Feasibility and Preliminary Outcomes of Web-Based Cognitive Remediation Therapy in Psychiatric Inpatients With Psychotic Disorders: A Pilot Pre–Post Study Using the MATRICS Consensus Cognitive Battery

Feasibility and Preliminary Outcomes of Web-Based Cognitive Remediation Therapy in Psychiatric Inpatients With Psychotic Disorders: A Pilot Pre–Post Study Using the MATRICS Consensus Cognitive Battery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Feasibility and Preliminary Outcomes of Web-Based Cognitive Remediation Therapy in Psychiatric Inpatients With Psychotic Disorders: A Pilot Pre–Post Study Using the MATRICS Consensus Cognitive Battery Brent Nixon, Anne Pleydon, Nicholas Deptuch, Peluola Fiyin, Patrick Emeka Okonji, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8564907/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Cognitive impairments are a core feature of psychotic disorders and are strongly associated with long-term functional disability. Cognitive Remediation Therapy (CRT) is an evidence-based intervention for improving cognition in psychosis; however, its feasibility and preliminary cognitive effects in acute inpatient settings—particularly using web-based platforms—remain underexplored. This pilot study evaluated the feasibility of delivering a web-based CRT program in an inpatient psychiatric setting and examined preliminary cognitive outcomes. Methods : This single-arm, pre–post pilot study was conducted in a secure psychiatric inpatient facility. Thirteen inpatients with psychotic disorders participated in a 15-week web-based CRT program delivered twice weekly (30 sessions total). Each session comprised approximately 50 minutes of adaptive computerized CRT exercises (Happy Neuron Pro) followed by a 40-minute therapist-led bridging discussion focused on metacognitive reflection and application of cognitive strategies to daily activities. Cognitive performance was assessed before and after the intervention using the MATRICS Consensus Cognitive Battery (MCCB). Feasibility outcomes included session attendance, study retention, and completion of pre–post cognitive assessments. Results : All participants completed pre- and post-intervention cognitive assessments, with no study withdrawals or adverse events reported. Participants attended a mean of 27.77 (SD = 5.28) of 30 scheduled sessions, corresponding to a mean attendance rate of 93.0%. Pre–post improvements were observed in processing speed, verbal learning, and overall composite cognition, with large within-sample effect sizes. Sensitivity analyses excluding outliers confirmed robustness of these findings. Exploratory regression analyses suggested potential associations between sex and history of self-harm with cognitive change; however, these findings should be interpreted cautiously given the small sample size. Conclusions : The findings support the feasibility of delivering web-based CRT with structured bridging discussions in an inpatient psychiatric setting and suggest a preliminary signal of cognitive benefit. Given the pilot, single-arm design, results should be considered hypothesis-generating. Further research using controlled designs and larger samples is warranted. Cognitive remediation therapy web-based intervention neurocognition psychotic disorders psychiatric inpatients. Background Cognitive impairments are a fundamental and persistent characteristic of schizophrenia and other psychotic diseases, significantly affecting quality of life, social integration, and functional recovery. Cognitive deficits have long been recognized as a core feature of schizophrenia and related psychotic disorders and are now understood to be a major determinant of long-term functional disability [1]. When comparing people with schizophrenia to healthy controls, meta-analytic research demonstrates that neurocognitive impairments have significant effect sizes and that these deficiencies continue even when positive symptoms subside [2, 3]. Importantly, it has been demonstrated that deficits in working memory and processing speed mediate functional outcomes, including the capacity to live independently, maintain employment, and interact with others [4, 5, 6]. This emphasizes the significance of directly addressing cognition in treatment paradigms. In this context, Cognitive Remediation Therapy (CRT), one of the most well-established evidence-based treatment options, was developed to target neurocognitive impairments in schizophrenia. CRT is an umbrella term used to denote a family of interventions delivered using computerized drills, pencil-and-paper exercises, and therapist-led cognitive strategy coaching targeted at specific cognitive domains. According to meta-analyses, CRT produces modest to moderate gains in real-world functioning (Cohen’s d = 0.36) [7], as well as small to moderate improvements in neurocognitive performance (mean Cohen’s d = 0.45) [3]. These effects hold up well under different control conditions and are sustained at follow-up evaluations. However, effect sizes differ significantly between trials, suggesting that treatment response are significantly influenced by program components, including length, intensity, incorporation of metacognitive bridging sessions, and integration with psychosocial rehabilitation [1, 8]. Greater transfer of benefits to everyday functioning has been repeatedly linked to bridging sessions, where participants discuss real-life applications and directly reflect on the tactics employed during cognitive exercises [9, 10]. To promote metacognitive awareness and skill generalization, the NEAR (Neuropsychological Educational Approach to Remediation) approach, for example, incorporates therapist-led conversations that match cognitive exercises to real-world problems like meal planning or money management [11, 12]. Programs without this element frequently exhibit comparable improvements on cognitive tests but less pronounced functional benefits [11, 13]. With the introduction of web-based cognitive remediation platforms, cognitive remediation is now more widely available and may be administered in both inpatient and outpatient settings through internet-enabled devices. Platforms like CogRem and Happy Neuron Pro provide personalized development through modules that focus on executive function, working memory, attention, and processing speed. They also adjust task difficulty in real time. Tests of web-based CRT in combination with supported employment programs showed that computerized delivery may bring about improvements in working memory and processing speed comparable to traditional face-to-face CRT [14]. It could also increase adherence since it was more convenient [15, 16]. Although, the evidence base for cognitive remediation therapy (CRT) in acute inpatient and forensic settings remains comparatively limited, emerging data suggest modest benefits. A meta-analysis of 20 randomized controlled trials of inpatient CRT demonstrated small-to-moderate cognitive improvements [17], although only one included a forensic inpatient population [11]. Patients, however, frequently deal with more severe symptoms, varying hospital stays, and diverse treatment plans in acute settings, all of which might complicate intervention delivery and reduce cognitive benefits. Furthermore, there hasn't been much empirical research done on CRT's applicability to forensically involved and culturally varied populations. Disparities in access to mental health services are common among Indigenous peoples with psychotic disorders, and they may encounter particular societal obstacles while using computerized therapies [18, 19]. Due to security concerns and treatment adherence issues, forensic patients who have been found not criminally responsible are another underserved group often excluded from cognitive remediation trials. Emerging evidence, however, suggests that patients can experience significant cognitive gains when CRT is customized to meet the unique requirements and circumstances of these subgroups, for example, by using culturally appropriate content or safe on-site delivery [20]. Despite considerable progress, several gaps persist in the CRT literature. First, most randomized controlled trials have enrolled relatively young, outpatient cohorts with stable symptoms, leaving questions about efficacy among older, acutely hospitalized, or medically complex patients unanswered. Second, there is disagreement over the best ways to dose and deliver CRT due to its heterogeneity, which includes variations in software platforms, session frequency (from twice to five times per week), and total duration (10 to 60 hours). Third, long-term follow-up data are scarce, limiting insights into the durability of cognitive gains and their downstream effects on employment, social functioning, and quality of life beyond six months post-treatment. To address these limitations, the present study was designed as a pilot feasibility and proof-of-concept evaluation, rather than a controlled efficacy trial. The study leverages the Happy Neuron Pro platform to deliver CRT program to psychiatric inpatients with schizophrenia spectrum or other severe persistent mental illnesses. By embedding structured bridging sessions and employing the MATRICS Consensus Cognitive Battery (MCCB) for comprehensive domain assessment, this investigation seeks to examine whether web-based CRT produces preliminary cognitive gains and is feasible in an inpatient setting, while also elucidating its feasibility among Indigenous and Not Criminally Responsible populations. By focusing on previously understudied population, the current study seeks to improve the science and application of cognitive rehabilitation in psychiatry. The study was conducted as a pilot feasibility and proof-of-concept evaluation and was not powered to yield definitive efficacy estimates. Methods Study Design and Setting This study employed a single-arm, pre–post pilot design to evaluate the feasibility and preliminary cognitive outcomes of a web-based Cognitive Remediation Therapy (CRT) program delivered in a psychiatric inpatient setting. The study was conducted within a secure inpatient mental health facility providing care to individuals with severe mental illness, including those with forensic legal status. The study protocol was reviewed and approved by the Research Ethics Board of the former Qu’Appelle Health Region, Saskatchewan Health Authority (RQHR; REB-20-29), and all participants provided written informed consent prior to participation. Participants Participants were recruited from inpatient units through referral by the clinical care team. Inclusion criteria were: (1) inpatient psychiatric admission; (2) clinical stability, defined as no psychotropic medication changes and no acute behavioral incidents requiring clinical intervention in the two weeks preceding baseline assessment; (3) ability to complete baseline cognitive testing; and (4) capacity to provide informed consent. Exclusion criteria included diagnosed neurodegenerative disorder, delirium, or other conditions that would preclude valid cognitive assessment. Primary diagnoses were categorized as psychotic or non-psychotic based on documented DSM diagnoses at enrollment. Schizophrenia and schizoaffective disorder were classified as psychotic disorders. Mood and substance use disorders were classified as non-psychotic unless psychotic features were explicitly documented. This dichotomous classification was selected to maximize interpretability and statistical stability given the pilot sample size. The participants in this study who had forensic history were those on hospital detention under the authority of the Saskatchewan Review Board as either Unfit to Stand Trial (UST) or Not Criminally Responsible (NCR) or had previous designations as UST or NCR. Cognitive Remediation Therapy Intervention The intervention comprised two sessions per week over the 15 weeks (total = 30 sessions). CRT sessions were conducted in a supervised hospital computer laboratory and consisted of structured computerized exercises targeting core cognitive processes, including processing speed, attention, working memory, and learning. Cohort sizes were smaller than initially planned due to institutional infection-control requirements during the COVID-19 pandemic, which necessitated cohorting participants by inpatient unit to mitigate exposure risk. Cohort 1 included two participants who completed the study; Cohort 2 included two participants; Cohort 3 comprised two groups of three participants (total n = 6); Cohort 4 included two participants; and Cohort 5 included one participant. Each session included approximately 50 minutes of computerized CRT followed by a 40-minute therapist-led bridging discussion, which focused on strategy development, reflection, and application of trained cognitive skills to real-world functional contexts. Web-based CRT exercises were delivered using the Happy Neuron platform, which adapts task difficulty based on participant performance to maintain an optimal level of challenge. The computerized exercises targeted core cognitive processes, including processing speed, working memory, and verbal fluency. Following the computerized component, participants met with a trained facilitator for the bridging discussion, which occurred after each CRT session (twice weekly). During these discussions, participants reflected on cognitive strategies used, challenges encountered, and applications to daily activities and ward routines, with the aim of promoting metacognitive awareness and generalization of skills. Adaptive functioning was initially planned for assessment using the ABAS-3; however, these data were not analyzed due to incomplete data collection. Measures Cognitive Outcomes Cognitive performance was assessed at baseline and post-intervention using the MATRICS Consensus Cognitive Battery (MCCB ) , the FDA-endorsed gold standard for assessing cognition-enhancing treatments in schizophrenia [21, 22]. Pre-testing occurred within two weeks prior to CRT initiation and post-testing within two weeks of program completion. The MCCB evaluates seven domains: Attention/vigilance, Working Memory, Verbal Learning, Visual Learning, Reasoning and Problem Solving, Social Cognition, and Processing Speed, yielding both domain-specific scores and an overall composite [21, 22]. Subtests include Trail Making Test Part A, Symbol Coding, Category Fluency (Animal Naming), Continuous Performance Test–Identical Pairs, Wechsler Memory Scale–III Spatial Span, Letter–Number Span, Hopkins Verbal Learning Test–Revised, Brief Visuospatial Memory Test–Revised, Neuropsychological Assessment Battery–Mazes, and the Mayer–Salovey–Caruso Emotional Intelligence Test [23, 24] Demographic, Clinical, and Feasibility Variables Demographic and clinical variables were extracted from medical records using standardized operational definitions. Participant age was calculated using date of birth and CRT program completion date. Substance use history was defined as a lifetime DSM diagnosis of a substance use disorder or documented substance use in clinical records. Sustained employment was defined as engagement in competitive employment for at least six months. Financial assistance referred to receipt of disability benefits or other formal income support. Two self-harm variables were available in the dataset: documented lifetime history of self-harm and self-harm within the past 12 months. Due to insufficient variability in the recent self-harm variable, analyses were conducted using documented lifetime history of self-harm. History variables (including aggression, self-harm, suicide attempts, and inappropriate sexual behavior) reflected lifetime history unless otherwise specified. Feasibility and adherence were assessed using attendance-based indicators, including the number of CRT sessions attended (out of 30) and the percentage of scheduled sessions attended. Statistical Analysis Descriptive statistics were used to summarize demographic, clinical, and feasibility characteristics. Paired-samples t-tests were conducted to examine pre–post changes in MCCB domain scores and composite cognition using one-tailed tests with α = .05, reflecting a priori directional hypotheses that cognitive performance would improve following CRT. Effect sizes (Cohen’s d ) were calculated to estimate the magnitude of change. Exploratory linear regression analyses were conducted to examine potential predictors of cognitive change, including sex, ethnicity, and documented lifetime history of self-harm. These analyses were considered hypothesis-generating and were not intended to identify definitive predictors of treatment response due to the pilot sample size. Forensic legal status was not included in regression models because of limited statistical power. Table 1 Sample demographics Characteristic Value Age, years Mean (SD) 34.08 (7.87) Sex Male, n (%) 10 (76.9%) Female, n (%) 3 (23.1%) Indigenous identity White n (%) 7 (53.8%) Indigenous/Metis, n (%) 5 (39.5%) Asian, n (%) 1 (7.7%) Primary Diagnosis Psychotic disorder, n (%) 11 (84.6%) Non-psychotic disorder, n (%) 2 (15.4%) Education 9th grade 3 (23.1%) 10th grade 2 (15.4%) 11th grade 1 (7.7%) 12th grade 6 (46.2%) University 1 (7.7%) Forensic history NCR Current, n (%) 7 (53.8%) Unfit-to-Stand Trial current, n (%) 1 (7.7%) Past forensic history, n (%) 1 (7.7%) Clinical history History of aggression, n (%) 13 (100.0%) History of self-harm, n (%) 5 (38.5%) History of suicide attempt, n (%) 4 (38.5%) Inappropriate sexual behavior (ISB), n (%) 3 (23.1%) History of family suicide attempt, n (%) 2 (15.4%) Substance use history Alcohol, n (%) 11 (84.6%) Cannabis, n (%) 2 (15.4%) Stimulants, n (%) 6 (46.2%) Opioids, n (%) 3 (23.1%) Others, n (%) 5 (38.5%) Socioeconomic characteristics Sustained employment†, n (%) 5 (38.5%) Currently receiving financial assistance, n (%) 4 (30.8%) Previously receiving financial assistance, n (%) 4 (30.8%) CRT attendance Sessions attended (out of 30), Mean (SD) 27.77 (5.28) Attendance rate %, Mean (SD) 93.0 (17.6) Note. Age was calculated using date of birth and CRT program completion date. Primary diagnoses were classified as psychotic or non-psychotic based on documented DSM diagnoses at enrollment. Substance use history reflects a lifetime DSM diagnosis or documented substance use in clinical records. Sustained employment was defined as engagement in competitive employment for ≥ 6 months. Financial assistance refers to receipt of disability benefits or other formal income support. ISB = inappropriate sexual behavior. Unless otherwise specified, history variables reflect lifetime history. History of suicide includes documented suicide attempts. Attendance rate reflects the percentage of the 30 scheduled CRT sessions attended. Table 2 Paired t-tests of cognitive domain T scores Variable Δ (SE) 95% CI t (df) Cohens d z p Processing Speed 6.23 (2.15) 1.54, 10.92 2.89 (12) 0.80 0.014 Attention 3.11 (2.76) -3.25, 9.47 1.13 (8) 0.38 0.292 Working Memory 3.69 (1.70) -0.02, 7.40 2.17 (12) 0.60 0.051 Verbal Learning 7.15 (1.71) 3.42, 10.89 4.12 (12) 1.16 0.001 Visual Learning 3.00 (2.89) -3.29, 9.29 1.04 (12) 0.29 0.320 Reasoning/Problem Solving 0.85 (2.51) -4.63, 6.31 0.34 (12) 0.09 0.742 Social Cognition 4.30 (3.82) -4.33, 12.93 1.13 (9) 0.36 0.289 Overall 4.20 (1.10) 1.70, 6.70 3.81 (9) 1.20 0.004 Δ (SE) = average change score and standard Error, 95% CI = 95% Confidence Interval, t (df) = test statistic and degrees of freedom, d z = effect size, bold, p < .05 Table 3 Paired t-tests of cognitive domain T scores with outliers removed Variable Δ (SE) 95% CI t (df) Cohens d z p Processing Speed 7.75 (1.66) 4.09, 11.41 4.67 (11) 1.35 < 0.001 Verbal Learning 8.41 (1.25) 5.64, 11.18 6.69 (11) 1.93 < 0.001 Reasoning/Problem Solving 2.75 (1.78) -1.17, 6.67 1.54 (11) 0.45 0.151 Overall 5.00 (0.85) 3.04, 6.96 5.88 (8) 1.96 < 0.001 Δ (SE) = average change score and standard Error, 95% CI = 95% Confidence Interval, t (df) = test statistic and degrees of freedom, d z = effect size, bold, p < .05 Table 4 Simple regression models of predictor variables on change scores B (SE B) 95% CI (B) Beta R 2 p Age 0.05 (0.15) -0.38, 0.29 -0.10 0.10 0.77 Sex (ref. female) 6.50 (1.96) 2.07, 10.93 0.74 0.55 0.01 Hx agg. 12 months (ref. absent) 0.71 (2.52) -4.99, 6.41 0.09 0.01 0.79 Hx.self harm (ref. absent) -4.82 (1.70) -8.68,-0.97 -0.69 0.47 0.02 Hx. Suicide (ref. absent) -2.96 (2.33) -8.22, 2.31 -0.39 0.15 0.24 Attendance rate 0.25 (6.24) -13.86, 14.37 0.01 0.00 0.97 Indigenous ethnicity (ref. not indigenous) -0.77 (2.25) -5.85, 4.32 -0.11 0.01 0.74 B = unstandardized coefficient, SE B = Standard Error of B, 95% CI B = 95% Confidence Interval, Beta = standardized coefficient, R 2 = Coefficient of Determination, bold p < .05 , ref. is the reference category (coded 0). Results Participants attended a mean of 27.77 sessions (SD = 5.28) out of 30 scheduled sessions, corresponding to a mean attendance rate of 93.0% (Please see Table 1 ). No study withdrawals or adverse events related to CRT participation were recorded. Paired-samples t-tests With our pilot sample, significant gains were observed in processing speed, working memory, verbal learning, and overall domains. Specifically, processing speed scores increased by an average of 6.23 points, working memory scores showed a mean increase of 3.69 and verbal learning improved by 7.15 points (Table 2 ). The composite Overall score rose by 4.20. Changes in attention, visual learning, reasoning, and social domains did not reach significance (all p ≥ .292). Because a small number of outliers were identified in difference scores, sensitivity analyses excluding these cases were performed (Table 3 ). Results remained robust for processing speed, verbal, and overall domains: MΔ = 5.00 (SE = 0.85), 95% CI [3.04, 6.96], t(8) = 5.88, p < .001, dz = 1.96. Reasoning/problem solving did not reach statistical significance after outlier removal (p = .07), though effect sizes increased. Other domains remained non-significant. The increase in mean change scores and effect sizes after outlier removal indicates that these participants had change scores far below the mean of the distribution, and represent those whose scores changed the least before and after training. Regression analyses Two predictors accounted for a substantial proportion of variance: sex (reference = female) and history of self-harm (reference = absent). Male participants showed greater improvement than females, and participants without a history of self-harm demonstrated greater gains than those with such history (Table 4 ). Age, history of aggression, history of suicide attempts, and attendance rate were not significant predictors (all p ≥ .24). Given small subgroup sizes (e.g., n = 3 females), these findings are preliminary and warrant replication in larger samples. Discussion The present study demonstrates that a 15-week, web-based Cognitive Remediation Therapy (CRT) program can yield meaningful pre–post improvements in processing speed, verbal learning, working-memory, and overall cognitive performance among psychiatric inpatients with schizophrenia spectrum and related disorders. Effect sizes observed for Processing Speed (d z = 1.35) and verbal learning (d z = 1.93) significantly exceed those reported in meta-analyses of traditional CRT [1, 3], suggesting that the integration of adaptive drill-and-practice exercises with structured metacognitive “bridging” discussions may potentiate cognitive gains in acute care settings. Unlike outpatient trials, where competing life demands and lower supervision often temper engagement [14], the inpatient environment affords a controlled context in which participants can immerse themselves in daily, web-based sessions without external distractions. The immediacy of feedback inherent in the Happy Neuron Pro platform likely bolstered motivation and mastery experiences, aligning with self-determination theory’s emphasis on competence and autonomy as drivers of sustained engagement [25, 26]. The limited change observed in higher-order domains such as reasoning/problem solving, visual learning, and social cognition is consistent with prior evidence indicating that drill-and-practice CRT preferentially improves basic processing capacities (e.g., processing speed and verbal learning) [11, 13], while more complex cognitive domains may require greater training intensity, extended duration, or enhanced strategy coaching within the CRT framework. It is also possible that the MCCB, while the gold-standard battery, lacks sensitivity to detect subtle CRT-related changes in higher-order cognition. Future studies may therefore benefit from longer intervention periods, refined bridging content, and complementary outcome measures to better capture domain-specific change. The twice-weekly therapist-led discussions played an indispensable role in translating gains from the computerized approach into daily routines. By dedicating 40 minutes twice weekly to examine task strategies and personal challenges, participants could contextualize cognitive exercises within ward activities and interpersonal interactions, thereby fostering generalization. This approach is consistent with the NEAR model’s assertion that metacognitive reflection amplifies functional relevance of neurocognitive training [26]. Indeed, studies in forensic outpatient settings have found that such bridging sessions not only boost cognitive performance but also improve adaptive behavior and symptom management [13, 20]. Future research should expand on these results by experimentally varying the timing and content intensity of bridging sessions (e.g., brief versus in-depth; weekly versus biweekly) to identify which formats best promote transfer to functional outcomes. Exploratory regression analyses suggested potential associations between sex, self-harm history, and cognitive change; however, these findings are preliminary and should be interpreted cautiously given small subgroup sizes. More robust investigation in larger, gender-balanced samples is required to clarify whether sex moderates response to web-based CRT. The negative association between self-harm history and cognitive improvement is consistent with literature linking self-injurious behaviors to executive dysfunction, affective dysregulation, and diminished treatment adherence [27]. Participants with a history of self-harm may experience heightened emotional distress that interferes with cognitive control and working-memory performance [28, 29], and because self-harm is strongly linked to emotion-regulation and executive-function deficits [30, 31], adjunctive distress-tolerance or mood-stabilizing interventions (e.g., DBT or pharmacologic mood stabilizers) may be necessary to maximize engagement with and benefit from cognitive remediation [32, 33]. The feasibility of implementing web-based CRT within an acute inpatient setting challenges widely held belief that structured cognitive therapies are not possible due to severe symptomatology and fluctuating lengths of stay [14]. High adherence rates in this study demonstrate that, when supported by facilitators and delivered via hospital-based desktop computers with secure Ethernet connections, even acutely ill patients can successfully engage in a regimented cognitive training protocol. This finding underscores the scalability of digital CRT and its potential to fill a critical treatment gap in settings where traditional face-to-face CRT is logistically impractical. Comparison with outpatient data further highlights the advantages of inpatient deployment. Effect sizes in this study surpass those typically observed in community settings where average d values range between 0.30 and 0.50 for Processing Speed and Working Memory [3, 14]. Two factors likely underpin these differences: the structured inpatient schedule that minimizes competing demands, and the novelty and immediacy of supervised, computer-based delivery, which may enhance motivation. However, it is unclear if these benefits last after discharge; long-term monitoring is necessary to ascertain how long cognitive advantages last and how well they translate into social and professional performance. Limitations of Study The absence of functional outcome data due to COVID-related restrictions on adaptive behavior assessment constitutes a notable limitation. ABAS-3 administration was not completed because of pandemic restrictions, staff turnover, small cohort sizes, and delayed post-testing, and re-contacting discharged participants was not possible without REB-approved consent. Consequently, adaptive functioning could not be evaluated. Future studies should include pre–post ABAS-3 or obtain REB-approved consent for post-discharge follow-up. Without direct measures linking cognitive gains to real-world activities, conclusions regarding the intervention’s impact on daily living capacities remain inferential. Moreover, the single-arm, pre–post design precludes causal attribution; future randomized controlled trials comparing web-based CRT with active control interventions (e.g., computer games or non-adaptive cognitive tasks) are necessary to establish specific treatment effects. The small sample size limits statistical power and may inflate effect-size estimates [34]. Also, precise CRT program commencement dates were not consistently documented in clinical records, precluding accurate calculation of program duration or time to completion. Consequently, feasibility was assessed using attendance-based indicators rather than treatment duration. In addition, formal screening logs were not maintained; therefore, the number of patients approached but not enrolled could not be reliably quantified. Finally, the inpatient setting and COVID-19–related operational constraints resulted in smaller-than-planned cohort sizes, which may have influenced group dynamics and generalizability. Despite these limitations, the pronounced cognitive improvements observed in this pilot study, particularly in processing speed and verbal learning, underscore the promise of web-based CRT for inpatient populations. By harnessing adaptive software and structured metacognitive reflection, psychiatric units may deliver high-intensity, scalable interventions that address the cognitive deficits most strongly linked to functional disability in schizophrenia. Future protocols should examine how variations in CRT dose, task composition, and the structure and timing of bridging sessions influence gains in higher-order cognitive domains and functional outcomes. Implications for Policy and Practice The present findings support the feasibility and efficacy of implementing web-based CRT within inpatient psychiatric settings. Health services should consider integrating scalable, computerized CRT platforms into standard care, leveraging the controlled environment of inpatient wards to ensure high adherence and consistent delivery. Given the robust gains in Processing Speed and Verbal Learning, inpatient CRT programs could be positioned as an early intervention strategy to mitigate cognitive decline and foster readiness for community reintegration. Policy makers must allocate resources for staff training in both computerized CRT delivery and metacognitive bridging techniques. Investment in digital infrastructure such as secure web-enabled devices and reliable internet access is critical to facilitate uninterrupted program delivery. Moreover, mental health authorities should develop clinical guidelines endorsing CRT as a core component of comprehensive rehabilitation for schizophrenia and other severe mental illnesses, comparable to existing, evidence-based interventions such as supported employment (e.g., Individual Placement and Support) and assertive community treatment (multidisciplinary, intensive, community-based care). Attention to cultural and forensic contexts is also essential. Indigenous patients often experience barriers to engagement with Western-centric interventions; therefore, culturally responsive adaptations; such as incorporating Indigenous languages, metaphors, and community elders into bridging discussions, may enhance relevance and uptake [35, 36]. Likewise, forensic patients may benefit from secure, on-ward CRT delivery that accommodates custodial restrictions while fostering cognitive recovery. With this approach, collaborative efforts between correctional services and mental health teams may establish dedicated CRT programs within forensic units. Finally, further research should examine long-term outcomes, including maintenance of cognitive gains and functional recovery metrics such as employment rates, independent living, and recidivism in forensic populations. Economic evaluations could elucidate cost-effectiveness, informing policy decisions on broader implementation. By embedding CRT within a continuum of psychiatric rehabilitation services, health systems can address the cognitive disabilities that underlie disability in schizophrenia, ultimately improving patient autonomy, community participation, and quality of life. Conclusion Web-based CRT shows preliminary evidence of improvement of neurocognitive functioning among psychiatric inpatients. While the strongest gains emerged in Processing Speed and Verbal Learning, future CRT trials should explore whether extending training duration, refining bridging strategies, or incorporating complementary outcome measures can enhance higher-order cognitive change. Web-based CRT appears feasible in inpatient psychiatric settings and shows preliminary signals of cognitive benefit, supporting further investigation in larger randomized controlled trials. Declarations Ethics Approval: Ethics approval was received from the Research Ethics Board (REB) of the former Qu’Appelle Haelth Region (RQHR) indicating the study meets the membership criteria for, and adheres to the requirements of, the 2 nd edition of Canda’s Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans, the International Conference on Harmonisation Good Clinical Practice (E6) guidelines (ICH GCP), and Part C Division 5 of Canada’s Food and Drug Regulations under RQHR File # REB-20-29, approved on April 20, 2020. Saskatchewan Health Authority provided Operational Approval (OA-SHA-20-29) on April 27, 2020. Consent to Participate: Written informed consent was obtained from all participants prior to participation in the study. Participants were provided with a detailed explanation of the study procedures, potential risks and benefits, and their right to withdraw at any time without impact on their clinical care. Acknowledgements: The research team would like to thank James Winder and Brittney Landstrom for their dedication in facilitating the Cognitive Remediation programming, for without their efforts patients would not have received the benefits of this program. Funding: This study was funded internally by the Saskatchewan Health Authority. The funders had no role in the design of the study; the collection, analysis, and interpretation of data; the writing of the manuscript; or the decision to submit the paper for publication. Clinical Trial Number: Not Applicable References Vita A, Barlati S, Ceraso A, Nibbio G, Ariu C, Deste G, Wykes T. Effectiveness, core elements, and moderators of response of cognitive remediation for schizophrenia: a systematic review and meta-analysis of randomized clinical trials. 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American Journal of Psychiatry. 2007 Dec;164(12):1791-802. https://doi.org/10.1176/appi.ajp.2007.07060906 Lejeune JA, Northrop A, Kurtz MM. A meta-analysis of cognitive remediation for schizophrenia: efficacy and the role of participant and treatment factors. Schizophrenia Bulletin. 2021 Jul 1;47(4):997-1006. https://doi.org/10.1093/schbul/sbab022 Chong NI, Maniam Y, Chua YC, Tang C. The implementation and review of cognitive remediation training for first episode psychosis in Singapore. Frontiers in Psychiatry. 2021 Nov 30;12:784935. https://doi.org/10.3389/fpsyt.2021.784935 Fitapelli B, Lindenmayer JP. Advances in cognitive remediation training in schizophrenia: A review. Brain Sciences. 2022 Jan 18;12(2):129. https://www.mdpi.com/2076-3425/12/2/129 Ahmed AO. Cognitive remediation for schizophrenia. Focus. 2020 Oct;18(4):436-9. Available online: https://psychiatryonline.org/doi/full/10.1176/appi.focus.20200035 Trapp W, Heid A, Röder S, Wimmer F, Hajak G. Cognitive remediation in psychiatric disorders: State of the evidence, future perspectives, and some bold ideas. Brain sciences. 2022 May 24;12(6):683. https://doi.org/10.3390/brainsci12060683 Taylor R, Cella M, Wykes T. Cognitive Remediation Is an Evidence-Based Psychological Therapy: Isn’t It Time It Was Treated Like One?. Behavior Modification. 2025 Nov;49(5-6):502-26. https://doi.org/10.1177/01454455251343303 Harris AW, Kosic T, Xu J, Walker C, Gye W, Hodge AR. Web-based cognitive remediation improves supported employment outcomes in severe mental illness: randomized controlled trial. JMIR Mental Health. 2017 Sep 20;4(3):e6982. doi:10.2196/mental.6982 Boschetti A, Maida E, Dini M, Tacchini M, Gamberini G, Comi G, Leocani L. A review on the feasibility and efficacy of home-based cognitive remediation in people with multiple sclerosis. Journal of Clinical Medicine. 2024 Mar 26;13(7):1916. https://www.mdpi.com/2077-0383/13/7/1916 Killikelly C, He Z, Reeder C, Wykes T. Improving adherence to web-based and mobile technologies for people with psychosis: systematic review of new potential predictors of adherence. JMIR mHealth and uHealth. 2017 Jul 20;5(7):e7088. doi:10.2196/mhealth.7088 Cella M, Price T, Corboy H, Onwumere J, Shergill S, Preti A. Cognitive remediation for inpatients with psychosis: a systematic review and meta-analysis. Psychological Medicine. 2020 May;50(7):1062-76. Goetz CJ, Mushquash CJ, Maranzan KA. An integrative review of barriers and facilitators associated with mental health help seeking among indigenous populations. Psychiatric Services. 2023 Mar 1;74(3):272-81. https://doi.org/10.1176/appi.ps.202100503 Bourassa C. Addressing the Duality of Access to Healthcare for Indigenous Communities: Racism and Geographical Barriers to Safe Care. HealthcarePapers. 2018 Jan 1;17(3):6-10. https://europepmc.org/article/med/30052180 Dark FL, Amado I, Erlich MD, Ikezawa S. International experience of implementing cognitive remediation for people with psychotic disorders. Schizophrenia Bulletin. 2024 Sep;50(5):1017-27. https://doi.org/10.1093/schbul/sbae071 Harvey PD. Cognition in Schizophrenia: MATRICS Consensus Cognitive Battery (MCCB): Development, Characteristics, and Usage. The SAGE Handbook of Clinical Neuropsychology: Clinical Neuropsychological Assessment and Diagnosis. 2023:617. https://www.torrossa.com/en/resources/an/5543082#page=648 Nuechterlein KH, Nasrallah H, Velligan D. Measuring cognitive impairments associated with schizophrenia in clinical practice: Overview of current challenges and future opportunities. Schizophrenia Bulletin. 2025 Mar;51(2):401-21. Schizophrenia Bulletin , 51 (2), 401-421. https://doi.org/10.1093/schbul/sbae051 Cai Y, Yang T, Yu X, Han X, Chen G, Shi C. The alternate-form reliability study of six variants of the brief visual-spatial memory test-revised and the Hopkins Verbal Learning Test-revised. Frontiers in Public Health. 2023 Mar 22;11:1096397. https://doi.org/10.3389/fpubh.2023.1096397 Jędrasik-Styła M, Ciołkiewicz A, Styła R, Linke M, Parnowska D, Gruszka A, Denisiuk M, Jarema M, Green MF, Wichniak A. The Polish academic version of the MATRICS Consensus Cognitive Battery (MCCB): Evaluation of psychometric properties. Psychiatric Quarterly. 2015 Sep;86(3):435-47. DOI 10.1007/s11126-015-9343-9 Revell ER, Neill JC, Harte M, Khan Z, Drake RJ. A systematic review and meta-analysis of cognitive remediation in early schizophrenia. Schizophrenia research. 2015 Oct 1;168(1-2):213-22. https://doi.org/10.1017/S0033291715000549 Saperstein AM, Medalia A. The role of motivation in cognitive remediation for people with schizophrenia. Behavioral neuroscience of motivation. 2015 Mar 15:533-46. https://doi.org/10.1016/j.schres.2012.04.030 Diefenbach GJ, Lord KA, Stubbing J, Rudd MD, Levy HC, Worden B, Sain KS, Bimstein JG, Rice TB, Everhardt K, Gueorguieva R. Brief cognitive behavioral therapy for suicidal inpatients: a randomized clinical trial. JAMA psychiatry. 2024 Dec 1;81(12):1177-86.https://jamanetwork.com/journals/jamapsychiatry/fullarticle/2823589 Raio CM, Orederu TA, Palazzolo L, Shurick AA, Phelps EA. Cognitive emotion regulation fails the stress test. Proceedings of the National Academy of Sciences. 2013 Sep 10;110(37):15139-44. https://doi.org/10.1073/pnas.1305706110 Hou TY, Cai WP. What emotion dimensions can affect working memory performance in healthy adults? A review. World Journal of Clinical Cases. 2022 Jan 14;10(2):401.doi: 10.12998/wjcc.v10.i2.401 Wolff JC, Thompson E, Thomas SA, Nesi J, Bettis AH, Ransford B, Scopelliti K, Frazier EA, Liu RT. Emotion dysregulation and non-suicidal self-injury: A systematic review and meta-analysis. European psychiatry. 2019 Jun;59:25-36. http://dx.doi.org/10.1016/j.eurpsy.2019.03.004 Li Y, Xiao X, Zhou Y, Su X, Wang H. The mediating role of executive function in the relationship between self-stigma and self-injury or suicidal ideation among men who have sex with men living with HIV. Frontiers in public health. 2023 Jan 9;10:1066781. https://doi.org/10.3389/fpubh.2022.1066781 Kothgassner OD, Goreis A, Robinson K, Huscsava MM, Schmahl C, Plener PL. Efficacy of dialectical behavior therapy for adolescent self-harm and suicidal ideation: a systematic review and meta-analysis. Psychological medicine. 2021 May;51(7):1057-67. DOI:https://doi.org/10.1017/S0033291721001355 Nayak R, Rosh I, Kustanovich I, Stern S. Mood stabilizers in psychiatric disorders and mechanisms learnt from in vitro model systems. International journal of molecular sciences. 2021 Aug 27;22(17):9315. https://doi.org/10.3390/ijms22179315 Button KS, Ioannidis JP, Mokrysz C, Nosek BA, Flint J, Robinson ES, Munafò MR. Power failure: why small sample size undermines the reliability of neuroscience. Nature reviews neuroscience. 2013 May;14(5):365-76. Nature Reviews Neuroscience, 14 (5), 365–376. https://doi.org/10.1038/nrn3475 Whalen DH, Lewis ME, Gillson S, McBeath B, Alexander B, Nyhan K. Health effects of Indigenous language use and revitalization: A realist review. International Journal for Equity in Health. 2022 Nov 28;21(1):169. https://doi.org/10.1186/s12939-022-01782-6 Ralph AP, McGrath SY, Armstrong E, Herdman RM, Ginnivan L, Lowell A, Lee B, Gorham G, Taylor S, Hefler M, Kerrigan V. Improving outcomes for hospitalised First Nations peoples through greater cultural safety and better communication: the Communicate Study Partnership study protocol. Implementation Science. 2023 Jun 22;18(1):23. https://doi.org/10.1186/s13012-023-01276-1 Additional Declarations No competing interests reported. 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07:27:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":898380,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8564907/v1/f428ed80-dd8b-4a86-a4df-0ccd9b87ff09.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Feasibility and Preliminary Outcomes of Web-Based Cognitive Remediation Therapy in Psychiatric Inpatients With Psychotic Disorders: A Pilot Pre–Post Study Using the MATRICS Consensus Cognitive Battery","fulltext":[{"header":"Background","content":"\u003cp\u003eCognitive impairments are a fundamental and persistent characteristic of schizophrenia and other psychotic diseases, significantly affecting quality of life, social integration, and functional recovery. Cognitive deficits have long been recognized as a core feature of schizophrenia and related psychotic disorders and are now understood to be a major determinant of long-term functional disability [1]. When comparing people with schizophrenia to healthy controls, meta-analytic research demonstrates that neurocognitive impairments have significant effect sizes and that these deficiencies continue even when positive symptoms subside [2, 3]. Importantly, it has been demonstrated that deficits in working memory and processing speed mediate functional outcomes, including the capacity to live independently, maintain employment, and interact with others [4, 5, 6]. This emphasizes the significance of directly addressing cognition in treatment paradigms.\u003c/p\u003e \u003cp\u003eIn this context, Cognitive Remediation Therapy (CRT), one of the most well-established evidence-based treatment options, was developed to target neurocognitive impairments in schizophrenia. CRT is an umbrella term used to denote a family of interventions delivered using computerized drills, pencil-and-paper exercises, and therapist-led cognitive strategy coaching targeted at specific cognitive domains. According to meta-analyses, CRT produces modest to moderate gains in real-world functioning (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.36) [7], as well as small to moderate improvements in neurocognitive performance (mean Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.45) [3]. These effects hold up well under different control conditions and are sustained at follow-up evaluations. However, effect sizes differ significantly between trials, suggesting that treatment response are significantly influenced by program components, including length, intensity, incorporation of metacognitive bridging sessions, and integration with psychosocial rehabilitation [1, 8].\u003c/p\u003e \u003cp\u003eGreater transfer of benefits to everyday functioning has been repeatedly linked to bridging sessions, where participants discuss real-life applications and directly reflect on the tactics employed during cognitive exercises [9, 10]. To promote metacognitive awareness and skill generalization, the NEAR (Neuropsychological Educational Approach to Remediation) approach, for example, incorporates therapist-led conversations that match cognitive exercises to real-world problems like meal planning or money management [11, 12]. Programs without this element frequently exhibit comparable improvements on cognitive tests but less pronounced functional benefits [11, 13].\u003c/p\u003e \u003cp\u003eWith the introduction of web-based cognitive remediation platforms, cognitive remediation is now more widely available and may be administered in both inpatient and outpatient settings through internet-enabled devices. Platforms like CogRem and Happy Neuron Pro provide personalized development through modules that focus on executive function, working memory, attention, and processing speed. They also adjust task difficulty in real time. Tests of web-based CRT in combination with supported employment programs showed that computerized delivery may bring about improvements in working memory and processing speed comparable to traditional face-to-face CRT [14]. It could also increase adherence since it was more convenient [15, 16]. Although, the evidence base for cognitive remediation therapy (CRT) in acute inpatient and forensic settings remains comparatively limited, emerging data suggest modest benefits. A meta-analysis of 20 randomized controlled trials of inpatient CRT demonstrated small-to-moderate cognitive improvements [17], although only one included a forensic inpatient population [11]. Patients, however, frequently deal with more severe symptoms, varying hospital stays, and diverse treatment plans in acute settings, all of which might complicate intervention delivery and reduce cognitive benefits.\u003c/p\u003e \u003cp\u003eFurthermore, there hasn't been much empirical research done on CRT's applicability to forensically involved and culturally varied populations. Disparities in access to mental health services are common among Indigenous peoples with psychotic disorders, and they may encounter particular societal obstacles while using computerized therapies [18, 19]. Due to security concerns and treatment adherence issues, forensic patients who have been found not criminally responsible are another underserved group often excluded from cognitive remediation trials. Emerging evidence, however, suggests that patients can experience significant cognitive gains when CRT is customized to meet the unique requirements and circumstances of these subgroups, for example, by using culturally appropriate content or safe on-site delivery [20].\u003c/p\u003e \u003cp\u003eDespite considerable progress, several gaps persist in the CRT literature. First, most randomized controlled trials have enrolled relatively young, outpatient cohorts with stable symptoms, leaving questions about efficacy among older, acutely hospitalized, or medically complex patients unanswered. Second, there is disagreement over the best ways to dose and deliver CRT due to its heterogeneity, which includes variations in software platforms, session frequency (from twice to five times per week), and total duration (10 to 60 hours). Third, long-term follow-up data are scarce, limiting insights into the durability of cognitive gains and their downstream effects on employment, social functioning, and quality of life beyond six months post-treatment.\u003c/p\u003e \u003cp\u003eTo address these limitations, the present study was designed as a pilot feasibility and proof-of-concept evaluation, rather than a controlled efficacy trial. The study leverages the Happy Neuron Pro platform to deliver CRT program to psychiatric inpatients with schizophrenia spectrum or other severe persistent mental illnesses. By embedding structured bridging sessions and employing the MATRICS Consensus Cognitive Battery (MCCB) for comprehensive domain assessment, this investigation seeks to examine whether web-based CRT produces preliminary cognitive gains and is feasible in an inpatient setting, while also elucidating its feasibility among Indigenous and Not Criminally Responsible populations. By focusing on previously understudied population, the current study seeks to improve the science and application of cognitive rehabilitation in psychiatry. The study was conducted as a pilot feasibility and proof-of-concept evaluation and was not powered to yield definitive efficacy estimates.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis study employed a single-arm, pre\u0026ndash;post pilot design to evaluate the feasibility and preliminary cognitive outcomes of a web-based Cognitive Remediation Therapy (CRT) program delivered in a psychiatric inpatient setting. The study was conducted within a secure inpatient mental health facility providing care to individuals with severe mental illness, including those with forensic legal status. The study protocol was reviewed and approved by the Research Ethics Board of the former Qu\u0026rsquo;Appelle Health Region, Saskatchewan Health Authority (RQHR; REB-20-29), and all participants provided written informed consent prior to participation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited from inpatient units through referral by the clinical care team. Inclusion criteria were: (1) inpatient psychiatric admission; (2) clinical stability, defined as no psychotropic medication changes and no acute behavioral incidents requiring clinical intervention in the two weeks preceding baseline assessment; (3) ability to complete baseline cognitive testing; and (4) capacity to provide informed consent. Exclusion criteria included diagnosed neurodegenerative disorder, delirium, or other conditions that would preclude valid cognitive assessment.\u003c/p\u003e \u003cp\u003ePrimary diagnoses were categorized as psychotic or non-psychotic based on documented DSM diagnoses at enrollment. Schizophrenia and schizoaffective disorder were classified as psychotic disorders. Mood and substance use disorders were classified as non-psychotic unless psychotic features were explicitly documented. This dichotomous classification was selected to maximize interpretability and statistical stability given the pilot sample size. The participants in this study who had forensic history were those on hospital detention under the authority of the Saskatchewan Review Board as either Unfit to Stand Trial (UST) or Not Criminally Responsible (NCR) or had previous designations as UST or NCR.\u003c/p\u003e\n\u003ch3\u003eCognitive Remediation Therapy Intervention\u003c/h3\u003e\n\u003cp\u003eThe intervention comprised two sessions per week over the 15 weeks (total\u0026thinsp;=\u0026thinsp;30 sessions). CRT sessions were conducted in a supervised hospital computer laboratory and consisted of structured computerized exercises targeting core cognitive processes, including processing speed, attention, working memory, and learning. Cohort sizes were smaller than initially planned due to institutional infection-control requirements during the COVID-19 pandemic, which necessitated cohorting participants by inpatient unit to mitigate exposure risk. Cohort 1 included two participants who completed the study; Cohort 2 included two participants; Cohort 3 comprised two groups of three participants (total \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6); Cohort 4 included two participants; and Cohort 5 included one participant.\u003c/p\u003e \u003cp\u003e Each session included approximately 50 minutes of computerized CRT followed by a 40-minute therapist-led bridging discussion, which focused on strategy development, reflection, and application of trained cognitive skills to real-world functional contexts. Web-based CRT exercises were delivered using the Happy Neuron platform, which adapts task difficulty based on participant performance to maintain an optimal level of challenge. The computerized exercises targeted core cognitive processes, including processing speed, working memory, and verbal fluency. Following the computerized component, participants met with a trained facilitator for the bridging discussion, which occurred after each CRT session (twice weekly). During these discussions, participants reflected on cognitive strategies used, challenges encountered, and applications to daily activities and ward routines, with the aim of promoting metacognitive awareness and generalization of skills. Adaptive functioning was initially planned for assessment using the ABAS-3; however, these data were not analyzed due to incomplete data collection.\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCognitive Outcomes\u003c/h2\u003e \u003cp\u003eCognitive performance was assessed at baseline and post-intervention using the MATRICS Consensus Cognitive Battery (MCCB\u003cb\u003e)\u003c/b\u003e, the FDA-endorsed gold standard for assessing cognition-enhancing treatments in schizophrenia [21, 22]. Pre-testing occurred within two weeks prior to CRT initiation and post-testing within two weeks of program completion. The MCCB evaluates seven domains: Attention/vigilance, Working Memory, Verbal Learning, Visual Learning, Reasoning and Problem Solving, Social Cognition, and Processing Speed, yielding both domain-specific scores and an overall composite [21, 22]. Subtests include Trail Making Test Part A, Symbol Coding, Category Fluency (Animal Naming), Continuous Performance Test\u0026ndash;Identical Pairs, Wechsler Memory Scale\u0026ndash;III Spatial Span, Letter\u0026ndash;Number Span, Hopkins Verbal Learning Test\u0026ndash;Revised, Brief Visuospatial Memory Test\u0026ndash;Revised, Neuropsychological Assessment Battery\u0026ndash;Mazes, and the Mayer\u0026ndash;Salovey\u0026ndash;Caruso Emotional Intelligence Test [23, 24]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDemographic, Clinical, and Feasibility Variables\u003c/h2\u003e \u003cp\u003eDemographic and clinical variables were extracted from medical records using standardized operational definitions. Participant age was calculated using date of birth and CRT program completion date. Substance use history was defined as a lifetime DSM diagnosis of a substance use disorder or documented substance use in clinical records. Sustained employment was defined as engagement in competitive employment for at least six months. Financial assistance referred to receipt of disability benefits or other formal income support.\u003c/p\u003e \u003cp\u003eTwo self-harm variables were available in the dataset: documented lifetime history of self-harm and self-harm within the past 12 months. Due to insufficient variability in the recent self-harm variable, analyses were conducted using documented lifetime history of self-harm. History variables (including aggression, self-harm, suicide attempts, and inappropriate sexual behavior) reflected lifetime history unless otherwise specified. Feasibility and adherence were assessed using attendance-based indicators, including the number of CRT sessions attended (out of 30) and the percentage of scheduled sessions attended.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize demographic, clinical, and feasibility characteristics. Paired-samples t-tests were conducted to examine pre\u0026ndash;post changes in MCCB domain scores and composite cognition using one-tailed tests with α\u0026thinsp;=\u0026thinsp;.05, reflecting a priori directional hypotheses that cognitive performance would improve following CRT. Effect sizes (Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e) were calculated to estimate the magnitude of change. Exploratory linear regression analyses were conducted to examine potential predictors of cognitive change, including sex, ethnicity, and documented lifetime history of self-harm. These analyses were considered hypothesis-generating and were not intended to identify definitive predictors of treatment response due to the pilot sample size. Forensic legal status was not included in regression models because of limited statistical power.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.08 (7.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (76.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndigenous identity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndigenous/Metis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary Diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychotic disorder, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (84.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-psychotic disorder, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (46.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eForensic history\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNCR Current, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnfit-to-Stand Trial current, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast forensic history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical history\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of aggression, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of self-harm, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of suicide attempt, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInappropriate sexual behavior (ISB), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of family suicide attempt, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubstance use history\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (84.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannabis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStimulants, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (46.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOpioids, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocioeconomic characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSustained employment\u0026dagger;, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently receiving financial assistance, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreviously receiving financial assistance, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCRT attendance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSessions attended (out of 30), Mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.77 (5.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttendance rate %, Mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93.0 (17.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003eNote.\u003c/em\u003e Age was calculated using date of birth and CRT program completion date. Primary diagnoses were classified as psychotic or non-psychotic based on documented DSM diagnoses at enrollment. Substance use history reflects a lifetime DSM diagnosis or documented substance use in clinical records. Sustained employment was defined as engagement in competitive employment for \u0026ge;\u0026thinsp;6 months. Financial assistance refers to receipt of disability benefits or other formal income support. ISB\u0026thinsp;=\u0026thinsp;inappropriate sexual behavior. Unless otherwise specified, history variables reflect lifetime history. History of suicide includes documented suicide attempts. Attendance rate reflects the percentage of the 30 scheduled CRT sessions attended.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePaired t-tests of cognitive domain T scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔ (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e (df)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCohens d\u003csub\u003ez\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcessing Speed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.23 (2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.54, 10.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.89 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.11 (2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.25, 9.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.13 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorking Memory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.69 (1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.02, 7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.17 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.051\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerbal Learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.15 (1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.42, 10.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.12 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisual Learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.00 (2.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.29, 9.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.04 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReasoning/Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.85 (2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.63, 6.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.34 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.30 (3.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.33, 12.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.13 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.20 (1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.70, 6.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.81 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eΔ (SE)\u0026thinsp;=\u0026thinsp;average change score and standard Error, 95% CI\u0026thinsp;=\u0026thinsp;95% Confidence Interval, t (df)\u0026thinsp;=\u0026thinsp;test statistic and degrees of freedom, d\u003csub\u003ez\u003c/sub\u003e = effect size, bold, \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePaired t-tests of cognitive domain T scores with outliers removed\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔ (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e (df)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCohens d\u003csub\u003ez\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcessing Speed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.75 (1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.09, 11.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.67 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerbal Learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.41 (1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.64, 11.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.69 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReasoning/Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.75 (1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.17, 6.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.54 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.00 (0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.04, 6.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.88 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eΔ (SE)\u0026thinsp;=\u0026thinsp;average change score and standard Error, 95% CI\u0026thinsp;=\u0026thinsp;95% Confidence Interval, t (df)\u0026thinsp;=\u0026thinsp;test statistic and degrees of freedom, d\u003csub\u003ez\u003c/sub\u003e = effect size, bold, \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSimple regression models of predictor variables on change scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB (SE B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI (B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.05 (0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.38, 0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (ref. female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.50 (1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.07, 10.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHx agg. 12 months (ref. absent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.71 (2.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.99, 6.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHx.self harm\u003c/p\u003e \u003cp\u003e(ref. absent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.82 (1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.68,-0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHx. Suicide\u003c/p\u003e \u003cp\u003e(ref. absent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.96 (2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.22, 2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttendance rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.25 (6.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-13.86, 14.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndigenous ethnicity (ref. not indigenous)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.77 (2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.85, 4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eB\u0026thinsp;=\u0026thinsp;unstandardized coefficient, SE B\u0026thinsp;=\u0026thinsp;Standard Error of B, 95% CI B\u0026thinsp;=\u0026thinsp;95% Confidence Interval, Beta\u0026thinsp;=\u0026thinsp;standardized coefficient, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;Coefficient of Determination, \u003cb\u003ebold p\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/b\u003e, ref. is the reference category (coded 0).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eParticipants attended a mean of 27.77 sessions (SD\u0026thinsp;=\u0026thinsp;5.28) out of 30 scheduled sessions, corresponding to a mean attendance rate of 93.0% (Please see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No study withdrawals or adverse events related to CRT participation were recorded.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePaired-samples t-tests\u003c/h2\u003e \u003cp\u003eWith our pilot sample, significant gains were observed in processing speed, working memory, verbal learning, and overall domains. Specifically, processing speed scores increased by an average of 6.23 points, working memory scores showed a mean increase of 3.69 and verbal learning improved by 7.15 points (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The composite Overall score rose by 4.20. Changes in attention, visual learning, reasoning, and social domains did not reach significance (all p\u0026thinsp;\u0026ge;\u0026thinsp;.292).\u003c/p\u003e \u003cp\u003eBecause a small number of outliers were identified in difference scores, sensitivity analyses excluding these cases were performed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Results remained robust for processing speed, verbal, and overall domains: MΔ\u0026thinsp;=\u0026thinsp;5.00 (SE\u0026thinsp;=\u0026thinsp;0.85), 95% CI [3.04, 6.96], t(8)\u0026thinsp;=\u0026thinsp;5.88, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, dz\u0026thinsp;=\u0026thinsp;1.96. Reasoning/problem solving did not reach statistical significance after outlier removal (p\u0026thinsp;=\u0026thinsp;.07), though effect sizes increased. Other domains remained non-significant. The increase in mean change scores and effect sizes after outlier removal indicates that these participants had change scores far below the mean of the distribution, and represent those whose scores changed the least before and after training.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRegression analyses\u003c/h2\u003e \u003cp\u003eTwo predictors accounted for a substantial proportion of variance: sex (reference\u0026thinsp;=\u0026thinsp;female) and history of self-harm (reference\u0026thinsp;=\u0026thinsp;absent). Male participants showed greater improvement than females, and participants without a history of self-harm demonstrated greater gains than those with such history (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Age, history of aggression, history of suicide attempts, and attendance rate were not significant predictors (all p\u0026thinsp;\u0026ge;\u0026thinsp;.24). Given small subgroup sizes (e.g., n\u0026thinsp;=\u0026thinsp;3 females), these findings are preliminary and warrant replication in larger samples.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study demonstrates that a 15-week, web-based Cognitive Remediation Therapy (CRT) program can yield meaningful pre\u0026ndash;post improvements in processing speed, verbal learning, working-memory, and overall cognitive performance among psychiatric inpatients with schizophrenia spectrum and related disorders. Effect sizes observed for Processing Speed (d\u003csub\u003ez\u003c/sub\u003e = 1.35) and verbal learning (d\u003csub\u003ez\u003c/sub\u003e = 1.93) significantly exceed those reported in meta-analyses of traditional CRT [1, 3], suggesting that the integration of adaptive drill-and-practice exercises with structured metacognitive \u0026ldquo;bridging\u0026rdquo; discussions may potentiate cognitive gains in acute care settings. Unlike outpatient trials, where competing life demands and lower supervision often temper engagement [14], the inpatient environment affords a controlled context in which participants can immerse themselves in daily, web-based sessions without external distractions. The immediacy of feedback inherent in the Happy Neuron Pro platform likely bolstered motivation and mastery experiences, aligning with self-determination theory\u0026rsquo;s emphasis on competence and autonomy as drivers of sustained engagement [25, 26].\u003c/p\u003e \u003cp\u003eThe limited change observed in higher-order domains such as reasoning/problem solving, visual learning, and social cognition is consistent with prior evidence indicating that drill-and-practice CRT preferentially improves basic processing capacities (e.g., processing speed and verbal learning) [11, 13], while more complex cognitive domains may require greater training intensity, extended duration, or enhanced strategy coaching within the CRT framework. It is also possible that the MCCB, while the gold-standard battery, lacks sensitivity to detect subtle CRT-related changes in higher-order cognition. Future studies may therefore benefit from longer intervention periods, refined bridging content, and complementary outcome measures to better capture domain-specific change.\u003c/p\u003e \u003cp\u003eThe twice-weekly therapist-led discussions played an indispensable role in translating gains from the computerized approach into daily routines. By dedicating 40 minutes twice weekly to examine task strategies and personal challenges, participants could contextualize cognitive exercises within ward activities and interpersonal interactions, thereby fostering generalization. This approach is consistent with the NEAR model\u0026rsquo;s assertion that metacognitive reflection amplifies functional relevance of neurocognitive training [26]. Indeed, studies in forensic outpatient settings have found that such bridging sessions not only boost cognitive performance but also improve adaptive behavior and symptom management [13, 20]. Future research should expand on these results by experimentally varying the timing and content intensity of bridging sessions (e.g., brief versus in-depth; weekly versus biweekly) to identify which formats best promote transfer to functional outcomes.\u003c/p\u003e \u003cp\u003eExploratory regression analyses suggested potential associations between sex, self-harm history, and cognitive change; however, these findings are preliminary and should be interpreted cautiously given small subgroup sizes. More robust investigation in larger, gender-balanced samples is required to clarify whether sex moderates response to web-based CRT. The negative association between self-harm history and cognitive improvement is consistent with literature linking self-injurious behaviors to executive dysfunction, affective dysregulation, and diminished treatment adherence [27]. Participants with a history of self-harm may experience heightened emotional distress that interferes with cognitive control and working-memory performance [28, 29], and because self-harm is strongly linked to emotion-regulation and executive-function deficits [30, 31], adjunctive distress-tolerance or mood-stabilizing interventions (e.g., DBT or pharmacologic mood stabilizers) may be necessary to maximize engagement with and benefit from cognitive remediation [32, 33].\u003c/p\u003e \u003cp\u003eThe feasibility of implementing web-based CRT within an acute inpatient setting challenges widely held belief that structured cognitive therapies are not possible due to severe symptomatology and fluctuating lengths of stay [14]. High adherence rates in this study demonstrate that, when supported by facilitators and delivered via hospital-based desktop computers with secure Ethernet connections, even acutely ill patients can successfully engage in a regimented cognitive training protocol. This finding underscores the scalability of digital CRT and its potential to fill a critical treatment gap in settings where traditional face-to-face CRT is logistically impractical.\u003c/p\u003e \u003cp\u003eComparison with outpatient data further highlights the advantages of inpatient deployment. Effect sizes in this study surpass those typically observed in community settings where average d values range between 0.30 and 0.50 for Processing Speed and Working Memory [3, 14]. Two factors likely underpin these differences: the structured inpatient schedule that minimizes competing demands, and the novelty and immediacy of supervised, computer-based delivery, which may enhance motivation. However, it is unclear if these benefits last after discharge; long-term monitoring is necessary to ascertain how long cognitive advantages last and how well they translate into social and professional performance.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of Study\u003c/h2\u003e \u003cp\u003eThe absence of functional outcome data due to COVID-related restrictions on adaptive behavior assessment constitutes a notable limitation. ABAS-3 administration was not completed because of pandemic restrictions, staff turnover, small cohort sizes, and delayed post-testing, and re-contacting discharged participants was not possible without REB-approved consent. Consequently, adaptive functioning could not be evaluated. Future studies should include pre\u0026ndash;post ABAS-3 or obtain REB-approved consent for post-discharge follow-up. Without direct measures linking cognitive gains to real-world activities, conclusions regarding the intervention\u0026rsquo;s impact on daily living capacities remain inferential. Moreover, the single-arm, pre\u0026ndash;post design precludes causal attribution; future randomized controlled trials comparing web-based CRT with active control interventions (e.g., computer games or non-adaptive cognitive tasks) are necessary to establish specific treatment effects. The small sample size limits statistical power and may inflate effect-size estimates [34]. Also, precise CRT program commencement dates were not consistently documented in clinical records, precluding accurate calculation of program duration or time to completion. Consequently, feasibility was assessed using attendance-based indicators rather than treatment duration. In addition, formal screening logs were not maintained; therefore, the number of patients approached but not enrolled could not be reliably quantified. Finally, the inpatient setting and COVID-19\u0026ndash;related operational constraints resulted in smaller-than-planned cohort sizes, which may have influenced group dynamics and generalizability.\u003c/p\u003e \u003cp\u003eDespite these limitations, the pronounced cognitive improvements observed in this pilot study, particularly in processing speed and verbal learning, underscore the promise of web-based CRT for inpatient populations. By harnessing adaptive software and structured metacognitive reflection, psychiatric units may deliver high-intensity, scalable interventions that address the cognitive deficits most strongly linked to functional disability in schizophrenia. Future protocols should examine how variations in CRT dose, task composition, and the structure and timing of bridging sessions influence gains in higher-order cognitive domains and functional outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImplications for Policy and Practice\u003c/h2\u003e \u003cp\u003eThe present findings support the feasibility and efficacy of implementing web-based CRT within inpatient psychiatric settings. Health services should consider integrating scalable, computerized CRT platforms into standard care, leveraging the controlled environment of inpatient wards to ensure high adherence and consistent delivery. Given the robust gains in Processing Speed and Verbal Learning, inpatient CRT programs could be positioned as an early intervention strategy to mitigate cognitive decline and foster readiness for community reintegration.\u003c/p\u003e \u003cp\u003ePolicy makers must allocate resources for staff training in both computerized CRT delivery and metacognitive bridging techniques. Investment in digital infrastructure such as secure web-enabled devices and reliable internet access is critical to facilitate uninterrupted program delivery. Moreover, mental health authorities should develop clinical guidelines endorsing CRT as a core component of comprehensive rehabilitation for schizophrenia and other severe mental illnesses, comparable to existing, evidence-based interventions such as supported employment (e.g., Individual Placement and Support) and assertive community treatment (multidisciplinary, intensive, community-based care).\u003c/p\u003e \u003cp\u003eAttention to cultural and forensic contexts is also essential. Indigenous patients often experience barriers to engagement with Western-centric interventions; therefore, culturally responsive adaptations; such as incorporating Indigenous languages, metaphors, and community elders into bridging discussions, may enhance relevance and uptake [35, 36]. Likewise, forensic patients may benefit from secure, on-ward CRT delivery that accommodates custodial restrictions while fostering cognitive recovery. With this approach, collaborative efforts between correctional services and mental health teams may establish dedicated CRT programs within forensic units.\u003c/p\u003e \u003cp\u003eFinally, further research should examine long-term outcomes, including maintenance of cognitive gains and functional recovery metrics such as employment rates, independent living, and recidivism in forensic populations. Economic evaluations could elucidate cost-effectiveness, informing policy decisions on broader implementation. By embedding CRT within a continuum of psychiatric rehabilitation services, health systems can address the cognitive disabilities that underlie disability in schizophrenia, ultimately improving patient autonomy, community participation, and quality of life.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWeb-based CRT shows preliminary evidence of improvement of neurocognitive functioning among psychiatric inpatients. While the strongest gains emerged in Processing Speed and Verbal Learning, future CRT trials should explore whether extending training duration, refining bridging strategies, or incorporating complementary outcome measures can enhance higher-order cognitive change. Web-based CRT appears feasible in inpatient psychiatric settings and shows preliminary signals of cognitive benefit, supporting further investigation in larger randomized controlled trials.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval:\u0026nbsp;\u003c/strong\u003eEthics approval was received from the Research Ethics Board (REB) of the former Qu’Appelle Haelth Region (RQHR) indicating the study meets the membership criteria for, and adheres to the requirements of, the 2\u003csup\u003end\u003c/sup\u003e edition of Canda’s \u003cem\u003eTri-Council Policy Statement: Ethical Conduct for Research Involving Humans,\u0026nbsp;\u003c/em\u003ethe \u003cem\u003eInternational Conference on Harmonisation Good Clinical Practice (E6)\u0026nbsp;\u003c/em\u003eguidelines (ICH GCP), and Part C Division 5 of Canada’s \u003cem\u003eFood and Drug Regulations\u0026nbsp;\u003c/em\u003eunder RQHR File # REB-20-29, approved on April 20, 2020. Saskatchewan Health Authority provided Operational Approval (OA-SHA-20-29) on April 27, 2020.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u0026nbsp;\u003c/strong\u003eWritten informed consent was obtained from all participants prior to participation in the study. Participants were provided with a detailed explanation of the study procedures, potential risks and benefits, and their right to withdraw at any time without impact on their clinical care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe research team would like to thank James Winder and Brittney Landstrom for their dedication in facilitating the Cognitive Remediation programming, for without their efforts patients would not have received the benefits of this program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was funded internally by the Saskatchewan Health Authority. The funders had no role in the design of the study; the collection, analysis, and interpretation of data; the writing of the manuscript; or the decision to submit the paper for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u003c/strong\u003e Not Applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVita A, Barlati S, Ceraso A, Nibbio G, Ariu C, Deste G, Wykes T. Effectiveness, core elements, and moderators of response of cognitive remediation for schizophrenia: a systematic review and meta-analysis of randomized clinical trials. JAMA psychiatry. 2021 Aug 1;78(8):848-58. https://doi.org/10.1001/jamapsychiatry.2021.0620 \u003c/li\u003e\n\u003cli\u003eW\u0026ouml;lwer W, Frommann N, Lowe A, Kamp D, Weide K, Bechdolf A, Brockhaus-Dumke A, Hurlemann R, Muthesius A, Klingberg S, Hellmich M. 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Implementation Science. 2023 Jun 22;18(1):23. https://doi.org/10.1186/s13012-023-01276-1 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cognitive remediation therapy, web-based intervention, neurocognition, psychotic disorders, psychiatric inpatients.","lastPublishedDoi":"10.21203/rs.3.rs-8564907/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8564907/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Cognitive impairments are a core feature of psychotic disorders and are strongly associated with long-term functional disability. Cognitive Remediation Therapy (CRT) is an evidence-based intervention for improving cognition in psychosis; however, its feasibility and preliminary cognitive effects in acute inpatient settings—particularly using web-based platforms—remain underexplored. This pilot study evaluated the feasibility of delivering a web-based CRT program in an inpatient psychiatric setting and examined preliminary cognitive outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This single-arm, pre–post pilot study was conducted in a secure psychiatric inpatient facility. Thirteen inpatients with psychotic disorders participated in a 15-week web-based CRT program delivered twice weekly (30 sessions total). Each session comprised approximately 50 minutes of adaptive computerized CRT exercises (Happy Neuron Pro) followed by a 40-minute therapist-led bridging discussion focused on metacognitive reflection and application of cognitive strategies to daily activities. Cognitive performance was assessed before and after the intervention using the MATRICS Consensus Cognitive Battery (MCCB). Feasibility outcomes included session attendance, study retention, and completion of pre–post cognitive assessments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: All participants completed pre- and post-intervention cognitive assessments, with no study withdrawals or adverse events reported. Participants attended a mean of 27.77 (SD = 5.28) of 30 scheduled sessions, corresponding to a mean attendance rate of 93.0%. Pre–post improvements were observed in processing speed, verbal learning, and overall composite cognition, with large within-sample effect sizes. Sensitivity analyses excluding outliers confirmed robustness of these findings. Exploratory regression analyses suggested potential associations between sex and history of self-harm with cognitive change; however, these findings should be interpreted cautiously given the small sample size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The findings support the feasibility of delivering web-based CRT with structured bridging discussions in an inpatient psychiatric setting and suggest a preliminary signal of cognitive benefit. Given the pilot, single-arm design, results should be considered hypothesis-generating. Further research using controlled designs and larger samples is warranted.\u003c/p\u003e","manuscriptTitle":"Feasibility and Preliminary Outcomes of Web-Based Cognitive Remediation Therapy in Psychiatric Inpatients With Psychotic Disorders: A Pilot Pre–Post Study Using the MATRICS Consensus Cognitive Battery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-21 08:45:55","doi":"10.21203/rs.3.rs-8564907/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"87de355c-fdfa-43d1-88ad-fd1e3003b62e","owner":[],"postedDate":"January 21st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-05T07:26:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-21 08:45:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8564907","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8564907","identity":"rs-8564907","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}