Richard Morriss

Background: Cognitive difficulties, including problems with attention and executive processing, are common in major depressive disorder (MDD), and strongly predict psychosocial and occupational functioning. Impairment in sustained attention contributes to increased intra-individual variability (IIV) in reaction times observed during cognitive tasks. Understanding brain network changes associated with IIV could guide novel neuromodulation strategies targeting cognitive difficulties. Methods: We analyzed baseline resting-state fMRI data from 209 patients with moderate-to-severe treatment-resistant MDD who participated in the BRIGhTMIND neuromodulation trial. Following a preregistered analytic protocol, we examined associations between: functional connectivity across three core brain networks (executive control, ECN; default mode, DMN; and salience network, SN); components of IIV derived from a choice reaction time task (using a three-parameter ex-Gaussian model); and functioning. Results: Greater IIV was linked to increased ECN-DMN functional connectivity. The ECN supports top-down control and externally directed cognition, while the DMN supports internal mentation and rumination. ECN-DMN connectivity was modulated by the SN, which prioritizes salient internal and external stimuli. Higher SN-ECN connectivity was associated with lower ECN-DMN connectivity and with faster mean reaction times. Both IIV and mean reaction time predicted functioning, with poorer functioning related to a slowed and inflexible response pattern. Conclusions: Distinct components of reaction time variability are associated with specific patterns of brain network connectivity, largely independent of mood severity. Connectivity between the salience and executive control networks may represent a promising target for neuromodulation interventions focused on cognitive deficits in MDD.

BACKGROUND Psychological therapies are effective for several physical and mental health problems, but their overall effectiveness has not improved for over forty years. Technology development has applied the approach of benchmarking effectiveness to evaluate the combined impact of multiple adaptations, compared to best practice outcomes. However, this approach has been used little in psychological therapy research, when the pace of digitally enhanced adaptations may mean this approach adds value to the field. OBJECTIVE This study evaluated the clinical effectiveness and efficiency of a psychological therapy service model that employed multiple, digitally enhanced adaptations across the care pathway for those living with and beyond cancer, experiencing moderate-to-severe depression and/or anxiety. Service outcomes were benchmarked against an internationally recognized standard of best practice in the National Health Service Talking Therapies (NHS TT) program. METHODS Between 20th January 2022 and 31st March 2026, adults with a cancer diagnosis and significant anxiety and/or depression were referred to the East Midlands Cancer Alliance Centre for Psychosocial Health (EMCA CPH), The service incorporated seven adaptations to the care pathway to improve outcomes: (1) training and supervision of referrers; (2) a digitally enhanced therapy preparation intervention that also included (3) personalized smart-messaging reminders of patients’ motivations for therapy attendance, and (4) accommodation of patient preferences; (5) Routine Outcome Monitoring that applied dynamic algorithm-based predictions of patient prognosis to alert therapists to patients who may not improve; (6) use of session recordings to support therapists to deliberately practice their individualized skill growing edges, and (7) a digitally supported relapse prevention intervention that extended beyond discharge. Employing a longitudinal, time-series design, clinical outcomes for depression and anxiety (PHQ‑9, GAD‑7) were analysed using NHS TT definitions of reliable improvement, reliable recovery, and reliable deterioration. EMCA CPH performance was benchmarked against the 145 NHS TT services reporting 2024–25 data. Logistic regressions were used to identify any predictors of reliable improvement. RESULTS Of 639 patients referred to EMCA CPH, 356 met criteria for the service and 282 (79%) provided follow-up data. The evaluated service achieved rates of reliable improvement (241/282, 85.5%) and recovery (166/277, 59.9%), above the 99th and 97th centiles respectively compared to benchmarked standard NHS TT services. The reliable deterioration rate reported (7/282, 2.5%) was lower than all 2024-25 NHS TT services. More severe baseline depression (OR=0.89, 95% CI [0.83, 0.94], P<.001) and longer waiting times (OR=0.99, 95% CI [0.98, 0.99], P=.012) predicted lower likelihood of reliable recovery. CONCLUSIONS Psychological therapy provided by EMCA CPH, employing a range of digitally supported personalization methods and pathway innovations, obtained greater effectiveness and efficiency compared to NHS TT services. Further research is required to determine whether the personalization methods contributed to this improved performance or if it was due to other factors.

Background: Ambulatory assessment and active and passive monitoring all offer a real-time, flexible approach to assessing mood and behavior in mood disorders. Despite their potential, concerns remain regarding the performance, usability, adherence, and potential safety of these tools. Objective: This study synthesizes the findings from 7 systematic reviews, integrating quantitative and qualitative data from randomized trials, observational studies, and user experience research to evaluate the performance, feasibility, acceptability, and clinical impact of ambulatory assessment and mood monitoring in people with depression and bipolar disorder. We assessed studies over the medium or long term (3 months or more). Methods: A summary of a series of systematic reviews was carried out by the authors—including meta-analyses (for quantitative data) and meta-syntheses (for qualitative data). Eight electronic databases were searched, and mixed methods studies were included. Studies were assessed for risk of bias. The results were checked for coherence, and recommendations were made by individuals with lived experience, methodologists, and psychiatrists. GRADE (Grading of Recommendations Assessment, Development, and Evaluation) was used to assess the quality and strength of the evidence. Results: The 111 included studies included 19,945 participants and used 69 different ambulatory assessment protocols or mood-monitoring interventions. Key barriers to implementation were identified, including performance inconsistency, adverse effects, and user disengagement. Evidence-based recommendations are provided to guide future clinical and research applications. Conclusions: Ambulatory assessment and mood monitoring hold promise in research and clinical practice, yet their implementation requires more rigorous evaluation, greater personalization, and responsible, user-centered design. Crucially, these measures can add granularity and confirmation, but additional context is often required, and none of these measures are robust enough yet to replace current outcomes.

Background Ambulatory assessment and mood monitoring offer a promising, flexible, and efficient approach for assessing mood, mental state, and behaviour, potentially improving on traditional clinical outcome measures. However, the real-world utility of these novel technologies fundamentally depends on their demonstrated performance. Aims This systematic review aimed to assess the performance and validity of active and passive ambulatory assessment and mood monitoring outcome measures in randomised and non-randomised studies in depression over 3 months or longer, evaluating their performance against established clinical measures and through inter-ambulatory assessment comparisons. Methods Systematic review of performance of ambulatory assessment and mood monitoring protocols in RCTs and non-randomised studies in depression (PROSPERO: CRD42023396473). Studies were identified and rated for risk of bias. We were not able to pool performance data to calculate effect sizes so we were unable to complete meta-analysis. Results 35 studies including 9310 participants used 28 different ambulatory assessment/mood tracking procedures and included 436 performance metrics. There was large inconsistency and heterogeneity in these reported metrics which prevented robust comparison and definitive inferences around performance. Active ambulatory assessment measures demonstrated stronger correlation coefficients than passive ambulatory assessment when compared to established measures. Aggregate passive ambulatory assessment measures may perform better than single item measures. Most studies had low-moderate risk of bias. Conclusions Despite ambulatory assessment’s promise, our findings indicate a critical knowledge gap: it remains unclear whether passive ambulatory assessment approaches have sufficient performance to provide a less subjective method of mood measurement. The reported methodological heterogeneity across studies, particularly in measurement and reporting of performance metrics prevents robust comparison and replication of findings. Increased standardization in ambulatory assessment methodology and reporting is needed to enable reliable assessment and widespread implementation of these novel behavioural measures.

Background Long covid affects a significant proportion of people following SARS-CoV-2 infection and is associated with persistent symptoms such as fatigue, cognitive dysfunction and breathlessness which can negatively impact a person’s ability to return to and remain in work. Although tiered vocational rehabilitation (VR) models have been proposed, these are often generic, lack empirical validation and may not address the complex, fluctuating needs of this population. Objectives To co-design a VR intervention (the COVID-19-VR intervention) to support return to work (RTW) for people with long covid (pwLC). Setting Primary and secondary care. Design Mixed-methods target population-centred, person-based approach in three stages: Stage 1: interviews (n=21) with pwLC to identify issues and challenges faced in working with long covid. Stage 2: three co-design workshops with pwLC and service providers to (a) generate guiding principles, (b) identify key intervention features to address work needs, (c) create a logic model to illustrate how the intervention could work and (d) develop a treatment plan and resources. Stage 3: feasibility and acceptability testing in six cases (three critical care admissions, three primary care referrals). Results PwLC described work-related problems relating to: fluctuating symptoms (cognition, fatigue and breathlessness), employer, coworker and family’s understanding of long covid and workplace adjustments. We developed a 6-session, 12-week individually tailored, remotely delivered intervention that included vocational goal setting, RTW planning, fatigue/symptom management, financial advice, and where permitted, education for family/employers, employer engagement and negotiation of a phased RTW. Following feasibility testing, changes included accommodating the long-term nature of long covid, addressing unmet psychological needs, and adding content on adjustment, processing traumatic experience and performance/symptom anxiety, with extended delivery including monitoring, review and case coordination. Conclusions PwLC may need specialist help to RTW. Our COVID-19-VR appears feasible and acceptable and warrants further evaluation using a staged approach, prior to any definitive effectiveness trial.

Background: The COVID-19 pandemic raised concerns about the mental health of an already burdened healthcare workforce. This study examined mental health trajectories among healthcare workers (HCWs) across the pandemic and identified personal and employment factors associated with different symptom patterns. Methods: Longitudinal data were drawn from the NHS CHECK cohort, including clinical and non-clinical staff from 18 NHS Trusts in England (April 2020–April 2023). Growth curve and growth mixture models identified latent classes of HCWs characterized by distinct trajectories of probable common mental disorders. Secondary outcomes included anxiety, depression, alcohol misuse, and post-traumatic stress symptoms. Logistic regression examined associations between baseline personal and employment characteristics and class membership. Results: The analytical sample included 22,764 participants. For each outcome, growth mixture models identified two latent classes. Approximately 31% of HCWs experienced persistently high symptoms of probable common mental disorders, while 69% experienced persistently low symptoms. Similar patterns were observed for secondary outcomes, with small subgroups demonstrating worsening symptoms followed by improvement. Logistic regression analyses showed that being female, younger, single, working as a nurse, or having a pre-existing mental health diagnosis increased the odds of belonging to a high symptom class. Perceived support from colleagues and managers was protective. Conclusions: While many HCWs reported consistently low mental health symptom levels, almost a third belonged to a latent class characterized by persistently high symptoms across all time points. These findings underscore the need for mental health support for vulnerable HCW groups, embedded within routine NHS practice rather than limited to crisis periods.

Background: Ambulatory assessment and mood monitoring are different methods that can use novel technology to deliver a more efficient, flexible, and usable method of clinical outcome assessment compared with established measures of behavior and mood. Concerns have been raised around attrition in and adherence to these new protocols, particularly over the medium to long term by people with mood disorders. Objective: This systematic review and meta-analysis assessed attrition from and adherence to active and passive ambulatory assessment and mood monitoring protocols by people with bipolar disorder and depression over the medium and long term. Methods: Randomized controlled trials and nonrandomized studies were identified and rated for risk of bias. Adherence and attrition data were pooled to calculate effect sizes. We analyzed specific factors that we hypothesized a priori could affect the prevalences of attrition and adherence by means of subgroup meta-analysis or metaregression modeling. Results: We evaluated 77 mood tracking or ambulatory assessment studies including 17,123 participants. Pooled adherence was 0.64% (95% CI 0.59%-0.70%; P <.001), and pooled attrition was 0.28% (95% CI 0.22%-0.34%; P <.001). Three factors had a statistically significant subgroup difference for adherence: The presence of financial incentives increased adherence, and the presence of mood monitoring reminders and a higher study risk of bias decreased adherence. Four factors had a statistically significant subgroup difference for attrition: Digital mood monitoring decreased attrition versus analogue studies, but mood monitoring reminders, mood monitoring versus other protocols, and a high risk of study bias increased attrition. These analyses, however, were vulnerable to confounding by study design and protocol design. Attrition rates were not reported by 17 studies (17/77, 22%), and 20 studies (20/77, 26%) did not report adherence rates. Most studies had a low-to-moderate risk of bias, but heterogeneity was very high. Only 16 studies reported adherence systematically. Conclusions: Reporting of attrition and adherence to ambulatory assessments was not systematic nor universal, and until it is, analyses are unlikely to demonstrate clear conclusions. We found very high heterogeneity and evidence of publication bias, and this limited the certainty of our conclusions. Financial incentives may increase adherence, and attrition may be lower in digital than analogue studies of mood monitoring. There was no statistically significant difference in adherence and attrition between studies of passive and active ambulatory assessments. Reminders of mood monitoring increased attrition and decreased adherence, but the results may be confounded by longer length of follow-up versus other studies.

Background: Mood monitoring is widely used by people with depression and bipolar disorder (BD) to prevent relapse and improve insight into their condition, but it is unclear if these interventions have an impact on symptoms and for whom. As the capacity for passive mood monitoring increases, it is vital to improve our understanding of frequent mood assessment. Objective: This systematic review and meta-analysis assessed the effect of mood monitoring interventions in people with depression and BD to decrease relapse risk and symptoms of depression and mania. Methods: We conducted a systematic review and meta-analysis (PROSPERO, International Prospective Register of Systematic Reviews: CRD42023396473) and reported results according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. Randomized controlled trials with clinically important follow-up periods were identified via multiple database searches and rated for risk of bias using the Cochrane Risk of Bias tool. The primary outcomes were symptoms of depression and mania. Available data were pooled to calculate standardized mean differences (SMDs) for the primary outcomes: severity of depression, bipolar depression, and mania/hypomania. Results: We included 8 trials of 1230 participants and 6 different mood monitoring protocols. In BD, meta-analysis found a small but not statistically significant effect of mood monitoring interventions on decreasing mania symptoms (6 comparisons, n=873; SMD 0.16, 95% CI−0.34 to 0.01; P =.06) and no effect on bipolar depression (6 comparisons, n=873; SMD −0.08, 95% CI −0.31 to 0.15; P =.02). In depression, we found a small effect in decreasing symptoms of depression of borderline statistical significance at 12 months (2 comparisons, n=262; SMD −0.25, 95% CI −0.49 to 0.00; P =.05) but not at 6 months (2 comparisons, n=268; SMD −0.21, 95% CI −0.54 to 0.12; P =.21). There was an absence of evidence on the effect of mood monitoring on decreased relapse rates or readmission rates. Studies had a low risk of bias. There was no evidence on mood monitoring through ecological momentary assessment. Conclusions: Overall mood monitoring interventions do not increase or decrease mood symptoms in people with BD, nor is there robust evidence of such effects in people with unipolar depression. Further research is merited on different forms of mood monitoring and to determine under what circumstances mood monitoring might have beneficial or adverse effects. These results initially suggest that ambulatory assessment does not induce large placebo effects or significantly negatively or positively affect mood, and thus that mood monitoring may be an appropriate outcome measure for research or for clinical practice.

Background: The PReDicT study showed that predictive algorithm-guided antidepressant treatment reduces anxiety and improves functioning in patients with depression. Aims: To estimate the costs, outcomes and cost-effectiveness of the PReDicT test compared with treatment as usual (TAU) for primary depression care in five European countries. Method: Within-trial economic analysis was conducted over 24 weeks from the health/social care and societal perspectives alongside the PReDicT trial (NCT02790970) in France, Germany, The Netherlands, Spain, and the UK, according to Consolidated Health Economic Evaluation Reporting Standards guidelines. We calculated quality-adjusted life-years (QALYs) based on the EQ-5D-5L, capability-weighted life-years based on the Oxford Capabilities Questionnaire – Mental Health (OxCAP-MH) (Germany and UK only), and costs for 2018 (€). Multiple imputation for missing data, multivariable regression for cost and outcome differences, and bootstrapping and sensitivity analyses for uncertainty were conducted. Results: There were significant outcome improvements (EQ-5D-5L PRedicT: +0.139; TAU: +0.140) and societal cost reductions (PRedicT: −€2589; TAU: −€2602) in both groups ( N = 913) between the before and during trial periods. In the UK and Germany ( n = 619), the PReDicT group showed significant additional capability well-being gains (OxCAP-MH: +2.127, p = 0.021). Cost-effectiveness probabilities ranged from 46 to 59% at trial level, but exceeded 80% in the UK. Results remained stable across different sensitivity analyses, with societal cost-effectiveness improved for those (self-)employed. Conclusions: We observed potentially meaningful health and economic benefits of closely monitored antidepressant treatment, as implemented in both treatment and control arms of the PReDicT trial. The PReDicT test itself had some added benefits in improved capabilities and productivity, however, with great uncertainty and country-level variations in cost-effectiveness.