Systemic Case Formulation, Individualized Process Monitoring, and State Dynamics in a Case of Dissociative Identity Disorder

Pattern transitions in diary data of MDD patients: a mixed-methods multiple case study of psychotherapy dynamics

Aim

Mixed-methods approaches promise a deep understanding of psychotherapeutic processes. This study uses qualitative and quantitative data from daily diary entries and daily self-assessments during inpatient treatment. The aim of the study is to get an insight into the similarities and differences between both types of data and how they represent self-organized pattern transitions in psychotherapy. While a complete correlation of results is not expected, we anticipate observing amplifying and subsidiary patterns from both perspectives.

Materials and methods

Daily, five MDD patients wrote diaries and completed self-assessments using the Therapy Process Questionnaire, a questionnaire for monitoring the change dynamics of psychotherapy. The data were collected using the Synergetic Navigation System, an online tool for real-time monitoring. Diary entries of the patients described their experiences in everyday life. The qualitative text analysis was conducted using Mixed Grounded Theory, which provided categories representing the patients' ongoing experiences of transformation and stagnation. The time series data was analyzed using the dynamic complexity algorithm and the pattern transition detection algorithm. Results from qualitative and quantitative analyses were combined and compared. Following the process of data triangulation, the leading perspective came from the theory of self-organization. In addition to presenting the overall results for all five patients, we delve into two specific case examples in greater detail.

Results

Specific and highly diversified diary entries of 5 patients were classified into the categories of perceived pattern stability, noticing improvement, broadening the perspective, critical instability, and experiencing moments of Kairos. Patients reported problems not only related to their disorder (e.g., lack of energy and hopelessness) but also to phases and steps of change, which could be related to the theory of self-organization (e.g., problem attractors, critical fluctuations, pattern transitions, and Kairos). Qualitative and quantitative analysis provide important supplementary results without being redundant or identical.

Conclusion

Data triangulation allows for a comprehensive and multi-perspective understanding of therapeutic change dynamics. The different topics expressed in the diary entries especially help to follow micro-psychological processes, which are far from being a simple reaction to interventions. The way patients experience themselves being in stability or instability and stagnation or transformation is surprisingly close to the general features of self-organizing processes in complex systems.

A complex systems perspective on chronic aggression and self-injury: case study of a woman with mild intellectual disability and borderline personality disorder

BACKGROUND

Challenging behaviors like aggression and self-injury are dangerous for clients and staff in residential care. These behaviors are not well understood and therefore often labeled as "complex". Yet it remains vague what this supposed complexity entails at the individual level. This case-study used a three-step mixed-methods analytical strategy, inspired by complex systems theory. First, we construed a holistic summary of relevant factors in her daily life. Second, we described her challenging behavioral trajectory by identifying stable phases. Third, instability and extraordinary events in her environment were evaluated as potential change-inducing mechanisms between different phases.

CASE PRESENTATION

A woman, living at a residential facility, diagnosed with mild intellectual disability and borderline personality disorder, who shows a chronic pattern of aggressive and self-injurious incidents. She used ecological momentary assessments to self-rate challenging behaviors daily for 560 days.

CONCLUSIONS

A qualitative summary of caretaker records revealed many internal and environmental factors relevant to her daily life. Her clinician narrowed these down to 11 staff hypothesized risk- and protective factors, such as reliving trauma, experiencing pain, receiving medical care or compliments. Coercive measures increased the chance of challenging behavior the day after and psychological therapy sessions decreased the chance of self-injury the day after. The majority of contemporaneous and lagged associations between these 11 factors and self-reported challenging behaviors were non-significant, indicating that challenging behaviors are not governed by mono-causal if-then relations, speaking to its complex nature. Despite this complexity there were patterns in the temporal ordering of incidents. Aggression and self-injury occurred on respectively 13% and 50% of the 560 days. On this timeline 11 distinct stable phases were identified that alternated between four unique states: high levels of aggression and self-injury, average aggression and self-injury, low aggression and self-injury, and low aggression with high self-injury. Eight out of ten transitions between phases were triggered by extraordinary events in her environment, or preceded by increased fluctuations in her self-ratings, or a combination of these two. Desirable patterns emerged more often and were less easily malleable, indicating that when she experiences bad times, keeping in mind that better times lie ahead is hopeful and realistic.

Using Progress Feedback to Enhance Treatment Outcomes: A Narrative Review

We face increasing demand for greater access to effective routine mental health services, including telehealth. However, treatment outcomes in routine clinical practice are only about half the size of those reported in controlled trials. Progress feedback, defined as the ongoing monitoring of patients' treatment response with standardized measures, is an evidence-based practice that continues to be under-utilized in routine care. The aim of the current review is to provide a summary of the current evidence base for the use of progress feedback, its mechanisms of action and considerations for successful implementation. We reviewed ten available meta-analyses, which report small to medium overall effect sizes. The results suggest that adding feedback to a wide range of psychological and psychiatric interventions (ranging from primary care to hospitalization and crisis care) tends to enhance the effectiveness of these interventions. The strongest evidence is for patients with common mental health problems compared to those with very severe disorders. Effect sizes for not-on-track cases, a subgroup of cases that are not progressing well, are found to be somewhat stronger, especially when clinical support tools are added to the feedback. Systematic reviews and recent studies suggest potential mechanisms of action for progress feedback include focusing the clinician's attention, altering clinician expectations, providing new information, and enhancing patient-centered communication. Promising approaches to strengthen progress feedback interventions include advanced systems with signaling technology, clinical problem-solving tools, and a broader spectrum of outcome and progress measures. An overview of methodological and implementation challenges is provided, as well as suggestions for addressing these issues in future studies. We conclude that while feedback has modest effects, it is a small and affordable intervention that can potentially improve outcomes in psychological interventions. Further research into mechanisms of action and effective implementation strategies is needed.

Psychological precursors of epileptic seizures

Psychological stress is the most commonly self-reported precursor of epileptic seizures. However, retrospective and prospective studies remain inconclusive in this regard. Here, we explored whether seizures would be preceded by significant changes in reported stressors or resource utilization. This study is based on high-frequency time series through daily online completion of personalized questionnaires of 9-24 items in epilepsy outpatients and compared responses 1-14 days before seizures with interictal time series. Fourteen patients (79% women, age = 23-64 years) completed daily questionnaires over a period of 87-898 days (median = 277 days = 9.2 months). A total of 4560 fully completed daily questionnaires were analyzed, 685 of which included reported seizure events. Statistically significant changes in preictal compared to interictal dynamics were found in 11 of 14 patients (79%) across 41 items (22% of all 187 items). In seven of 14 patients (50%), seizures were preceded by a significant mean increase of stressors and/or a significant mean decrease of resource utilization. This exploratory analysis of long-term prospective individual patient data on specific stressors and personal coping strategies generates the hypothesis that medium-term changes in psychological well-being may precede the occurrence of epileptic seizures in some patients.

Understanding the complexity of individual developmental pathways: A primer on metaphors, models, and methods to study resilience in development

The modern study of resilience in development is conceptually based on a complex adaptive system ontology in which many (intersystem) factors are involved in the emergence of resilient developmental pathways. However, the methods and models developed to study complex dynamical systems have not been widely adopted, and it has recently been noted this may constitute a problem moving the field forward. In the present paper, I argue that an ontological commitment to complex adaptive systems is not only possible, but highly recommended for the study of resilience in development. Such a commitment, however, also comes with a commitment to a different causal ontology and different research methods. In the first part of the paper, I discuss the extent to which current research on resilience in development conceptually adheres to the complex systems perspective. In the second part, I introduce conceptual tools that may help researchers conceptualize causality in complex systems. The third part discusses idiographic methods that could be used in a research program that embraces the interaction dominant causal ontology and idiosyncratic nature of the dynamics of complex systems. The conclusion is that a strong ontological commitment is warranted, but will require a radical departure from nomothetic science.

The geometry of synchronization: quantifying the coupling direction of physiological signals of stress between individuals using inter-system recurrence networks

In the study of synchronization dynamics between interacting systems, several techniques are available to estimate coupling strength and coupling direction. Currently, there is no general 'best' method that will perform well in most contexts. Inter-system recurrence networks (IRN) combine auto-recurrence and cross-recurrence matrices to create a graph that represents interacting networks. The method is appealing because it is based on cross-recurrence quantification analysis, a well-developed method for studying synchronization between 2 systems, which can be expanded in the IRN framework to include N > 2 interacting networks. In this study we examine whether IRN can be used to analyze coupling dynamics between physiological variables (acceleration, blood volume pressure, electrodermal activity, heart rate and skin temperature) observed in a client in residential care with severe to profound intellectual disabilities (SPID) and their professional caregiver. Based on the cross-clustering coefficients of the IRN conclusions about the coupling direction (client or caregiver drives the interaction) can be drawn, however, deciding between bi-directional coupling or no coupling remains a challenge. Constructing the full IRN, based on the multivariate time series of five coupled processes, reveals the existence of potential feedback loops. Further study is needed to be able to determine dynamics of coupling between the different layers.

How to make the most of routine outcome monitoring (ROM): A multitude of clinical decisions and nuances to consider

Routine outcome monitoring (ROM) involves the use of patient-reported standardized outcome measures to monitor progress throughout the course of treatment, followed by feedback of the patient's scores to the therapist. The potential benefits of ROM have been established, however, from our own experiences, we know that the implementation in clinical practice can be challenging. We therefore wanted to explore in more detail exactly how we might be able to apply ROM in difficult clinical contexts. The inspiring case illustrations in this issue of Journal of Clinical Psychology: In Session highlight the heterogeneity in ROM systems, and the way in which ROM can be used in treatment. Just as there are many ways of interpreting a survey data-point, there are also many ways in which ROM may be used to complement the treatment and supervision. Whether or not ROM is implemented may partly be determined by clinic policies and routines, but there remain a multitude of clinical decisions that require careful consideration by the individual therapist. To complement the evidence supporting the benefits of using ROM, further empirical support and clinical guidance is needed on how exactly therapists are to use ROM in their work and how ROM may be used in evidence-based practice. We make suggestions for additional uses of ROM for deliberate practice, and teletherapy practice, and look toward novel ways of assessing progress in the near future.

Personality traits and complex problem solving: Personality disorders and their effects on complex problem-solving ability

Complex problem solving (CPS) can be interpreted as the number of psychological mechanisms that allow us to reach our targets in difficult situations, that can be classified as complex, dynamic, non-transparent, interconnected, and multilayered, and also polytelic. The previous results demonstrated associations between the personality dimensions neuroticism, conscientiousness, and extraversion and problem-solving performance. However, there are no studies dealing with personality disorders in connection with CPS skills. Therefore, the current study examines a clinical sample consisting of people with personality and/or depressive disorders. As we have data for all the potential personality disorders and also data from each patient regarding to potential depression, we meet the whole range from healthy to impaired for each personality disorder and for depression. We make use of a unique operationalization: CPS was surveyed in a simulation game, making use of the microworld approach. This study was designed to investigate the hypothesis that personality traits are related to CPS performance. Results show that schizotypal, histrionic, dependent, and depressive persons are less likely to successfully solve problems, while persons having the additional behavioral characteristics of resilience, action orientation, and motivation for creation are more likely to successfully solve complex problems.

Early Warning Signals in Phase Space: Geometric Resilience Loss Indicators From Multiplex Cumulative Recurrence Networks

The detection of Early Warning Signals (EWS) of imminent phase transitions, such as sudden changes in symptom severity could be an important innovation in the treatment or prevention of disease or psychopathology. Recurrence-based analyses are known for their ability to detect differences in behavioral modes and order transitions in extremely noisy data. As a proof of principle, the present paper provides an example of a recurrence network based analysis strategy which can be implemented in a clinical setting in which data from an individual is continuously monitored for the purpose of making decisions about diagnosis and intervention. Specifically, it is demonstrated that measures based on the geometry of the phase space can serve as Early Warning Signals of imminent phase transitions. A publicly available multivariate time series is analyzed using so-called cumulative Recurrence Networks (cRN), which are recurrence networks with edges weighted by recurrence time and directed towards previously observed data points. The results are compared to previous analyses of the same data set, benefits, limitations and future directions of the analysis approach are discussed.

Detecting pattern transitions in psychological time series - A validation study on the Pattern Transition Detection Algorithm (PTDA)

With the increasing use of real-time monitoring procedures in clinical practice, psychological time series become available to researchers and practitioners. An important interest concerns the identification of pattern transitions which are characteristic features of psychotherapeutic change. Change Point Analysis (CPA) is an established method to identify the point where the mean and/or variance of a time series change, but changes of other and more complex features cannot be detected by this method. In this study, an extension of the CPA, the Pattern Transition Detection Algorithm (PTDA), is optimized and validated for psychological time series with complex pattern transitions. The algorithm uses the convergent information of the CPA and other methods like Recurrence Plots, Time Frequency Distributions, and Dynamic Complexity. These second level approaches capture different aspects of the primary time series. The data set for testing the PTDA (300 time series) is created by an instantaneous control parameter shift of a simulation model of psychotherapeutic change during the simulation runs. By comparing the dispersion of random change points with the real change points, the PTDA determines if the transition point is significant. The PTDA reduces the rate of false negative and false positive results of the CPA below 5% and generalizes its application to different types of pattern transitions. RQA quantifiers also can be used for the identification of nonstationary transitions in time series which was illustrated by using Determinism and Entropy. The PTDA can be easily used with Matlab and is freely available at Matlab File Exchange (https://www.mathworks.com/matlabcentral/fileexchange/80380-pattern-transition-detection-algorithm-ptda).

About-Weekly Pattern in the Dynamic Complexity of a Healthy Subject's Cellular Immune Activity: A Biopsychosocial Analysis

In a previous integrative single-case study, we collected biological, psychological and social time-series data on a 25-year-old healthy woman over the course of 126 12-h intervals (63 days) and used urinary neopterin as an indicator of cellular immune activity [Schubert et al. 2012 (1)]. The present re-evaluation introduced Dynamic Complexity (DC) as an additional non-linear and non-stationary measure to further investigate the subject's biopsychosocial dynamics during the study. The new time series dealing with urinary neopterin complexity revealed a cyclic, circaseptan (about-weekly) repeating pattern (6.59 days). The only weekly reoccurring events over the course of the study that were associated with this immunological pattern were the in-depth interviews with the subject (mean distance between interviews: 6.5 days). Superposed epoch analysis (SEA) revealed a U-shaped relation between neopterin complexity and interviews, with a decrease in neopterin complexity before and during interviews and an increase after interviews. Furthermore, the complexity scores for irritation, anxiousness/depressiveness and mental activity were positively correlated with neopterin complexity. The results suggest that the interviews, which had been found to be related to the subject's need for educational and/or social accomplishment, were marked by stress (decrease in psycho-immunological flexibility and adaptability), which was then relieved after the interviews (increase in psycho-immunological flexibility and adaptability). It appears that the subject's cellular immune activity, as indicated by neopterin complexity, functionally mirrored the emotional meaning she ascribed to the in-depth interviews. This re-evaluation is in line with the view that biopsychosocial research requires multimodal analysis of single cases based on qualitative (e.g., in-depth interviews) and quantitative (e.g., time series analysis) data under conditions of "life as it is lived".

Pathologically reduced neural flexibility recovers during psychotherapy of OCD patients

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Psychiatric impairment is associated with decreased neural flexibility.

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Psychotherapy was able to increase the neural flexibility of the patients.

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Psychotherapy should increase adaptivity of cognitive-emotional-behavioral patterns.

Flexibility is a key feature of psychological health, allowing the individual to dynamically adapt to changing environmental demands, which is impaired in many psychiatric disorders like obsessive–compulsive disorder (OCD). Adequately responding to varying demands requires the brain to switch between different patterns of neural activity, which are represented by different brain network configurations (functional connectivity patterns). Here, we operationalize neural flexibility as the dissimilarity between consecutive connectivity matrices of brain regions (jump length). In total, 132 fMRI scans were obtained from 17 patients that were scanned four to five times during inpatient psychotherapy, and from 17 controls that were scanned at comparable time intervals. Significant negative correlations were found between the jump lengths and the symptom severity scores of OCD, depression, anxiety, and stress, suggesting that high symptom severity corresponds to inflexible brain functioning. Further analyses revealed that impaired reconfiguration (pattern stability) of the brain seems to be more related to general psychiatric impairment rather than to specific symptoms, e.g., of OCD or depression. Importantly, the group × time interaction of a repeated measures ANOVA was significant, as well as the post-hoc paired t-tests of the patients (first vs. last scan). The results suggest that psychotherapy is able to significantly increase the neural flexibility of patients. We conclude that psychiatric symptoms like anxiety, stress, depression, and OCD are associated with an impaired adaptivity of the brain. In general, our results add to the growing evidence that dynamic functional connectivity captures meaningful properties of brain functioning.

Integration of Cognitive and Emotional Processing Predicts Poor and Good Outcomes of Psychotherapy

Abstract

With the aim of investigating analogies and differences between psychotherapeutic processes, ten good-outcome and ten poor-outcome cases were selected from a sample of patients treated at the University Hospital of Psychiatry, Salzburg, Austria, and the Department of Psycho-Traumatology of the Clinic St. Irmingard, Prien am Chiemsee, Germany. They were monitored daily using the Therapy Process Questionnaire (TPQ), and their evolution over time was analyzed by means of Principal Components Analysis and Linear Discriminant Analysis. The results highlight that poor-outcome patients show a separation between cognitive processes (Principal Component 1) and relational-emotional processes (Principal Component 2) (r = − 0.25; p = n.s.), while in the good-outcome patients these aspects are well integrated (r = 0.70; p = 0.02). These results corroborate the validity of the daily monitoring procedure and also indicate the need for greater attention to the relational and emotional aspects of the patients rather than merely to their cognitive functioning and well-being.

Key Message

In poor-outcome cases, burdensome emotions and interpersonal experiences on the one hand and cognitive/well-being aspects of the mental processing on the other, stay unrelated. Successful therapeutic processing, as in good-outcome cases, requires an integration of cognitive and affective components.

Process-oriented and personalized psychotherapeutic care for epilepsy: Interim results of a feasibility study

BACKGROUND

There is great scientific and clinical interest in the effective integration of psychological treatments into comprehensive epilepsy care to optimize treatment outcomes and psychosocial functioning in people with epilepsy. Stepped care is a promising approach to accommodate personalized psychotherapeutic care in academic and regular outpatient settings. It aims at providing patients with the most adequate treatment duration, number of sessions, and treatment method while systematically monitoring their treatment processes.

METHODS

This is an uncontrolled feasibility study of process-oriented and personalized psychotherapeutic care for epilepsy in a naturalistic setting. The objective of this study was to evaluate individual changes of health-related quality of life (QOLIE-31) and psychiatric comorbidity (BDI-II, BSI) in participants by applying the concept of the reliable change index (RCI) to outcomes that were obtained at baseline and six months after the beginning of the intervention. Additionally, we assessed the relationship between outcome scores, the number of attended sessions, and history of childhood trauma by linear regression models.

RESULTS

Twenty patients [15 women/5 men, median age 48 years (range: 23-73 years)] were recruited. The median number of scheduled sessions was 11 (range: 6-22); there were no drop-outs. After psychotherapy quality of life (QOLIE-31), global distress (BSI) and depression (BDI-II) scores improved significantly (p-values: QOLIE-31: 0.03; BSI: 0.01; BDI-II: 0.01). The largest improvements were achieved for the emotional well-being subscale of the QOLIE-31 (47%, p-value: 0.02), the global severity index of the BSI (83%), and depression severity (BDI-II) (60%). Linear regression models did not reveal any significant association between interim changes, number of attended treatment sessions, and history of childhood trauma.

CONCLUSION

The results suggest that process-oriented and personalized psychotherapeutic has low attrition and results in improved quality of life and reduced psychiatric symptoms in people with epilepsy. Our findings indicate that responsiveness to psychotherapy is not dependent on the number of attended treatment sessions. Participants with childhood trauma did not need more treatment sessions to achieve an improvement. More research is needed to understand and address mechanisms and precursors of responsiveness to psychotherapy.

High-frequency monitoring of personalized psychological variables during outpatient psychotherapy in people with seizures: An uncontrolled feasibility study

BACKGROUND

This feasibility study applied the concept of daily systematic monitoring of personalized psychological variables and investigated patients' compliance in order to evaluate if its integration in outpatient psychotherapy is feasible and if patients found the development and daily application of personalized questionnaires user-friendly and useful.

METHODS

A naturalistic sample of patients with epilepsy (PWE) was enrolled to participate in an outpatient psychotherapy program. A personalized process questionnaire was developed with each patient based on an individual psychological system's model at the outset of therapy. Daily time-stamped self-assessments were collected during outpatient psychotherapy. This process-monitoring was technically realized by an internet-based device for data collection and data analysis, the Synergetic Navigation System (SNS). The reflection of person-specific time series informed by patients' replies to their personalized process questionnaire was integrated in the therapy process. Compliance rates were assessed during a period of six months (i.e., 180 days) after the first entry of the questionnaire [compliance rate = (number of completed questionnaires/180) × 100]. User-friendliness and usefulness of this process monitoring were evaluated quantitatively.

RESULTS

Twenty patients [15 women/5 men, median age 48 years (range 23-73 years)] were recruited. Compliance rates were high (median: 93%, range 31-100%) among the participants. Participants reported a high overall satisfaction with the application and user-friendliness of SNS.

CONCLUSION

The results support the feasibility of high-frequency monitoring of personalized psychological processes during outpatient psychotherapy. Repeated daily assessments of a personalized questionnaire yield highly resolved, equidistant time series data, which gives insight into individual psychological processes during outpatient psychotherapy.

Feasibility and utility of idiographic models in the clinic: A pilot study

AbstractIntroduction: Idiographic, or individual-level, methodology has been touted for its potential clinical utility. Empirically modeling relationships between symptoms for a single individual may offer both the client and therapist information that is useful for case conceptualization and treatment planning. However, few studies have investigated the feasibility and utility of integrating idiographic models in a clinical setting.Methods: Clients (n = 12) completed ecological momentary assessment regarding psychological symptoms five times per day for three weeks. Clients also generated predictions about the associative and directed relationships in their networks. Graphical vector autoregression was used to generate contemporaneous and directed networks from each client's data, and both clients and therapists completed self-report questionnaires regarding the feasibility and utility of these methods.Results: Results indicated that the idiographic model structures varied widely across participants and differed markedly from the client's own predictions. Clients found the models useful, whereas their therapists demonstrated a more tempered response.Discussion: These results echo previous findings suggesting that clients are willing to complete intensive data collection and are interested in the output, whereas therapists may be less open to idiographic methods. We provide recommendations for future implementation of personalized models in clinical settings.

Early warning signals and critical transitions in psychopathology: challenges and recommendations

Empirical evidence is mounting that monitoring momentary experiences for the presence of early warning signals (EWS) may allow for personalized predictions of meaningful symptom shifts in psychopathology. Studies aiming to detect EWS require intensive longitudinal measurement designs that center on individuals undergoing change. We recommend that researchers (1) define criteria for relevant symptom shifts a priori to allow specific hypothesis testing, (2) balance the observation period length and high-frequency measurements with participant burden by testing ambitious designs with pilot studies, and (3) choose variables that are meaningful to their patient group and facilitate replication by others. Thoroughly considered designs are necessary to assess the promise of EWS as a clinical tool to detect, prevent, or encourage impending symptom changes in psychopathology.

What too strict a method obscures about the validity of outcome measures

Objective: To assess the outcome of psychotherapeutic treatments, psychotherapy researchers often compare pre- and post-treatment scores on self-report outcome measures. In this paper, the common assumption is challenged that pre-to-post decreasing and increasing outcome scores are indicative of successful and failed therapies, respectively.Method: The outcome of 29 psychotherapeutic treatments was evaluated by means of quantitative analysis of pre- and post-treatment scores on commonly used outcome measures (such as the Symptom Checklist-90-R, the Inventory of Interpersonal Problems, and the General Health Questionnaire-12), as well as through consensual qualitative research.Results: Overall, a moderate to low convergence between qualitative and quantitative evaluations of outcome was observed. Detailed analyses of six cases are presented in which pre-to-post comparisons of outcome measures proved misleading.Conclusions: It is concluded that psychotherapy outcome research might benefit from assessment strategies that are sensitive to the singularities of individual treatments and to the complexity of the phenomenon of therapeutic outcome. Furthermore, classical psychometric evaluations of the validity of outcome measures might be supplemented with less-systematic evaluations that take any contingent source of information on outcome into account.

Using person-specific networks in psychotherapy: challenges, limitations, and how we could use them anyway

BACKGROUND

The complexity of psychopathology is evident from its multifactorial etiology and diversity of symptom profiles and hampers effective treatment. In psychotherapy, therapists approach this complexity by using case conceptualization. During this process, patients and therapists closely collaborate on a personalized working theory of the patient's psychopathology. This is a challenging process and shows low reliability between therapists. With the experience sampling method (ESM), time-series data-valuable for case conceptualization-can be systematically gathered in a patient's normal daily life. These data can be analyzed and visualized in person-specific networks (PSNs). PSNs may support case conceptualization by providing a schematic representation of association patterns between affective, cognitive, behavioral, and context variables.

MAIN TEXT

We adopt a clinical perspective in considering how PSNs might be implemented to serve case conceptualization and what their role could be in psychotherapy. We suggest PSNs to be based on personalized ESM assessment to capture the unique constellation of variables in each patient. We reflect on the lack of a gold standard for creating PSNs, which may result in substantially different PSNs and thereby disparate information for case conceptualization. Moreover, even if PSNs are created in a consistent manner, results remain ambiguous as they are subject to multiple interpretations. Therefore, associations in PSNs do not allow for firm conclusions about a patient's psychopathology, but they may nevertheless be valuable in the process of case conceptualization. PSNs are based on systematically gathered, ecologically valid ESM data and provide a unique personalized perspective. When used responsibly, PSNs may be able to support case conceptualization by generating questions that serve as a starting point for a dialog between therapists and patients. Well-targeted questions are an essential tool for therapists to gain insight into the patients' psychopathology patterns and improve the quality of case conceptualization.

CONCLUSIONS

PSNs have limitations in terms of the reliability of the insights they provide directly. However, taking these challenges into account, we believe they have potential as a tool to help therapists and patients in their collaborative exploration of a patient's psychopathology. Clearly, this would need to be validated in future clinical research.

Long-Term Effects of Home-Based Family Therapy for Non-responding Adolescents With Psychiatric Disorders. A 3-Year Follow-Up

Objective

Home-based treatment of families with low socio-economic status and multiple psychosocial problems (multi-problem families, MPFs) is gaining importance in clinical social epidemiology and health services research. The sustainability of the treatment is of special importance in order to breach transgenerational effects.

Methods

We examined outcome, effect size, and clinical significance of home-based treatment for 84 multi-problem families in a naturalistic setting. 48 of the families were available for a follow-up after 3 years. The baseline characteristics of these family systems included low collaboration, an increased family adversity index, minors with high rates of child psychiatric disorders, a high prevalence of comorbidity, low relational family functioning, and adolescents who refused any form of treatment or had unilaterally terminated different forms of treatment before. The home-based family therapy consisted of one or two face-to-face counseling sessions per week over an average of 28.8 months (SD = 19.2). The symptoms and competence of the adolescents, the caregivers, and the family structure were assessed with 13 variables.

Results

All variables showed significant improvement rates (pre- vs. post- treatment) with medium to high effect sizes (mean of Cohen's d = 1.04, range = 0.34 - 2.18). All variables showed a sustained or even further improvement at follow-up.

Conclusion

This study provides evidence of statistically (p), practically (d), and clinically (RCI) significant changes in symptom and competence-related variables among adolescents and caregivers in MPFs with sustainable long-term effects in the 3-year follow-up period.

An Initial Study of Practicing Psychologists' Views of the Utility of Ecological Momentary Assessment for Difficult Psychotherapy Cases

Ecological momentary assessment (EMA) is a burgeoning area of research, and several clinical applications of the resulting data have been identified by researchers, suggesting potential benefit to psychotherapy practice. However, practitioners often do not use traditional empirically-supported tools for diagnosis and outcome monitoring (e.g., validated interview measures and questionnaires). Thus, it is not clear how readily practitioners will take up newer technology-enhanced assessment methods, despite current enthusiasm among researchers. The current study aimed to explore the perceived usefulness of EMA-based tools for clinical assessment and outcome monitoring of difficult psychotherapy cases, as well as to identify correlates of attitudes about the usefulness of these tools. Clinical psychologists in active therapy practice with adults (n = 375) completed an internet survey including the Attitudes toward Standardized Assessment scale and the Attitudes toward Standardized Assessment Scales-Monitoring and Feedback. Respondents characterized their current diagnostic and outcome monitoring practices and rated how helpful they would find several assessment and outcome monitoring resources for a difficult case, including both traditional instruments and EMA-based methods. EMA-based tools had lower perceived usefulness than existing instruments. Attitudes toward standardized assessment and outcome monitoring predicted the perceived utility of these methods, as did several professional variables. Practicing psychologists may not adopt EMA for clinical assessment more readily than traditional assessment tools. Recommendations for facilitating the uptake of new technologies by psychotherapists are offered.

Complexity in psychological self-ratings: implications for research and practice

BACKGROUND

Psychopathology research is changing focus from group-based "disease models" to a personalized approach inspired by complex systems theories. This approach, which has already produced novel and valuable insights into the complex nature of psychopathology, often relies on repeated self-ratings of individual patients. So far, it has been unknown whether such self-ratings, the presumed observables of the individual patient as a complex system, actually display complex dynamics. We examine this basic assumption of a complex systems approach to psychopathology by testing repeated self-ratings for three markers of complexity: memory, the presence of (time-varying) short- and long-range temporal correlations; regime shifts, transitions between different dynamic regimes; and sensitive dependence on initial conditions, also known as the "butterfly effect," the divergence of initially similar trajectories.

METHODS

We analyzed repeated self-ratings (1476 time points) from a single patient for the three markers of complexity using Bartels rank test, (partial) autocorrelation functions, time-varying autoregression, a non-stationarity test, change point analysis, and the Sugihara-May algorithm.

RESULTS

Self-ratings concerning psychological states (e.g., the item "I feel down") exhibited all complexity markers: time-varying short- and long-term memory, multiple regime shifts, and sensitive dependence on initial conditions. Unexpectedly, self-ratings concerning physical sensations (e.g., the item "I am hungry") exhibited less complex dynamics and their behavior was more similar to random variables.

CONCLUSIONS

Psychological self-ratings display complex dynamics. The presence of complexity in repeated self-ratings means that we have to acknowledge that (1) repeated self-ratings yield a complex pattern of data and not a set of (nearly) independent data points, (2) humans are "moving targets" whose self-ratings display non-stationary change processes including regime shifts, and (3) long-term prediction of individual trajectories may be fundamentally impossible. These findings point to a limitation of popular statistical time series models whose assumptions are violated by the presence of these complexity markers. We conclude that a complex systems approach to mental health should appreciate complexity as a fundamental aspect of psychopathology research by adopting the models and methods of complexity science. Promising first steps in this direction, such as research on real-time process monitoring, short-term prediction, and just-in-time interventions, are discussed.

Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems

Aim

In many cases, the dynamics of psychotherapeutic change processes is characterized by sudden and critical transitions. In theoretical terms, these transitions may be “phase transitions” of self-organizing nonlinear systems. Meanwhile, a variety of methods is available to identify phase transitions even in short time series. However, it is still an open question if different methods for timeseries analysis reveal convergent results indicating the moments of critical transitions and related precursors.

Methods and Procedures

Seven concepts which are commonly used in nonlinear time series analysis were investigated in terms of their ability to identify changes in psychological time series: Recurrence Plots, Change Point Analysis, Dynamic Complexity, Permutation Entropy, Time Frequency Distributions, Instantaneous Frequency, and Synchronization Pattern Analysis, i.e., the dynamic inter-correlation of the system’s variables. Phase transitions were simulated by shifting control parameters in the Hénon map dynamics, in a simulation model of psychotherapy processes (one by an external shift of the control parameter and one created by a simulated control parameter shift), and three sets of empirical time series generated by daily self-ratings of patients during the treatment.

Results

The applied methods showed converging results indicating the moments of dynamic transitions within an acceptable tolerance. The convergence of change points was confirmed statistically by a comparison to random surrogates. In the three simulated dynamics with known phase transitions, these could be identified, and in the empirical cases, the methods converged indicating one and the same transition (possibly the phase transitions of the cases). Moreover, changes that did not manifest in a shift of mean or variance could be detected.

Conclusion

Changes can occur in many different ways in the psychotherapeutic process. For instance, there can be very slow and small transitions or very high and sudden ones. The results show the validity and stability of different measures indicating pattern transitions and/or early warning signals of those transitions. This has profound implications for real-time monitoring in psychotherapy, especially in cases where a transition is not obvious to the eye. Reliably identifying points of change is mandatory also for research on precursors, which in turn can help improving treatment.

A Phase Transition of the Unconscious: Automated Text Analysis of Dreams in Psychoanalytic Psychotherapy

AIM

Psychotherapy could be interpreted as a self-organizing process which reveals discontinuous pattern transitions (so-called phase transitions). Whereas this was shown in the conscious process of awake patients by different measures and at different time scales, dreams came very seldom into the focus of investigation. The present work tests the hypothesis that, by dreaming, the patient gets progressively more access to affective-laden (i.e., emotionally charged) unconscious dimensions. Furthermore, the study investigates if, over the course of psychotherapy, a discontinuous phase transition occurs in the patient's capacity to get in contact with those unconscious dimensions.

METHODS AND PROCEDURES

A series of 95 dream narratives reported during a psychoanalytic psychotherapy of a female patient (published as the "dreams of Amalie X") was used for analysis. An automated text analysis procedure based on multiple correspondence analysis was applied to the textual corpus of the dreams, highlighting a 10-factor structure. The factors, interpreted as affective-laden unconscious meaning dimensions, were adopted to define a 10-dimensional phase space, in which the ability of a dream to be associated with one or more local factors representing complex affective-laden meanings is measured by the Euclidean distance (ED) from the origin of this hyperspace. The obtained ED time series has been fitted by an autoregressive integrated moving average (ARIMA) model and by non linear methods like dynamic complexity, recurrence plot, and time frequency distribution. Change point analysis was applied to these non linear methods.

RESULTS

The results show an increased frequency and intensity of dreams to get access to affective-laden meanings. Non linear methods identified a phase transition-like jump of the ED dynamics onto a higher complexity level of the dreaming process, suggesting a non linear process in the patient's capacity to get in contact with unconscious dimensions.

CONCLUSION

The study corroborates the hypothesis that, by dreaming, the patient gets progressively more access to affective-laden meaning intended as unconscious dimensions. The trajectory of this process has been reproduced by an ARIMA model, and beyond this, non linear methods of time series analysis allowed the identification of a phase transition in the unconscious process of the psychoanalytic therapy under investigation.

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).

The Therapy Process Questionnaire - Factor analysis and psychometric properties of a multidimensional self-rating scale for high-frequency monitoring of psychotherapeutic processes

Many outcome measures and session‐related questionnaires in psychotherapy are designed for weekly or biweekly administration. Yet, today, technical developments allow for higher frequency assessments to monitor human change dynamics more closely by daily assessments. For this purpose, the Therapy Process Questionnaire (TPQ) was developed, with a specific focus on inpatient psychotherapy. In this article, we present an explorative and confirmative factor analysis of the TPQ on the basis of the time series data of 150 patients collected during their hospital stay (mean time series length: 69.1 measurement points). A seven‐factor solution was identified, which explains 68.7% of variance and associates 43 items onto the factors, which are “well‐being and positive emotions,” “relationship with fellow patients,” “therapeutic relationship and clinical setting,” “emotional and problem intensity,” “insight/confidence/therapeutic progress,” “motivation for change,” and “mindfulness/self‐care.” The internal consistency (Cronbach's α), the inter‐item correlations of the subscales, and the discriminative power of the items are excellent. The TPQ can be applied in practice and research for creating time series with equidistant measurement points and time series lengths, which are appropriate for the application of nonlinear analysis methods. Especially in clinical practice, it is important to identify precursors of phase transitions, changing synchronization patterns, and critical or instable periods of a process, which now is possible by internet‐ or app‐based applications of this multidimensional questionnaire.

Integrating the systematic assessment of psychological states in the epilepsy monitoring unit: Concept and compliance

BACKGROUND

Admission to the epilepsy monitoring unit (EMU) for long-term video-electroencephalography (EEG) monitoring (VEEG) constitutes the gold standard for seizure diagnosis and presurgical evaluation. This study applied the concept of a high-frequency systematic monitoring of psychological states and tested patients' compliance in order to evaluate if its integration in the EMU is feasible and if patients benefit from the graphically underpinned discussion of their EMU stay-related cognitions and emotions.

METHODS

The process-monitoring is technically realized by an internet-based device for data collection and data analysis, the Synergetic Navigation System (SNS). A convenient sample was enrolled: All eligible patients who were admitted to the EMU of the Department of Neurology, Christian Doppler Medical Center, Salzburg, Austria, between November 6th 2017 and January 26th 2018 were approached and recruited upon consent. After a short resource-oriented interview, each enrolled patient was provided with a tablet. The daily questionnaire included eight standardized and up to three personalized items. Self-assessments were collected every 5 h prior to meal times (6:30 am, 11:30 am, and 4:30 pm) and at 9:30 pm. The detailed visualizations of the patients' replies were discussed with the participants during a feedback session at the end of the EMU stay.

RESULTS

Twenty-one patients (12 women/9 men, median age 29 years [range 18-74 years]) were consecutively recruited (72% of all eligible patients). Compliance rates were high (median: 82%, range 60%-100%) among the respondents. Mood correlated strongly with hopefulness (r = 0.71) and moderately with energy (r = 0.63) in all patients. When correlating the intraindividual medians of the process questionnaire time series with the pretest total scores, energy correlated moderately and negatively with the Perceived Stress Scale (PSS) (r = -0.45), while self-efficacy correlated moderately and negatively with the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) total scores in all patients (r = -0.5). Nine patients (43%) reported that they learned something meaningful about themselves after the feedback discussion of their individual time series.

CONCLUSION

The results support the feasibility of high-frequency monitoring of psychological states and processes in routine EMU settings. Repeated daily collections four times per day of psychological surveys allow for the assessment of highly resolved, equidistant time series data, which gives insight into psychological states and processes during EMU admission.

From e-Health to i-Health: Prospective Reflexions on the Use of Intelligent Systems in Mental Health Care

Depressive disorders cover a set of disabling problems, often chronic or recurrent. They are characterized by a high level of psychiatric and somatic comorbidities and represent an important public health problem. To date, therapeutic solutions remain unsatisfactory. For some researchers, this is a sign of decisive paradigmatic failure due to the way in which disorders are conceptualized. They hypothesize that the symptoms of a categorical disorder, or of different comorbid disorders, can be interwoven in chains of interdependencies on different elements, of which it would be possible to act independently and synergistically to influence the functioning of the symptom system, rather than limiting oneself to targeting a hypothetical single underlying cause. New connected technologies make it possible to invent new observation and intervention tools allowing better phenotypic characterization of disorders and their evolution, that fit particularly well into this new "symptoms network" paradigm. Synergies are possible and desirable between these technological and epistemological innovations and can possibly help to solve some of the difficult problems people with mental disorders face in their everyday life, as we will show through a fictional case study exploring the possibilities of connected technologies in mental disorders in the near future.

Psychotherapy Is Chaotic-(Not Only) in a Computational World

Objective: The aim of this article is to outline the role of chaotic dynamics in psychotherapy. Besides some empirical findings of chaos at different time scales, the focus is on theoretical modeling of change processes explaining and simulating chaotic dynamics. It will be illustrated how some common factors of psychotherapeutic change and psychological hypotheses on motivation, emotion regulation, and information processing of the client's functioning can be integrated into a comprehensive nonlinear model of human change processes.

Methods: The model combines 5 variables (intensity of emotions, problem intensity, motivation to change, insight and new perspectives, therapeutic success) and 4 parameters into a set of 5 coupled nonlinear difference equations. The results of these simulations are presented as time series, as phase space embedding of these time series (i.e., attractors), and as bifurcation diagrams.

Results: The model creates chaotic dynamics, phase transition-like phenomena, bi- or multi-stability, and sensibility of the dynamic patterns on parameter drift. These features are predicted by chaos theory and by Synergetics and correspond to empirical findings. The spectrum of these behaviors illustrates the complexity of psychotherapeutic processes.

Conclusion: The model contributes to the development of an integrative conceptualization of psychotherapy. It is consistent with the state of scientific knowledge of common factors, as well as other psychological topics, such as: motivation, emotion regulation, and cognitive processing. The role of chaos theory is underpinned, not only in the world of computer simulations, but also in practice. In practice, chaos demands technologies capable of real-time monitoring and reporting on the nonlinear features of the ongoing process (e.g., its stability or instability). Based on this monitoring, a client-centered, continuous, and cooperative process of feedback and control becomes possible. By contrast, restricted predictability and spontaneous changes challenge the usefulness of prescriptive treatment manuals or other predefined programs of psychotherapy.