Administration and Policy in Mental Health and Mental Health Services Research最新文献

At the centre of POR is the concept of collaboration between patients, therapists, agencies, and third-party payers. For this commentary, I review the articles of the special issue with attention to both the opportunities and challenges offered by practice-oriented research (POR). I also reviewed some previous research on practice-research networks and how that research might inform POR. The use of routine outcome monitoring (ROM), artificial intelligence (AI), and program evaluation (PE) models show promise for advancing POR. However, each comes with its challenges. The use of ROM to improve patient outcomes has research support. However, researchers have identified problems with implementing ROM because of low uptake by clinicians and because clinicians may see ROM as a potential intrusion. AI shows promise to improve patient outcomes by potentially providing therapists with immediate and nuanced data to inform interventions and interpersonal stances specific to each patient. However, the scaling up of AI runs the risk of dehumanizing psychological interventions. PE may provide a context for allowing therapists to engage in POR to address real-world processes and outcomes of mental health interventions. However, like ROM PE faces the challenge of trust among clinicians and patients who may be reluctant to participate. Despite these challenges, and because of efforts to nurture and maintain respectful collaborations, articles in this special issue highlight how POR can play a pivotal role in bridging the gap between theory and practice.

Despite its demonstrated value, many mental health institutions struggle to implement progress feedback effectively. There is also insufficient information about how therapists utilize progress feedback. To gain more insight, two qualitative studies were conducted. The first study compared the attitudes and motives of therapists who used and those who did not use progress feedback. The second study examined how psychologists incorporated progress feedback into their practice. In total, 23 therapists were interviewed, and the data were analyzed using thematic analysis. The first study found that almost all the therapists had a positive attitude about progress feedback. Those who did not use it indicated reasons such as a heavy workload and patient-related factors, and they also lacked sufficient information about the potential benefits of progress feedback. The second study revealed four major ways in which the therapists utilized feedback, namely: supporting actions to discuss progress feedback, discussing progress feedback with patients, modifications in the ongoing treatment, and peer consultation. However, discussions during peer consultations about using progress feedback for patients who were not benefitting from treatment and how the treatment might be adjusted accordingly were often lacking. In conclusion, it is crucial that training and education be provided to therapists on how to use progress feedback effectively. Having regular discussions about progress feedback during peer consultations could also facilitate its integration into clinical practice.

This paper describes the successful implementation of Measurement-Based Care (MBC) within a Partial Hospitalization Program (PHP) for children and adolescents. Measurement-based care (MBC), the practice of using patient-reported measures routinely to inform decision-making, is associated with improved clinical outcomes for behavioral health patients (Jong et al., Clinical Psychology Review 85, 2021; Fortney & Sladek, 2015). MBC holds great promise in partial hospital programs (PHP) to improve outcomes, yet implementation strategies are as complex as the setting itself. This paper provides a case study example of MBC implementation in a PHP for youth. Over the course of 18 months, an interdisciplinary staff of approximately 20 behavioral health professionals provided partial hospitalization level of care to 633 (39% in-person, 61% telehealth) youth from ages 5 to 18 years old. MBC in this setting incorporated daily patient self-report and weekly caregiver-reported measurements. This descriptive reconstruction, which includes examples of the data that were used during the implementation project, illustrates specific barriers and facilitators in a successful implementation in the local PHP setting. Implementation strategies to address workflow integration, leadership and supervision, and coaching are described, including evolution of these strategies over the course of implementation. Practical considerations for implementing MBC in youth PHP settings are discussed. Finally, the authors explore the potential relationships between the data-driven MBC model of decision making and the development of resilient organizations.

Aimed at understanding and improving psychological therapies as they are conducted in clinical routine, practice-oriented research (POR) is now a well-established approach to the scientific foundations of mental health care services. Resting on the accumulation of a wide range of practice-based evidence related to treatment outcome and process, as well as factors associated with the participants of psychotherapy and its context, POR is ripe for new developments – regarding what to investigate and how to investigate it. This paper is the introduction of a series devoted to recent advances and future directions of POR as their pertained to routine outcome monitoring, technologies and artificial intelligence, the integration of constructs and methods from program evaluation and implementation science, and the investigation of populations with limited financial resources across various regions of the world. The series also includes commentaries from two leaders of POR.

Based on patient-reported outcomes data analyzed at the provider level, there is evidence that psychotherapists can possess effectiveness strengths and weaknesses when treating patients with different presenting concerns. These within-therapist differences hold promise for personalizing care by prospectively matching patients to therapists’ historical effectiveness strengths. In a double-masked randomized controlled trial (RCT; NCT02990000), such matching outperformed pragmatically determined usual case assignment—which leaves personalized, measurement-based matching to chance—in naturalistic outpatient psychotherapy (Constantino et al., JAMA Psychiatry 78:960–969, 2021). Demonstrating that personalization can be even more precise, some research has demonstrated that the strength of this positive match effect was moderated by certain patient characteristics. Notably, though, it could also be that matching is especially important for some therapists to achieve more effective outcomes. Examining this novel question, the present study drew on the Constantino et al. (JAMA Psychiatry 78:960–969, 2021) trial data to explore three therapist-level moderators of matching: (a) effectiveness “spread” (i.e., greater performance variability across patients’ presenting problem domains), (b) overestimation of their measurement-based and problem-specific effectiveness, and (c) the frequency with which they use patient-reported routine outcomes monitoring in their practice. Patients were 206 adults, randomized to the match or control condition, treated by 40 therapists who were crossed over conditions. The therapist variables were assessed at the trial’s baseline and patients’ symptomatic/functional impairment and global distress were assessed regularly up to 16 weeks of treatment. Hierarchical linear models revealed that only therapist effectiveness spread significantly moderated the match effect for the global distress outcome; for therapists with more spread, the match effect was more pronounced, whereas the match effect was minimal for therapists with less effectiveness spread. Notably, two therapist-level covariates unexpectedly emerged as significant moderators for the symptomatic/functional impairment outcome; for clinicians who consistently treated patients with higher versus lower average severity levels and who relatedly treated a higher proportion of patients with primary presenting problems of substance misuse or violence, the beneficial match effect was even stronger. Thus, measurement-based matching may be especially potent for therapists with more variable effectiveness across problem domains, and who consistently treat patients with more severe presenting concerns or with particular primary problems, which provides further precision in conceptualizing personalized care.

We aim to use topic modeling, an approach for discovering clusters of related words (“topics”), to predict symptom severity and therapeutic alliance in psychotherapy transcripts, while also identifying the most important topics and overarching themes for prediction. We analyzed 552 psychotherapy transcripts from 124 patients. Using BERTopic (Grootendorst, 2022), we extracted 250 topics each for patient and therapist speech. These topics were used to predict symptom severity and alliance with various competing machine-learning methods. Sensitivity analyses were calculated for a model based on 50 topics, LDA-based topic modeling, and a bigram model. Additionally, we grouped topics into themes using qualitative analysis and identified key topics and themes with eXplainable Artificial Intelligence (XAI). Symptom severity could be predicted with highest accuracy by patient topics ((r)=0.45, 95%-CI 0.40, 0.51), whereas alliance was better predicted by therapist topics ((r)=0.20, 95%-CI 0.16, 0.24). Drivers for symptom severity were themes related to health and negative experiences. Lower alliance was correlated with various themes, especially psychotherapy framework, income, and everyday life. This analysis shows the potential of using topic modeling in psychotherapy research allowing to predict several treatment-relevant metrics with reasonable accuracy. Further, the use of XAI allows for an analysis of the individual predictive value of topics and themes. Limitations entail heterogeneity across different topic modeling hyperparameters and a relatively small sample size.

Ecological momentary assessment (EMA) allows measuring intra-individual processes moment by moment, identifying and modeling, in a naturalistic way, individual levels and changes in different psychological processes. However, active EMA requires a high degree of adherence, as it implies a significant burden for patients. Moreover, there is still no consensus on standardized procedures for implementation. There have been few results in detecting desirable characteristics for the design and implementation of an EMA device. Studies that address these issues from the perspectives of participants in psychotherapeutic processes are needed. To analyze the perspectives of patients, therapists and supervisors on the implementation of an EMA device in a psychotherapeutic treatment for depression. The sample will include eight patients, eleven therapists and five supervisors, taken from a research project that implemented an EMA system for monitoring the dynamics of affectivity at the beginning of psychotherapies for depression. Semi-structured interviews specific to each group are being conducted and analyzed from a qualitative approach based on consensual qualitative research (CQR). Participants reported having a positive evaluation of the study's informational resources and implementation. Difficulties were expressed in responding in the morning hours and the importance of having a customized EMA that is tailored to the needs of the patients was expressed. Furthermore, patients and therapists agreed that the impact of the use of the monitoring system on treatment was neutral or positive. In contrast, patients considered the EMA to be positive for their daily life.

Disruptive behavior of patients in acute psychiatric care is a problem for both patients and staff. Preventing a patient’s impending disruption requires recognizing and understanding early signals. There are indications that a change in a patient’s global functioning may be such a signal. The global functioning of patients is a multidimensional view on their functioning. It captures a patient’s psychological symptoms, social skills, symptoms of violence, and activities in daily living. The aim of this study was to gain insight into the predictive value of global functioning on the risk of disruptive behavior of patients in acute psychiatric care. Also assessed was the time elapsed between the change in global functioning and a patient’s disruptive behavior, which is necessary to know for purposes of early intervention. In a longitudinal retrospective study, we used daily measurements with the Brøset Violence Checklist (BVC) and the Kennedy Axis V (K-As) of each patient admitted to two acute psychiatric units over a period of six years. Data from 931 patients for the first 28 days after their admission were used for survival analysis and cox regression analysis. Disruptive behavior was mostly observed during the first days of hospitalization. Global functioning predicted disruptive behavior from the very first day of hospitalization. A cut-off score of 48 or lower on the K-As on the first admission day predicted a higher risk of disruptive behavior. If functioning remained poor or deteriorated substantially over three days, this was an additional signal of increased risk of disruptive behavior. Improvement in global functioning was associated with a decreased risk of disruptive behavior. More attention is needed for early interventions on global functioning to prevent disruptive behavior.