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.

An examination of therapists' professional characteristics as moderators of the effect of feedback on psychological treatment outcomes.

Feedback-informed treatment (FIT) has been shown to reduce the gap between more and less effective therapists. This study aimed to examine therapists' professional characteristics as potential moderators of the effect of feedback on treatment outcomes.The IAPT-FIT Trial was a clinical trial where therapists were randomly assigned to a FIT group or a usual care control group. Treatment response was monitored using measures of depression (PHQ-9), anxiety (GAD-7) and functional impairment (WSAS). In a secondary analysis of this trial (n = 1,835 patients; t = 67 therapists), we used multilevel modelling to examine interactions between therapists' professional characteristics (e.g., attitude towards and self-efficacy regarding feedback utilization, decision-making style, job satisfaction, burnout, difficulties in practice, coping styles, caseload size) with random allocation (FIT vs. controls) to identify moderators of the effects of feedback.Between 9.6% and 10.8% of variability in treatment outcomes was attributable to therapist effects. Therapist-level caseload sizes and external feedback propensity (EFP) moderated the effect of feedback on depression outcomes. No statistically significant main effects were found for any of the included therapist characteristics.FIT reduced variability in outcomes between therapists and was particularly effective for therapists with high EFP and larger caseloads.

Practice-based evidence for spiritually integrated psychotherapies: Examining trajectories of psychological and spiritual distress.

The aims of this practice-based evidence study were to (a) examine clients' trajectories of psychological and spiritual distress over the course of spiritually integrated psychotherapies (SIPs) and (b) explore the role of varying types of spiritual interventions in these outcomes. In total, 164 practitioners of SIPs from 37 settings in a practice-research network administered the Clinically Adaptive Multidimensional Outcome Survey (Sanders et al., 2018) at each session with 1,227 clients and reported their use of theoretical orientations and spiritual interventions on an after-session summary checklist. Focusing on sessions over an initial 12-week period, latent growth curve modeling analyses revealed that clients, on average, experienced significant reduction of psychological distress during their engagement in SIPs with improvements occurring most sharply in the first month. Further, other findings revealed a salient reciprocal interplay with spiritual distress throughout treatment, such that clients who were struggling with their religious faith and/or spirituality were more psychologically distressed and displayed a more attenuated and gradual pattern of symptom reduction. In such cases, clinicians frequently utilized spiritual interventions involving basic skills (e.g., spiritual assessment), virtues (e.g., discuss self-control), and religious attachment (e.g., encourage acceptance of divine love) that were uniquely associated with clients' rate and duration of decline in psychological and spiritual distress. The present findings affirm the routine effectiveness of SIPs along with highlighting the potential value of certain spiritual interventions in supporting holistic recovery among clients who want clinicians to be culturally responsive to their spiritual and/or religious identities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The efficacy of individual humanistic-experiential therapies for the treatment of depression: A systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: Conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating the efficacy of individual humanistic-experiential therapies (HEPs) for depression. METHOD: Database searches (Scopus, Medline, and PsycINFO) identified RCTs comparing any HEP intervention with a treatment-as-usual (TAU) control or active alternative intervention for the treatment of depression. Included studies were assessed using the Risk of Bias 2 tool and narratively synthesized. Post-treatment and follow-up effect sizes were aggregated using random-effects meta-analysis and moderators of treatment effect were explored (PROSPERO: CRD42021240485). RESULTS: Seventeen RCTs, synthesized across four meta-analyzes, indicated HEP depression outcomes were significantly better than TAU controls at post-treatment (g = 0.41, 95% CI [0.18, 0.65], n = 735), but not significantly different at follow-up (g = 0.14, 95% CI [-0.30, 0.58], n = 631). HEP depression outcomes were comparable to active treatments at post-treatment (g = -0.09, 95% CI [-0.26, 0.08], n = 2131), but significantly favored non-HEP alternative interventions at follow-up (g = -0.21, 95% CI [-0.35, -0.07], n = 1196). CONCLUSION: Relative to usual care, HEPs are effective in the short-term and comparable to non-HEP alternative interventions at post-treatment, but not at follow-up. However, imprecision, inconsistency, and risk of bias concerns were identified as limitations of the evidence included. Future large-scale trials of HEPs with equipoise between comparator conditions are required.

What factors facilitate partnerships between higher education and local mental health services for students? A case study collective.

BACKGROUND: Higher education institutions face challenges in providing effective mental health services for diverse student needs. In the UK, discrepancies between healthcare and education service provision create barriers for students and require stronger alignment through partnerships. OBJECTIVES: This study aimed to identify risks, barriers and enablers to developing service partnerships between universities and the National Health Service (NHS) in England. It investigated existing partnerships and strategies that facilitate effective collaborative working. DESIGN AND SETTING: A case study approach was employed, including coproduction and stakeholder involvement with staff and service users, to gather information from eight English universities developing regional student mental health hubs. This research received appropriate ethical approval. PARTICIPANTS: In total, 27 professional staff from counselling, mental health, disability and well-being services participated and represented their respective services. OUTCOME MEASURES: Descriptive information was collected from service websites, handbooks, reports and 11 focus groups using a standardised data collection template. Inter-rater reliability was used to determine the agreement between coders and finalise focus group themes. EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Standards for Reporting Qualitative Research were adopted. RESULTS: Using inductive thematic analysis, five themes were identified for developing partnerships: building blocks, facing barriers, achieving positive outcomes, shaping student services and developing coordinated care. Fleiss' kappa showed strong agreement between raters regarding the partnership factors (k=0.84 (95% CI 0.81 to 0.87), p<0.0005). Effective communication, shared understanding and trust were essential. Barriers included restrictions to information sharing and incompatible data infrastructures between services. CONCLUSIONS: Stronger partnerships between universities and NHS are needed to meet increasing student mental health demands. Addressing barriers and implementing strategies to develop partnerships can enhance student services. PREREGISTRATION: https://osf.io/u54qk/.

Applying precision methods to treatment selection for moderate/severe depression in person-centered experiential therapy or cognitive behavioral therapy.

OBJECTIVE: To develop two prediction algorithms recommending person-centered experiential therapy (PCET) or cognitive-behavioral therapy (CBT) for patients with depression: (1) a full data model using multiple trial-based and routine variables, and (2) a routine data model using only variables available in the English NHS Talking Therapies program. METHOD: Data was used from the PRaCTICED trial comparing PCET vs. CBT for 255 patients meeting a diagnosis of moderate or severe depression. Separate full and routine data models were derived and the latter tested in an external data sample. RESULTS: The full data model provided the better prediction, yielding a significant difference in outcome between patients receiving their optimal vs. non-optimal treatment at 6- (Cohen's d = .65 [.40, .91]) and 12 months (d = .85 [.59, 1.10]) post-randomization. The routine data model performed similarly in the training and test samples with non-significant effect sizes, d = .19 [-.05, .44] and d = .21 [-.00, .43], respectively. For patients with the strongest treatment matching (d ≥ 0.3), the resulting effect size was significant, d = .38 [.11, 64]. CONCLUSION: A treatment selection algorithm might be used to recommend PCET or CBT. Although the overall effects were small, targeted matching yielded somewhat larger effects.

A Clinical Leadership Lens on Implementing Progress Feedback in Three Countries: Development of a Multidimensional Qualitative Coding Scheme.

BACKGROUND: Progress feedback, also known as measurement-based care (MBC), is the routine collection of patient-reported measures to monitor treatment progress and inform clinical decision-making. Although a key ingredient to improving mental health care, sustained use of progress feedback is poor. Integration into everyday workflow is challenging, impacted by a complex interrelated set of factors across patient, clinician, organizational, and health system levels. This study describes the development of a qualitative coding scheme for progress feedback implementation that accounts for the dynamic nature of barriers and facilitators across multiple levels of use in mental health settings. Such a coding scheme may help promote a common language for researchers and implementers to better identify barriers that need to be addressed, as well as facilitators that could be supported in different settings and contexts. METHODS: Clinical staff, managers, and leaders from two Dutch, three Norwegian, and four mental health organizations in the USA participated in semi-structured interviews on how intra- and extra-organizational characteristics interact to influence the use of progress feedback in clinical practice, supervision, and program improvement. Interviews were conducted in the local language, then translated to English prior to qualitative coding. RESULTS: A team-based consensus coding approach was used to refine an a priori expert-informed and literature-based qualitative scheme to incorporate new understandings and constructs as they emerged. First, this hermeneutic approach resulted in a multi-level coding scheme with nine superordinate categories and 30 subcategories. Second-order axial coding established contextually sensitive categories for barriers and facilitators. CONCLUSIONS: The primary outcome is an empirically derived multi-level qualitative coding scheme that can be used in progress feedback implementation research and development. It can be applied across contexts and settings, with expectations for ongoing refinement. Suggestions for future research and application in practice settings are provided. Supplementary materials include the coding scheme and a detailed playbook.

Mental health trajectories in university students across the COVID-19 pandemic: findings from the Student Wellbeing at Northern England Universities prospective cohort study.

Introduction: Psychological wellbeing in university students is receiving increased focus. However, to date, few longitudinal studies in this population have been conducted. As such, in 2019, we established the Student Wellbeing At Northern England Universities (SWANS) cohort at the University of York, United Kingdom aiming to measure student mental health and wellbeing every six months. Furthermore, the study period included the COVID-19 pandemic, giving an opportunity to track student wellbeing over time, including over the pandemic. Methods: Eligible participants were invited to participate via email. Data were collected, using Qualtrics, from September 2019 to April 2021, across five waves (W1 to W5). In total, n = 4,622 students participated in at least one wave of the survey. Data collection included sociodemographic, educational, personality measures, and mental health and wellbeing. Latent profile analyses were performed, exploring trajectories of student wellbeing over the study period for those who had completed at least three of the five waves of the survey (n = 765), as measured by the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS). Results: Five latent profile trajectories of student wellbeing were identified. Of these, the two latent classes with initially higher wellbeing scores had broadly stable wellbeing across time (total n = 505, 66%). Two classes had lower initial scores, which lowered further across time (total n = 227, 30%). Additionally, a fifth class of students was identified who improved substantially over the study period, from a mean WEMWBS of 30.4 at W1, to 49.4 at W5 (n = 33, 4%). Risk factors for having less favourable wellbeing trajectories generally included identifying as LGBT+, self-declaring a disability, or previously being diagnosed with a mental health condition. Conclusion: Our findings suggest a mixed picture of the effect of the COVID-19 pandemic on student wellbeing, with a majority showing broadly consistent levels of wellbeing across time, a smaller but still substantial group showing a worsening of wellbeing, and a small group that showed a very marked improvement in wellbeing. Those from groups traditionally underrepresented in higher education were most at risk of poorer wellbeing. This raises questions as to whether future support for wellbeing should target specific student subpopulations.

Efficacy of personalized psychological interventions: A systematic review and meta-analysis.

OBJECTIVE: To evaluate the efficacy of different approaches to personalization in psychological therapy. METHOD: This was a systematic review and meta-analysis of randomized controlled trials that compared the mental health outcomes of personalized treatment with standardized treatment and other control groups. Eligible studies were identified through three databases (Scopus, APA PsycInfo, and Web of Science). We conducted a narrative synthesis and random effects meta-analysis of available outcomes date, including subgroup analyses to investigate sources of effect size heterogeneity. The review protocol was preregistered in the Open Science Framework. RESULTS: Seventeen studies (N = 7,617) met inclusion criteria for the review, nine of which (N = 5,134) provided sufficient data for inclusion in meta-analysis. Eight studies were classed as having high risk of bias, eight had moderate risk, and one had low risk. There was no significant evidence of publication bias. A statistically significant effect size was found in favor of personalized treatment relative to standardized treatment (d = 0.22, 95% CI [0.05, 0.39], p = .011). When studies with a high risk of bias were removed, this effect size was smaller but remained statistically significant (d = 0.14, 95% CI [0.08, 0.20], p < .001). CONCLUSION: Current evidence indicates that personalization is an effective strategy to improve outcomes from psychological therapy, and the seemingly small effect size advantage of personalization could have an important impact at a clinical population level. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Bayesian network analysis of psychosocial risk and protective factors for suicidal ideation.

Background: The aim of this study was to investigate and model the interactions between a range of risk and protective factors for suicidal ideation using general population data collected during the critical phase of the COVID-19 pandemic. Methods: Bayesian network analyses were applied to cross-sectional data collected 1 month after the COVID-19 lockdown measures were implemented in Austria and the United Kingdom. In nationally representative samples (n = 1,005 Austria; n = 1,006 UK), sociodemographic features and a multi-domain battery of health, wellbeing and quality of life (QOL) measures were completed. Predictive accuracy was examined using the area under the curve (AUC) within-sample (country) and out-of-sample. Results: The AUC of the Bayesian network models were ≥ 0.84 within-sample and ≥0.79 out-of-sample, explaining close to 50% of variability in suicidal ideation. In total, 15 interrelated risk and protective factors were identified. Seven of these factors were replicated in both countries: depressive symptoms, loneliness, anxiety symptoms, self-efficacy, resilience, QOL physical health, and QOL living environment. Conclusions: Bayesian network models had high predictive accuracy. Several psychosocial risk and protective factors have complex interrelationships that influence suicidal ideation. It is possible to predict suicidal risk with high accuracy using this information.

Pragmatic randomized controlled trial of the Mind Management Skills for Life Programme as an intervention for occupational burnout in mental healthcare professionals.

BACKGROUND: Occupational burnout is highly prevalent in the mental healthcare workforce and associated with poorer job satisfaction, performance and outcomes. AIMS: To evaluate the effects of the Mind Management Skills for Life Programme on burnout and wellbeing. METHODS: N = 173 mental health nurses were recruited from the English National Health Service during the acute phase of the COVID-19 crisis. Participants were allocated to an immediate intervention or a delayed intervention control group, using a stepped wedge randomized controlled trial design. Measures of burnout (OLBI) and wellbeing (WEMWBS) were completed at four time-points: [1] baseline; [2] after the first group finished the intervention; [3] after the second group finished the intervention; and [4] six-months follow-up. RESULTS: Between-group differences were compared at each time-point using ANCOVA adjusting for baseline severity. Statistically significant effects on burnout (d = 0.60) and wellbeing (d = -0.62) were found at time-point 2, favouring the intervention relative to waitlist control. No significant differences were found at subsequent time-points, indicating that both groups improved and maintained their gains after the intervention. CONCLUSIONS: This intervention led to moderate improvements in burnout and wellbeing, despite the adverse circumstances of the COVID-19 pandemic at the time of the study.

The role of socioeconomic deprivation in explaining neighborhood and clinic effects in the effectiveness of psychological interventions.

OBJECTIVE: Treatment outcomes are known to vary according to therapist and clinic/organization (therapist effect, clinic effect). Outcomes may also vary according to the neighborhood where a person lives (neighborhood effect), but this has not previously been formally quantified. Evidence suggests that deprivation may contribute to explaining such cluster effects. This study aimed to (a) simultaneously quantify neighborhood, clinic, and therapist effects on intervention effectiveness and (b) determine the extent to which deprivation variables explain neighborhood and clinic effects. METHOD: The study used a retrospective, observational cohort design with a high intensity psychological intervention sample (N = 617,375), and a low intensity (LI) psychological intervention sample (N = 773,675). Samples each included 55 clinics, 9,000-10,000 therapists/practitioners, and over 18,000 neighborhoods in England. Outcomes were postintervention depression and anxiety scores and clinical recovery. Deprivation variables included individual employment status, domains of neighborhood deprivation, and clinic-level mean deprivation. Data were analyzed using cross-classified multilevel models. RESULTS: Unadjusted neighborhood effects of 1%-2% and unadjusted clinic effects of 2%-5% were detected, with proportionally larger effects for LI interventions. After controlling for predictors, adjusted neighborhood effects of 0.0%-0.1% and clinic effects of 1%-2% remained. Deprivation variables were able to explain a significant proportion of the neighborhood effect (80%-90% of neighborhood variance) but not clinic effect. The majority of neighborhood variance could only be explained by a shared effect of baseline severity and socioeconomic deprivation variables. CONCLUSIONS: People in different neighborhoods respond differently to psychological intervention, and this clustering effect was mainly explained by socioeconomic factors. People also respond differently according to the clinic they access, but this could not be completely explained by deprivation in the present study. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Routine Outcome Monitoring (ROM) and Feedback: Research Review and Recommendations.

OBJECTIVE: To provide a research review of the components and outcomes of routine outcome monitoring (ROM) and recommendations for research and therapeutic practice. METHOD: A narrative review of the three phases of ROM - data collection, feeding back data, and adapting therapy - and an overview of patient outcomes from 11 meta-analytic studies. RESULTS: Patients support ROM when its purpose is clear and integrated within therapy. Greater frequency of data collection is more important for shorter-term therapies, and use of graphs, greater specificity of feedback, and alerts are helpful. Overall effects on patient outcomes are statistically significant (g ≈ 0.15) and increase when clinical support tools (CSTs) are used for not-on-track cases (g ≈ 0.36-0.53). Effects are additive to standard effects of psychological therapies. Organizational, personnel, and resource issues remain the greatest obstacles to the successful adoption of ROM. CONCLUSION: ROM offers a low-cost method for enhancing patient outcomes, on average resulting in an ≈ 8% advantage (success rate difference; SRD) over standard care. CSTs are particularly effective for not-on-track patients (SRD between ≈ 20% and 29%), but ROM does not work for all patients and successful implementation is a major challenge, along with securing appropriate cultural adaptations.

Clinical Effectiveness and Cost-Effectiveness of Supported Mindfulness-Based Cognitive Therapy Self-help Compared With Supported Cognitive Behavioral Therapy Self-help for Adults Experiencing Depression: The Low-Intensity Guided Help Through Mindfulness (LIGHTMind) Randomized Clinical Trial.

Importance: Depression is prevalent. Treatment guidelines recommend practitioner-supported cognitive behavioral therapy self-help (CBT-SH) for mild to moderate depression in adults; however, dropout rates are high. Alternative approaches are required. Objective: To determine if practitioner-supported mindfulness-based cognitive therapy self-help (MBCT-SH) is superior to practitioner-supported CBT-SH at reducing depressive symptom severity at 16 weeks postrandomization among patients with mild to moderate depression and secondarily to examine if practitioner-supported MBCT-SH is cost-effective compared with practitioner-supported CBT-SH. Design, Setting, and Participants: This was an assessor- and participant-blinded superiority randomized clinical trial with 1:1 automated online allocation stratified by center and depression severity comparing practitioner-supported MBCT-SH with practitioner-supported CBT-SH for adults experiencing mild to moderate depression. Recruitment took place between November 24, 2017, and January 31, 2020. The study took place in 10 publicly funded psychological therapy services in England (Improving Access to Psychological Therapies [IAPT]). A total of 600 clients attending IAPT services were assessed for eligibility, and 410 were enrolled. Participants met diagnostic criteria for mild to moderate depression. Data were analyzed from January to October 2021. Interventions: Participants received a copy of either an MBCT-SH or CBT-SH workbook and were offered 6 support sessions with a trained practitioner. Main Outcomes and Measures: The preregistered primary outcome was Patient Health Questionnaire (PHQ-9) score at 16 weeks postrandomization. The primary analysis was intention-to-treat with treatment arms masked. Results: Of 410 randomized participants, 255 (62.2%) were female, and the median (IQR) age was 32 (25-45) years. At 16 weeks postrandomization, practitioner-supported MBCT-SH (n = 204; mean [SD] PHQ-9 score, 7.2 [4.8]) led to significantly greater reductions in depression symptom severity compared with practitioner-supported CBT-SH (n = 206; mean [SD] PHQ-9 score, 8.6 [5.5]), with a between-group difference of -1.5 PHQ-9 points (95% CI, -2.6 to -0.4; P = .009; d = -0.36). The probability of MBCT-SH being cost-effective compared with CBT-SH exceeded 95%. However, although between-group effects on secondary outcomes were in the hypothesized direction, they were mostly nonsignificant. Three serious adverse events were reported, all deemed not study related. Conclusions and Relevance: In this randomized clinical trial, practitioner-supported MBCT-SH was superior to standard recommended treatment (ie, practitioner-supported CBT-SH) for mild to moderate depression in terms of both clinical effectiveness and cost-effectiveness. Findings suggest that MBCT-SH for mild to moderate depression should be routinely offered to adults in primary care services. Trial Registration: isrctn.org Identifier: ISRCTN13495752.

Telephone treatments in Improving Access to Psychological Therapies services: an analysis of use and impact on treatment uptake.

BACKGROUND: There is debate about how best to increase access to psychological therapy and deliver mental healthcare effectively and efficiently at a national level. One trend is the increased use of the telephone to deliver therapy. However, there is the potential to disadvantage certain patient groups and/or impact on uptake of help. This study aims to answer three questions: (i) Which factors are associated with being offered an assessment by telephone? (ii) Which factors are associated with attendance at assessment? and (iii) What is the impact of an assessment by telephone on subsequent treatment appointment? METHODS: Routine outcome data was provided by seven UK Improving Access to Psychological Therapy services. The analysis sample comprised 49,923 patients who referred to 615 general practices in 2017. Multilevel modelling, including service and GP practice as random factors, was used to answer the three research questions. RESULTS: The offer of an initial assessment by telephone was strongly associated with local service configuration. Patient self-referral, a shorter wait, greater age and lower deprivation were associated with attendance at assessment and subsequent treatment session. Telephone mode assessment had no impact on the uptake of the assessment but may influence the uptake of further treatment if this was also by telephone. The practitioner carrying out the assessment had a significant effect on subsequent treatment uptake. CONCLUSION: Offering telephone assessments does not have a negative impact on uptake of assessment and services may benefit by facilitating and integrating telephone assessments into their systems. The COVID-19 pandemic has accelerated the use of telephone and other remote means of delivery, and results from this study can inform services to consider how best to re-configure post-pandemic.

Idiographic patient reported outcome measures (I-PROMs) for routine outcome monitoring in psychological therapies: Position paper.

Idiographic patient-reported outcome measures (I-PROMs) are a growing set of individualized tools for use in routine outcome monitoring (ROM) in psychological therapies. This paper presents a position statement on their conceptualization, use, and analysis, based on contemporary evidence and clinical practice. Four problem-based, and seven goal-based, I-PROMs, with some evidence of psychometric evaluation and use in psychotherapy, were identified. I-PROMs may be particularly valuable to the evaluation of psychological therapies because of their clinical utility and their alignment with a patient-centered approach. However, there are several challenges for I-PROMs: how to generate items in a robust manner, their measurement model, methods for establishing their reliability and validity, and the meaning of an aggregated I-PROM score. Based on the current state of the literature, we recommend that I-PROMs are used to complement nomothetic measures. Research recommendations are also made regarding the most appropriate methods for analyzing I-PROM data.