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.

Objective Within the network approach to psychopathology, cross-sectional partial correlation networks have frequently been used to estimate relationships between symptoms. The resulting relationships have been used to generate hypotheses about causal links between symptoms. In order to justify such exploratory use of partial correlation networks, one needs to assume that the between-subjects relationships in the network approximate systematic within-subjects relationships, which are in turn the results of some within-subjects causal mechanism. If this assumption holds, relationships in the network should be mirrored by relationships between symptom changes; if links in networks approximate systematic within-subject relationships, change in a symptom should relate to change in connected symptoms. Method To investigate this implication, we combined longitudinal data on the Borderline Personality Disorder Severity Index from four samples of borderline personality disorder patients (N = 683). We related parameters from baseline partial correlation networks of symptoms to relationships between change trajectories of these symptoms. Results Across multiple levels of analysis, our results showed that parameters from baseline partial correlation networks are strongly predictive of relationships between change trajectories. Conclusions By confirming its implication, our results support the idea that cross-sectional partial correlation networks hold a relevant amount of information about systematic within-subjects relationships and thereby have exploratory value to generate hypotheses about the causal dynamics between symptoms.

Background Major depressive disorder (MDD) is a highly prevalent mental disorder with large disease burden, high levels of relapse or persistence, and overall suboptimal outcomes of protocolized pharmacological and psychotherapeutic treatments. There is an urgent need to improve treatment effectiveness, possibly through systematic treatment personalization. In psychotherapeutic treatments this can be achieved by case conceptualization. To support this process, we developed the Therap-i module, which consists of personalized Experienced Sampling Methodology (ESM) and feedback. The Therap-i module is integrated into outpatient psychotherapeutic treatment as usual (TAU) for depression. The study aim is to investigate the efficacy of the Therap-i module in decreasing symptomatology in unresponsive or relapsing patients diagnosed with MDD. We hypothesize that the Therap-i module will contribute to TAU by i) decreasing depressive symptoms, and ii) improving general functioning, therapeutic working alliance, and illness perception. This paper provides details of the study rationale, aims, procedures, and a discussion on potential pitfalls and promises of the module. Methods Patients diagnosed with MDD (n = 100) will enrol in a pragmatic two-armed randomized controlled trial. Randomization is stratified according to the patient’s treatment resistance level assessed with the Dutch Method for quantification of Treatment Resistance in Depression (DM-TRD). All fill-out the Inventory of Depressive Symptomatology Self Report (IDS-SR), Outcome Questionnaire (OQ-45), Illness Perception Questionnaire Mental Health (IPQ-MH), and Work Alliance Inventory Self Report (WAI-SR). In the intervention arm, through close collaboration between patient, clinician, and researcher, a personalized ESM diary is developed based on the patient’s case conceptualization. During the ESM monitoring period (8 weeks, 5 assessments/day), patients receive feedback three times, which is discussed among the abovementioned three parties. Both patients and clinicians will evaluate the Therap-i module. Results Data collection is ongoing. Discussion This is the first study in which personalized ESM and feedback is integrated in outpatient psychotherapeutic TAU for depression. The labour intensive procedure and methodological pitfalls are anticipated challenges and were taken into account when designing the study. When hypotheses are confirmed, the Therap-i module may advance treatment for depression by providing insights into personalized patterns driving or perpetuating depressive complaints. Trial registration Trial NL7190 (NTR7381), registered prospectively 03-08-2018.

Background: Smartphone self-monitoring through ecological momentary assessment (EMA) provides insights into the daily lives of people in psychiatric treatment and has the potential to improve their care. Currently, no clinical tools are available that help clients and clinicians with creating personalized EMA diaries and interpreting the gathered data. Integration of EMA in treatment is therefore difficult.Objective: To develop a web-based application for personalized EMA in routine psychiatric care, in close collaboration with all stakeholders (i.e., clients, clinicians, researchers, and software developers). Methods: We engaged 52 clients with mood, anxiety, and/or psychotic disorders and 45 clinicians (psychiatrists, psychologists, and psychiatric nurses) in interviews, focus groups, and usability sessions. We used human-centered design principles to determine important requirements for the web-app and designed high-fidelity prototypes that were continuously reevaluated and adapted. Results: The iterative development process resulted in PETRA (PErsonalized Treatment by Real-time Assessment), which is a scientifically grounded web-app for the integration of personalized EMA in clinical care. PETRA includes a decision aid to support clients and clinicians with constructing personalized EMA diaries, an EMA diary item repository, a text-message-based diary delivery system, and a feedback module for visualizing the gathered EMA data. PETRA is integrated in electronic health record (EHR) systems to ensure ease-of-use and sustainability, 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 co-development process, its extensive yet user-friendly personalization options, its integration in EHR 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 awaits further research. As such, PETRA paves the way for a systematic investigation into the utility of personalized EMA for routine mental health care.

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.

No abstract

Experience sampling studies into daily-life affective reactivity indicate that depressed individuals react more strongly to both positive and negative stimuli than non-depressed individuals, particularly on negative affect (NA). Given the different mean levels of both positive affect (PA) and NA between patients and controls, such findings may be influenced by floor/ceiling effects, leading to violations of the normality and homoscedasticity assumptions underlying the used statistical models. Affect distributions in prior studies suggest that this may have particularly influenced NA-reactivity findings. Here, we investigated the influence of floor/ceiling effects on the observed PA- and NA-reactivity to both positive and negative events. Data came from 346 depressed, non-depressed, and remitted participants from the Netherlands Study of Depression and Anxiety (NESDA). In PA-reactivity analyses, no floor/ceiling effects and assumption violations were observed, and PA-reactivity to positive events, but not negative events, was significantly increased in the depressed and remitted groups versus the non-depressed group. However, NA-scores exhibited a floor effect in the non-depressed group and naively estimated models violated model assumptions. When these violations were accounted for in subsequent analyses, group differences in NA-reactivity that had been present in the naive models were no longer observed. In conclusion, we found increased PA-reactivity to positive events but no evidence of increased NA-reactivity in depressed individuals when accounting for violations of assumptions. The results indicate that affective-reactivity results are very sensitive to modeling choices and that previously observed increased NA-reactivity in depressed individuals may (partially) reflect unaddressed assumption violations resulting from floor effects in NA.

No abstract