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Treatment with antidepressants results in a modest improvement in social functioning for patients with MDD. Antidepressants are associated with a small, but significant, improvement in social functioning (SF) for patients with major depressive disorder (MDD), as described in a systematic review and meta-analysis published in Psychotherapy and Psychosomatics. Many psychiatric disorders are associated with reduced sociability, which greatly impacts quality of life. Normative SF majorly contributes to a healthy life and well-being, and as such, is an important outcome in the treatment of psychiatric disorders. To evaluate the existing body of evidence regarding antidepressants and SF, investigators from the University of Cologne, Cologne, Germany, searched publication databases for relevant studies published through December 2022. The investigators selected a total of 39 publications covering 40 randomized controlled trials (RCTs) that investigated the efficacy of antidepressants compared with placebo for the treatment of MDD and measured SF as an outcome. The studies were published between 1995 and 2020 and were designed to evaluate primary depression (RCTs=27) or comorbid depression (k=13). The most common instruments for assessing SF were the Short Form Health Survey (SF-36), Social Role Functioning subsection; the Social Adaptation Self-Evaluation Scale (SASS); Work and Social Adjustment Scale (WSAS); and Activities of Daily Living for Mild Cognitive Impairment, Activities of Daily Living Scale (ADCS-ADL). "Since fulfilling social obligations is of enormous importance to patients, the field needs to increase its efforts in finding means beyond antidepressant drugs to help our patients live a successful social life." Across all studies analyzed, a total of 10,537 patients were randomly assigned to receive antidepressants and 6049 received placebo. The study participants were aged 46.8 years, on average, and 64.2% were women. In their meta-analysis, the investigators found a significant effect of antidepressants on SF relative to placebo for both primary (standardized mean difference [SMD], 0.25; 95% CI, 0.21-0.30; I2, 39%; P =.02) and comorbid (SMD, 0.24; 95% CI, 0.10-0.37; I2, 75%; P <.001) depression. When studies were stratified by risk for bias, the SMD of antidepressants on SF among patients with primary depression was 0.32 (95% CI, 0.24-0.40; I2, 35%) among studies with low risk for bias, compared with 0.23 (95% CI, 0.18-0.28; I2, 27%) for studies with high or uncertain risk for bias. Conversely, for comorbid depression, the SMD of antidepressants on SF did not have an effect in studies with low risk for bias 0.04 (95% CI, -0.16 to 0.24; I2, 0%) compared with 0.29 (95% CI, 0.13-0.44; I2, 79%) for studies with high or uncertain risk for bias. Notably, antidepressants’ impact on SF was correlated with improvements in depression (r =0.67; P <.001) and quality of life (r =0.63; P <.001). The investigators posit that this association suggests a construct overlap or redundancy in the measurement of these factors. Study authors concluded, “Since fulfilling social obligations is of enormous importance to patients, the field needs to increase its efforts in finding means beyond antidepressant drugs to help our patients live a successful social life.” This analysis may be limited by the stratification of studies by primary or comorbid depression status, which was a deviation from the original study design protocol. References: Kremer S, Wiesinger T, Bschor T, Baethge C. Antidepressants and social functioning in patients with major depressive disorder: systematic review and meta-analysis of double-blind, placebo-controlled RCTs.

The prevalence of e-cigarette use during late pregnancy among US adolescents has significantly increased, but does not elevate small-for-gestational-age birth risk. The prevalence of e-cigarette use during late pregnancy has increased among adolescents from 2016 to 2021, according to study results published in JAMA Network Open. Particularly, White adolescents were the most likely to use e-cigarettes during pregnancy, relative to other races/ethnicities. However, unlike combustible cigarettes, e-cigarette use did not significantly elevate the risk for small-for-gestational-age (SGA) births. Although the popularity of e-cigarettes has increased among adolescents in the United States, little is known about the prevalence of e-cigarette use among pregnant adolescents. Thus, researchers conducted a cohort study of data from the 2016 to 2021 Pregnancy Risk Assessment Monitoring System (PRAMS). This dataset used a mixed-mode approach to collect information on maternal behaviors, attitudes, and experiences throughout the perinatal period and covers approximately 83% of all US births. Participants self-reported their e-cigarette and combustible cigarette use. The researchers then categorized participants into the following groups: adolescents who abstained from both, exclusive e-cigarette users, exclusive combustible cigarette users, and individuals who engaged in dual use of both cigarette types. Additionally, SGA birth was defined as a weight below the 10th percentile for the corresponding sex and gestational duration, in accordance with the established criteria by the World Health Organization. A total of 10,428 adolescents, aged 10 to 19 years, who were pregnant between 2016 to 2021 were included in the final analysis. At baseline, 27.3% of individuals were aged 10 to 17 years and 72.7% were aged 18 to 19 years. By self-reported race/ethnicity, 58.9% of individuals identified as White, 23.3% as Black, and 69.8% as non-Hispanic. The researchers observed a significant increase in the weighted prevalence of pregnant women exclusively using e-cigarettes during late pregnancy (the last 3 months of gestation), from 0.8% in 2016 to 4.1% in 2021 (P =.001). In contrast, the prevalence of exclusive combustible cigarette use declined from 9.2% in 2017 to just 3.2% in 2021(P <.001). Dual use of both cigarette types did not significantly differ across the time period, fluctuating between 0.6% and 1.6% (P =.38). In 2021, the prevalence of cigarette use during late pregnancy among adolescents was highest for exclusive e-cigarette use (4.1%), then exclusive cigarette use (3.2%), and lastly dual use of both cigarette types (1.1%). Further, White adolescents had the highest prevalence of exclusive e-cigarette use (2.7%) and exclusive cigarette use (9.8%), compared to other race/ethnicity groups. Relative to pregnant adolescents who did not use cigarettes, the risk for SGA birth was not significantly elevated among adolescents who solely used e-cigarettes during late pregnancy (adjusted odds ratio [aOR], 1.68; 95% CI, 0.89-3.18) or adolescents who had dual use of both cigarette types (aOR, 1.68; 95% CI, 0.79-3.53). However, adolescents with exclusive use of combustible cigarettes had double the risk for SGA birth compared to nonusers (24.6% vs 12.9%; aOR, 2.51; 95% CI, 1.79-3.52). Study authors concluded, “In this cohort study of US pregnant adolescents, there was an increase in e-cigarette use and a decrease in cigarette use during late pregnancy from 2016 to 2021.” These study findings may be limited by recall bias, the potential confounding factors when distinguishing between cannabis and nicotine inhalation devices, and a lack of information on secondhand smoke exposure during pregnancy. Disclosure: One study author declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of authors’ disclosures. This article originally appeared on Psychiatry Advisor

MDMA-assisted therapy for PTSD led to significant self-experience improvements, even after controlling for CAPS-5 score changes. In study findings published in PLOS One, 3,4-methylene-dioxymethamphetamine (MDMA)-assisted therapy for post-traumatic stress disorder (PTSD) had a positive effect on transdiagnostic mental processes of self-experience. Given that these processes are often associated with poor treatment outcomes, psychedelic agents that target these psychological capacities could lead to major improvements in PTSD symptomatology. Based on its positive performance with significant and sustained reductions in PTSD symptoms and acceptable safety profiles, the Food and Drug Administration (FDA) has designated MDMA-assisted therapy as a breakthrough therapy for PTSD. Studies involving healthy volunteers have demonstrated a positive effect of MDMA on self-regulatory capacities and self-compassion. Therefore, researchers assessed exploratory data from a randomized, double-blind, placebo-controlled study comparing the safety and efficacy of MDMA-assisted therapy to therapy with placebo among participants with severe PTSD. Treatment effects for self-experience were compared across scales of alexithymia, self-compassion, and an inventory of altered self-capacities. The study sample consisted of 90 participants with severe PTSD, as confirmed via the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria and the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5). Among the participants, 64.4% were women, 80.3% were White, and 92.7% were non-Hispanic or Latino. All participants underwent 3 preparation therapy sessions prior to experimental assignments, which consisted of 3 separate 8-hour experimental sessions, spaced about 4 weeks apart, of either MDMA-assisted therapy or therapy with placebo. The dosage was 80 mg + 40 mg MDMA HCl for the first experimental session and increased to 120 mg + 60 mg MDMA HCl in the second and third sessions. Relative to therapy with placebo, the group receiving MDMA-assisted therapy showed significantly greater improvements in all self-experience measures, except for the altered self-capacity factor of identity diffusion (P =.08). The MDMA-assisted therapy resulted in greater improvements in alexithymia (P =.0002), self-compassion (P <.0001), and most altered self-capacity factors, compared to placebo. However, upon adjusting for changes in CAPS-5 scores, only the improvements in self-compassion remained statistically significant (unadjusted for CAPS-5 change, P <.0001; adjusted for CAPS-5 change, P =.0076). In addition to the main treatment effects, the researchers evaluated interactions between treatment groups and the baseline categories. Participants with greater baseline alexithymia experienced a greater reduction in CAPS-5 scores in the MDMA-assisted therapy group, with a decrease of 16.16 (95% CI, -28.80 to -7.52). Additionally, when compared to individuals in the placebo group who had high baseline alexithymia, there were significantly greater improvements in CAPS-5 scores for participants in the MDMA-assisted therapy group with both low (P =.02) and high (P <.0001) baseline alexithymia. These findings indicate that MDMA has a significant impact on the regulation of emotions and self-experience measures, particularly alexithymia and self-compassion. Study authors concluded, “MDMA may be particularly effective for enhancing treatment efficacy by improving a range of problems with self-experience that are associated with treatment resistance.” The study results may be limited by a lack of information on outcomes of trust and intimacy, an inability to control for age and type of trauma exposure, and the homogenous demographics that may not reflect an epidemiologically representative PTSD population. This article originally appeared on Psychiatry Advisor

Regular THC use in adolescence is not a benign activity—it can have life-changing consequences. Here’s what you need to know. Although an epidemic of mental disorders in youth has been widely acknowledged, the role of cannabis has largely been ignored. Opioid and alcohol use disorders have long been recognized as substantial risks to the adolescent population, but the negative effects of cannabis tend to be overlooked. Although adolescents do not die from cannabis overdoses as they may from opiate overdoses, cannabis presents a significant danger. Tetrahydrocannabinol (THC), the euphoria-inducing cannabinoid in cannabis, is toxic to the adolescent brain, which is not fully developed until the age of 25 years. This toxicity is present even with non-disordered use (cannabis use that does not meet the DSM 5-TR criteria for a substance use disorder) and can lead to increased susceptibility to mental illness. Despite this evidence, we are seeing an increase in adolescent cannabis use. In 2019, 37% of US high school students reported use of cannabis in the past year, and 22% reported use in the past 30 days.3 Additionally, an increase in cannabis use has been observed in younger youth, with increased use observed in middle school. Increased THC Potency Not only is the frequency of cannabis use increasing, but so is the potency of THC in cannabis. Various preparations account for this increase. Cannabis plants have been bred to enrich THC and to decrease cannabidiol (CBD). Analysis of more than 38,000 cannabis samples seized by the US Drug Enforcement Administration (DEA) between 1995 and 2014 showed an average increase in THC from 4% in 1995 to 12% in 2014. This trend has continued over the past 9 years. Concentrated THC oil from buds called “wax” is 50% THC. With the increased use of vaping, adolescents can expose themselves to the very high levels of THC, as the concentration of THC in vaping cartridges can be as high as 80% to 90%. There is a paucity of literature on how high concentration of THC achieved through vaping impacts the developing brains of adolescents. Normal Brain Development A detailed examination of the neurodevelopment of the adolescent brain provides a hypothesis as to how THC can cause significant negative effects. In infancy, neurons are disparate and unconnected but begin connecting and forming synapses at an enormous rate, with 2 million synapses being formed every second up to age 2 years. At that time, the process of pruning ensues so that half of the hundred trillion synapses formed will disappear. A second period of overproduction of synapses, especially in the prefrontal cortex, occurs at the time of puberty, and pruning continues for the following 10 years. In addition, neurogenesis in the dentate gyrus of the hippocampus has a peak value near puberty. Pruning allows the brain to remove synapses that are no longer being utilized, providing much-needed space in the limited cranium for increased synaptogenesis to maximize the efficiency of developing brain circuits. During puberty, this surge in synaptogenesis occurs in the prefrontal cortex, which controls attention, impulsivity, emotional regulation, and recognition of possible consequences of one’s actions. This is followed by more pruning until full maturation is achieved at the age of 25 years. Possible Consequences of THC Use in Adolescence If something were to hinder the brain from strengthening neuronal connections or to alter their morphology during adolescence, those connections may become disrupted for the rest of that individual’s life. It is well established that THC interferes with the functioning of the endogenous cannabinoid anandamide, a retrograde neurotransmitter that modulates the release of other synaptic chemicals. The addition of THC to the developing brain may have major detrimental effects on the large-scale changes in neural connections occurring during this time. These developing neuro-networks, which are highly influenced by hormones and the environment, would make the developing adolescent brain vulnerable to THC. In particular, the prefrontal cortex seems to be susceptible to these changes, which could be the explanation for some of the long-term symptoms associated with chronic cannabis use. One of the most significant of these symptoms involves impairment of cognition including working memory, attention, information processing, judgment, and decision making. A New Zealand prospective study showed that regular cannabis use before the age of 18 years correlated with the loss of 5 to 8 IQ points at 20-year follow-up. These results were not confirmed by a subsequent twin study, but they did demonstrate that regular use of cannabis impaired academic functioning and subsequent socioeconomic levels. The investigators hypothesized that common vulnerability factors may make some individuals more prone to both cannabis use and negative outcomes. Impaired cognition, especially with executive function problems and poor school performance, occurs with acute cannabis use. It is unclear whether this returns to a normal level if cannabis use is stopped. Clinical experience has shown that some adolescents develop acute psychosis from smoking cannabis, which often recurs if they resume using cannabis again after remission of the first psychotic episode. Follow-up studies have shown that cannabis use increases the risk of the future development of schizophrenia. Regular cannabis use in adolescence also increases risk of depression, suicide attempts, anxiety, and gastrointestinal problems. Observations in Our Treatment Program In our adolescent substance abuse intensive outpatient program, during 2020 and 2021, approximately 40% of teens reported that cannabis was their drug of choice. Most of them begin by smoking cannabis once or twice a week, along with drinking some alcohol, and then progressed to vaping highly concentrated THC oils. When they reached the point of smoking and vaping 3 to 4 times a week, their schoolwork declined and cannabis use became the focus of their lives. In our clinical experience, almost every adolescent acknowledges that cannabis causes short-term memory loss. Comorbid attention-deficit/hyperactivity disorder (ADHD), anxiety, depression, and suicidal ideation often become more severe in adolescents who use cannabis. Cannabis appears to impair the prefrontal cortex’s ability for them to recognize their impairments. This becomes a major problematic issue in their treatment. It often takes 3 or 4 weeks of THC abstinence before the adolescent acknowledges the negative effects that cannabis has caused. Many adolescents and young adults with opiate use disorder attempt to use cannabis as a harm reduction means to prevent relapse to opiates. Our experience is that the high from using cannabis increases urges and cravings for opiates and can lead to opiate relapse. The Need for Early Intervention Many adolescents with psychiatric disorders including ADHD, anxiety, depression, and posttraumatic stress disorder (PTSD) will smoke or vape THC in order to feel better with the unfortunate outcome that a significant number of them will become addicted. This presents unique problems for treatment because adolescents will often participate in psychosocial and pharmacological treatments but resist stopping THC use. This in turn leads to negative cognitive and motivational effects that interfere with treatments such as cognitive behavioral therapy (CBT) and dialectical behavior therapy (DBT). Efforts to decrease or eliminate cannabis use may make a significant difference in treatment response. Educating adolescents as to the negative effects of THC as well as how long it stays in the brain (a single ingestion lasts a week, while regularly ingested THC will last a month) can be helpful. We ask the adolescents to commit to 30 days without cannabis to see for themselves how different and clearheaded they feel. If possible, family therapy with parents learning to set appropriate limits can help. Recovery groups may give needed support. There is a paucity of pharmacological studies of antidepressants in this population, with efficacy over placebo not developing until week 13 in 1 study. Significantly, in this study, both groups continued to smoke large amounts of cannabis. From a psychodynamic viewpoint, adolescence is a time of learning to develop the ego strategies to deal with anxiety, loss, and disappointment. If adolescents use THC to cope with these normal developmental challenges, these basic ego factors may be stunted, and this can contribute to them becoming more narcissistic and less empathic young adults. Concluding Thoughts The possible effects of THC on the adolescent brain are often not acknowledged in clinical and research studies. Studies on the marked increase of emotional problems in youth often explore important issues contributing to youth mental health crises such as the influence of psychosocial stressors, social media, bullying, trauma, and the lack of school attendance during the COVID-19 pandemic. This occurs despite growing literature that supports the fact that heavy THC use during brain development increases the risk of psychotic episodes, and negatively impacts cognition, emotional functioning, and school performance. Clinicians need to ask every adolescent, especially those with emotional challenges, about the role that cannabis plays in their life and educate them on the negative impact it may have on their brain development and treatment. Parents, adolescents, teachers, and health care providers need to become aware that regular THC use in adolescence is not a benign activity and can have life-changing consequences. In addition, legislatures and voters need to recognize that THC can be toxic to adolescent brain functioning. Note: This article originally appeared on Psychiatric Times

Among patients with Alzheimer disease, light therapy led to significant improvements in sleep quality, depression, and agitation. Light therapy significantly improved sleep and psychobehavioral outcomes among patients with Alzheimer disease (AD), according to a systematic review and meta-analysis published in PLoS One. The primary treatment for AD is pharmacologic therapy which may alleviate some AD-induced cognitive and memory impairment but are neither curative nor halt disease progression. These medications are associated with side effects including poor appetite, diarrhea, and hallucinations. Increasing attention has been paid to photobiomodulation as a potential nonpharmacologic treatment option, however, no systematic evaluation of the efficacy of light therapy in AD has been performed. Researchers from Weifang Medical University in China searched publication databases through December 2022 for randomized controlled trials evaluating phototherapy in AD. This analysis had 12 outcomes of interest: Sleep efficiency, Interdaily stability, Interdaily variability, Pittsburgh Sleep Quality Index (PSQI), Relative amplitude, Wake after sleep onset (WASO), Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-cog), Cohen-Mansfield Agitation Inventory (CMAI), Cornell Scale for Depression in Dementia (CSDD), Zarit Caregiver Burden Interview (ZBI), Neuropsychiatric Inventory (NPI), and Mini-Mental State Examination (MMSE). A total of 15 studies comprising 598 patients with AD were included in this analysis. The studies were published between 2005 and 2022 and were conducted in 7 countries across North America, Europe, and Asia. The studies recruited patients with mild to moderate AD (n=9) or moderate to severe AD (n=6). The interventions involved light therapy (n=11) or light therapy devices (n=4). Light therapy was associated with significant improvements to: Interdaily stability (mean difference [MD], -0.04; 95% CI, -0.05 to -0.03; I2, 0%; P <.00001), Interdaily variability (MD, -0.07; 95% CI, -0.10 to -0.05; I2, 48%; P <.00001), ADAS-cog scores (MD, -0.46; 95% CI, -0.66 to 0.25; I2, 89%; P <.00001), CMAI scores (MD, -3.97; 95% CI, -5.09 to 2.84; I2, 0%; P <.00001), and CSDD scores (MD, -2.55; 95% CI, -2.98 to -2.12; I2, 0%; P <.00001). Relative to usual care, light therapy improved sleep efficacy (MD, -2.42; 95% CI, -3.37 to -1.48; I2, 60%; P <.00001) and PSQI scores (MD, -1.73; 95% CI, -2.00 to -1.45; I2, 0%; P <.00001). Light therapy also reduced caregiver burden according to the ZBI (MD, -3.57; 95% CI, -5.28 to -1.87; I2, 0%; P <.00001) and psychobehavioral symptoms according to the NPI (MD, -3.07; 95% CI, -4.14 to -2.00; I2, 79%; P <.00001). No significant effect of light therapy was observed for: Relative amplitude (MD, -0.06; 95% CI, -0.14 to 0.01; P =.10), WASO (MD, -20.38; 95% CI, -41.88 to 1.13; P =.06), or MMSE scores (MD, 0.44; 95% CI, -0.71 to 1.59; P =.45). This analysis was limited by pooling data from patients with different AD severity. “[L]ight therapy significantly improved sleep and psychobehavioral symptoms in patients with AD. These findings combined with its low side effects suggest the role of light therapy as a promising treatment for AD,” the researchers concluded. This article originally appeared on Neurology Advisor

CONFERENCE REPORTER Individuals with attention-deficit/hyperactivity (ADHD) show distinct motivations and patterns of substance use. Additionally, treating ADHD symptoms does not decrease an individual’s likelihood of misusing substances. The poster, “Substance Use Motives and Patterns in People With and Without ADHD,” presented at the American Professional Society of ADHD and Related Disorders 2024 conference sought to understand motivations and patterns of substance use in individuals with ADHD compared with controls. Coping Strategies for Individuals with ADHD Investigators recruited 404 participants between the ages of 18-65, and of that 404, 175 self-reported ADHD. The ASRS-v1.1 and ASSIST were used to assess ADHD and substance use, respectively, along with additional scales such as the GAD-7 and an updated Substance Use Motives Measure (SUMM). Participants were also assessed via brief questionnaires that inquired about usage patterns. Then, data were analyzed through correlation and regression models. Results confirmed different substance use motivations and patterns between the ADHD and control groups. Investigators identified distinctive patterns in the ADHD group, such as paradoxical reactions, solitary usage, and heightened susceptibility to cues. However, gender, age, and anxiety levels were not significant mediators. Furthermore, treatment of ADHD did not decrease the likelihood of participant substance misuse, especially among participants with severe ADHD symptoms. For those with ADHD, motives were primarily linked to “coping, social interaction, and performance.” This aligns with the self-medication hypothesis, which posits that “suffering (not pleasure seeking) is at the heart of addictive disorders.” While this hypothesis holds weight, it is important to note that in a previous study seeking to examine ADHD and self-medication, investigators surveyed participants and found that only 36% of used substances for self-medication, while 25% used to get high, and 39% had unknown motivation. Separate research found that adolescents with ADHD are highly likely to have a comorbid substance use disorder, potentially self-medicating, and the most commonly misused substances are marijuana, alcohol, or the combination of the two. New research also indicates individuals with ADHD may use caffeine to self-medicate as well. In order to develop targeted psychotherapy interventions and healthier coping strategies for individuals with ADHD, more knowledge and understanding of these motivations is needed. This article originally appeared on Psychiatric Times

Although there has been a substantial increase in awareness—and, I hope, understanding—of depression, there has been far less public discussion of the challenges that clinicians face in the management of this condition and of the challenges that many patients face getting better. The public are increasingly aware that there are a range of antidepressant medications, and that some of these have problematic adverse effects. However, there has been far less public discussion about the frequent problems of therapeutic nonresponse and how we go about addressing these from a clinical perspective. I wrote Curing Stubborn Depression: Emerging & Breakthrough Therapies for Treatment-Resistant Depression1 to try to help fill this information gap. The book is aimed at patients, interested members of the general public, and potentially non-psychiatry clinicians (other doctors and health workers) interested in the management of patients with mood disorders. The book aims to make clear that response to antidepressant treatments, be they pharmaceutical or psychological, is not always simple, straightforward, or immediate: and that many patients will struggle to get better with standard treatments. But the book also emphasizes that the story is not all negative. There are a range of existing and emerging therapies that offer hope to many of these patients for improved treatment outcomes. The book begins with an overview of depression and a description of the standard pharmaceutical and psychotherapeutic approaches that are most commonly used in its management. It then continues with a chapter exploring what should be considered when initial therapy is not working; how the diagnosis and potential presence of comorbidity should be thought about and addressed; and what second-, third-, and fourth-line pharmacotherapy options tend to look like. This includes a discussion about treatment doses, augmentation, and other strategies. The book then addresses a range of lesser-known but increasingly important and prominent therapies. Chapters address the use of electroconvulsive therapy (ECT), repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation, bright light therapy, deep brain stimulation, ketamine, and the emerging field of psychedelic-assisted psychotherapy. Across these chapters, brief clinical vignettes are used to highlight important aspects of the treatments or areas of research being discussed. These are taken directly from my clinical experience over the years, managing patients with these modalities in clinical practice and in research trials. The history and context of the therapeutic area under discussion are addressed in each chapter, along with some of the controversies and challenges that have emerged over time. There is an intent that some of these chapters will open the eyes of patients to the availability, efficacy, and tolerability of novel treatments such as rTMS, which are underused in certain areas of clinical practice. The book ends with a series of practical suggestions for patients beginning, or who have already embarked on, the journey of treatment for depression. It includes what these patients should expect when being assessed, what to anticipate when commencing treatment, and the sorts of important questions to explore with their treating clinicians. The book aims to help them become actively engaged in their treatment, to understand what is being proposed, and to understand this, as well as the alternatives, in a way that allows them to make meaningfully considered decisions. As such, I am hoping to make our patients more genuine participants and drivers of their care—to be able to work with their treating clinicians in an informed and up-to-date manner. In particular, I hope the book encourages individuals with depression to “set the bar high” in regard to their treatment and recovery. Ultimately, the goal of treatment should be not just an improvement in symptoms but meaningful wellness. The pathway to this end may be a challenging one, but it is possible for many—if not most—individuals to get there. If these individuals are stuck in treatment (if, for example, they have been taking a medication for some time without optimal response), they should advocate for change and should have an expectation of fully engaged and proactive therapy. I wrote this book because of the patients who have been coming to me for help for many years. Because of the patients who have been treated with 3 or 4 selective serotonin reuptake inhibitors (SSRIs) in a row, but nothing else. Because of those who were prescribed a single antidepressant that was not working for months, if not years, at a time. Because of those who spent many hours in psychotherapy, but probably only received some form of supportive counseling despite the fact that they continued to suffer the travails of their condition. Because of those who had been told that “rTMS is a sham” or that “all ECT will do is cause brain damage.” There are many fantastic doctors and therapists out there helping patients with depression who provide excellent all-around care. However, there are also some who remain quite conservative and limited in their scope of practice, who predominantly practice psychopharmacology or psychotherapy, and who are not willing or able to recommend or discuss other treatment options. All patients with depression deserve to understand all of their treatment options and to be able to weigh how these options may or may not be relevant to them. These patients also deserve some sense of hope for the future, and I hope Curing Stubborn Depression can provide some of both to them.

Benzodiazepine treatment during pregnancy is associated with a significantly elevated risk for miscarriage. Benzodiazepine use during pregnancy is associated with an increased risk for miscarriage, according to new research published in JAMA Psychiatry. Health care professionals should carefully consider the risk-benefit ratio when considering benzodiazepine treatment for pregnant individuals. Although benzodiazepines can cross the placental barrier and may potentially impact fetal development, they are still used to treat psychiatric and sleep disorders in pregnancy. Studying the effect of benzodiazepines on pregnancy outcomes is challenging as pregnant women are often precluded from randomized clinical trials and confounding factors can bias results in observational studies. The current study aimed to quantify the risk for miscarriage associated with benzodiazepine use during pregnancy, using a case-time-control design that accounts for confounders. This nationwide, population-based study was conducted in Taiwan using pregnancy data from the National Health Insurance (NHI) database from 2002 to 2019 and the National Birth Certificate Application (BCA) database from 2004 to 2018. Researchers employed a case-time-control design to investigate the association between benzodiazepine use during pregnancy and the risk for miscarriage, comprising 2 analyses: a case-crossover analysis and an exposure time-trend control crossover analysis. The researchers used a conditional logistic model to estimate the odds ratios (ORs) of miscarriage. Overall, the study included 3,067,122 pregnancies among 1,957,601 women (mean age=30.61; SD, 5.91). Of those pregnancies, 136,134 (4.4%) resulted in miscarriage. The researchers then matched the case group of individuals who experienced miscarriage with controls (based on age, psychiatric medical conditions, lifestyle factors, chronic comorbidities, medication use, and health care utilization), resulting in 134,864 pairs of pregnant women. Among the cases cohort, 1502 pregnant women were exposed to benzodiazepines during the risk period only (1 to 28 days before miscarriage), and 2806 were exposed during the reference period only (181 to 208 days before the last menstrual period). Case-time-control ORs confirmed that exposure to benzodiazepines was associated with an increased risk for miscarriage (OR, 1.69; 95% CI, 1.52-1.87). Further, subgroup analyses revealed a dose-response association between benzodiazepine exposure and miscarriage, with the OR increasing from 1.61 (95% CI, 1.43-1.82) for low-dose exposure to 1.86 (95% CI, 1.53-2.25) for high-dose exposure. This nationwide case-time-control study revealed that benzodiazepine use during pregnancy was associated with an approximately 70% increased risk for miscarriage, even after accounting for measurable confounders. Study authors concluded, “Prescribing benzodiazepines should only be considered following a comprehensive evaluation of the potential benefits and risks for both the mother and the child.” The primary limitation of the study is the potential bias resulting from the use of birth certificate-based and claims-based databases for pregnancy and benzodiazepine exposure measures. This article originally appeared on Psychiatry Advisor

Delerium is tied to a significantly increased risk for dementia and death in older adults, with men at particular risk, new research showed. Incident dementia risk was more than three times higher in those who experienced just one episode of delirium, with each additional episode linked to a further 20% increase in dementia risk. The association was strongest in men. Patients with delirium also had a 39% higher mortality risk than those with no history of delirium. "We have known for a long time that delirium is dangerous, and this provides evidence that it's even more dangerous than perhaps we had appreciated," study investigator Emily H. Gordon, MBBS, PhD, a geriatrician and senior lecturer at the University of Queensland, Brisbane, Australia, told Medscape Medical News. "But we also know delirium is preventable. There are no excuses anymore; we really need to work together to improve the hospital system, to implement what are known to be effective interventions," she added. Close Matching Prior studies that suggested an association between delirium and dementia were relatively small with short follow-up and varied in their adjustment for confounders. They also didn't account for the competing risk for death, researchers noted. Investigators used a linked New South Wales (NSW) statewide dataset that includes records of care episodes from all NSW hospitals as well as personal, administrative, clinical, and death information. The study included an eligible sample of 626,467 older adults without dementia at baseline with at least one hospital admission between 2009 and 2014. For these patients, researchers calculated a hospital frailty risk score and collected other information including primary diagnosis and mean length of hospital stay and stay in the intensive care unit. From diagnostic codes, they categorized patients into no delirium and delirium groups and determined the number of delirium episodes. Investigators matched patients in the delirium group to patients with no delirium according to characteristics with potential to confound the association between delirium and risk for dementia, including age, gender, frailty, reason for hospitalization, and length of stay in hospital and intensive care. The matched study sample included 55,211 (mean age, 83 years) each in the delirium and the no delirium groups. Despite matching, the length of hospital stay for the index episode was longer for the delirium group than the no delirium group (mean, 9 days vs 6 days). The primary outcomes were death and incident dementia, determined via diagnostic codes. During a follow-up of 5.25 years, 58% of patients died, and 17% had a new dementia diagnosis. Among patients with at least one episode of delirium, the rate of incident dementia was 3.4 times higher than in those without delirium. After accounting for the competing risk for death, incident dementia risk remained three times higher among the delirium group (hazard ratio [HR], 3.00; 95% CI, 2.91-3.10). This association was stronger for men than women (HR, 3.17 and 2.88, respectively; P = .004). Sex Differences The study is thought to be the first to identify a difference between sexes in dementia risk and delirium, Gordon said. It's possible delirium in men is more severe in intensity or lasts longer than in women, or the male brain is, for whatever reason, more vulnerable to the effects of delirium, said Gordon. But she stressed these are only theories. Investigators also found a mortality rate 1.4 times higher in the delirium group vs those without delirium, equating to a 39% increased risk for death (HR, 1.39; 95% CI, 1.37-1.41). The risk was similar for men and women (interaction P = .62). When researchers categorized delirium by number of episodes, they found each additional episode was associated with a 10% increased risk for death (HR, 1.10; 95% CI, 1.09-1.12). In addition to its large size, long follow-up, and close matching, what sets this new study apart from previous research is it accounted for the competing risk for death, said Gordon. "This is really important because you're not going to get dementia if you die, and in this population, the rate of death is incredibly high," Gordon said. "If we just assume people who died didn't get dementia, then that screws the results." Causal Link? For those who experienced at least one episode of delirium within the first 12 months, each additional episode of delirium was associated with a 20% increased risk for dementia (HR, 1.20; 95% CI, 1.18-1.23). That dose-response association suggests a causal link between the two, Gordon said. "The number one way to prove causality is to do a randomized controlled trial," which isn't feasible with delirium, she said. "By demonstrating a dose-response relationship suggests that it could be a causal pathway." Exact mechanisms linking delirium with dementia are unclear. Delirium might uncover preexisting or preclinical dementia, or it might cause dementia by accelerating underlying neuropathologic processes or de novo mechanisms, the authors noted. Study limitations included the potential for residual confounding from unmeasured variables in the matching criteria. Delirium and dementia diagnoses depended on clinical coding of medical information recorded in the administrative dataset, and under-coding of dementia during hospitalization is well-recognized. Although the study controlled for length of stay in hospital and in intensive care, this may not have fully captured differences in severity of medical conditions. Data about the duration and severity of delirium episodes were also unavailable, which limited the dose-response analysis. Commenting on the findings for Medscape Medical News, Christopher Weber, PhD, Alzheimer's Association as director of Global Science Initiatives, said the results are consistent with other research on the association between delirium and incidents of dementia. The increased risk for dementia following delirium in males is "an interesting finding," said Weber. "This suggests a need for more research to understand the impact of sex differences in delirium, as well as research to see if preventing incidents of delirium could ultimately reduce rates of dementia." The study received support from the National Health and Medical Research Council: Partnership Centre for Health System Sustainability. Gordon and Weber reported no relevant conflicts of interest. Note: This article originally appeared on Medscape Medical News

A tablet-based screening tool that analyzes children’s behavior in response to specific video clips shows promise for enhancing early autism screening, according to a study supported in part by the National Institute of Mental Health. While early autism screening typically depends on parent questionnaires, data suggest the accuracy of these assessments may vary across settings and populations. Objective measurement tools, including digital technologies, could help improve screening in real-world settings and reduce disparities in early screening and identification. What did the researchers do? A toddler watching video clips via the SenseToKnow app. Photo courtsey of Geri Dawson. In the study, researchers Geraldine Dawson, Ph.D. , Guillermo Sapiro, Ph.D. , and colleagues at the Duke Center for Autism and Brain Development tested a tablet-based app called SenseToKnow. The app uses the tablet’s camera to capture a variety of child behaviors, including gaze patterns, facial expressions, head movements, blink rate, and whether the child responded to their name. According to the researchers, this multimodal approach allows them to capture the range of behavioral variations that children with autism may show. During routine health care visits, toddlers watched specially designed video clips while the device recorded their behaviors and quantified them using computer vision, a type of artificial intelligence. The app then used machine learning to analyze the behavioral data, providing a diagnostic classification and a prediction confidence score indicating the reliability of that classification. The app also produced a quality score that indicated whether the app was administered correctly. Study participants included 475 toddlers, ages 17 to 36 months. Of these toddlers, 49 later received an autism diagnosis and 98 later received a diagnosis of developmental delay and/or language delay without autism. What did the researchers find? Overall, the app showed high accuracy for classifying children with autism compared to neurotypical children, and even higher accuracy when the analyses included only the results that had high prediction confidence scores. Classification accuracy remained high when the analyses included data from children with developmental delay and/or language delay. The app correctly classified nine children with autism who were not correctly identified using a standard early autism screening tool, the Modified Checklist for Autism in Toddlers (M-CHAT-Revised with Follow-Up). Classification accuracy increased further when the researchers combined the app analyses with input from the M-CHAT screening tool. Importantly, classification accuracy was consistent regardless of the child’s sex, race, ethnicity, and age. According to the researchers, these initial findings suggest that objective digital screening tools may help reduce existing disparities in early autism screening, although more work is needed to establish the app’s performance across diverse groups. What do the results mean? Advantages of the SenseToKnow app include its usability in real-world settings and the fact that it provides actionable information. For example, a low quality score indicates the app wasn’t administered correctly and may need to be re-administered. On the other hand, a high prediction confidence score lends weight to the classification results and can help identify toddlers who are likely to benefit from further screening and evaluation. Dawson and colleagues are now evaluating SenseToKnow in a variety of contexts. In another NIMH-funded study, the researchers are examining accuracy when parents administer the app at home on their own devices. They are also exploring whether the app can be used to detect early behavioral signs of autism in infants as young as 6-9 months. The researchers emphasize that they do not intend for SenseToKnow to be the only data source for diagnosis. Rather, they envision autism screening as a multi-part process that includes parent-report questionnaires, objective digital screening tools, and other data sources such as electronic health records. They also note that screening is one part of a broader clinical pathway that includes provider training, careful implementation, and built-in links to services, supports, and interventions. “We conclude that quantitative, objective, and scalable digital phenotyping offers promise in increasing the accuracy of autism screening and reducing disparities in access to diagnosis and intervention, complementing existing autism screening questionnaires,” Dawson and colleagues write. Note: This article originally appeared on NIMH

According to the results of a nationwide cohort study1 in Denmark, antidepressants differed in their efficacy for improving symptoms and preventing relapse of major depressive disorder (MDD) in patients over a 2-year period. Designed to emulate a randomized controlled trial (RCT), the investigators compared the long-term responses to 17 antidepressants within their respective pharmacologic classes. Lars Vedel Kessing, MD, of the Copenhagen Affective Disorder Research Centre, Psychiatric Center Copenhagen, and colleagues pointed out that clinical trials of antidepressants are commonly conducted against placebo, with few comparing active agents and fewer extending beyond short-term assessment of acute effects. The investigators referenced a comprehensive, systematic review and meta-analysis2 of 522 trials comprising 21 different antidepressants that differentiated some by acute treatment response, but they pointed out that the need remains for comparisons by long-term effect. “Although antidepressants also reduce relapse rates, there is no consensus on which antidepressants should be preferred as a first option for long-term use,” Kessing and colleagues wrote. This study, the investigators said, “presents for the first time systematic, population-based, nationwide data on comparative 2-year long-term response within 6 antidepressant drug classes and 17 different antidepressants in patients with a first diagnosis of MDD in psychiatric hospital settings.” Differentiating Antidepressants by Long-Term Response The investigators accessed Danish national health care records from 1995 to 2018 to identify 106,920 patients treated for a first diagnosis of a single depressive episode or recurrent depressive disorder who then received a prescribed antidepressant. The cohort excluded patients with additional mental health disorder diagnoses and those who initially obtained multiple prescriptions, or who had antidepressants or antipsychotics prescribed 1 and 5 years prior to the index diagnosis. The antidepressants were compared within pharmacologic classes and within each class to a reference medication. Sertraline was the reference in both the selective serotonin reuptake inhibitor (SSRI) and noradrenalin reuptake inhibitor (NARI) classes, following Danish National Board of Health guidelines stating that sertraline had fewer drug interactions, less association with cardiac effects, and greater safety during breastfeeding. Although 8 pharmacologic classes were identified, the comparative analysis was not conducted when the sample size was less than 100. Six classes were used in the final analysis, then excluding monoamine oxidase inhibitors (MAOIs) versus sertraline, as well as bupropion versus sertraline. In addition to the SSRI and NARI, the classes were serotonin and noradrenalin reuptake inhibitors (SNRIs), venlafaxine reference, adrenergic receptor inhibitors (NaSSAs), mirtazapine reference, tricyclic antidepressants (TCAs), amitriptyline reference, and “other,” with sertraline reference. The study’s primary measure was nonresponse, defined as switch to or add-on of another antidepressant, an antipsychotic or lithium, or inpatient hospitalization for depression. The analyses yielded estimated risk, risk difference, and relative risk (RR) of nonresponse for each antidepressant against the corresponding reference during a 2-year follow-up. Kessing et al reported that within the SSRIs, there was no statistically significant difference in absolute or relative risk difference between citalopram and the reference sertraline—but that in comparison with sertraline, there was statistically significantly higher RR of nonresponse with fluoxetine (1.13; 95% CI, 1.10-1.17), paroxetine (1.06; 1.01-1.10), and escitalopram (1.22; 1.18-1.25). Other analyses’ results included as follows: Sertraline ranked higher, with less risk of nonresponse, than reboxetine in the NARI class. Venlafaxine ranked higher than duloxetine in the SNRI class. Mirtazapine ranked higher than mianserin in the NaSSA class. Imipramine was not statistically different from amitriptyline, which ranked higher than nortriptyline, clomipramine, and dosulepin in the TCA class. Sertraline ranked higher than agomelatine and vortioxetine in the “other” class. Contrasting Antidepressant Assessments Kessing et al contrasted some findings with those from a previous comparison2 of antidepressants by meta-analysis of short-term trials—typically 8 weeks—conducted by Andrea Cipriani, MD, of the Department of Psychiatry at the University of Oxford in England, and colleagues. Cipriani’s group found, for example, no statistically significant differences in odds ratios of response between sertraline and other SSRIs, or between sertraline and reboxetine, agomelatine, or vortioxetine. There was also no statistically significant difference between the TCAs amitriptyline and clomipramine. In addition to the principal differences in these studies of short- and long-term treatment durations, Kessing and colleagues pointed out that their “real-world,” naturalistic, register-based data minimized selection bias as well as recall bias. They also note that the meta-analysis encountered variations between clinical trials in design and cohort criteria and had relatively low statistical power available for some of the comparisons. Cipriani discussed this latest comparison of antidepressants and its focus on longer-term treatment with Psychiatric Times. According to Cipriani, the findings that antidepressants are not all created equal for the maintenance treatment of depression and that there are differences within the same drug class “is in line with what we found for the acute treatment of depression in our previous network meta-analyses of randomized controlled trials.” Although their meta-analysis of all RCTs, including antidepressants vs placebo, revealed few differences in rates of response, subsequent analysis of only the head-to-head comparative trials did reveal diversity in range of efficacy and dropout patterns. In that analysis, agomelatine, amitriptyline, escitalopram, mirtazapine, paroxetine, venlafaxine, and vortioxetine were the most effective; fluoxetine, fluvoxamine, reboxetine, and trazadone were the least efficacious. Cipriani commented on the differences between RCTs and “real world” observations as a basis for comparing efficacy of agents. A principal distinction, he pointed out, is that RCTs apply strict inclusion and exclusion criteria and are designed primarily to assess relative effects. “Some studies have aimed to explore and quantify potential differences in drug effects between RCTs and observational real-world studies for the treatment of depression with selected antidepressants—ie, venlafaxine and duloxetine,” Cipriani noted. “Differences in effect sizes between these real-world studies and RCTs were found, but it remains unclear whether they were due to differences in study populations—selected in RCTs versus unselected in real-world studies—or due to other factors. This is relevant, as lack of representativeness might impact the generalizability of RCT findings to real-world populations, particularly when there are important differences in the distribution of effect modifiers between RCT and [real-world] patient populations.” Cipriani anticipates that additional studies will help overcome the dichotomy between observational and randomized data, and he appreciates that both contribute complementary information that can advance treatment. “The big challenge now is to move from estimating average effects at population level to predicting which is the best outcome for each individual patient, so we can personalize treatment and move a step forward in the field of precision psychiatry,” Cipriani said. Note: This article originally appeared on Psychiatric Times

Early-life exposure to air and noise pollution is associated with a higher risk for psychosis, depression, and anxiety in adolescence and early adulthood, results from a longitudinal birth cohort study showed. While air pollution was associated primarily with psychotic experiences and depression, noise pollution was more likely to be associated with anxiety in adolescence and early adulthood. "Early-life exposure could be detrimental to mental health given the extensive brain development and epigenetic processes that occur in utero and during infancy," the researchers, led by Joanne Newbury, PhD, of Bristol Medical School, University of Bristol, in Bristol, England, wrote, adding that "the results of this cohort study provide novel evidence that early-life exposure to particulate matter is prospectively associated with the development of psychotic experiences and depression in youth." The findings were published online on May 28 in JAMA Network Open. Large, Longitudinal Study To learn more about how air and noise pollution may affect the brain from an early age, the investigators used data from the Avon Longitudinal Study of Parents and Children, an ongoing longitudinal birth cohort capturing data on new births in Southwest England from 1991 to 1992. Investigators captured levels of air pollutants, which included nitrogen dioxide and fine particulate matter with a diameter smaller than 2.5 µm (PM2.5), in the areas where expectant mothers lived and where their children lived until age 12. They also collected decibel levels of noise pollution in neighborhoods where expectant mothers and their children lived. Participants were assessed for psychotic experiences, depression, and anxiety when they were 13, 18, and 24 years old. Among the 9065 participants who had mental health data, 20% reported psychotic experiences, 11% reported depression, and 10% reported anxiety. About 60% of the participants had a family history of mental illness. When they were age 13, 13.6% of participants reported psychotic experiences; 9.2% reported them at age 18, and 12.6% at age 24. A lower number of participants reported feeling depressed and anxious at 13 years (5.6% for depression and 3.6% for anxiety) and 18 years (7.9% for depression and 5.7% for anxiety). After adjusting for individual and family-level variables, including family psychiatric history, maternal social class, and neighborhood deprivation, elevated PM2.5 levels during pregnancy (P = .002) and childhood (P = .04) were associated with a significantly increased risk for psychotic experiences later in life. Pregnancy PM2.5 exposure was also associated with depression (P = .01). Participants exposed to higher noise pollution in childhood and adolescence had an increased risk for anxiety (P = .03) as teenagers. Vulnerability of the Developing Brain The investigators noted that more information is needed to understand the underlying mechanisms behind these associations but noted that early-life exposure could be detrimental to mental health given "extensive brain development and epigenetic processes that occur in utero." They also noted that air pollution could lead to restricted fetal growth and premature birth, both of which are risk factors for psychopathology. Martin Clift, PhD, of Swansea University in Swansea, Wales, who was not involved in the study, said that the paper highlights the need for more consideration of health consequences related to these exposures. "As noted by the authors, this is an area that has received a lot of recent attention, yet there remains a large void of knowledge," Clift said in a UK Science Media Centre release. "It highlights that some of the most dominant air pollutants can impact different mental health diagnoses, but that time-of-life is particularly important as to how each individual air pollutant may impact this diagnosis." Study limitations included limitations to generalizability of the data — the families in the study were more affluent and less diverse than the UK population overall. The study was funded by the UK Medical Research Council, Wellcome Trust, and University of Bristol. Disclosures were noted in the original article. Note: This article originally appeared on Medscape