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Interventions for the management of obesity in people with bipolar disorder.
BACKGROUND: Bipolar disorder is one of the most common serious mental illnesses, affecting approximately 60 million people worldwide. Characterised by extreme alterations in mood, cognition, and behaviour, bipolar disorder can have a significant negative impact on the functioning and quality of life of the affected individual. Compared with the general population, the prevalence of comorbid obesity is significantly higher in bipolar disorder. Approximately 68% of treatment seeking bipolar patients are overweight or obese. Clinicians are aware that obesity has the potential to contribute to other physical health conditions in people with bipolar disorder, including diabetes, hypertension, metabolic syndrome, cardiovascular disease, and coronary heart disease. Cardiovascular disease is the leading cause of premature death in bipolar disorder, happening a decade or more earlier than in the general population. Contributing factors include illness-related factors (mood-related factors, i.e. mania or depression), treatment-related factors (weight implications and other side effects of medications), and lifestyle factors (physical inactivity, poor diet, smoking, substance abuse). Approaches to the management of obesity in individuals with bipolar disorder are diverse and include non-pharmacological interventions (i.e. dietary, exercise, behavioural, or multi-component), pharmacological interventions (i.e. weight loss drugs or medication switching), and bariatric surgery. OBJECTIVES: To assess the effectiveness of interventions for the management of obesity in people with bipolar disorder. SEARCH METHODS: We searched the Cochrane Common Mental Disorders Controlled Trials Register (CCMDCTR) and the Cochrane Central Register for Controlled Trials (CENTRAL) to February 2019. We ran additional searches via Ovid databases including MEDLINE, Embase, and PsycInfo to May 2020. We searched the World Health Organization (WHO) trials portal (International Clinical Trials Registry Platform (ICTRP)) and ClinicalTrials.gov. We also checked the reference lists of all papers brought to full-text stage and all relevant systematic reviews. SELECTION CRITERIA: Randomised controlled trials (RCTs), randomised at the level of the individual or cluster, and cross-over designs of interventions for management of obesity, in which at least 80% of study participants had a clinical diagnosis of bipolar disorder and comorbid obesity (body mass index (BMI) ≥ 30 kg/m²), were eligible for inclusion. No exclusions were based on type of bipolar disorder, stage of illness, age, or gender. We included non-pharmacological interventions comprising dietary, exercise, behavioural, and multi-component interventions; pharmacological interventions consisting of weight loss medications and medication switching interventions; and surgical interventions such as gastric bypass, gastric bands, biliopancreatic diversion, and vertical banded gastroplasty. Comparators included the following approaches: dietary intervention versus inactive comparator; exercise intervention versus inactive comparator; behavioural intervention versus inactive comparator; multi-component lifestyle intervention versus inactive comparator; medication switching intervention versus inactive comparator; weight loss medication intervention versus inactive comparator; and surgical intervention versus inactive comparator. Primary outcomes of interest were changes in body mass, patient-reported adverse events, and quality of life. DATA COLLECTION AND ANALYSIS: Four review authors were involved in the process of selecting studies. Two review authors independently screened the titles and abstracts of studies identified in the search. Studies brought to the full-text stage were then screened by another two review authors working independently. However, none of the full-text studies met the inclusion criteria. Had we included studies, we would have assessed their methodological quality by using the criteria recommended in the Cochrane Handbook for Systematic Reviews of Interventions. We intended to combine dichotomous data using risk ratios (RRs), and continuous data using mean differences (MDs). For each outcome, we intended to calculate overall effect size with 95% confidence intervals (CIs). MAIN RESULTS: None of the studies that were screened met the inclusion criteria. AUTHORS' CONCLUSIONS: None of the studies that were assessed met the inclusion criteria of this review. Therefore we were unable to determine the effectiveness of interventions for the management of obesity in individuals with bipolar disorder. Given the extent and impact of the problem and the absence of evidence, this review highlights the need for research in this area. We suggest the need for RCTs that will focus only on populations with bipolar disorder and comorbid obesity. We identified several ongoing studies that may be included in the update of this review.
Smartphones in mental health: a critical review of background issues, current status and future concerns.
There has been increasing interest in the use of smartphone applications (apps) and other consumer technology in mental health care for a number of years. However, the vision of data from apps seamlessly returned to, and integrated in, the electronic medical record (EMR) to assist both psychiatrists and patients has not been widely achieved, due in part to complex issues involved in the use of smartphone and other consumer technology in psychiatry. These issues include consumer technology usage, clinical utility, commercialization, and evolving consumer technology. Technological, legal and commercial issues, as well as medical issues, will determine the role of consumer technology in psychiatry. Recommendations for a more productive direction for the use of consumer technology in psychiatry are provided.
Increasing Cybercrime Since the Pandemic: Concerns for Psychiatry.
PURPOSE OF REVIEW: Since the pandemic, the daily activities of many people occur at home. People connect to the Internet for work, school, shopping, entertainment, and doctor visits, including psychiatrists. Concurrently, cybercrime has surged worldwide. This narrative review examines the changing use of technology, societal impacts of the pandemic, how cybercrime is evolving, individual vulnerabilities to cybercrime, and special concerns for those with mental illness. RECENT FINDINGS: Human factors are a central component of cybersecurity as individual behaviors, personality traits, online activities, and attitudes to technology impact vulnerability. Mental illness may increase vulnerability to cybercrime. The risks of cybercrime should be recognized as victims experience long-term psychological and financial consequences. Patients with mental illness may not be aware of the dangers of cybercrime, of risky online behaviors, or the measures to mitigate risk. Technology provides powerful tools for psychiatry but technology must be used with the appropriate safety measures. Psychiatrists should be aware of the potential aftermath of cybercrime on mental health, and the increased patient risk since the pandemic, including from online mental health services. As a first step to increase patient awareness of cybercrime, psychiatrists should provide a recommended list of trusted sources that educate consumers on cybersecurity.
Internet of things issues related to psychiatry.
BACKGROUND: Internet of Things (IoT) devices for remote monitoring, diagnosis, and treatment are widely viewed as an important future direction for medicine, including for bipolar disorder and other mental illness. The number of smart, connected devices is expanding rapidly. IoT devices are being introduced in all aspects of everyday life, including devices in the home and wearables on the body. IoT devices are increasingly used in psychiatric research, and in the future may help to detect emotional reactions, mood states, stress, and cognitive abilities. This narrative review discusses some of the important fundamental issues related to the rapid growth of IoT devices. MAIN BODY: Articles were searched between December 2019 and February 2020. Topics discussed include background on the growth of IoT, the security, safety and privacy issues related to IoT devices, and the new roles in the IoT economy for manufacturers, patients, and healthcare organizations. CONCLUSIONS: The use of IoT devices will increase throughout psychiatry. The scale, complexity and passive nature of data collection with IoT devices presents unique challenges related to security, privacy and personal safety. While the IoT offers many potential benefits, there are risks associated with IoT devices, and from the connectivity between patients, healthcare providers, and device makers. Security, privacy and personal safety issues related to IoT devices are changing the roles of manufacturers, patients, physicians and healthcare IT organizations. Effective and safe use of IoT devices in psychiatry requires an understanding of these changes.
DSM-5 and ICD-11 criteria for bipolar disorder: Implications for the prevalence of bipolar disorder and validity of the diagnosis - A narrative review from the ECNP bipolar disorders network.
This narrative review summarizes and discusses the implications of the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 and the upcoming International Classification of Diseases (ICD)-11 classification systems on the prevalence of bipolar disorder and on the validity of the DSM-5 diagnosis of bipolar disorder according to the Robin and Guze criteria of diagnostic validity. Here we review and discuss current data on the prevalence of bipolar disorder diagnosed according to DSM-5 versus DSM-IV, and data on characteristics of bipolar disorder in the two diagnostic systems in relation to extended Robin and Guze criteria: 1) clinical presentation, 2) associations with para-clinical data such as brain imaging and blood-based biomarkers, 3) delimitation from other disorders, 4) associations with family history / genetics, 5) prognosis and long-term follow-up, and 6) treatment effects. The review highlights that few studies have investigated consequences for the prevalence of the diagnosis of bipolar disorder and for the validity of the diagnosis. Findings from these studies suggest a substantial decrease in the point prevalence of a diagnosis of bipolar with DSM-5 compared with DSM-IV, ranging from 30-50%, but a smaller decrease in the prevalence during lifetime, corresponding to a 6% reduction. It is concluded that it is likely that the use of DSM-5 and ICD-11 will result in diagnostic delay and delayed early intervention in bipolar disorder. Finally, we recommend areas for future research.
Lamotrigine Therapy for Bipolar Depression: Analysis of Self-Reported Patient Data.
BACKGROUND: Depression in people with bipolar disorder is a major cause of long-term disability, possibly leading to early mortality and currently, limited safe and effective therapies exist. Although existing monotherapies such as quetiapine have limited proven efficacy and practical tolerability, treatment combinations may lead to improved outcomes. Lamotrigine is an anticonvulsant currently licensed for the prevention of depressive relapses in individuals with bipolar disorder. A double-blinded randomized placebo-controlled trial (comparative evaluation of Quetiapine-Lamotrigine [CEQUEL] study) was conducted to evaluate the efficacy of lamotrigine plus quetiapine versus quetiapine monotherapy in patients with bipolar type I or type II disorders. OBJECTIVE: Because the original CEQUEL study found significant depressive symptom improvements, the objective of this study was to reanalyze CEQUEL data and determine an unbiased classification accuracy for active lamotrigine versus placebo. We also wanted to establish the time it took for the drug to provide statistically significant outcomes. METHODS: Between October 21, 2008 and April 27, 2012, 202 participants from 27 sites in United Kingdom were randomly assigned to two treatments; 101: lamotrigine, 101: placebo. The primary variable used for estimating depressive symptoms was based on the Quick Inventory of Depressive Symptomatology-self report version 16 (QIDS-SR16). The original CEQUEL study findings were confirmed by performing t test and linear regression. Multiple features were computed from the QIDS-SR16 time series; different linear and nonlinear binary classifiers were trained to distinguish between the two groups. Various feature-selection techniques were used to select a feature set with the greatest explanatory power; a 10-fold cross-validation was used. RESULTS: From weeks 10 to 14, the mean difference in QIDS-SR16 ratings between the groups was -1.6317 (P=.09; sample size=81, 77; 95% CI -0.2403 to 3.5036). From weeks 48 to 52, the mean difference was -2.0032 (P=.09; sample size=54, 48; 95% CI -0.3433 to 4.3497). The coefficient of variation (σ/μ) and detrended fluctuation analysis (DFA) exponent alpha had the greatest explanatory power. The out-of-sample classification accuracy for the 138 participants who reported more than 10 times after week 12 was 62%. A consistent classification accuracy higher than the no-information benchmark was obtained in week 44. CONCLUSIONS: Adding lamotrigine to quetiapine treatment decreased depressive symptoms in patients with bipolar disorder. Our classification model suggested that lamotrigine increased the coefficient of variation in the QIDS-SR16 scores. The lamotrigine group also tended to have a lower DFA exponent, implying a substantial temporal instability in the time series. The performance of the model over time suggested that a trial of at least 44 weeks was required to achieve consistent results. The selected model confirmed the original CEQUEL study findings and helped in understanding the temporal dynamics of bipolar depression during treatment. TRIAL REGISTRATION: EudraCT Number 2007-004513-33; https://www.clinicaltrialsregister.eu/ctr-search/trial/2007-004513-33/GB (Archived by WebCite at http://www.webcitation.org/73sNaI29O).
Defining Faecal Calprotectin Thresholds as a Surrogate for Endoscopic and Histological Disease Activity in Ulcerative Colitis-a Prospective Analysis.
BACKGROUND: Faecal calprotectin [FCal] levels are used as a surrogate marker for mucosal inflammation, but thresholds for defining endoscopic or histological disease activity in ulcerative colitis [UC] remain unclear. METHODS: Using validated indices, prospective measurements of FCal, symptoms [Simple Colitis Clinical Activity Index, SCCAI], endoscopic [Ulcerative Colitis Endoscopic Index of Severity, UCEIS] and histological activity [Nancy index] were made over 6 months in patients enrolled into the TrueColours UC web-based monitoring programme. Repeated measurements correlation was performed between FCal and SCCAI, UCEIS, and Nancy indices using definitions for remission and active disease [UCEIS: remission ≤1, active ≥4; Nancy: remission ≤1, active ≥2; combined criteria: remission UCEIS ≤1 and Nancy ≤1, active UCEIS ≥4 and Nancy ≥2]. Receiver operating characteristic curves investigated FCal thresholds after maximising sensitivity for active disease. RESULTS: In 39 patients followed prospectively for 6 months, correlation coefficients between FCal and SCCAI, UCEIS, and Nancy indices were 0.271 (95% confidence interval [CI] 0.114-0.415), 0.741 [95% CI 0.289-0.922], and 0.876 [95% CI 0.605-0.965], respectively. Median FCal thresholds for remission using endoscopic, histological, or combined criteria were 71 μg/g [range 8-624], 91 μg/g [range 8-858], and 67 μg/g [range 8-479], respectively. The FCal threshold above which active disease was confirmed was 187 μg/g for UCEIS (area under the curve [AUC] 0.915), 72 μg/g for Nancy [AUC 0.824], and 187 μg/g for combined endoscopic and histological criteria [AUC 0.936]. CONCLUSIONS: Correlation between FCal and symptoms in UC is weak. In contrast, the correlation between FCal and endoscopic or histological activity is strong. An FCal ≥72 μg/g indicates histological inflammation [Nancy ≥2] and ≥187 μg/g indicates endoscopically active disease [UCEIS ≥4], whether combined with histopathology or not.
Lithium for acute mania
© 2019 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd. This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: 1. To determine the efficacy of lithium in alleviating acute manic symptoms compared to placebo and other drug treatments. 2. To review acceptability of treatment with lithium measured by: a.Overall drop-out from study b.Adherence to study medication c.Patient preference 3. To investigate the adverse effects of lithium treatment, including general prevalence of side effects. Specific unwanted effects that will be studied include: a.Gastrointestinal disturbances b.Tremor c.Polyuria and polydipsia d.Weight gain e.Precipitation of depressive episodes f.Documented renal pathology g.Lithium intoxication 4. To determine overall mortality rates on lithium treatment.
Translating big data to better treatment in bipolar disorder - a manifesto for coordinated action.
Bipolar disorder (BD) is a major healthcare and socio-economic challenge. Despite its substantial burden on society, the research activity in BD is much smaller than its economic impact appears to demand. There is a consensus that the accurate identification of the underlying pathophysiology for BD is fundamental to realize major health benefits through better treatment and preventive regimens. However, to achieve these goals requires coordinated action and innovative approaches to boost the discovery of the neurobiological underpinnings of BD, and rapid translation of research findings into development and testing of better and more specific treatments. To this end, we here propose that only a large-scale coordinated action can be successful in integrating international big-data approaches with real-world clinical interventions. This could be achieved through the creation of a Global Bipolar Disorder Foundation, which could bring government, industry and philanthropy together in common cause. A global initiative for BD research would come at a highly opportune time given the seminal advances promised for our understanding of the genetic and brain basis of the disease and the obvious areas of unmet clinical need. Such an endeavour would embrace the principles of open science and see the strong involvement of user groups and integration of dissemination and public involvement with the research programs. We believe the time is right for a step change in our approach to understanding, treating and even preventing BD effectively.
The True Colours Remote Symptom Monitoring System: A Decade of Evolution.
The True Colours remote mood monitoring system was developed over a decade ago by researchers, psychiatrists, and software engineers at the University of Oxford to allow patients to report on a range of symptoms via text messages, Web interfaces, or mobile phone apps. The system has evolved to encompass a wide range of measures, including psychiatric symptoms, quality of life, and medication. Patients are prompted to provide data according to an agreed personal schedule: weekly, daily, or at specific times during the day. The system has been applied across a number of different populations, for the reporting of mood, anxiety, substance use, eating and personality disorders, psychosis, self-harm, and inflammatory bowel disease, and it has shown good compliance. Over the past decade, there have been over 36,000 registered True Colours patients and participants in the United Kingdom, with more than 20 deployments of the system supporting clinical service and research delivery. The system has been adopted for routine clinical care in mental health services, supporting more than 3000 adult patients in secondary care, and 27,263 adolescent patients are currently registered within Oxfordshire and Buckinghamshire. The system has also proven to be an invaluable scientific resource as a platform for research into mood instability and as an electronic outcome measure in randomized controlled trials. This paper aimed to report on the existing applications of the system, setting out lessons learned, and to discuss the implications for tailored symptom monitoring, as well as the barriers to implementation at a larger scale.
Comparative Efficacy and Acceptability of 21 Antidepressant Drugs for the Acute Treatment of Adults With Major Depressive Disorder: A Systematic Review and Network Meta-Analysis.
(Reprinted with permission from Lancet 2018; 391:1357-66).
Women with a history of previous childbirths show less evident white matter brain ageing
AbstractMaternal brain adaptations occur in response to pregnancy, but little is known about how parity impacts white matter (WM) microstructure and WM ageing trajectories later in life. Utilising global and regional brain-age prediction based on multi-shell diffusion MRI data, we investigated the association between previous childbirths and WM brain age in 8,895 women in the UK Biobank cohort (age range = 54 - 81 years). The results showed that a higher number of previous childbirths was associated with lower WM brain age, in line with previous studies showing less evident grey matter (GM) brain ageing in parous relative to nulliparous women. Both global WM and GM brain age estimates showed unique contributions to the association with previous childbirths, suggesting partly independent processes. Corpus callosum contributed uniquely to the global WM association with previous childbirths, and showed a stronger relationship relative to several other tracts. While our findings demonstrate a link between reproductive history and brain WM characteristics later in life, longitudinal studies are required to understand how parity influences women’s WM trajectories across the lifespan.
In vivo amygdala nuclei volumes in schizophrenia and bipolar disorders
AbstractBackgroundAbnormalities in amygdala volume are well-established in schizophrenia and commonly reported in bipolar disorders. However, the specificity of volumetric differences in individual amygdala nuclei is largely unknown.MethodsPatients with schizophrenia disorders (SCZ, n=452, including schizophrenia, schizoaffective and other psychotic disorders, mean age 30.7±9.2 (SD), females 44.4%), bipolar disorders (BP, n=316, including bipolar I and II, 33.7±11.4, 58.5%) and healthy controls (n=753, 34.1±9.1, 40.9%) underwent T1-weighted magnetic resonance imaging. Total amygdala and nuclei volumes as well as intracranial volume (ICV) were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple linear regression models, adjusting for age, age2, ICV and sex, were fitted to examine diagnostic group and subgroup differences in volume, respectively.ResultsBilateral total amygdala and all nuclei volumes, except the medial and central nuclei, were significantly smaller in patients relative to controls. The largest effect sizes were found for the basal nucleus, accessory basal nucleus and cortico-amygdaloid transition area (partial η2 > 0.02). The diagnostic subgroup analysis showed that reductions in amygdala nuclei volume were most widespread in schizophrenia, with the lateral, cortical, paralaminar and central nuclei being solely reduced in this disorder. The right accessory basal nucleus was marginally smaller in SCZ relative to BP (t = 2.32, p = 0.05).ConclusionsOur study is the first to demonstrate distinct patterns of amygdala nuclei volume reductions in a well-powered sample of patients with schizophrenia and bipolar disorders. Volume differences in the basolateral complex (lateral, basal, accessory basal nuclei) may be putative neuroimaging markers for differentiating schizophrenia and bipolar disorders.
Multimodal imaging improves brain age prediction and reveals distinct abnormalities in patients with psychiatric and neurological disorders
BackgroundThe deviation between chronological age and age predicted using brain MRI is a putative marker of brain health and disease-related deterioration. Age prediction based on structural MRI data shows high accuracy and sensitivity to common brain disorders. However, brain aging is complex and heterogenous, both in terms of individual differences and the biological processes involved. Here, we implemented a multimodal age prediction approach and tested the predictive value across patients with a range of disorders with distinct etiologies and clinical features.MethodsWe implemented a multimodal model to estimate brain age using different combinations of cortical area, thickness and sub-cortical volumes, cortical and subcortical T1/T2-weighted ratios, and cerebral blood flow (CBF) calculated from functional arterial spin labeling (ASL) data. For each of the 11 models we assessed the age prediction accuracy in HC n=761 and compared the resulting brain age gaps (BAGs) between each clinical group and age-matched subsets of HC in patients with Alzheimer’s disease (AD, n=54), mild cognitive impairment (MCI, n=88), subjective cognitive impairment (SCI, n=55), schizophrenia (SZ, n=156), bipolar disorder (BD, n=136), autism spectrum disorder (ASD, n=28).ResultsAmong the 11 models, we found highest age prediction accuracy in HC when integrating all modalities (mean absolute error=6.5 years). Beyond this global BAG, the area under the curve for the receiver-operating characteristics based on two-group case-control classifications showed strongest effects for AD and ASD in global T1-weighted BAG (T1w-BAG), while MCI, SCI, BD and SZ showed strongest effects in CBF-based BAGs.ConclusionsCombining multiple MRI modalities improves brain age prediction and reveals distinct deviations in patients with psychiatric and neurological disorders. The multimodal BAG was most accurate in predicting age in HC, while group differences between patients and controls were often larger for BAGs based on single modalities. These findings demonstrate that multidimensional phenotyping provides a mapping of overlapping and distinct pathophysiology in common disorders of the brain, and specifically suggest metabolic and neurovascular aberrations in SZ and at-risk and early stage dementia.
Prevalence and incidence of clinical outcomes in patients presenting to secondary mental health care with mood instability and sleep disturbance.
BACKGROUND: Mood instability and sleep disturbance are common symptoms in people with mental illness. Both features are clinically important and associated with poorer illness trajectories. We compared clinical outcomes in people presenting to secondary mental health care with mood instability and/or sleep disturbance with outcomes in people without either mood instability or sleep disturbance. METHODS: Data were from electronic health records of 31,391 patients ages 16-65 years presenting to secondary mental health services between 2008 and 2016. Mood instability and sleep disturbance were identified using natural language processing. Prevalence of mood instability and sleep disturbance were estimated at baseline. Incidence rate ratios were estimates for clinical outcomes including psychiatric diagnoses, prescribed medication, and hospitalization within 2-years of presentation in persons with mood instability and/or sleep disturbance compared to individuals without either symptom. RESULTS: Mood instability was present in 9.58%, and sleep disturbance in 26.26% of patients within 1-month of presenting to secondary mental health services. Compared with individuals without either symptom, those with mood instability and sleep disturbance showed significantly increased incidence of prescription of any psychotropic medication (incidence rate ratios [IRR] = 7.04, 95% confidence intervals [CI] 6.53-7.59), and hospitalization (IRR = 5.32, 95% CI 5.32, 4.67-6.07) within 2-years of presentation. Incidence rates of most clinical outcomes were considerably increased among persons with both mood instability and sleep disturbance, relative to persons with only one symptom. CONCLUSIONS: Mood instability and sleep disturbance are present in a wide range of mental disorders, beyond those in which they are conventionally considered to be symptoms. They are associated with poor outcomes, particularly when they occur together. The poor prognosis associated with mood instability and sleep disorder may be, in part, because they are often treated as secondary symptoms. Mood instability and sleep disturbance need better recognition as clinical targets for treatment in their own right.
European Network of Bipolar Research Expert Centre (ENBREC): a network to foster research and promote innovative care.
Bipolar disorders rank as one of the most disabling illnesses in working age adults worldwide. Despite this, the quality of care offered to patients with this disorder is suboptimal, largely due to limitations in our understanding of the pathology. Improving this scenario requires the development of a critical mass of expertise and multicentre collaborative projects. Within the framework of the European FP7 programme, we developed a European Network of Bipolar Research Expert Centres (ENBREC) designed specifically to facilitate EU-wide studies. ENBREC provides an integrated support structure facilitating research on disease mechanisms and clinical outcomes across six European countries (France, Germany, Italy, Norway, Spain and the UK). The centres are adopting a standardised clinical assessment that explores multiple aspects of bipolar disorder through a structured evaluation designed to inform clinical decision-making as well as being applicable to research. Reliable, established measures have been prioritised, and instruments have been translated and validated when necessary. An electronic healthcare record and monitoring system (e-ENBREC©) has been developed to collate the data. Protocols to conduct multicentre clinical observational studies and joint studies on cognitive function, biomarkers, genetics, and neuroimaging are in progress; a pilot study has been completed on strategies for routine implementation of psycho-education. The network demonstrates 'proof of principle' that expert centres across Europe can collaborate on a wide range of basic science and clinical programmes using shared protocols. This paper is to describe the network and how it aims to improve the quality and effectiveness of research in a neglected priority area.