Frontiers in Psychiatry
ISSN / EISSN : 1664-0640 / 1664-0640
Published by: Frontiers Media SA (10.3389)
Total articles ≅ 6,418
Latest articles in this journal
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.764246
Background: Mental disorder of people living with HIV (PLWH) has become a common and increasing worldwide public health concern. We aimed to explore the relationship between anxiety, depression, and sleep disturbance for PLWH from a network perspective.Methods: The network model featured 28 symptoms on the Hospital Anxiety and Depression scale questionnaire and Pittsburgh Sleep Quality Index questionnaire in a sample of 4,091 HIV-infected persons. Node predictability and strength were computed to assess the importance of items. We estimated and compared 20 different networks based on subpopulations such as males and females to analyze similarities and differences in network structure, connections, and symptoms.Results: Several consistent patterns and interesting differences emerged across subgroups. Pertaining to the connections, some symptoms such as S12–S13 (“sleepy”—“without enthusiasm”) shown a strong positive relationship, indicating that feeling sleepy was a good predictor of lacking enthusiasm, and vice versa. While other symptoms, such as A3–D3 (“worried”—“cheerful”), were negatively related in all networks, revealing that nodes A3 and D3 were bridge symptoms between anxiety and depression. Across all subgroups, the most central symptom was A7 “panic” and S2 “awake”, which had the greatest potential to affect an individual's mental state. While S3 “bathroom” and S5 “cough or snore” shown consistent lower node importance, which would be of limited therapeutic use.Conclusions: Mental conditions of PLWH varied considerably among subgroups, inspiring psychiatrists and clinicians that personalized invention to a particular subgroup was essential and might be more effective during treatment than adopting the same therapeutic schedule.
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.745734
We describe a case of an adolescent male with Niemann-Pick Type C (NP-C), a neurodegenerative lysosomal lipid storage disorder, who presented with recurrent catatonia which required repeated treatment with electroconvulsive therapy (ECT). During the ECT-course, seizure threshold increased substantially, leading to questions about the influence of NP-C on neuronal excitability. In this exemplary ECT-patient, NP-C was diagnosed not until after the first ECT-course when initial psychopharmacology for catatonia had failed and antipsychotics and benzodiazepines showed significant side-effects. Clinicians should be aware of NP-C in patients referred for ECT, especially in the case of treatment resistance, neurological symptoms and intolerance of psychopharmacological drugs. As was shown in our NP-C patient, ECT can be repeatedly effective for catatonic features. In the literature, effectiveness of ECT in patients with NP-C has sparsely been reported. This case demonstrates that detection of NP-C is beneficial for patients because more optimal treatment with ECT can be provided earlier without further exposure to side-effects.
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.665536
Background: Psychiatric disorders have been historically classified using symptom information alone. Recently, there has been a dramatic increase in research interest not only in identifying the mechanisms underlying defined pathologies but also in redefining their etiology. This is particularly relevant for the field of personalized medicine, which searches for data-driven approaches to improve diagnosis, prognosis, and treatment selection for individual patients.Methods: This review aims to provide a high-level overview of the rapidly growing field of functional magnetic resonance imaging (fMRI) from the perspective of unsupervised machine learning applications for disease subtyping. Following the PRISMA guidelines for protocol reproducibility, we searched the PubMed database for articles describing functional MRI applications used to obtain, interpret, or validate psychiatric disease subtypes. We also employed the active learning framework ASReview to prioritize publications in a machine learning-guided way.Results: From the 20 studies that met the inclusion criteria, five used functional MRI data to interpret symptom-derived disease clusters, four used it to interpret clusters derived from biomarker data other than fMRI itself, and 11 applied clustering techniques involving fMRI directly. Major depression disorder and schizophrenia were the two most frequently studied pathologies (35% and 30% of the retrieved studies, respectively), followed by ADHD (15%), psychosis as a whole (10%), autism disorder (5%), and the consequences of early exposure to violence (5%).Conclusions: The increased interest in personalized medicine and data-driven disease subtyping also extends to psychiatric disorders. However, to date, this subfield is at an incipient exploratory stage, and all retrieved studies were mostly proofs of principle where further validation and increased sample sizes are craved for. Whereas results for all explored diseases are inconsistent, we believe this reflects the need for concerted, multisite data collection efforts with a strong focus on measuring the generalizability of results. Finally, whereas functional MRI is the best way of measuring brain function available to date, its low signal-to-noise ratio and elevated monetary cost make it a poor clinical alternative. Even with technology progressing and costs decreasing, this might incentivize the search for more accessible, clinically ready functional proxies in the future.
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.738368
Objectives: Neurocognitive functions might indicate specific pathways in developing attention deficit hyperactivity disorder (ADHD). We focus on reward-related dysfunctions and analyze whether reward-related inhibitory control (RRIC), approach motivation, and autonomic reactivity to reward-related stimuli are linked to developing ADHD, while accounting for comorbid symptoms of oppositional defiant disorder (ODD), and callous-unemotional (CU) traits.Methods: A sample of 198 preschool children (115 boys; age: m = 58, s = 6 months) was re-assessed at age 8 years (m = 101.4, s = 3.6 months). ADHD diagnosis was made by clinical interviews. We measured ODD symptoms and CU traits using a multi-informant approach, RRIC (Snack-Delay task, Gift-Bag task) and approach tendency using neuropsychological tasks, and autonomic reactivity via indices of electrodermal activity (EDA).Results: Low RRIC and low autonomic reactivity were uniquely associated with ADHD, while longitudinal and cross-sectional links between approach motivation and ADHD were completely explained by comorbid ODD and CU symptoms.Conclusion: High approach motivation indicated developing ADHD with ODD and CU problems, while low RRIC and low reward-related autonomic reactivity were linked to developing pure ADHD. The results are in line with models on neurocognitive subtypes in externalizing disorders.
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.736887
Objective: The purpose of this study was to examine the psychometric properties and posited nine-factor structure of the Chinese version of the Cognitive Emotion Regulation Questionnaire (CERQ-C) in high school students and adolescents with major depressive disorder (MDD), including assessment of measurement invariance of CERQ-C and its subscales across gender, time, and presence of depression.Methods: Chinese high school students from Hunan Province (N = 1,253) and adolescents with major depressive disorder (MDD) from the Medical Psychological Institute outpatient clinic at The Second Xiangya Hospital (N = 205) were enrolled. We examined the reliability, and model fit of the CERQ-C. Multigroup confirmatory factor analysis (CFA) was used to test measurement invariance of the subscales across gender, time, and presence of depression.Results: The CERQ-C subscales showed good internal consistency and moderate test-retest reliability in high school students and excellent internal consistency in adolescents with MDD group. The nine-factor model yielded adequate fit indices in different samples. Multigroup CFA confirmed that CERQ-C is strongly equivalent across gender, time, and presence of depression.Conclusions: The CERQ-C is a valid, reliable, and stable instrument for the evaluation of the cognitive emotion regulation (ER) strategies for different samples, including high school students and adolescents with MDD. The horizontal and longitudinal equivalences are strongly established.
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.741225
Objectives: In several high-income countries, family-focused practice programs have been introduced in adult mental health care settings to identify and support children whose parents live with mental health problems. Whilst their common goal is to reduce the impact of parental mental illness on children, the mechanisms by which they improve outcomes in different systems and settings are less well known. This kind of knowledge can importantly contribute to ensuring that practice programs achieve pre-defined impacts.Methods: The aim of this study was to develop knowledge about relationships between contextual factors, mechanisms and impact that could inform a program theory for developing, implementing, and evaluating family-focused practice. Principles of a realist evaluation approach and complex system thinking were used to conceptualize the design of semi-structured in-depth interviews with individuals who led the implementation of programs. Seventeen individuals from eight countries participated in the study.Results: Interviewees provided rich accounts of the components that programs should include, contextual factors in which they operated, as well as the behavior changes in practitioners that programs needed to achieve. Together with information from the literature, we developed an initial program theory, which illustrates the interconnectedness between changes that need to co-occur in practitioners, parents, and children, many of which related to a more open communication about parental mental health problems. Stigma, risk-focused and fragmented health systems, and a lack of management commitment were the root causes explaining, for example, why conversations about parents' mental illness did not take place, or not in a way that they could help children. Enabling practitioners to focus on parents' strengths was assumed to trigger changes in knowledge, emotions and behaviors in parents that would subsequently benefit children, by reducing feelings of guilt and improving self-esteem.Conclusion: To our knowledge, this is the first research, which synthesizes knowledge about how family-focused practice programs works in a way that it can inform the design, implementation, and evaluation of programs. Stakeholder, who fund, design, implement or evaluate programs should start co-developing and using program theories like the one presented in this paper to strengthen the design and delivery of family-focused practice.
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.762988
Background: Problematic drug use is common among psychiatric patients and is linked with poorer course and outcomes of illness. The aim of this study is to assess the prevalence of problematic drug use, and to explore its sociodemographic correlates and associations with health behaviors and outcomes among outpatients with schizophrenia and related psychoses in Singapore.Methods: Data from 397 individuals who were aged 21–65 years and were seeking treatment for schizophrenia and related psychoses in the outpatient clinics of a tertiary psychiatric hospital were analyzed. The Drug Abuse Screening Test (DAST-10) was used to assess problematic drug use. Information on sociodemographics, smoking status, alcohol use, symptoms severity and quality of life were collected. Multivariable logistic regressions were conducted to explore correlates and associations of problematic drug use.Results: The prevalence of problematic drug use was 5.8% (n = 23) in the sample, and 10.6% (n = 42) of the participants reported having problematic drug use and/or problematic alcohol use. More males than females reported having problematic drug use (p = 0.021), and also problematic drug and/or alcohol use (p = 0.004). Significant associations were observed between problematic drug use and smokers with nicotine dependence, and with physical health domain of quality of life. Individuals with greater symptom severity were approximately twice as likely to have problematic drug use and/or alcohol use.Conclusion: While the prevalence of problematic drug use in this sample population is relatively lower compared to other countries, there is a considerable number who might be at risk. Routine screening and close monitoring of drug use is recommended as part of psychiatric assessment, particularly among males and patients with nicotine dependence.
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.786019
Editorial on the Research Topic Problematic Internet Technology Use: Assessment, Risk Factors, Comorbidity, Adverse Consequences and Intervention There is no doubt that many personal and societal advantages are associated with using Internet technology such as social networking sites (SNS), gaming, and smartphones. For instance, smartphones have enhanced productivity in workplace (1) and educational (2) settings, and can facilitate health and mental health treatment with apps designed to complement traditional interventions (3). Furthermore, using SNS can boost social capital (4, 5), which can in turn promote mental health (6, 7). Such advantages of Internet technology use are relevant when such use is of mild to moderate frequency, conducted in healthy and adaptive ways. However, Internet technology is a double-edged sword, and can alternatively be used in unhealthy, maladaptive ways (8, 9). In the current Research Topic, we address when Internet technology is used in ways that are problematic or excessive, causing dysfunction in daily life. Problematic use of Internet technology is influenced by risk factors such as mental health symptoms (10–12) which drive such problematic use in an effort to alleviate negative affect (13, 14). Additional risk factors for problematic Internet use involve predispositional characteristics such as personality, genetics and other biological factors, deep seated cognitions (14–16), as well as cognitive and affective responses and dysfunctional coping processes (17, 18). In fact, theoretical models have been developed and supported that discuss how this variety of risk factors may contribute to problematic Internet use (19). Furthermore, consequences of problematic Internet use include physical pain in the hands and neck (20, 21), pedestrian and driving collisions (22), distraction and poor performance in school and work (23–25), and can involve cyberbullying (26), problematic pornography use (27), and internet radicalization (28). In the present Research Topic, authors present research in several domains related to problematic Internet use. Several papers report the development and/or validation of scales used to measure aspects of problematic Internet use—including problematic use symptoms [(29), Paschke et al.] and distractions from the smartphone (Throuvala et al.). These papers also report how these scales are related to external constructs such as mental health symptoms. For instance, Burkauskas et al. discovered that the nine-item Problematic Internet Use Questionnaire was valid in a sample of Lithuanian residents, and correlated positively with mental health symptom severity. Paschke et al. found that their newly developed Social Media Use Disorder Scale for Adolescents correlated positively with severity of depression and stress in German adolescents. And Throuvala et al. discovered that their newly developed Smartphone Distraction Scale correlated positively with emotional dysregulation and problematic SNS use in a sample of British university students. Such studies are important in providing researchers and clinicians with valid assessment instruments for measuring problematic Internet use and its consequences. Other authors in this Research Topic examined stress and anxiety as potential risk factors for the problematic use of Internet technology (Yang et al.; Li et al.; Zhao and Zhao). These papers also importantly examine potential mediators or moderators (mechanisms) that can explain how stress or anxiety are related to problematic Internet use, including the fear of missing out (FOMO) on rewarding experiences (Yang et al.), self-efficacy (Li et al.), and active SNS use or SNS flow (Zhao and Zhao). Examining such mechanisms is important because psychopathology alone may not adequately explain the development or maintenance of problematic Internet use (14, 15). For example, Yang et al. revealed that FOMO mediated relations between stress and problematic smartphone use severity in a sample of Chinese university students. Li et al. found support for self-efficacy in partially mediating associations between anxiety and problematic smartphone use symptoms in a sample of Chinese college students. And Zhao and Zhao discovered that active SNS use and SNS flow mediated relations between stress about COVID-19 and problematic SNS use in Chinese college students. We believe that future research should continue to prioritize testing of moderators and mediators that explain associations between both stress and anxiety with problematic Internet use. Other papers examine additional risk factors for problematic Internet use. Guo et al. sampled Chinese residents using a population-based survey, and examined how using different features of the smartphone may relate not only to problematic use but also to its different facets. Schivinski et al., Zhang et al., and Heng et al. examined social-related variables in association with problematic Internet use. Specifically, Schivinski et al. used an English-speaking sample of SNS users, finding that particular social motives (especially intrapersonal) were related to problematic SNS use severity. Heng et al. used a Chinese sample of undergraduates, discovering that social capital mediated relations between within-game social interactions and problematic gaming. And Zhang et al. sampled participants from China and Germany, finding that autistic traits were related to problematic Internet use. Finally, Luo et al. sampled Chinese college students, finding that adaptability regarding emotions, homesickness, and learning were related to perceived distress from losing smartphone access (or nomophobia). Studying such risk factors as social-related variables, autistic traits, and adaptability are important in furthering our understanding of why some people excessively engage in Internet use. Finally, we mention the important commentary by Montag and Hegelich. The authors present a compelling...
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.777090
Editorial on the Research Topic mHealth: Self-Management and Complementary Psychiatric Treatment The need to disseminate medical and psychological interventions using technology has been a pressing issue for psychiatric populations who are significantly underserved by traditional health services. As a case in point, only 44.8% of adults with mental illness in the United States have received treatment in 2019 (1). mHealth refers to services and devices, such as online programmes, mobile applications, virtual reality (VR) systems and videogames, that can be used to identify and support those with mental health needs beyond the traditional one-to-one conversations in a clinic with a doctor or therapist (2–4). The purpose of this special issue was to capture recent advances in the way technology—under the umbrella of mHealth—can be used to understand and monitor the manifestation and trajectory of emotional and psychiatric problems. The included papers illustrate how mHealth can be used to support treatment and care, from fully automated self-management and monitoring systems to blended interventions in which technology-enabled self-care is supported by a clinician, or clinician-led care is supplemented by technology. Three articles in this collection relate to schizophrenia and psychotic disorders. The first paper by Buck et al. suggests that frequent measurements delivered by mobile technologies could be leveraged to detect increases in psychotic symptoms that may precede relapses. Gowarty et al. found that two smoking cessation mobile apps were usable and appealing among young adult smokers with psychotic disorders; however, coaching at the start of treatment and app notifications throughout treatment were important to promote uptake and engagement. Finally, Hänsel et al. identified less color, lower saturation, and fewer faces in uploaded images on Instagram by individuals with schizophrenia compared to healthy volunteers, suggesting that image-sharing social media platforms can be an intriguing medium for prediction, identification, and monitoring of serious mental illness. Two studies were conducted at the interface of physical and mental health. First, Duthely et al. designed a mobile two-way texting system that sends and receives simple messages to promote adherence to anti-retroviral medications and medical appointments for ethnic minority women living with HIV/AIDS. The authors concluded that depression was a significant predictor of viral non-suppression and that mHealth has the potential to supplement medical care in this population, once patient concerns about privacy and confidentiality are addressed. The second study by Janney et al. identified patient preferences for three different wearables to promote physical activity in bipolar disorder. The armband (worn around the upper arm) was the favorite, followed by the pedometer (worn around the hip), and the actigraph (worn around the waist). Interestingly, the order of preference was the reverse to the order of accuracy of activity monitoring and reported problems (e.g., skin irritation), and may have been influenced by factors such as being able to wear the device discreetly or conceal it under clothes. Both studies flagged patient preferences that could influence uptake and usage of mHealth devices. Virtual reality featured in two papers that discussed mechanisms of reducing stress and fear. The first paper by Lindner et al. used a VR system to enable graded, controlled and repeated exposure to phobic stimuli associated with spiders. Through longitudinal modeling that indirectly compared two studies, one with instructions for real-life exposure virtual reality post-therapy and one without such instructions, the paper suggests that virtual exposure paired with real-life exposure can maximize fear reduction as part of therapy. The second paper by Kim et al. used VR natural scenes with a soothing soundtrack to induce relaxation in individuals with high stress, as an alternative to traditional biofeedback. The two relaxation methods showed no differences in total perceived stress, but differential effects on physiological outcomes suggested that VR may be more effective for relaxation by means of parasympathetic activity and traditional biofeedback by reducing muscle tension. Finally, a brief report by Grunebaum et al. is the first to show evidence of increased assay sensitivity of computerized adaptive testing over traditional measures in a clinical trial with participants who experienced suicidal depression. The importance of this work is in showing that brief phone or computer-based long-term follow-up assessments can be a reliable method in detecting suicide risk and has the added value of minimizing repeated measurement bias that can occur with traditional fixed-length assessments. This collection of eight articles exemplifies the diverse ways in which mHealth can be applied across mental health conditions and vulnerable populations, including suicidal depression, generalized anxiety, specific phobia, HIV/AIDS, bipolar disorder, schizophrenia, and psychotic disorders. With reference to wearable technologies, a computerized adaptive test, a mobile assessment system, two VR systems, a text messaging service, Instagram and mobile apps, these eight articles demonstrate how mHealth can support physical activity, smoking cessation, psychiatric treatment adherence, detection of onset or relapse of mental illness, symptom severity monitoring, stress management, and psychological therapy. One caveat that permeates all papers in this special issue is that mHealth remains largely experimental and confined within research settings, rather than being deployed in the real world and in routine clinical settings. Digital media can overcome geographical barriers and make the most of the available workforce through remote consultations, task-shifting and self-management; however, large-scale implementation of...
Frontiers in Psychiatry, Volume 12; https://doi.org/10.3389/fpsyt.2021.755744
Background and Objectives: While the consequences of the COVID-19 pandemic for general mental health and the increase in anxiety and depression are clear, less is known about the potential effect of the pandemic on OCD. The purpose of this study is to collect new data to monitor the symptomatic status of patients with OCD during the period of emergency due to COVID-19 and to make a comparison between two psychodiagnostic evaluations.Methods: Eleven OCD patients and their psychotherapists were recruited. All patients had a specific psychodiagnostic assessment for OCD (SCL-90; OCI-R; Y-BOCS self-report) performed between December 2019 and January 2020 (t0), and undertook cognitive behavioral therapy (CBT) and exposure and prevention of response protocol (ERP) before the lockdown. The psychodiagnostic assessment carried out at t0 was re-administered (t1) to all patients, together with a set of qualitative questions collected through an online survey. The respective therapists were asked to document the status of the therapy and the monitoring of symptoms through use of a semi-structured interview (Y-BOCS) and a qualitative interview. Non-parametric analyses were conducted.Results: Patients reported a significant decrease in OCD symptoms. Data analysis showed a decrease in the scores across t0 and at t1 on the Y-BOCS (SR) total self-report, and on OCD symptoms' severity assessed by means of the OCI-r and SCL-90 r OC subscale, for 11 participants. Relating to the measures detected by psychotherapists, marginally significant improvements and lower scores were found in the Y-BOCS (I). An improvement in symptoms was noticed by 90.9% of the clinical sample; this was confirmed by 45.4% of the therapists, who claimed moderate progress in their patients.Conclusions: The data collected through standardized measurements at two different times, albeit relative to a small sample, assume relevance from a clinical point of view. In the literature, some studies document the worsening of OCD. However, in many studies, the type of treatment, the detection time, and the intervention period are not well-specified. These results confirm the effectiveness of CBT/ERP as an elective treatment for OCD through a specific intervention procedure.