treatment with virtual reality based cognitive behavioral therapy (VR-CBT) for paranoia influences momentary affective states, and whether VR-CBT changes the adverse interplay between affective states and paranoia. METHODS: Patients with a psychotic disorder (n = 91) were randomized to 16-session VR-CBT or treatment as usual (TAU). With the experience sampling method (structured diary technique) mental states were assessed for 6-10 days at baseline, posttreatment and 6-month follow-up. Multilevel analysis were performed to establish treatment effects and time-lagged associations between mental states, that were visualized with networks of mental states. RESULTS: Average levels of paranoia (feeling suspicious [b = -032., p = .04], disliked [b = -49., p < .01] and hurt [b = -0.52, p < .01]) and negative affect (anxious [b = -0.37, p = .01], down [b = -0.33, p = .04] and insecure [b = -0.17, p = .03) improved more after VR-CBT than TAU, but positive affect did not. Baseline mental state networks had few significant connections, with most stable connections being autocorrelations of mental states. The interplay between affective states and paranoia did not change in response to treatment. A trend reduction in average intranode connections (autocorrelations) was found after VR-CBT (b = -0.07, p = .08), indicating that mental states reinforce themselves less after treatment. CONCLUSIONS: VR-CBT reduced paranoid symptoms and lowered levels of negative affect in daily life, but did not affect the extent to which mental states influenced each other. Findings do suggest that as a result of treatment mental states regain flexibility.

Feasibility and predictors of change of narrative exposure therapy for displaced populations: a repeated measures design.

BACKGROUND: Displaced victims of interpersonal violence, such as refugees, asylum seekers, and victims of sexual exploitation, are growing in numbers and are often suffering from a post-traumatic stress disorder (PTSD). At the same time, these victims are known to benefit less from trauma-focused therapy (TFT) and to be less compliant to treatment. The objective of this paper is to describe the rationale and research protocol of an ongoing trial that aims to evaluate different variables that might influence the feasibility of TFT for the study population. Specifically, perceived daily stress, emotion regulation, and mood are investigated as predictors of change in PTSD symptoms during a trauma-focused therapy (narrative exposure therapy (NET)). The feasibility of administering measures tapping these constructs repeatedly during treatment will also be evaluated. METHODS/DESIGN: Using an observational treatment design, 80 displaced victims of interpersonal violence will be measured before, during, and after partaking in NET. Several questionnaires tapping PTSD plus the aforementioned possible predictors of PTSD change will be administered: Post-traumatic Stress Disorder Checklist-5, Perceived Stress Scale, Difficulties in Emotion Regulation Scale-18 (pre-test, post-test, and follow-up),subscale impulsivity of the Difficulties in Emotion Regulation Scale-18, Perceived Stress Scale short version, Primary Care Post-traumatic Stress Disorder and a single Mood item (each session). Multilevel modelling will be used to examine the relation between the possible predictors and treatment outcome. DISCUSSION: The present study is the first to examine the interplay of facilitating and interfering factors possibly impacting treatment feasibility and effectiveness in displaced victims of interpersonal violence with PTSD receiving NET, using repeated measures. The current study can help to improve future treatment based on individual characteristics. TRIAL REGISTRATION: Netherlands Trial Register: NTR7353, retrospectively registered. Date of registration: July 11, 2018.

Sudden gains in day-to-day change: Revealing nonlinear patterns of individual improvement in depression.

OBJECTIVE: We examined individual overall trajectories of change and the occurrence of sudden gains in daily self-rated problem severity and the relation of these patterns to treatment response. METHOD: Mood disorder patients (N = 329, mean age = 44, 55% women) completed daily self-ratings about the severity of their complaints as a standard part of treatment, using the Therapy Process Questionnaire (TPQ). Per individual, the best-fitting defined (linear, log-linear, 1-step) trajectory was tested for significance: for change over time, and for specificity of the best-fitting trajectory. Two-hundred and three cases had ICD-10 Symptom Rating (ISR) depression scores posttreatment: a score ≤1 identified 114 treatment responders. Relation to response was examined for sudden gains and type of change trajectory. RESULTS: 138 cases (42%) had a significant decrease in problem severity, of which 54 cases (16%) had a defined trajectory: 50 cases with one-step improvement, and 4 with a linear improvement in daily problem severity. Sudden gains occurred in 28% of the total sample, and within 58% of improvement patterns. Specifically, sudden gains occurred in 68% of significant 1-step trajectories and 25% of the linear cases. Sudden gains and nonspecific change trajectories were significantly more frequent for treatment responders. CONCLUSIONS: At the day-level, patterns of improvement are nonlinear for most patients. Sudden gains occur within various forms of overall change and are associated with treatment response. Clinically relevant improvements in depression occur both gradually and abruptly, and this finding allows for the possibility that the remission process functions according to dynamical systems principles. (PsycINFO Database Record (c) 2020 APA, all rights reserved).