Designing mHealth Apps to Incorporate Evidence-Based Techniques for Prolonging User Engagement.

Maintaining user engagement with mobile health (mHealth) apps can be a challenge. Previously, we developed a conceptual model to optimize patient engagement in mHealth apps by incorporating multiple evidence-based methods, including increasing health literacy, enhancing technical competence, and improving feelings about participation in clinical trials. This viewpoint aims to report on a series of exploratory mini-experiments demonstrating the feasibility of testing our previously published engagement conceptual model. We collected data from 6 participants using an app that showed a series of educational videos and obtained additional data via questionnaires to illustrate and pilot the approach. The videos addressed 3 elements shown to relate to engagement in health care app use: increasing health literacy, enhancing technical competence, and improving positive feelings about participation in clinical trials. We measured changes in participants' knowledge and feelings, collected feedback on the videos and content, made revisions based on this feedback, and conducted participant reassessments. The findings support the feasibility of an iterative approach to creating and refining engagement enhancements in mHealth apps. Systematically identifying the key evidence-based elements intended to be included in an app's design and then systematically testing the implantation of each element separately until a satisfactory level of positive impact is achieved is feasible and should be incorporated into standard app design. While mHealth apps have shown promise, participants are more likely to drop out than to be retained. This viewpoint highlights the potential for mHealth researchers to test and refine mHealth apps using approaches to better engage users.

A New Approach to Enhancing Engagement in eHealth Apps.

This viewpoint presents a 3-phase conceptual model of the process of user engagement with eHealth apps. We also describe how knowledge gleaned from psychosocial, behavioral, and cognitive science can be incorporated into this model to enhance user engagement with an eHealth app in each phase of the engagement process.

Self-injurious behavior in the nursing home setting.

BACKGROUND: Self-injurious behavior (SIB) in older adults is defined as harm inflicted on oneself without conscious suicidal intent. SIB as a separate entity distinct from suicidal intent is poorly understood. However, it is of great concern to the patients' families and caregivers and it poses serious clinical challenges for clinicians. METHODS: We searched the database of PubMed, Ovid Medline, and ScienceDirect for reports published between 1970 and 2009 using combination of the following keywords: "self-injurious behavior", "self-destructive behavior", "self-mutilating behavior", "older adults", "geriatric population", and "nursing homes". The term "self-harm behavior" which also appears in the literature is broader in scope than "self-injurious behavior". It encompasses high suicide intent and failed suicide attempts; therefore, we excluded this term in order to focus purely on "self-injurious behavior". Our search yielded 10 publications concerning SIB in older adults, four of which included studies investigating SIB in nursing homes. RESULTS: Clinical studies of SIB in older adult nursing home residents are sparse. This limited literature suggests that SIB is a prevalent phenomenon and is reported to be as high as 14% in one study of nursing home subjects aged 65 and older. It is reported to be strongly associated with dementia and a risk of accidental death. It has been suggested that SIB among demented patients occurs in the context of poor impulse control and physical isolation. CONCLUSION: SIB is likely a common phenomenon in older adult nursing home residents. There is little evidence-based treatment guidance for SIB in older population.

A hypothesized role for dendritic remodeling in the etiology of mood and anxiety disorders.

An elegant theory that links hippocampal neurogenesis to mood and anxiety disorders and to the mechanism of action of antidepressant drugs has gained widespread attention. However, depression and anxiety disorders involve multiple areas of the brain, such as the amygdala and prefrontal cortex, where neurogenesis does not appear to occur in the adult mammalian brain. A complementary theory is proposed here in which neurogenesis is seen as an epiphenomenon of a more widespread alteration in dendritic length and spine number. According to this theory, exposure to chronic stress and stressful life events increases excitotoxic glutamatergic neurotransmission in multiple brain areas. To protect neurons from consequent apoptosis, dendrites retract and spine number decreases, thus limiting the number of exposed glutamate receptors. Drugs that reduce glutamatergic neurotransmission under these circumstances, many of which have already been shown helpful in treating mood and anxiety disorders, may prevent this dendritic retraction and thus protect synaptic connections throughout the brain.

Use of technology for care coordination initiatives for patients with mental health issues: a systematic literature review.

This systematic literature review investigates the use of technology for the coordination and management of mental health care with an emphasis on outcomes. Searches of MEDLINE/PubMed, Scopus, and EMBASE were conducted between January 1, 2003, and January 4, 2018, to identify articles that assessed patient outcomes associated with care coordination, evaluated technology to improve care, or discussed management of mental health care using technology. A total of 21 articles were included in a qualitative review based on the recommendations set forth by the PRISMA statement. Among the various health technologies, electronic health records were most commonly used for care coordination, with primary care being the most frequent setting. Care coordination was shown to provide easier patient access to health care providers and to improve communication between caregiver and patient, especially in cases where geographic location or distance is a challenge. Barriers to coordinated care included, but were not limited to, insufficient funding for health information technology, deficient reimbursement plans, limited access to technologies, cultural barriers, and underperforming electronic health record templates. In conclusion, many studies showed the benefit of coordinated and collaborative care through the use of technology; however, further research and development efforts are needed to continue technological innovation for advanced patient care.

Expert Consensus Survey on Digital Health Tools for Patients With Serious Mental Illness: Optimizing for User Characteristics and User Support.

BACKGROUND: Digital technology is increasingly being used to enhance health care in various areas of medicine. In the area of serious mental illness, it is important to understand the special characteristics of target users that may influence motivation and competence to use digital health tools, as well as the resources and training necessary for these patients to facilitate the use of this technology. OBJECTIVE: The aim of this study was to conduct a quantitative expert consensus survey to identify key characteristics of target users (patients and health care professionals), barriers and facilitators for appropriate use, and resources needed to optimize the use of digital health tools in patients with serious mental illness. METHODS: A panel of 40 experts in digital behavioral health who met the participation criteria completed a 19-question survey, rating predefined responses on a 9-point Likert scale. Consensus was determined using a chi-square test of score distributions across three ranges (1-3, 4-6, 7-9). Categorical ratings of first, second, or third line were designated based on the lowest category into which the CI of the mean ratings fell, with a boundary >6.5 for first line. Here, we report experts' responses to nine questions (265 options) that focused on (1) user characteristics that would promote or hinder the use of digital health tools, (2) potential benefits or motivators and barriers or unintended consequences of digital health tool use, and (3) support and training for patients and health care professionals. RESULTS: Among patient characteristics most likely to promote use of digital health tools, experts endorsed interest in using state-of-the-art technology, availability of necessary resources, good occupational functioning, and perception of the tool as beneficial. Certain disease-associated signs and symptoms (eg, more severe symptoms, substance abuse problems, and a chaotic living situation) were considered likely to make it difficult for patients to use digital health tools. Enthusiasm among health care professionals for digital health tools and availability of staff and equipment to support their use were identified as variables to enable health care professionals to successfully incorporate digital health tools into their practices. The experts identified a number of potential benefits of and barriers to use of digital health tools by patients and health care professionals. Experts agreed that both health care professionals and patients would need to be trained in the use of these new technologies. CONCLUSIONS: These results provide guidance to the mental health field on how to optimize the development and deployment of digital health tools for patients with serious mental illness.

Patient-based and clinician-based support for the remission criteria in schizophrenia.

This analysis characterizes patients with schizophrenia or schizoaffective disorder treated with risperidone who met remission criteria. In a 50-week, open-label trial, stable patients received long-acting injectable risperidone every 2 weeks. Remission criteria included severity (absent-mild ratings on core symptoms of the Positive and Negative Syndrome Scale) and duration (> or =6 months) components. The patients not remitted (severity component only) at baseline (n=394) are the subjects of this report. Measures applied included the PANSS, Clinical Global Impressions-Severity, patient-rated mental health status (Short Form-36), and Drug Attitude Inventory. Among patients who met remission criteria during the study (n=82), mean scores for all 30 PANSS items reflected absent-mild ratings at endpoint. The highest items represented an 'interpersonal' cluster, although mean ratings were still minimal to mild. Remitted patients experienced substantial improvements in Short Form-36 and Drug Attitude Inventory scores at endpoint. Although improvement occurred, it was less robust in patients who remained nonremitted (n=312). Logistic regression analysis found that remission (severity component only) was associated with a 97.1% probability of a 'not ill' rating on the Clinical Global Impressions-Severity. These remission criteria identified patients who differed from the nonremitted population on symptoms of psychopathology, medication attitude, health status, and overall clinical status, supporting the clinical validity of the remission criteria.

Why do psychiatric patients stop antipsychotic medication? A systematic review of reasons for nonadherence to medication in patients with serious mental illness.

BACKGROUND: Antipsychotic medication reduces the severity of serious mental illness (SMI) and improves patient outcomes only when medicines were taken as prescribed. Nonadherence to the treatment of SMI increases the risk of relapse and hospitalization and reduces the quality of life. It is necessary to understand the factors influencing nonadherence to medication in order to identify appropriate interventions. This systematic review assessed the published evidence on modifiable reasons for nonadherence to antipsychotic medication in patients with SMI. METHODS: Articles published between January 1, 2005, and September 10, 2015, were searched on MEDLINE through PubMed. Abstracts were independently screened by 2 randomly assigned authors for inclusion, and disagreement was resolved by another author. Selected full-text articles were divided among all authors for review. RESULTS: A qualitative analysis of data from 36 articles identified 11 categories of reasons for nonadherence. Poor insight was identified as a reason for nonadherence in 55.6% (20/36) of studies, followed by substance abuse (36.1%, 13/36), a negative attitude toward medication (30.5%, 11/36), medication side effects (27.8%, 10/36), and cognitive impairments (13.4%, 7/36). A key reason directly associated with intentional nonadherence was a negative attitude toward medication, a mediator of effects of insight and therapeutic alliance. Substance abuse was the only reason consistently associated with unintentional nonadherence, regardless of type and stage of SMI. DISCUSSION: Although adherence research is inherently biased because of numerous methodological limitations and specific reasons under investigation, reasons for nonadherence consistently identified as significant across studies likely reflect valid existing associations with important clinical implications. CONCLUSION: This systematic review suggests that a negative attitude toward medication and substance abuse are consistent reasons for nonadherence to antipsychotic medication among people with SMI. Adherence enhancement approaches that specifically target these reasons may improve adherence in a high-risk group. However, it is also important to identify drivers of poor adherence specific to each patient in selecting and implementing intervention strategies.

Expert Consensus Survey on Medication Adherence in Psychiatric Patients and Use of a Digital Medicine System.

BACKGROUND: There is an unmet need to objectively assess adherence problems that are a common cause of unexplained or unexpected suboptimal outcome. A digital medicine system (DMS) has been developed to address this need in patients with serious mental illness. OBJECTIVE: To conduct a quantitative expert consensus survey to (1) assess relative importance of causes of suboptimal outcomes, (2) examine modalities used to assess adherence, (3) provide guidance on when and how to use the DMS in clinical practice once available, and (4) suggest interventions for specific reasons for nonadherence. METHODS: A panel of 58 experts in psychiatry completed a 23-question survey (October 13 through December 23, 2013) and rated their responses on a 9-point Likert scale. A χ² test of score distributions was used to determine consensus (P < .05). RESULTS: The panel rated adherence as the most important factor in suboptimal outcomes and yet the least likely to be assessed accurately. All predefined uses of the DMS received high mean first-line ratings (≥ 7.4). The experts recognized the utility of the DMS in managing adherence problems, identified clinical situations appropriate for DMS, and assessed potential benefits and challenges of this technology. Consensus was reached on first-line interventions for 10 of 11 reasons for nonadherence. CONCLUSIONS: The results provide a guide to clinicians on the evaluation of suboptimal outcomes, when and how to use the DMS, and the most appropriate interventions to address detected adherence problems.

Predicting Future High-Cost Schizophrenia Patients Using High-Dimensional Administrative Data.

BACKGROUND: The burden of serious and persistent mental illness such as schizophrenia is substantial and requires health-care organizations to have adequate risk adjustment models to effectively allocate their resources to managing patients who are at the greatest risk. Currently available models underestimate health-care costs for those with mental or behavioral health conditions. OBJECTIVES: The study aimed to develop and evaluate predictive models for identification of future high-cost schizophrenia patients using advanced supervised machine learning methods. METHODS: This was a retrospective study using a payer administrative database. The study cohort consisted of 97,862 patients diagnosed with schizophrenia (ICD9 code 295.*) from January 2009 to June 2014. Training (n = 34,510) and study evaluation (n = 30,077) cohorts were derived based on 12-month observation and prediction windows (PWs). The target was average total cost/patient/month in the PW. Three models (baseline, intermediate, final) were developed to assess the value of different variable categories for cost prediction (demographics, coverage, cost, health-care utilization, antipsychotic medication usage, and clinical conditions). Scalable orthogonal regression, significant attribute selection in high dimensions method, and random forests regression were used to develop the models. The trained models were assessed in the evaluation cohort using the regression R2, patient classification accuracy (PCA), and cost accuracy (CA). The model performance was compared to the Centers for Medicare & Medicaid Services Hierarchical Condition Categories (CMS-HCC) model. RESULTS: At top 10% cost cutoff, the final model achieved 0.23 R2, 43% PCA, and 63% CA; in contrast, the CMS-HCC model achieved 0.09 R2, 27% PCA with 45% CA. The final model and the CMS-HCC model identified 33 and 22%, respectively, of total cost at the top 10% cost cutoff. CONCLUSION: Using advanced feature selection leveraging detailed health care, medication utilization features, and supervised machine learning methods improved the ability to predict and identify future high-cost patients with schizophrenia when compared with the CMS-HCC model.

Integrated multisystem analysis in a mental health and criminal justice ecosystem.

BACKGROUND: Patients with a serious mental illness often receive care that is fragmented due to reduced availability of or access to resources, and inadequate, discontinuous, and uncoordinated care across health, social services, and criminal justice organizations. This article describes the creation of a multisystem analysis that derives insights from an integrated dataset including patient access to case management services, medical services, and interactions with the criminal justice system. METHODS: Data were combined from electronic systems within a US mental health ecosystem that included mental health and substance abuse services, as well as data from the criminal justice system. Cox models were applied to test the associations between delivery of services and re-incarceration. Additionally, machine learning was used to train and validate a predictive model to examine effects of non-modifiable risk factors (age, past arrests, mental health diagnosis) and modifiable risk factors (outpatient, medical and case management services, and use of a jail diversion program) on re-arrest outcome. RESULTS: An association was found between past arrests and admission to crisis stabilization services in this population (N = 10,307). Delivery of case management or medical services provided after release from jail was associated with a reduced risk for re-arrest. Predictive models linked non-modifiable and modifiable risk factors and outcomes and predicted the probability of re-arrests with fair accuracy (area under the receiver operating characteristic curve of 0.67). CONCLUSIONS: By modeling the complex interactions between risk factors, service delivery, and outcomes, systems of care might be better enabled to meet patient needs and improve outcomes.

Optimization of a Digital Medicine System in Psychiatry.

BACKGROUND: Nonadherence to medication compromises the effectiveness of psychiatric treatments in patients with serious mental illness (SMI). A newly developed digital medicine system (DMS) offers an opportunity to objectively assess and report patient medication adherence. DMS includes a wearable sensor that receives a data signal from a medication tablet with an embedded ingestible sensor after ingestion of the medication and transmits that data to the patient's mobile device to display health care information for the patient and treatment team. METHODS/RESULTS: Development of a DMS requires a program that investigates safety, tolerability, and usability of the system in patients with SMI. It necessitates rapid design adaptation of the individual components and the integrated system and human factors studies with the intended users. This article describes the program's methodology and shows results from 3 early studies, conducted in 2013 and 2014, to illustrate diversity of the programs' methodology. First, a standard 28-day study showed minimal skin irritation and demonstrated acceptable wearability of the wearable sensor. Second, a 16-week study provided usability feedback from patients with SMI and caregivers to improve the mobile application. Third, end-to-end bench-level integrated system testing led to multiple substudies of a master protocol (ClinicalTrials.gov identifier: NCT02091882) to investigate various aspects of the system (eg, ingestible sensor detection and latency). CONCLUSIONS: To develop a DMS in psychiatry, the system's multiple components must be considered simultaneously using various methodologies. A focus on usability, along with agile evaluation and feedback across studies, provides an optimal strategy for ensuring patient acceptance and successful regulatory review.

Developing a Digital Medicine System in Psychiatry: Ingestion Detection Rate and Latency Period.

BACKGROUND: A digital medicine system (DMS) has been developed to measure and report adherence to an atypical antipsychotic, aripiprazole, in psychiatric patients. The DMS consists of 3 components: ingestible sensor embedded in a medication tablet, wearable sensor, and secure mobile and cloud-based applications. An umbrella study protocol was designed to rapidly assess the technical performance and safety of the DMS in multiple substudies to guide the technology development. METHODS: Two sequential substudies enrolled 30 and 29 healthy volunteers between March-April 2014 and February-March 2015, respectively, to assess detection accuracy of the ingestible sensor by the DMS and the latency period between ingestion and detection of the ingestion by the wearable sensor or the cloud-based server. RESULTS: The first substudy identified areas for improvement using early versions of the wearable sensor and the mobile application. The second substudy tested updated versions of the components and showed an overall ingestion detection rate of 96.6%. Mean latency times for the signal transmission were 1.1-1.3 minutes (from ingestion to the wearable sensor detection) and 6.2-10.3 minutes (from the wearable sensor detection to the server detection). Half of transmissions were completed in < 2 minutes, and ~90% of ingestions were registered by the smartphone within 30 minutes of ingestion. No serious adverse events, discontinuations, or clinically significant laboratory/vital signs findings were reported. CONCLUSIONS: The DMS implementing modified versions of the smartphone application and the wearable sensor has the technical capability to detect and report tablet ingestion with high accuracy and acceptable latency time. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02091882.

Usability of a novel digital medicine system in adults with schizophrenia treated with sensor-embedded tablets of aripiprazole.

OBJECTIVE: Digital medicine system (DMS) is a novel drug-device combination that objectively measures and reports medication ingestion. The DMS consists of medication embedded with an ingestible sensor (digital medicine), a wearable sensor, and software applications. This study evaluated usability of the DMS in adults with schizophrenia rated by both patients and their health care providers (HCPs) during 8-week treatment with prescribed doses of digital aripiprazole. METHODS: Six US sites enrolled outpatients into this Phase IIa, open-label study (NCT02219009). The study comprised a screening phase, a training phase (three weekly site visits), and a 5-week independent phase. Patients and HCPs independently rated usability of and satisfaction with the DMS. RESULTS: Sixty-seven patients were enrolled, and 49 (73.1%) patients completed the study. The mean age (SD) of the patients was 46.6 years (9.7 years); the majority of them were male (74.6%), black (76.1%), and rated mildly ill on the Clinical Global Impression - Severity scale (70.1%). By the end of week 8 or early termination, 82.1% (55/67) of patients had replaced the wearable sensor independently or with minimal assistance, based on HCP rating. The patients used the wearable sensor for a mean (SD) of 70.7% (24.7%) and a median of 77.8% of their time in the trial. The patients contacted a call center most frequently at week 1. At the last visit, 78% (47/60) of patients were somewhat satisfied/satisfied/extremely satisfied with the DMS. CONCLUSION: A high proportion of patients with schizophrenia were able to use the DMS and reported satisfaction with the DMS. These data support the potential utility of the DMS in clinical practice.

The expert consensus guideline series. Treatment of behavioral emergencies 2005.

OBJECTIVES: Due to inherent dangers and barriers to research in emergency settings, few data are available to guide clinicians about how best to manage behavioral emergencies. Key constructs such as agitation are poorly defined. This lack of empirical data led us to undertake a survey of expert opinion, results of which were published in the 2001 Expert Consensus Guidelines on the Treatment of Behavioral Emergencies. Several second-generation (atypical) antipsychotics (SGAs) are now available in new formulations for treating behavioral emergencies (e.g., intramuscular [i.m.] olanzapine and ziprasidone; rapidly dissolving tablets of olanzapine and risperidone). Critical questions face the field. The SGAs are significantly different from the FGAs and from each other and have not been studied in unselected patients as were the FGAs. Can the SGAs can be thought of as a class, do all antipsychotics have similar anti-agitation effects in different conditions, and, if equally effective, what limits might their safety profiles impose? Should antipsychotics be used more specifically to treat psychotic conditions, while benzodiazepines (BNZs) alone are used nonspecifically? Few data are available concerning combinations of SGAs and BNZs, and findings concerning the traditional combination of haloperidol plus a BNZ may not be relevant to combinations with SGAs. The culture is also evolving with more emphasis on patient involvement in treatment decisions. An international consensus has been developing that calming rather than sedation is the appropriate endpoint of behavioral emergency interventions. We undertook a new survey of expert opinion to update recommendations from the earlier survey. METHOD: A written survey of 61 questions (1,020 options) was mailed to 50 experts in the field, 48 (96%) of whom completed it. The survey sought to define level of agitation at which emergency interventions are appropriate, scope of assessment depending on urgency and patients' ability to cooperate, guiding principles for selecting interventions, and appropriate physical and medication strategies at different levels of diagnostic confidence for a variety of provisional diagnoses and complicating conditions. A modified version of the RAND Corporation's 9-point scale for rating appropriateness of medical decisions was used to score most options. Consensus was defined as a non-random distribution of scores by chi-square "goodness-of-fit" test. We assigned a categorical rank (first line/preferred, second line/alternate, third line/usually inappropriate) to each option based on the 95% confidence interval around the mean. Ratings were used to develop guidelines for preferred strategies in key clinical situations. This study received financial support from multiple sponsors, with the panel kept blind to sponsorship to reduce possible bias. Medication ratings were based on responses of only those respondents with direct experience with each drug. In reporting practice patterns, the panel was asked to respond based on actual data rather than estimates. RESULTS: The expert panel reached consensus on 78% of the options rated on the 9-point scale. The responses suggest that physicians can make provisional diagnoses with some confidence and that pharmacological and nonpharmacological interventions are selected differentially based on diagnosis and other salient demographic and medical features. BNZs are recommended when no data are available, when there is no specific treatment (e.g., personality disorder), or when they may have specific benefits (e.g., intoxication). No single SGA emerges as a nonspecific replacement for haloperidol; instead, different SGAs are preferred in various circumstances consistent with current evidence. To the degree that haloperidol is recommended, it is almost always in combination with a BNZ; haloperidol alone is preferred only in the medically compromised. In contrast, the SGAs are more often recommended for use alone, and the panel would avoid combining BNZs with some SGAs. Oral risperidone alone or combined with a BNZ receives strong support in a variety of situations. Oral olanzapine was rated very similarly to risperidone, with slightly higher ratings than risperidone in situations where it has been studied (e.g., schizophrenia, mania) and slightly lower ratings where it has not been studied or safety may be a concern; there was less support for combining oral olanzapine with a BNZ. For oral treatment of agitation related to schizophrenia or mania, olanzapine alone, risperidone alone or combined with a BNZ, and haloperidol plus a BNZ are first line, with strong support also for combining divalproex with the antipsychotic for presumed mania. Oral ziprasidone and quetiapine generally received similar second-line ratings in most situations. If a parenteral agent is needed, i.m. olanzapine alone received somewhat more support than i.m. ziprasidone alone; however, there was more support for i.m. ziprasidone alone or combined with a BNZ than for i.m. olanzapine plus a BNZ, probably reflecting safety concerns. For example, for a provisional diagnosis of schizophrenia, first-line parenteral options are i.m. olanzapine or ziprasidone alone or i.m. haloperidol or ziprasidone combined with a BNZ. Neither of the new parenteral formulations received as much support as traditional agents (i.m. BNZs, i.m. haloperidol) when no data are available or the diagnosis involves medical comorbidity or intoxication. When initial intervention with risperidone, ziprasidone, or haloperidol is unsuccessful, the panel recommended adding a BZD to the antipsychotic. However, when initial treatment with olanzapine or quetiapine is unsuccessful, increasing the dosage is recommended. Perphenazine was consistently rated second line and droperidol and chlorpromazine received third-line ratings throughout. CONCLUSIONS: Within the limits of expert opinion and with the expectation that future research data will take precedence, these guidelines suggest that the SGAs are now preferred for agitation in the setting of primary psychiatric illnesses but that BNZs are preferred in other situations.

A double-blind, placebo-controlled, exploratory trial of chromium picolinate in atypical depression: effect on carbohydrate craving.

BACKGROUND: : In a small pilot trial, patients with atypical depression demonstrated significant positive therapeutic response to chromium picolinate. This finding is of interest because of the demonstrated link between depression, decreased insulin sensitivity, and subsequent diabetes and chromium picolinate's insulin enhancing effect. METHODS: : In this double-blind, multicenter, 8-week replication study, 113 adult outpatients with atypical depression were randomized 2:1 to receive 600 mug/day of elemental chromium, as provided by chromium picolinate (CrPic), or placebo. Primary efficacy measures were the 29-item Hamilton Depression Rating Scale (HAM-D-29) and the Clinical Global Impressions Improvement Scale (CGI-I). RESULTS: : Of the 113 randomized patients, 110 (70 CrPic, 40 placebo) constituted the intent-to-treat (ITT) population (i.e., received at least one dose of study medication and completed at least one efficacy evaluation) and 75 (50 CrPic, 25 placebo) were evaluable (i.e., took at least 80% of study drug with no significant protocol deviations). In the evaluable population, mean age was 46 years, 69% were female, 81% were Caucasian, and mean body mass index (BMI) was 29.7. There was no significant difference between the CrPic and placebo groups in both the ITT and evaluable populations on the primary efficacy measures, with both groups showing significant improvement from baseline on total HAM-D-29 scores during the course of treatment (p < 0.0001). However, in the evaluable population, the CrPic group showed significant improvements from baseline compared with the placebo group on 4 HAM-D-29 items: appetite increase, increased eating, carbohydrate craving, and diurnal variation of feelings. A supplemental analysis of data from the subset of 41 patients in the ITT population with high carbohydrate craving (26 CrPic, 15 placebo; mean BMI = 31.1) showed that the CrPic patients had significantly greater response on total HAM-D-29 scores than the placebo group (65% vs. 33%; p < 0.05) as well as significantly greater improvements on the following HAM-D-29 items: appetite increase, increased eating, carbohydrate craving, and genital symptoms (e.g., level of libido). Chromium treatment was well-tolerated. LIMITATIONS: : The study did not include a placebo run-in period, did not require minimum duration or severity of depression, and enrolled patients with major depression, dysthymia, or depression NOS. CONCLUSIONS: : In a population of adults with atypical depression, most of whom were overweight or obese, CrPic produced improvement on the following HAM-D-29 items: appetite increase, increased eating, carbohydrate craving, and diurnal variation of feelings. In a subpopulation of patients with high carbohydrate craving, overall HAM-D-29 scores improved significantly in patients treated with CrPic compared with placebo. The results of this study suggest that the main effect of chromium was on carbohydrate craving and appetite regulation in depressed patients and that 600 mug of elemental chromium may be beneficial for patients with atypical depression who also have severe carbohydrate craving. Further studies are needed to evaluate chromium in depressed patients specifically selected for symptoms of increased appetite and carbohydrate craving as well as to determine whether a higher dose of chromium would have an effect on mood.

The expert consensus guideline series. Treatment of dementia and its behavioral disturbances. Introduction: methods, commentary, and summary.

OBJECTIVES: New treatment options for dementia and its behavioral disturbances have become available since publication of The Expert Consensus Guidelines on the Treatment of Agitation in Older Persons with Dementia in 1998. While only 2 cholinesterase inhibitors, donepezil and tacrine, were available in 1998, 3 new cognitive-enhancing agents have been introduced since that time as well as several new atypical antipsychotics and antidepressants. However, there are still limited data from controlled studies to guide clinicians in choosing among these agents and sequencing and combining treatments. We therefore conducted a new survey study of expert opinion on the treatment of cognitive impairment and behavioral disturbances associated with dementia. METHODS: Based on a literature review, a 61-question survey was developed with 1,225 options. Most options were scored using a modified version of the RAND 9-point scale for rating appropriateness of medical decisions. For other options, the experts were asked to write in answers. The survey was sent to 50 North American experts on dementia, 100% of whom completed it. In analyzing responses to items rated on the 9-point scale, consensus was defined as a nonrandom distribution of scores by chi-square "goodness-of-fit" test. Based on the 95% confidence interval around the mean, we assigned a categorical rank (first line/preferred, second line/alternate, third line/usually inappropriate) to each option. Guidelines indicating preferred treatment strategies were then developed for selected clinical situations. RESULTS: For patients at risk for dementia, the experts recommended control of hypertension and diabetes. They also recommended aspirin and would consider a lipid-lowering agent in patients at risk for vascular dementia. Cholinesterase inhibitors were an option for patients with mild cognitive impairment (i.e., at risk for Alzheimer's dementia [AD]). To slow cognitive impairment in mild/moderate AD, the experts recommended a cholinesterase inhibitor alone or combined with vitamin E. Donepezil and galantamine were the preferred cholinesterase inhibitors. The experts recommended combining a cholinesterase inhibitor with a N-methyl-D-aspartate (NMDA) antagonist (e.g., memantine) if a patient with mild/moderate dementia has an inadequate response to monotherapy. Control of hypertension and diabetes was the treatment of choice, in patients with mild/moderate vascular or mixed AD/vascular dementia, with aspirin another first-line option. Cholinesterase inhibitors were also a first-line option for mild/moderate mixed AD/vascular dementia. Among nonpharmacological interventions for mild/moderate dementia, the experts recommended caregiver education, supportive therapy for caregivers, referral to day treatment, exercise programs, and respite care. For moderate/severe AD or mixed AD/vascular dementia, the experts recommended combining an NMDA antagonist with a cholinesterase inhibitor. For moderate/severe vascular or mixed AD/vascular dementia, they recommended control of hypertension and diabetes. The experts' ratings underscore the importance of nonpharmacological strategies aimed at reducing caregiver burden in more severe dementia. Management of agitation and other behavioral disturbances was another focus of this study. The experts recommended using an atypical antipsychotic for agitation associated with delirium, psychosis, aggression, or anger. They would also consider divalproex to manage anger with a risk of physical aggression. Selective serotonin reuptake inhibitors were recommended for the treatment of depression or anxiety in patients with dementia. Benzodiazepines or atypical antipsychotics were viewed as short-term options for acute anxiety. Trazodone was recommended for insomnia. The experts also gave recommendations concerning dosage levels, duration of treatment, and choice of medications for patients with different complicating conditions. CONCLUSIONS: The experts reached high levels of consensus on key steps in treating dementia and associated behavioral disturbances. Within the limits of expert opinion and with the expectation that new research data will take precedence, these guidelines may provide direction for clinicians offering care to patients with dementia.

The expert consensus guideline series. Optimizing pharmacologic treatment of psychotic disorders. Introduction: methods, commentary, and summary.

OBJECTIVES: A growing number of atypical antipsychotics are available for clinicians to choose from in the treatment of psychotic disorders. However, a number of important questions concerning medication selection, dosing and dose equivalence, and the management of inadequate response, compliance problems, and relapse have not been adequately addressed by clinical trials. To aid clinical decision-making, a consensus survey of expert opinion on the pharmacologic treatment of psychotic disorders was undertaken to address questions not definitively answered in the research literature. METHOD: Based on a literature review, a written survey was developed with 60 questions and 994 options. Approximately half of the options were scored using a modified version of the RAND 9-point scale for rating the appropriateness of medical decisions. For the other options, the experts were asked to write in answers (e.g., average doses) or check a box to indicate their preferred answer. The survey was sent to 50 national experts on the pharmacologic treatment of psychotic disorders, 47 (94%) of whom completed it. In analyzing the responses to items rated on the 9-point scale, consensus on each option was defined as a non random distribution of scores by chi-square "goodness-of-fit"test. We assigned a categorical rank (first line/preferred choice,second line/alternate choice, third line/usually inappropriate) to each option based on the 95% confidence interval around the mean rating. Guideline tables indicating preferred treatment strategies were then developed for key clinical situations. RESULTS: The expert panel reached consensus on 88% of the options rated on the 9-point scale. The experts overwhelmingly endorsed the atypical antipsychotics for the treatment of psychotic disorders. Risperidone was the top choice for first-episode and multi-episode patients, with the other newer atypicals rated first line or high second line depending on the clinical situation. Clozapine and a long-acting injectable atypical (when available)were other high second line options for multi-episode patients. The expert's dosing recommendations agreed closely with the package inserts for the drugs, and their estimates of dose equivalence among the antipsychotics followed a linear pattern. The experts considered 3-6 weeks an adequate antipsychotic trial, but would wait a little longer (4-10 weeks) before making a major change in treatment regimen if there is a partial response. The experts recommended trying to improve response by increasing the dose of atypical and depot antipsychotics before switching to a different agent; there was less agreement about increasing the dose of conventional antipsychotics before switching, probably because of concern about side effects at higher doses. If it is decided to switch because of inadequate response, risperidone was the expert's first choice to switch to, no matter what drug was initially tried. Although there was some disparity in the expert's recommendations concerning how many agents to try before switching to clozapine, the expert's responses suggest that switching to clozapine should be Clozapine was also the antipsychotic of choice for patients with suicidal behavior. When switching oral antipsychotics,the experts considered cross-titration the preferred strategy. When switching to an injectable antipsychotic, the experts stressed the importance of continuing the oral antipsychotic until therapeutic levels of the injectable agent are achieved. The experts considered psychosocial interventions the first choice strategy for partially compliant patients, with pharmacologic interventions the first choice for patients with clear evidence of noncompliance. However, because it can be difficult to distinguish partially compliant from noncompliant patients, the editors recommended combining psychosocial and pharmacologic interventions to improve compliance whenever possible. When patients relapse because of compliance problems or if there is any doubt about compliance, the experts recommended the use of a long-acting injectable antipsychotic and would select an injectable atypical when this option becomes available. The experts would also consider using an injectable atypical antipsychotic (when available) in many clinical situations that do not involve compliance problems. The experts stressed the importance of monitoring for health problems-especially obesity, diabetes, cardiovascular problems,HIV risk behaviors, medical complications of substance abuse, heavy smoking and its effects, hypertension, and amenorrhea-in patients being treated with antipsychotics. Although many patients are prescribed adjunctive treatments,multiple antipsychotics, and combinations of different classes of drugs (e.g., antipsychotics plus mood stabilizers or antidepressants) in an effort to enhance response, the experts gave little support to any of these strategies, with the exception of antidepressants for patients with dysphoria/depression, antidepressants or ECT for patients with suicidal behavior, and mood stabilizers for patients with aggression/violence. When asked about indicators of remission and recovery, the experts considered acute improvement in psychotic symptoms the most important indicator of remission, whereas they considered more sustained improvement in multiple outcome domains (e.g., occupational/educational functioning, peer relationships,independent living) important in assessing recovery. CONCLUSIONS: The experts reached a high level of consensus on many of the key treatment questions in the survey. Within the limits of expert opinion and with the expectation that future research data will take precedence, these guidelines provide direction for addressing common clinical dilemmas that arise in the pharmacologic treatment of psychotic disorders. They can be used to inform clinicians and educate patients regarding the relative merits of a variety of interventions. Clinicians should keep in mind that no guidelines can address the complexities involved in the care of each individual patient and that sound clinical judgment based on clinical experience should be used in applying these recommendations.

Using antipsychotic agents in older patients.

OBJECTIVES: Antipsychotics are widely used in geriatric psychiatric disorders. A growing number of atypical antipsychotics are available, expanding clinical options but complicating decision-making. Many questions about use of antipsychotics in older patients remain unanswered by available clinical literature. We therefore surveyed expert opinion on antipsychotic use in older patients (65 years of age or older) for recommendations concerning indications for antipsychotics, choice of antipsychotics for different conditions (e.g., delirium, dementia, schizophrenia, delusional disorder, psychotic mood disorders) and for patients with comorbid conditions or history of side effects, dosing strategies, duration of treatment, and medication combinations. METHOD: Based on a literature review, a 47-question survey with 1,411 options was developed. Approximately three quarters of the options were scored using a modified version of the RAND 9-point scale for rating appropriateness of medical decisions. For other options, experts were asked to write in answers. The survey was sent to 52 American experts on treatment of older adults (38 geriatric psychiatrists, 14 geriatric internists/family physicians), 48 (92%) of whom completed it. In analyzing responses to items rated on the 9-point scale, consensus was defined as a nonrandom distribution of scores by chi-square "goodness-of-fit" test. We assigned a categorical rank (first line/preferred, second line/alternate, third line/usually inappropriate) to each option based on the 95% confidence interval around the mean. Guidelines indicating preferred treatment strategies were then developed for key clinical situations. RESULTS: The expert panel reached consensus on 78% of options rated on the 9-point scale. The experts did not recommend using antipsychotics in panic disorder, generalized anxiety disorder, nonpsychotic major depression, hypochondriasis, neuropathic pain, severe nausea, motion sickness, or irritability, hostility, and sleep disturbance in the absence of a major psychiatric syndrome. However, antipsychotics were favored in several other disorders. For agitated dementia with delusions, the experts' first-line recommendation is an antipsychotic drug alone; they would also consider adding a mood stabilizer. Risperidone (0.5-2.0 mg/day) was first line followed by quetiapine (50-150 mg/day) and olanzapine (5.0-7.5 mg/day) as high second-line options. There was no first-line recommendation for agitated dementia without delusions; an antipsychotic alone was high second line (rated first line by 60% of the experts). The experts'first-line recommendation for late-life schizophrenia was risperidone (1.25-3.5 mg/day). Quetiapine (100-300 mg/day), olanzapine (7.5-15 mg/day), and aripiprazole (15-30 mg/day) were high second line. For older patients with delusional disorder, an antipsychotic was the only treatment recommended. For agitated nonpsychotic major depression in an older patient, the experts' first-line recommendation was an antidepressant alone (77% first line); second-line options were an antidepressant plus an antipsychotic, electroconvulsive therapy (ECT), an antidepressant plus a benzodiazepine, and an antidepressant plus a mood stabilizer. For nonpsychotic major depression with severe anxiety, the experts recommended an antidepressant alone (79% first line) and would also consider adding a benzodiazepine or mood stabilizer to the antidepressant. If an older patient with adequate dosages for adequate duration, there was limited support for adding an atypical antipsychotic to the antidepressant (36% first line after two failed antidepressant trials). Treatment of choice for geriatric psychotic major depression was an antipsychotic plus an antidepressant (98% first line), with ECT another first-line option (71% first line). For mild geriatric nonpsychotic mania, the first-line recommendation is a mood stabilizer alone; the experts would also consider discontinuing an antidepressant if the patient is receiving one. For severe nonpsychotic mania, the experts recommend a mood stabilizer alone; the experts would also consider discontinuing an antidepressant if the patient is receiving one. For severe nonpsychotic mania, the experts recommend a mood stabilizer plus an antipsychotic (57%; first line) or a mood stabilizer alone (48%; first line) and would discontinue any antidepressant the patient is receiving. For psychotic mania, treatment of choice is a mood stabilizer plus an antipsychotic (98%; first line). Risperidone (1.25-3.0 mg/day) and olanzapine (5-15 mg/day) were first-line options in combination with a mood stabilizer for mania with psychosis, with quetiapine (50-250 mg/day) high second line. If a patient has responded well, the experts recommended the following duration of treatment before attempting to taper and discontinue the antipsychotic: delirium, 1 week; agitated dementia, taper within 3-6 months to determine the lowest effective maintenance dose; schizophrenia, indefinite treatment at the lowest effective dose; delusional disorder, 6 months-indefinitely at the lowest effective dose; psychotic major depression, 6 months; and mania with psychosis, 3 months. For patients with diabetes, dyslipidemia, or obesity, the experts would avoid clozapine, olanzapine, and conventional antipsychotics (especially low- and mid-potency). Quetiapine is first line for a patient with Parkinson's disease. Clozapine, ziprasidone, and conventional antipsychotics (especially low- and mid-potency) should be avoided in patients with QTc prolongation or congestive heart failure. For patients with cognitive impairment, constipation, diabetes, diabetic neuropathy, dyslipidemia, xerophthalmia, and xerostomia, the experts prefer risperidone, with quetiapine high second line. More than a quarter of the experts considered these combinations contraindicated: clozapine + carbamazepine, ziprasidone + tricyclic antidepressant (TCA), and a low-potency conventional antipsychotic + fluoxetine. In combining antidepressants and antipsychotics, the experts would be much more cautious with selective serotonin reuptake inhibitors that are more potent inhibitors of the CYP 450 enzymes (i.e., fluoxetine, fluvoxamine, paroxetine) and with nefazodone, TCAs, and monoamine oxidase inhibitors. The experts recommended extra monitoring when combining any antipsychotic with lithium, carbamazepine, lamotrigine, or valproate (except aripiprazole, risperidone, or a high-potency conventional plus valproate) or with codeine, phenytoin, or tramadol. CONCLUSIONS: The experts reached a high level of consensus on many of the key treatment questions. Within the limits of expert opinion and with the expectation that future research data will take precedence, these guidelines provide direction for common clinical dilemmas in the use of antipsychotics in elderly patients. Clinicians should keep in mind that no guidelines can address the complexities of an individual patient and that sound clinical judgment based on clinical experience should be used in applying these recommendations.