Recorded poor insight as a predictor of service use outcomes: cohort study of patients with first-episode psychosis in a large mental healthcare database

Identification of Psychosis Risk and Diagnosis of First-Episode Psychosis: Advice for Clinicians

Early detection of psychotic-spectrum disorders among adolescents and young adults is crucial, as the initial years after psychotic symptom onset encompass a critical period in which psychosocial and pharmacological interventions are most effective. Moreover, clinicians and researchers in recent decades have thoroughly characterized psychosis-risk syndromes, in which youth are experiencing early warning signs indicative of heightened risk for developing a psychotic disorder. These insights have created opportunities for intervention even earlier in the illness course, ideally culminating in the prevention or mitigation of psychosis onset. However, identification and diagnosis of early signs of psychosis can be complex, as clinical presentations are heterogeneous, and psychotic symptoms exist on a continuum. When a young person presents to a clinic, it may be unclear whether they are experiencing common, mild psychotic-like symptoms, early warning signs of psychosis, overt psychotic symptoms, or symptoms better accounted for by a non-psychotic disorder. Therefore, the purpose of this review is to provide a framework for clinicians, including those who treat non-psychotic disorders and those in primary care settings, for guiding identification and diagnosis of early psychosis within the presenting clinic or via referral to a specialty clinic. We first provide descriptions and examples of first-episode psychosis (FEP) and psychosis-risk syndromes, as well as assessment tools used to diagnose these conditions. Next, we provide guidance as to the differential diagnosis of conditions which have phenotypic overlap with psychotic disorders, while considering the possibility of co-occurring symptoms in which case transdiagnostic treatments are encouraged. Finally, we conclude with an overview of early detection screening and outreach campaigns, which should be further optimized to reduce the duration of untreated psychosis among youth.

The role of insight, social rank, mindfulness and self-compassion in depression following first episode psychosis

Gaining awareness of psychosis (i.e., insight) is linked to depression, particularly in the post-acute phase of psychosis. Informed by social rank theory, we examined whether the insight-depression relationship is explained by reduced social rank related to psychosis and whether self-compassion (including uncompassionate self-responding [UCS] and compassionate self-responding [CSR]) and mindfulness buffered the relationship between social rank and depression in individuals with first episode psychosis during the post-acute phase. Participants were 145 young people (Mage  = 20.81; female = 66) with first episode psychosis approaching discharge from an early psychosis intervention centre. Questionnaires and interviews assessed insight, depressive symptoms, perceived social rank, self-compassion, mindfulness and illness severity. Results showed that insight was not significantly associated to depression and thus no mediation analysis was conducted. However, lower perceived social rank was related to higher depression, and this relationship was moderated by self-compassion and, more specifically, UCS. Mindfulness was related to depression but had no moderating effect on social rank and depression. Results supported previous findings that depressive symptoms are common during the post-acute phase. The role of insight in depression for this sample is unclear and may be less important during the post-acute phase than previously considered. Supporting social rank theory, the results suggest that low perceived social rank contributes to depression, and reducing UCS may ameliorate this effect. UCS, social rank and possibly mindfulness may be valuable intervention targets for depression intervention and prevention efforts in the recovery of psychosis.

The relationship between sex and functional outcome in first-episode schizophrenia: the role of premorbid adjustment and insight

BACKGROUND

Studies that examined sex differences in first-episode patients consistently show that males compared to females have poor premorbid adjustment, earlier age of onset, worse clinical characteristics, and poorer outcomes. However, little is known about potential mediators that could explain these sex differences.

METHODS

Our sample consisted of 137 individuals with first episode schizophrenia (males, n = 105; 77%) with a mean age of 22.1(s.d. = 4.1) years and mean education of 12.5(s.d. = 1.7) years. At entry, patients were within 2 years of their first psychotic episode onset. Baseline assessments were conducted for premorbid adjustment, symptoms, cognitive functioning, insight, and at 6-months for role and social functioning.

RESULTS

Males as compared to females had poorer premorbid adjustment across several key developmental periods (p < 0.01), an earlier age of onset [M = 20.3(3.3) v. 22.8(5.6), p = 0.002], more negative symptoms (p = 0.044), poorer insight (p = 0.031), and poorer baseline and 6-month role (p = 0.002) and social functioning (p = 0.034). Several of these variables in which males showed impairment were significant predictors of 6-month role and social functioning. Premorbid adjustment and insight mediated the relationship between sex and role and social functioning at 6-months, but not negative symptoms.

DISCUSSION

Males compared to females were at lower levels across several key premorbid and clinical domains which are strongly associated with functional outcome supporting the hypothesis that males might have a more disabling form of schizophrenia. The relationship between sex with role and social functioning was mediated through premorbid adjustment and insight suggesting pathways for understanding why females might have a less disabling form of schizophrenia.

Role of Clinical Insight at First Month in Predicting Relapse at the Year in First Episode of Psychosis (FEP) Patients

INTRODUCTION

Clinical insight constitutes a useful marker of the progress and outcome of the First Episode of Psychosis (FEP), and lack of insight has been associated with more severe psychopathology, treatment non-adherence, and rehospitalization/relapse. In this study, we aimed to further investigate the possible role of insight as a predictor of relapse, its relation to diagnosis, and other parameters of positive psychotic symptomatology (delusions, hallucinations, and suspiciousness).

METHODS

The Athens FEP study employed a prospective, longitudinal cohort design in which consecutive newly diagnosed patients with psychosis were interviewed and asked to voluntarily participate after completing informed consent. A total of 88/225 patients were examined at three different time points (baseline, month, and year). Their scores in the relevant items of the Positive and Negative Syndrome Scale (PANSS) were compared (G12 for insight, P1 for delusions, P3 for hallucinations, and P6 for suspiciousness), and they were further associated to diagnosis and the outcome at the end of the year (remission/relapse).

RESULTS

In total, 22/88 patients with relapse at the year had greater scores in G12 for both the month and the year, and this finding was corroborated after adjusting the statistical analysis for demographics, diagnosis, social environment, and depression via multiple logistic regression analysis. Moreover, delusions and suspiciousness were significantly higher in patients diagnosed with non-affective psychosis compared to those diagnosed with affective psychosis (p < 0.001) at the first month.

CONCLUSIONS

Lack of insight at the first month may serve as a predictor of relapse at the year.

Treatment characteristics among patients with binge-eating disorder: an electronic health records analysis

OBJECTIVES

Treatment for adults diagnosed with binge-eating disorder (BED) includes psychotherapy and/or pharmacotherapy and aims to reduce the frequency of binge-eating episodes and disordered eating, improve metabolic-related issues and reduce weight, and address mood symptoms. Data describing real-world treatment patterns are lacking; therefore, this study aims to characterize real-world treatment patterns among patients with BED.

METHODS

This retrospective study identified adult patients with BED using natural language processing of clinical notes from the Optum electronic health record database from 2009 to 2015. Treatment patterns were examined during the 12 months preceding the BED recognition date and during a follow-up period after BED recognition (1-3 years for most patients).

RESULTS

Among 1042 patients, 384 were categorized as the BED cohort and 658, who met less stringent criteria, were categorized as probable BED. In the BED cohort, mean ± SD age was 45.2 ± 13.4 years and 81.8% were women (probable BED, 45.9 ± 12.8 years, 80.2%). A greater percentage of patients in the BED cohort were prescribed pharmacotherapy (70.6% [probable BED, 66.9%]) than received/discussed psychotherapy (53.1% [probable BED, 39.2%]) at baseline. In the BED cohort, 54.4% of patients were prescribed antidepressants (probable BED, 52.4%), 25.3% stimulants (probable BED, 20.1%), and 34.4% nonspecific psychotherapy (probable BED, 24.6%) at baseline, with no substantive differences observed during follow-up. Low percentages of patients in the BED cohort received/discussed cognitive behavioral therapy at baseline (12.5% [probable BED, 9.0%) or during follow-up (13.0% [probable BED, 8.8%). Among patients with ≥1 psychotherapy visit, the mean ± SD number of visits in the BED cohort was 1.2 ± 5.9 at baseline (probable BED, 1.7 ± 7.3) and 2.2 ± 7.7 during follow-up (probable BED, 2.6 ± 7.7).

CONCLUSION

This cohort of patients with BED was treated more frequently with pharmacotherapy than psychotherapy. These data may help inform strategies for reducing differences between real-world treatment patterns and evidence-based recommendations.

Incidence and factors associated of early non-response in first-treatment and drug-naïve patients with schizophrenia: a real-world study

Background

Schizophrenia is a severe and persistent mental condition that causes disability. For subsequent clinical care, it is extremely practical to effectively differentiate between patients who respond to therapy quickly and those who do not. This study set out to document the prevalence and risk factors for patient early non-response.

Methods

The current study included 143 individuals with first-treatment and drug-naïve (FTDN) schizophrenia. Patients were classified as early non-responders based on a Positive and Negative Symptom Scale (PANSS) score reduction of less than 20% after 2 weeks of treatment, otherwise as early responders. Clinical subgroups' differences in demographic data and general clinical data were compared, and variables related to early non-response to therapy were examined.

Results

Two weeks later, a total of 73 patients were described as early non-responders, with an incidence of 51.05%. The early non-response subgroup had significantly higher PANSS scores, Positive symptom subscale (PSS) scores, General psychopathology subscale (GPS) scores, Clinical global impression scale - severity of illness (CGI-SI) and Fasting blood glucose (FBG) levels compared to the early-response subgroup. CGI-SI and FBG were risk factors for early non-response.

Conclusion

High rates of early non-response have been seen in FTDN schizophrenia patients, and risk variables for predicting early non-response include CGI-SI scores and FBG levels. However, we need more in-depth studies to confirm the generalizable range of these two parameters.

A survey on clinical natural language processing in the United Kingdom from 2007 to 2022

Much of the knowledge and information needed for enabling high-quality clinical research is stored in free-text format. Natural language processing (NLP) has been used to extract information from these sources at scale for several decades. This paper aims to present a comprehensive review of clinical NLP for the past 15 years in the UK to identify the community, depict its evolution, analyse methodologies and applications, and identify the main barriers. We collect a dataset of clinical NLP projects (n = 94; £ = 41.97 m) funded by UK funders or the European Union's funding programmes. Additionally, we extract details on 9 funders, 137 organisations, 139 persons and 431 research papers. Networks are created from timestamped data interlinking all entities, and network analysis is subsequently applied to generate insights. 431 publications are identified as part of a literature review, of which 107 are eligible for final analysis. Results show, not surprisingly, clinical NLP in the UK has increased substantially in the last 15 years: the total budget in the period of 2019-2022 was 80 times that of 2007-2010. However, the effort is required to deepen areas such as disease (sub-)phenotyping and broaden application domains. There is also a need to improve links between academia and industry and enable deployments in real-world settings for the realisation of clinical NLP's great potential in care delivery. The major barriers include research and development access to hospital data, lack of capable computational resources in the right places, the scarcity of labelled data and barriers to sharing of pretrained models.

Natural Language Processing Methods and Bipolar Disorder: Scoping Review

BACKGROUND

Health researchers are increasingly using natural language processing (NLP) to study various mental health conditions using both social media and electronic health records (EHRs). There is currently no published synthesis that relates specifically to the use of NLP methods for bipolar disorder, and this scoping review was conducted to synthesize valuable insights that have been presented in the literature.

OBJECTIVE

This scoping review explored how NLP methods have been used in research to better understand bipolar disorder and identify opportunities for further use of these methods.

METHODS

A systematic, computerized search of index and free-text terms related to bipolar disorder and NLP was conducted using 5 databases and 1 anthology: MEDLINE, PsycINFO, Academic Search Ultimate, Scopus, Web of Science Core Collection, and the ACL Anthology.

RESULTS

Of 507 identified studies, a total of 35 (6.9%) studies met the inclusion criteria. A narrative synthesis was used to describe the data, and the studies were grouped into four objectives: prediction and classification (n=25), characterization of the language of bipolar disorder (n=13), use of EHRs to measure health outcomes (n=3), and use of EHRs for phenotyping (n=2). Ethical considerations were reported in 60% (21/35) of the studies.

CONCLUSIONS

The current literature demonstrates how language analysis can be used to assist in and improve the provision of care for people living with bipolar disorder. Individuals with bipolar disorder and the medical community could benefit from research that uses NLP to investigate risk-taking, web-based services, social and occupational functioning, and the representation of gender in bipolar disorder populations on the web. Future research that implements NLP methods to study bipolar disorder should be governed by ethical principles, and any decisions regarding the collection and sharing of data sets should ultimately be made on a case-by-case basis, considering the risk to the data participants and whether their privacy can be ensured.

The relationship between psychological characteristics of patients and their utilization of psychiatric inpatient treatment: A cross-sectional study, using machine learning

High utilizers (HU) are patients with an above-average use of psychiatric inpatient treatment. A precise characterization of this patient group is important when tailoring specific treatment approaches for them. While the current literature reports evidence of sociodemographic, and socio-clinical characteristics of HU, knowledge regarding their psychological characteristics is sparse. This study aimed to investigate the association between patients’ psychological characteristics and their utilization of psychiatric inpatient treatment. Patients from the University Psychiatric Clinics (UPK) Basel diagnosed with schizophrenia spectrum or bipolar affective disorders participated in a survey at the end of their inpatient treatment stay. The survey included assessments of psychological characteristics such as quality of life, self-esteem, self-stigma, subjective experience and meaning of psychoses, insight into the disease, and patients’ utilization of psychiatric inpatient treatment in the last 30 months. The outcome variables were two indicators of utilization of psychiatric inpatient treatment, viz. “utilization pattern” (defined as HU vs. Non-HU [NHU]) and “length of stay” (number of inpatient treatment days in the last 30 months). Statistical analyses included multiple regression models, the least absolute shrinkage and selection operator (lasso) method, and the random forest model. We included 112 inpatients, of which 50 were classified as HU and 62 as NHU. The low performance of all statistical models used after cross-validation suggests that none of the estimated psychological variables showed predictive accuracy and hence clinical relevance regarding these two outcomes. Results indicate no link between psychological characteristics and inpatient treatment utilization in patients diagnosed with schizophrenia spectrum or bipolar affective disorders. Thus, in this study, the examined psychological variables do not seem to play an important role in patients’ use of psychiatric inpatient treatment; this highlights the need for additional research to further examine underlying mechanisms of high utilization of psychiatric inpatient treatment.

An Update on Clinical Insight, Cognitive Insight, and Introspective Accuracy in Schizophrenia-Spectrum Disorders: Symptoms, Cognition, and Treatment

INTRODUCTION

Poor insight, or unawareness of morbid changes in cognition, emotional states, or behavior, is commonly observed among people with schizophrenia. Poor insight represents a persistent barrier to wellness because it interferes with treatment and self-direction. Paradoxically, good insight may also be a barrier to health when awareness of these changes leads to depression or self-stigma.

AREAS COVERED

This paper builds upon this previous work by exploring these issues in schizophrenia separately as they have appeared in published research over the last three years in three different kinds of insight: clinical, cognition, and introspective accuracy. Specifically, studies are reviewed that address: the adverse effects of poor insight, the paradoxical effects of good insight, correlates with other forms of cognition, and emerging treatments.

EXPERT OPINION

The evidence continues to offer a nuanced picture of the complex effects of good insight in schizophrenia. Incremental improvements were also found in the development of novel integrative treatment approaches. This work also highlights the intricacy of the concept of insight, the need for further exploration of the effects of culture, and conceptual work that distinguishes the points of convergence and divergence of these forms of insight.

Introspective accuracy for substance use across a year of treatment for first episode psychosis

Substance use exacerbates psychosis, mania, depression, and poor functioning in people with first episodes of psychosis (FEP) and is associated with poor treatment outcomes, even when it does not reach the level of a formal disorder. Impaired insight and substance use are common issues that may interfere with treatment outcomes among people experiencing FEP, yet both are treatable. Improvements in these domains are associated with better outcomes. Low insight could increase risk for substance use by impairing the ability to self-appraise and assess consequences. Introspective accuracy (IA) is understudied in this area and is one way of considering self-appraisal. This study is an archival review using data collected from NAVIGATE, a coordinated specialty care program treating people with FEP. IA was operationalized as the difference between clinician and client ratings of substance use. We tested whether IA changed over one year of treatment and whether those changes occurred alongside changes in symptoms and illness self-management. No changes in IA were detected in relation to illness self-management. Changes in IA for substance use occurred midway through treatment-individuals with greater symptom remission had more overconfident IA. Prior research on insight has shown a paradox where greater insight accompanies more symptoms. However, past research has also shown a relationship between IA and functional outcomes, like illness self-management, and that overconfidence in one domain can positively bias clinician ratings in another. Our findings suggest either a positive bias for ratings associated with overconfident IA or an insight paradox type effect.

Delineating insight-processing-related functional activations in the precuneus in first-episode psychosis patients

Poor insight is a central characteristic of psychotic disorders, and it has been suggested to result from a general dysfunction in self-reflection. However, brain processing of clinical insight and more general self-reflection has not been directly compared. We compared tasks on (1) self-reflection on psychosis-related mental functioning (clinical insight, in patients only), (2) self-reflection on mental functioning unrelated to psychosis (general metacognition), and (3) semantic control during blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging with 19 first-episode psychosis patients and 24 control participants. Arterial-spin-labeling (ASL) images were collected at rest. Clinical insight was evaluated with the Schedule for the Assessment of Insight. In patients, posterosuperior precuneus showed stronger activation during the insight task than during the semantic control task, while anteroinferior precuneus and posterior cingulate cortex (PCC) showed stronger activation during the insight task than during the general metacognition task. No significant group differences in brain activation emerged during the general metacognition task. Although the BOLD measures did not correlate with clinical insight measures, ASL-measured cerebral blood flow (CBF) values did correlate when extracted from the task-selective precuneus/PCC areas: higher CBF correlated with higher clinical insight scores. These results suggest that regions in the posteromedial cortex are selective for clinical insight.

A narrative review of intervention in first-episode affective psychoses

While first-episode schizophrenia has received extensive attention in the literature, few studies have focused on the first episode of affective psychoses. Considering the lack of structured data regarding this diagnostic grouping commonly used in clinical settings, our aim was to scope the literature on first-episode affective psychoses to consolidate current knowledge and to identify areas to be targeted in future studies. We also planned to investigate the relevance of the "affective psychosis" concept regarding diagnostic categories and specific needs of intervention. We conducted a search on the Embase, Medline, PubMed, PsycINFO and Web Of Science databases until October 2020. We selected studies and synthesized the key findings into a narrative review regarding major topics of early intervention research: diagnostic categorization, premorbid factors, intervention, duration of untreated illness, neurobiology and neurocognition. After screening 961 titles and abstracts and 193 full-text papers, we selected 77 studies for inclusion. Our results showed heterogeneity in diagnosis-related grouping under the concept of affective psychoses, especially variability regarding the inclusion of schizoaffective disorder. Nonetheless, this concept still encompasses patients with different psychopathological and neurocognitive profiles from the non-affective patients requiring specialized intervention. This study thus provided support for the relevance of this concept as well as a need for further investigation.

Cognitive Impairments in Schizophrenia: A Study in a Large Clinical Sample Using Natural Language Processing

Background: Cognitive impairments are a neglected aspect of schizophrenia despite being a major factor of poor functional outcome. They are usually measured using various rating scales, however, these necessitate trained practitioners and are rarely routinely applied in clinical settings. Recent advances in natural language processing techniques allow us to extract such information from unstructured portions of text at a large scale and in a cost effective manner. We aimed to identify cognitive problems in the clinical records of a large sample of patients with schizophrenia, and assess their association with clinical outcomes. Methods: We developed a natural language processing based application identifying cognitive dysfunctions from the free text of medical records, and assessed its performance against a rating scale widely used in the United Kingdom, the cognitive component of the Health of the Nation Outcome Scales (HoNOS). Furthermore, we analyzed cognitive trajectories over the course of patient treatment, and evaluated their relationship with various socio-demographic factors and clinical outcomes. Results: We found a high prevalence of cognitive impairments in patients with schizophrenia, and a strong correlation with several socio-demographic factors (gender, education, ethnicity, marital status, and employment) as well as adverse clinical outcomes. Results obtained from the free text were broadly in line with those obtained using the HoNOS subscale, and shed light on additional associations, notably related to attention and social impairments for patients with higher education. Conclusions: Our findings demonstrate that cognitive problems are common in patients with schizophrenia, can be reliably extracted from clinical records using natural language processing, and are associated with adverse clinical outcomes. Harvesting the free text from medical records provides a larger coverage in contrast to neurocognitive batteries or rating scales, and access to additional socio-demographic and clinical variables. Text mining tools can therefore facilitate large scale patient screening and early symptoms detection, and ultimately help inform clinical decisions.

Gender differences in clinical presentation and illicit substance use during first episode psychosis: a natural language processing, electronic case register study

OBJECTIVE

To determine whether gender differences in symptom presentation at first episode psychosis (FEP) remain even when controlling for substance use, age and ethnicity, using natural language processing applied to electronic health records (EHRs).

DESIGN, SETTING AND PARTICIPANTS

Data were extracted from EHRs of 3350 people (62% male patients) who had presented to the South London and Maudsley NHS Trust with a FEP between 1 April 2007 and 31 March 2017. Logistic regression was used to examine gender differences in the presentation of positive, negative, depressive, mania and disorganisation symptoms.

EXPOSURES FOR OBSERVATIONAL STUDIES

Gender (male vs female).

MAIN OUTCOMES AND MEASURES

Presence of positive, negative, depressive, mania and disorganisation symptoms at initial clinical presentation.

RESULTS

Eight symptoms were significantly more prevalent in men (poverty of thought, negative symptoms, social withdrawal, poverty of speech, aggression, grandiosity, paranoia and agitation). Conversely, tearfulness, low energy, reduced appetite, low mood, pressured speech, mood instability, flight of ideas, guilt, mutism, insomnia, poor concentration, tangentiality and elation were more prevalent in women than men. Negative symptoms were more common among men (OR 1.85, 95% CI 1.33 to 2.62) and depressive and manic symptoms more common among women (OR 0.30, 95% CI 0.26 to 0.35). After adjustment for illicit substance use, the strength of associations between gender and negative, manic and depression symptoms increased, whereas gender differences in aggression, agitation, paranoia and grandiosity became insignificant.

CONCLUSIONS

There are clear gender differences in the clinical presentation of FEP. Our findings suggest that gender can have a substantial influence on the nature of clinical presentation in people with psychosis, and that this is only partly explained by exposure to illicit substance use.

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk

BACKGROUND

Using novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis.

METHOD

The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and Maudsley (SLaM) NHS Foundation Trust between January 1, 2008, and July 28, 2018. Least Absolute Shrinkage and Selection Operator (LASSO)-regularized Cox regression was used to refine and externally validate a refined version of a five-item individualized, transdiagnostic, clinically based risk calculator previously developed (Harrell's C = 0.79) and piloted for implementation. The refined version included 14 additional NLP-predictors: tearfulness, poor appetite, weight loss, insomnia, cannabis, cocaine, guilt, irritability, delusions, hopelessness, disturbed sleep, poor insight, agitation, and paranoia.

RESULTS

A total of 92 151 patients with a first index diagnosis of nonorganic and nonpsychotic mental disorder within the SLaM Trust were included in the derivation (n = 28 297) or external validation (n = 63 854) data sets. Mean age was 33.6 years, 50.7% were women, and 67.0% were of white race/ethnicity. Mean follow-up was 1590 days. The overall 6-year risk of psychosis in secondary mental health care was 3.4 (95% CI, 3.3-3.6). External validation indicated strong performance on unseen data (Harrell's C 0.85, 95% CI 0.84-0.86), an increase of 0.06 from the original model.

CONCLUSIONS

Using NLP on EHRs can considerably enhance the prognostic accuracy of psychosis risk calculators. This can help identify patients at risk of psychosis who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes.

The Potential of Research Drawing on Clinical Free Text to Bring Benefits to Patients in the United Kingdom: A Systematic Review of the Literature

Background: The analysis of clinical free text from patient records for research has potential to contribute to the medical evidence base but access to clinical free text is frequently denied by data custodians who perceive that the privacy risks of data-sharing are too high. Engagement activities with patients and regulators, where views on the sharing of clinical free text data for research have been discussed, have identified that stakeholders would like to understand the potential clinical benefits that could be achieved if access to free text for clinical research were improved. We aimed to systematically review all UK research studies which used clinical free text and report direct or potential benefits to patients, synthesizing possible benefits into an easy to communicate taxonomy for public engagement and policy discussions. Methods: We conducted a systematic search for articles which reported primary research using clinical free text, drawn from UK health record databases, which reported a benefit or potential benefit for patients, actionable in a clinical environment or health service, and not solely methods development or data quality improvement. We screened eligible papers and thematically analyzed information about clinical benefits reported in the paper to create a taxonomy of benefits. Results: We identified 43 papers and derived five themes of benefits: health-care quality or services improvement, observational risk factor-outcome research, drug prescribing safety, case-finding for clinical trials, and development of clinical decision support. Five papers compared study quality with and without free text and found an improvement of accuracy when free text was included in analytical models. Conclusions: Findings will help stakeholders weigh the potential benefits of free text research against perceived risks to patient privacy. The taxonomy can be used to aid public and policy discussions, and identified studies could form a public-facing repository which will help the health-care text analysis research community better communicate the impact of their work.

Co-occurring Deficits in Clinical and Cognitive Insight in Prolonged Schizophrenia-Spectrum Disorders: Relationship to Metacognitive Deficits

People diagnosed with schizophrenia have been broadly observed to experience deficits in clinical and cognitive insight; however, less is understood about how these deficits are related. One possibility is that these deficits co-occur among people when other deficits in cognition are present, such as in executive function, social cognition, and metacognition, which may either promote the development of both forms of poor insight or allow one to negatively influence the other. To explore this possibility, we conducted a cluster analysis using assessments of clinical and cognitive insight among 95 adults with a schizophrenia spectrum disorder. As predicted, this analysis yielded a group with concurrently poor clinical and cognitive insight (n = 36). Additional groups were found with concurrently good clinical and cognitive insight (n = 28) and poor clinical insight and good cognitive insight (n = 31). Groups were then compared on assessments of executive function, social cognition, and metacognition. The group with concurrently lower levels of cognitive and clinical insight had significantly poorer metacognition relative to the other groups. In particular, they tended to form more fragmented and less integrated ideas about themselves and others. No differences were found for executive function or social cognition. The result may suggest that while clinical and cognitive insight is partially orthogonal phenomena, relatively lower levels of metacognition, or difficulties forming integrated ideas about oneself and others, maybe a condition leading to the confluence of lower clinical and cognitive insight. Interventions targeting metacognition may be of particular use for this group.

Stages of recovery in psychosis: Converging qualitative research and psychoanalysis

PURPOSE

The purpose of this study is to find common points of view between the results of qualitative studies researching stages of the recovery process in persons with psychosis and mental changes in a therapeutic relationship in psychoanalytically oriented psychotherapy.

CONCLUSIONS

Both concepts correspond one to another. The added psychoanalytical perspective highlights milestones in psychic change: attainment of mental differentiation; integration of self together with the transformation of psychotic grandiosity into decentration, which implies responsibility for illness and own life.

PRACTICE IMPLICATIONS

These conclusions highlight the importance of supporting relationships for people suffering from psychoses.

Real-World Clinical Outcomes Two Years After Transition to Psychosis in Individuals at Clinical High Risk: Electronic Health Record Cohort Study

The objective of this study is to describe the 2-year real-world clinical outcomes after transition to psychosis in patients at clinical high-risk. The study used the clinical electronic health record cohort study including all patients receiving a first index primary diagnosis of nonorganic International Classification of Diseases (ICD)-10 psychotic disorder within the early psychosis pathway in the South London and Maudsley (SLaM) National Health Service (NHS) Trust from 2001 to 2017. Outcomes encompassed: cumulative probability (at 3, 6, 12, and 24 months) of receiving a first (1) treatment with antipsychotic, (2) informal admission, (3) compulsory admission, and (4) treatment with clozapine and (5) numbers of days spent in hospital (at 12 and 24 months) in patients transitioning to psychosis from clinical high-risk services (Outreach and Support in south London; OASIS) compared to other first-episode groups. Analyses included logistic and 0-inflated negative binomial regressions. In the study, 1561 patients were included; those who had initially been managed by OASIS and had subsequently transitioned to a first episode of psychosis (n = 130) were more likely to receive antipsychotic medication (at 3, 6, and 24 months; all P < .023), to be admitted informally (at all timepoints, all P < .004) and on a compulsory basis (at all timepoints, all P < .013), and to have spent more time in hospital (all timepoints, all P < .007) than first-episode patients who were already psychotic when seen by the OASIS service (n = 310), or presented to early intervention services (n = 1121). The likelihood of receiving clozapine was similar across all groups (at 12/24 months, all P < .101). Transition to psychosis from a clinical high-risk state is associated with severe real-world clinical outcomes. Prevention of transition to psychosis should remain a core target of future research. The study protocol was registered on www.researchregistry.com; researchregistry5039).