Who\u27s your expert? Use of an expert opinion survey to inform development of American Psychiatric Association practice guidelines.

OBJECTIVE: For many clinical questions in psychiatry, high-quality evidence is lacking. Credible practice guidelines for such questions depend on transparent, reproducible, and valid methods for assessing expert opinion. The objective of this study was to develop and demonstrate the feasibility of a method for assessing expert opinion to aid in the development of practice guidelines by the American Psychiatric Association (APA). METHODS: A snowball process initially soliciting nominees from three sets of professional leaders was used to identify experts on a guideline topic (psychiatric evaluation). In a Web-based survey, the experts were asked to rate their level of agreement that specific assessments improve specific outcomes when they are included in an initial psychiatric evaluation. The experts were also asked about their own practice patterns with respect to the doing of the assessments. The main outcome measures are the following: number of nominated experts, number of experts who participated in the survey, and number and nature of quantitative and qualitative responses. RESULTS: The snowball process identified 1,738 experts, 784 (45 %) of whom participated in the opinion survey. Participants generally, but not always, agreed or strongly agreed that the assessments asked about would improve specified outcomes. Participants wrote 716 comments explaining why they might not typically include some assessments in an initial evaluation and 1,590 comments concerning other aspects of the topics under consideration. CONCLUSIONS: The snowball process based on initial solicitation of Psychiatry\u27s leaders produced a large expert panel. The Web-based survey systematically assessed the opinions of these experts on the utility of specific psychiatric assessments, providing useful information to substantiate opinion-based practice guidelines on how to conduct a psychiatric evaluation. The considerable engagement of respondents shows promise for using this methodology in developing future APA practice guidelines

An Integrated Process for Co-Developing and Implementing Written and Computable Clinical Practice Guidelines

The goal of this article is to describe an integrated parallel process for the co-development of written and computable clinical practice guidelines (CPGs) to accelerate adoption and increase the impact of guideline recommendations in clinical practice. From February 2018 through December 2021, interdisciplinary work groups were formed after an initial Kaizen event and using expert consensus and available literature, produced a 12-phase integrated process (IP). The IP includes activities, resources, and iterative feedback loops for developing, implementing, disseminating, communicating, and evaluating CPGs. The IP incorporates guideline standards and informatics practices and clarifies how informaticians, implementers, health communicators, evaluators, and clinicians can help guideline developers throughout the development and implementation cycle to effectively co-develop written and computable guidelines. More efficient processes are essential to create actionable CPGs, disseminate and communicate recommendations to clinical end users, and evaluate CPG performance. Pilot testing is underway to determine how this IP expedites the implementation of CPGs into clinical practice and improves guideline uptake and health outcomes

Twenty-year progression of body mass index in a county-wide cohort of people with schizophrenia and bipolar disorder identified at their first episode of psychosis

There is an increased prevalence of obesity in schizophrenia and bipolar disorder, leading to a disproportionate risk of adverse health conditions. Prospective, long-term weight gain data, however, are scarce. We analyzed data from the Suffolk County Mental Health Project cohort of consecutive first admissions with psychosis recruited from September 1989 to December 1995 and subsequently followed for 20 years, focusing on people with schizophrenia (n=146) and bipolar disorder (n=87). The time course of weight gain was examined using a 2 (group)×5 (time) mixed-model repeated measures ANOVA, and body mass index (BMI) scores at the first (6 months) and second (2 years) assessments were compared to examine whether early overweight predicted later obesity. There was a statistically significant effect of time (F(1,210)=68.06, P<.001) and diagnosis (F(1,210)=29.18, P<.001) on BMI, but not the interaction of time×diagnosis (F(1,210)=0.88, P=.48). Most participants had normal BMIs at the first two assessments. Early overweight was a predictor of eventual obesity for both groups. At the 20-year follow-ups, approximately 50% of the bipolar and 62% of the schizophrenia sample were obese, with a greater prevalence of obesity in schizophrenia at each assessment (all P<.02), except for years 4 (P=.12) and 20 (P=.27). Nearly two-thirds of the participants with schizophrenia and over half of those with bipolar disorder were obese 20 years after first hospitalization for psychosis, considerably higher than the rate for adults in New York State (27%). Early intervention may be required to prevent long-term consequences of obesity-related morbidity and mortality

Long-term Changes in Cognitive Functioning in Individuals with Psychotic Disorders:Findings from the Suffolk County Mental Health Project

Importance: It remains uncertain whether people with psychotic disorders experience progressive cognitive decline or normal cognitive aging after first hospitalization. This information is essential for prognostication in clinical settings, deployment of cognitive remediation, and public health policy. Objective: To examine long-term cognitive changes in individuals with psychotic disorders and to compare age-related differences in cognitive performance between people with psychotic disorders and matched control individuals (ie, individuals who had never had psychotic disorders). Design, Setting, and Participants: The Suffolk County Mental Health Project is an inception cohort study of first-admission patients with psychosis. Cognitive functioning was assessed 2 and 20 years later. Patients were recruited from the 12 inpatient facilities of Suffolk County, New York. At year 20, the control group was recruited by random digit dialing and matched to the clinical cohort on zip code and demographics. Data were collected between September 1991 and July 2015. Analysis began January 2016. Main Outcomes and Measures: Change in cognitive functioning in 6 domains: verbal knowledge (Wechsler Adult Intelligence Scale-Revised vocabulary test), verbal declarative memory (Verbal Paired Associates test I and II), visual declarative memory (Visual Reproduction test I and II), attention and processing speed (Symbol Digit Modalities Test-written and oral; Trail Making Test [TMT]-A), abstraction-executive function (Trenerry Stroop Color Word Test; TMT-B), and verbal fluency (Controlled Oral Word Association Test). Results: A total of 705 participants were included in the analyses (mean [SD] age at year 20, 49.4 [10.1] years): 445 individuals (63.1%) had psychotic disorders (211 with schizophrenia spectrum [138 (65%) male]; 164 with affective psychoses [76 (46%) male]; 70 with other psychoses [43 (61%) male]); and 260 individuals (36.9%) in the control group (50.5 [9.0] years; 134 [51.5%] male). Cognition in individuals with a psychotic disorder declined on all but 2 tests (average decline: d = 0.31; range, 0.17-0.54; all P <.001). Cognitive declines were associated with worsening vocational functioning (Visual Reproduction test II: r = 0.20; Symbol Digit Modalities Test-written: r = 0.25; Stroop: r = 0.24; P <.009) and worsening negative symptoms (avolition: Symbol Digit Modalities Test-written: r = -0.24; TMT-A: r = -0.21; Stroop: r = -0.21; all P <.009; inexpressivity: Stroop: r = -0.22; P <.009). Compared with control individuals, people with psychotic disrders showed age-dependent deficits in verbal knowledge, fluency, and abstraction-executive function (vocabulary: β = -0.32; Controlled Oral Word Association Test: β = -0.32; TMT-B: β = 0.23; all P <.05), with the largest gap among participants 50 years or older. Conclusions and Relevance: In individuals with psychotic disorders, most cognitive functions declined over 2 decades after first hospitalization. Observed declines were clinically significant. Some declines were larger than expected due to normal aging, suggesting that cognitive aging in some domains may be accelerated in this population. If confirmed, these findings would highlight cognition as an important target for research and treatment during later phases of psychotic illness

Boundaries of Schizoaffective Disorder: Revisiting Kraepelin

Importance Established nosology identifies schizoaffective disorder as a distinct category with boundaries separating it from mood disorders with psychosis and from schizophrenia. Alternative models argue for a single boundary distinguishing mood disorders with psychosis from schizophrenia (kraepelinian dichotomy) or a continuous spectrum from affective to nonaffective psychosis. Objective To identify natural boundaries within psychotic disorders by evaluating associations between symptom course and long-term outcome. Design, Setting, and Participants The Suffolk County Mental Health Project cohort consists of first-admission patients with psychosis recruited from all inpatient units of Suffolk County, New York (72% response rate). In an inception cohort design, participants were monitored closely for 4 years after admission, and their symptom course was charted for 526 individuals; 10-year outcome was obtained for 413. Main Outcomes and Measures Global Assessment of Functioning (GAF) and other consensus ratings of study psychiatrists. Results We used nonlinear modeling (locally weighted scatterplot smoothing and spline regression) to examine links between 4-year symptom variables (ratio of nonaffective psychosis to mood disturbance, duration of mania/hypomania, depression, and psychosis) and 10-year outcomes. Nonaffective psychosis ratio exhibited a sharp discontinuity—10 days or more of psychosis outside mood episodes predicted an 11-point decrement in GAF—consistent with the kraepelinian dichotomy. Duration of mania/hypomania showed 2 discontinuities demarcating 3 groups: mania absent, episodic mania, and chronic mania (manic/hypomanic \u3e1 year). The episodic group had a better outcome compared with the mania absent and chronic mania groups (12-point and 8-point difference on GAF). Duration of depression and psychosis had linear associations with worse outcome. Conclusions and Relevance Our data support the kraepelinian dichotomy, although the study requires replication. A boundary between schizoaffective disorder and schizophrenia was not observed, which casts further doubt on schizoaffective diagnosis. Co-occurring schizophrenia and mood disorder may be better coded as separate diagnoses, an approach that could simplify diagnosis, improve its reliability, and align it with the natural taxonomy. The delineation of schizophrenia (dementia praecox) and psychotic mood disorders (manic-depressive insanity) as 2 distinct entities was one of Emil Kraepelin’s seminal contributions to nosology.1 More than 100 years later, this kraepelinian dichotomy remains highly influential.2 However, some patients exhibit features of both schizophrenia and psychotic mood disorders, which led Kasanin3 to propose a new category labeled schizoaffective disorder. Conceptualization of this condition evolved across editions of the DSM from a subtype of schizophrenia to a distinct disorder. DSM-IV4 defines it as (A) co-occurrence of schizophrenia symptoms and mood episodes, (B) psychosis present for at least 2 weeks in the absence of mood symptoms, and (C) mood episodes present for a substantial portion of illness duration. Thus, DSM-IV elaborates on the kraepelinian dichotomy by adding an intermediate condition, with criterion B defining its boundary with psychotic mood disorder and criterion C with schizophrenia. The key to classifying these disorders is the ratio of nonaffective psychosis to mood disturbance: in psychotic mood disorder, nonaffective psychosis is absent; in schizoaffective disorder, both nonaffective psychosis and mood episodes are prominent; and in schizophrenia, nonaffective psychosis predominates. However, some have argued that these boundaries are artificial and that psychotic disorders fall along a continuous spectrum that ranges from psychotic mood disorder to schizophrenia.5,6 These conflicting accounts inspired a substantial body of literature that evaluated the validity of schizoaffective disorder using several basic approaches. Investigations of phenomenology found support for the continuum model,7 the kraepelinian 2-disorders model,8,9 and the DSM-IV 3-disorders model.10 Studies of neurobiological and cognitive functioning, as well as family and genetic research, reported evidence favoring the continuum7,11 and 3-disorders12-14 models. Longitudinal studies of illness course produced the most support for the continuum15,16 and 2-disorders8,17-20 models. Thus, to date, the literature is too conflicting to offer firm recommendations for nosology. Some of these inconsistencies likely result from changes in schizoaffective diagnosis, which was defined more broadly by earlier diagnostic manuals. Among diagnostic validators, illness course is of particular interest. Indeed, it was most central to Kraepelin’s work because he sought to develop diagnoses that would be prognostic of future symptoms and functioning (ie, global outcome).2Unfortunately, existing longitudinal studies were not designed to answer questions about the natural organization of psychotic disorders. They typically compared outcomes among diagnostic groups: schizophrenia, schizoaffective disorder, and psychotic mood disorder, but such analyses cannot distinguish gradual differences (ie, a continuum) from qualitative changes (ie, natural boundaries). Indeed, in many studies15,16 outcome of schizoaffective disorder fell between that of schizophrenia and psychotic mood disorder, which is consistent with both the continuum and 3-disorders models. Kendell and Brockington21 proposed a solution to this problem. They examined associations between the spectrum ranging from typical psychotic mood disorder to typical schizophrenia and continuous outcome measures. Their hypothesis was that a natural boundary would manifest as a significant drop in the outcome at some point along the spectrum, whereas a continuum would result in a linear decline. Kendell and Brockington found no evidence of a boundary, but their study was underpowered and analyses were limited to visual inspection of graphs.22 The latter shortcoming might explain why this technique has not been widely adopted. More recent developments in statistical methods23 make it possible to test such data for nonlinearity rigorously. The aim of the present study was to test for the existence of natural boundaries in psychotic disorders using modern statistical methods. We analyzed detailed symptom course data from an epidemiologic cohort of inpatients with psychosis monitored prospectively for 10 years after their first hospitalization. In particular, we examined links between nonaffective psychosis ratio during the first 4 years of the study and outcomes at year 10. The continuum model predicts a linear association, the kraepelinian model predicts a single boundary between psychotic mood disorder and the schizophrenia spectrum, and the DSM-IV model predicts 2 boundaries, one between psychotic mood disorder and schizoaffective disorder and another between schizoaffective disorder and schizophrenia (Supplement [eFigure 1]). In the latter 2 models, differences are expected between groups (eg, low nonaffective psychosis and high nonaffective psychosis), but no association is predicted between nonaffective psychosis and outcome within groups. We constructed statistical models to test these hypotheses. We also used this method to explore natural boundaries within depression and mania