Search

Proportional odds models are commonly used to model ordinal responses, but the proportional odds assumption may not hold in practice, leading to biased inference. Tests such as score, Wald and likelihood ratio (LR) have been proposed to evaluate the proportional odds assumption based on models without the assumption. Brant has proposed an independent binary model-based Wald-type test, and Wolfe and Gould have extended the idea to propose an LR-type test. This paper provides a brief review of the Brant and Wolfe-Gould tests for evaluating the proportional odds assumption and evaluates their performance through simulation studies and a real data example. Sample programs are provided in SAS, SPSS and Stata to facilitate the implementation of these tests using standard statistical software packages. This study highlights the importance of evaluating the proportional odds assumption when using proportional odds models for ordinal responses. The sample programs provided in this paper make it easy for researchers to apply these tests in their own analyses using standard statistical software packages. [ABSTRACT FROM AUTHOR]

Although logistic regression is the most popular for modelling regression relationships with binary responses, many find relative risk (RR), or risk ratio, easier to interpret and prefer to use this measure of risk in regression analysis. Indeed, since Zou published his modified Poisson regression approach for modelling RR for cross-sectional data, his paper has been cited over 7 000 times, demonstrating the popularity of this alternative measure of risk in regression analysis involving binary responses. As longitudinal studies have become increasingly popular in clinical trials and observational studies, it is imperative to extend Zou's approach for longitudinal data. The two most popular approaches for longitudinal data analysis are the generalised linear mixed-effects model (GLMM) and generalised estimating equations (GEE). However, the parametric GLMM cannot be used for the extension within the current context, because Zou's approach treats the binary response as a Poisson variable, which is at odds with the Bernoulli distribution for the binary response. On the other hand, as it imposes no mathematical model on data distributions, the semiparametric GEE is coherent with Zou's modified Poisson regression. In this paper, we develop a GEE-based longitudinal model for binary responses to provide inference about RR. [ABSTRACT FROM AUTHOR]

Incentivised by breakthroughs and data generated by the high-throughput sequencing technology, this paper proposes a distance-based framework to fulfil the emerging needs in elucidating insights from the high-dimensional microbiome data in psychiatric studies. By shifting focus from traditional methods that focus on the observations from each subject to the between-subject attributes that aggregate two or more subjects' entire feature vectors, the described approach revolutionises the conventional prescription for high-dimensional observations via microbiome diversity. To this end, we enrich the classical generalised linear models to articulate the multivariable regression relationship between distance-based variables. We also discuss a robust and computationally feasible semiparametric inference technique. Benefitting from the latest advances in the semiparametric efficiency theory for such attributes, the proposed estimators enjoy robustness and good asymptotic properties that guarantee sensitivity in detecting signals between clinical outcomes and microbiome diversity. It offers a readily implementable and easily interpretable solution for deciphering the gut-brain axis in mental health research. [ABSTRACT FROM AUTHOR]

Nicotine use is more prevalent in patients with psychiatric disorders, especially those diagnosed with psychotic illnesses. Previously, this higher prevalence has been partially attributed to the potential ameliorative effects of nicotine on symptom severity and cognitive impairment. Some healthcare professionals and patients perceive there is a beneficial effect of nicotine on mental health. Emerging data show that the harm associated with nicotine in the population of patients with mental health conditions outweighs any potential benefit. This paper will review the evidence surrounding the nicotinic system and schizophrenia, with a focus on any causality between nicotine and psychosis. [ABSTRACT FROM AUTHOR]

Proportional odds models are commonly used to model ordinal responses, but the proportional odds assumption may not hold in practice, leading to biased inference. Tests such as score, Wald and likelihood ratio (LR) have been proposed to evaluate the proportional odds assumption based on models without the assumption. Brant has proposed an independent binary model-based Wald-type test, and Wolfe and Gould have extended the idea to propose an LR-type test.This paper provides a brief review of the Brant and Wolfe-Gould tests for evaluating the proportional odds assumption and evaluates their performance through simulation studies and a real data example. Sample programs are provided in SAS, SPSS and Stata to facilitate the implementation of these tests using standard statistical software packages.This study highlights the importance of evaluating the proportional odds assumption when using proportional odds models for ordinal responses. The sample programs provided in this paper make it easy for researchers to apply these tests in their own analyses using standard statistical software packages.

Although logistic regression is the most popular for modelling regression relationships with binary responses, many find relative risk (RR), or risk ratio, easier to interpret and prefer to use this measure of risk in regression analysis. Indeed, since Zou published his modified Poisson regression approach for modelling RR for cross-sectional data, his paper has been cited over 7 000 times, demonstrating the popularity of this alternative measure of risk in regression analysis involving binary responses. As longitudinal studies have become increasingly popular in clinical trials and observational studies, it is imperative to extend Zou’s approach for longitudinal data.The two most popular approaches for longitudinal data analysis are the generalised linear mixed-effects model (GLMM) and generalised estimating equations (GEE). However, the parametric GLMM cannot be used for the extension within the current context, because Zou’s approach treats the binary response as a Poisson variable, which is at odds with the Bernoulli distribution for the binary response. On the other hand, as it imposes no mathematical model on data distributions, the semiparametric GEE is coherent with Zou’s modified Poisson regression. In this paper, we develop a GEE-based longitudinal model for binary responses to provide inference about RR.

Mental health questions can be tackled through machine learning (ML) techniques. Apart from the two ML methods we introduced in our previous paper, we discuss two more advanced ML approaches in this paper: support vector machines and artificial neural networks. To illustrate how these ML methods have been employed in mental health, recent research applications in psychiatry were reported.

Background The alexithymia trait is of high clinical interest. The Perth Alexithymia Questionnaire (PAQ) was recently developed to enable detailed facet-level and valence-specific assessments of alexithymia.Aims In this paper, we introduce the first Chinese version of the PAQ and examine its psychometric properties and clinical applications.Methods In Study 1, the PAQ was administered to 990 Chinese participants. We examined its factor structure, internal consistency, test-retest reliability, as well as convergent, concurrent and discriminant validity. In Study 2, four groups, including a major depressive disorder (MDD) group (n=50), a matched healthy control group for MDD (n=50), a subclinical depression group (n=50) and a matched healthy control group for subclinical depression (n=50), were recruited. Group comparisons were conducted to assess the clinical relevance of the PAQ.Results In Study 1, the intended five-factor structure of the PAQ was found to fit the data well. The PAQ showed good internal consistency and test-retest reliability, as well as good convergent, concurrent and discriminant validity. In Study 2, the PAQ was able to successfully distinguish the MDD group and the subclinical depression group from their matched healthy controls.Conclusions The Chinese version of the PAQ is a valid and reliable instrument for comprehensively assessing alexithymia in the general population and adults with clinical/subclinical depression.

SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to facilitate analysis of data from complex survey studies. On the other hand, PROC MEANS and many other classic SAS procedures also provide an option for including weights and yield identical point estimates, but different standard errors (SEs), as their corresponding survey procedures. This paper takes an in-depth look at different types of weights and provides guidance on use of different SAS procedures. [ABSTRACT FROM AUTHOR]

Background Therapeutic drug monitoring guides clinical individualised medication by measuring plasma concentration, which could improve the curative effect, avoid drug overdose and reduce the incidence of adverse reactions. At present, there are few reports on the clinical detection of venlafaxine and its active metabolite O-desmethylvenlafaxine. In this paper, the detection method of venlafaxine and O-desmethylvenlafaxine in blood plasma was established, which provides an effective and convenient means for guiding clinical application of medication. Aim To establish a method for determination of venlafaxine and its active metabolite O-desmethylvenlafaxine in human plasma by highperformance liquid chromatography with fluorescence detection. Methods Chromatographic separation was achieved on an Agilent Eclipse XDB-C18 Column (4.6×150 mm, 5 µm) with water containing sodium dihydrogen phosphate (0.05 mol/L) and acetonitrile (72:28) as the mobile phases. The following parameters were employed: flow rate 0.5 mL/min, column temperature 30°C, fluorescence excitation wavelength 276 nm and emission wavelength 598 nm. Results The method showed good linearity in the concentration range 10-1000 ng/mL. The regression equation for venlafaxine was R=0.0054C+0.0264, r2=0.99991. The regression equation for O-desmethylvenlafaxine was R=0.0034C+0.0272, r2=0.99969. The intraday and interday precisions (relative SD) were less than 10%, and the quantitative limit was 10 ng/mL. Conclusion We established a sensitive, specific and simple method for the detection of venlafaxine and O-desmethylvenlafaxine. This method fully meets the needs of clinical trials of venlafaxine and the requirements of relevant guidelines. It provided a reference for the clinical detection of venlafaxine and O-desmethylvenlafaxine plasma concentrations and pharmacokinetic study. [ABSTRACT FROM AUTHOR]

Nicotine use is more prevalent in patients with psychiatric disorders, especially those diagnosed with psychotic illnesses. Previously, this higher prevalence has been partially attributed to the potential ameliorative effects of nicotine on symptom severity and cognitive impairment. Some healthcare professionals and patients perceive there is a beneficial effect of nicotine on mental health. Emerging data show that the harm associated with nicotine in the population of patients with mental health conditions outweighs any potential benefit. This paper will review the evidence surrounding the nicotinic system and schizophrenia, with a focus on any causality between nicotine and psychosis.

Power analysis is a key component of planning prospective studies such as clinical trials. However, some journals in biomedical and psychosocial sciences request power analysis for data already collected and analysed before accepting manuscripts for publication. Many have raised concerns about the conceptual basis for such post-hoc power analyses. More recently, Zhang et al showed by using simulation studies that such power analyses do not indicate true power for detecting statistical significance since post-hoc power estimates vary in the range of practical interests and can be very different from the true power. On the other hand, journals’ request for information about the reliability of statistical findings in a manuscript due to small sample sizes is justified since the sample size plays an important role in the reproducibility of statistical findings. The problem is the wording of the journals' request, as the current power analysis paradigm is not designed to address journals’ concerns about the reliability of the statistical findings. In this paper, we propose an alternate formulation of power analysis to provide a conceptually valid approach to the journals’ wrongly worded but practically significant concern.

Suppose we have a sample of subjects in two treatment groups. To study the difference of the treatment effects, we can analyse the data using all subjects (overall analysis). We may also divide the subjects into several subgroups based on some covariates of interest (eg, gender), and study the treatment effects within each subgroup. The results of these two analyses may be different or even in opposite directions. In this paper, we give a general sufficient condition of consistency between the overall and subgroup analyses.

There is an increasing heavy disease burden of major depressive disorder (MDD) globally. Both high diagnostic heterogeneity and complicated pathological mechanisms of MDD pose significant challenges. There is much evidence to support anhedonia as a core feature of MDD. In the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, anhedonia is further emphasised as a key item in the diagnosis of major depression with melancholic features. Anhedonia is a multifaceted symptom that includes deficits in various aspects of reward processing, such as anticipatory anhedonia, consummatory anhedonia, and decision-making anhedonia. Anhedonia is expected to become an important clinicopathological sign for predicting the treatment outcome of MDD and assisting clinical decision making. However, the precise neurobiological mechanisms of anhedonia in MDD are not clearly understood. In this paper, we reviewed (1) the current understanding of the link between anhedonia and MDD; (2) the biological basis of the pathological mechanism of anhedonia in MDD; and (3) challenges in research on the pathological mechanisms of anhedonia in MDD. A more in-depth understanding of anhedonia associated with MDD will improve the diagnosis, prediction, and treatment of patients with MDD in the future.

Diagnostic tests are usually based on some quantitative biomarkers. Two key parameters used to characterise the quality of a test are test sensitivity and specificity. Predictive values of the disease status based on test results are also of interest in medical research and public health management. In this paper, we study the relations among sensitivity, specificity and predictive values of the test. The core concept is risk function, which is assumed to be an increasing function of the biomarker. Our results show that test sensitivity and specificity change in opposite directions. The positive predictive value and the sensitivity also change in opposite directions. Likewise, the negative predictive value and the specificity change in opposite directions.

Maladaptive daydreaming (MD) is an immersive fantasy activity that leads to distress and socio-occupational dysfunction. MD has many features suggestive of behavioural addiction, but research exploring the phenomenology of this clinical construct is limited. MD has also been purported to be a maladaptive strategy to cope with distress, but often leads to uncontrollable absorption in fantasy world, social withdrawal and neglected aspects of everyday life. In this paper, we report the case of a 16-year-old boy who developed internet gaming disorder and MD after experiencing cyberbullying from his peers. The patient engaged in vivid, fanciful imagery that lasted for hours, leading to social dysfunction and academic deterioration. Baseline assessment revealed a Maladaptive Daydreaming Scale-16 score of 65 (cut-off 50) and an Internet Gaming Test-20 score of 86 (cut-off 71). The patient was managed primarily with psychological intervention. The therapy focused on behaviour modification and cognitive restructuring. Patients in clinical setting should be questioned about MD when presenting with excessive use of technology or other forms of behavioural addictions. Further studies are necessary to determine the biopsychosocial factors of MD and its correlates. There is also a need to study treatment and management approaches for treating MD.

Background Cognitive behavioural therapy (CBT) is considered to be an effective treatment for schizophrenia. In recent years, researchers have published clinical research results on CBT for schizophrenia. However, there is currently a lack of bibliometric analysis on CBT for schizophrenia.Aims To understand the current situation and research trends of CBT for schizophrenia, and to provide valuable information for researchers in this field.Methods Literature was retrieved from the Web of Science Core Collection database. CiteSpace was used to visually analyse the current status of research on CBT for schizophrenia, as well as trends and points of general interest on this topic.Results A total of 1151 papers were retrieved. The annual number of publications has increased 417.65% from 2000 to 2019. Schizophrenia Research was the most active journal. McGorry enjoys considerable influence. The University of London is deemed to be the most active research institution. England and the USA retain the highest scientific productivity in this field. China and Norway might make more contributions to this field in the future. The most important research topics are randomised controlled trials of CBT for schizophrenia, meta-analysis, scale selection and research on the improvement of quality of life. Results from the following keywords ‘psychoeducation’, ‘insomnia’, ‘individual’, ‘mental illness’, ‘major depressive disorder’, ‘efficacy’, ‘internalised stigma’ and ‘remediation’ indicated new research frontiers in this field.Conclusions The field of CBT for schizophrenia is progressing and has great potential. The level and quality of research in this field is high. The proposal of research hotspots and frontiers serves as a direction for researchers in this field. Researchers around the world should strengthen their cooperation and communication to promote further development of this field.

Adolescent suicide is the leading cause of death among South Korean (Korean) youth. Despite great efforts being made towards suicide prevention in Korea, the suicide rate has not decreased significantly. There is an urgent need for a new adolescent suicide prevention strategy. This paper describes the seriousness of the issue of adolescent suicide in Korea, evaluates its current management by the SWOT analysis (strengths, weaknesses, opportunities and threats) and further recommends a new suicide prevention programme that integrates national/social involvement (State Suicide Intervention Committee, suicide posts’ monitoring, parental divorce information sharing and Adolescence Mental Health Promotion Foundation), school-based programmes (continuous monitoring system, psychology consultation team and mental health educational curricula) and family-based programmes (parental education and family-school communication). In addition, genetic analysis, biochemical tests and psychological disease registration are the indispensable elements that aid in suicidal behaviour prevention and prediction.

In recent years, research on meditation as an important alternative therapy has developed rapidly and been widely applied in clinical medicine. Mechanism studies of meditation have also developed progressively, showing that meditation has great impact on brain structure and function, and epigenetic and telomere regulation. In line with this, the application of meditation has gradually been expanded to mental illness, most often applied for major depressive disorders and substance-related and addictive disorders. The focus of this paper is to illustrate the biological mechanisms of meditation and its application in mental disorders.

Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder that is characterised by obsessions and compulsions. The recommended treatments for OCD are cognitive– behavioural therapy using exposure and response prevention and/or pharmacotherapy. On the other hand, some nutritional and herbal supplements may be effective in the treatment of OCD. Nutritional and herbal supplements in OCD treatment will be reviewed in this paper. PubMed (Medline), Cochrane Library and Google Scholar databases were reviewed for the topic. There are some supplements that have been researched in OCD treatment studies such as vitamin D, vitamin B12, folic acid, homocysteine, trace elements, N-acetyl cysteine, glycine, myoinositol, St John’s wort, milk thistle, valerian root, curcumin and borage. The effectiveness of herbal and nutritional supplements in the treatment of OCD should be supported with more conclusive evidence.

BackgroundTreatments for anxiety disorders are among the most effective in psychiatry. Yet, there is considerable room for improvement.AimIn this paper, we discuss the value of ecological momentary assessment as a research method and clinical tool.MethodsWe begin by describing ecological momentary assessment and its advantages, including the ability to collect ecologically valid information about mental disorders, in real time, in individual patients. We then illustrate the value of this approach for anxiety disorder treatment using two patients with panic disorder who completed ecological momentary assessments for 2 weeks before and after a cognitive-behavioural therapy intervention. We focus especially on two key pieces of information provided by ecological momentary assessment data: information about symptom dynamics and information about the relationships among symptoms as they unfold over time within individual patients.PerspectiveAlthough considerable work is needed to further develop this methodology in the context of anxiety disorder treatment, we believe that these pieces of information may ultimately inform our understanding of how anxiety disorder treatments have their effect and how those treatments can be tailored to individual patients.

Machine learning (ML) techniques have been widely used to address mental health questions. We discuss two main aspects of ML in psychiatry in this paper, that is, supervised learning and unsupervised learning. Examples are used to illustrate how ML has been implemented in recent mental health research.