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Background: Selective Serotonin Reuptake Inhibitors (SSRIs) represent a diverse class of medications widely prescribed for depression and anxiety. Despite their common use, there is an absence of large-scale, real-world evidence capturing the heterogeneity in their effects on individuals. This study addresses this gap by utilizing naturalistic search data to explore the varied impact of six different SSRIs on user behavior., Methods: The study sample included ∼508 thousand Bing users with searches for one of six SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline) from April-December 2022, comprising 510 million queries. Cox proportional hazard models were employed to examine 30 topics (e.g., shopping, tourism, health) and 195 health symptoms (e.g., anxiety, weight gain, impotence), using each SSRI as a reference. We assessed the relative hazard ratios between drugs and, where feasible, ranked the SSRIs based on their observed effects. We used Cox proportional hazard models in order to account for both the likelihood of users searching for a particular topic or symptom and the associated time to that search. The temporal aspect aided in distinguishing between potential symptoms of the disorder, short-term medication side effects, and later appearing side effects., Results: Differences were found in search behaviors associated with each SSRI. E.g., fluvoxamine was associated with a significantly higher likelihood of searching weight gain compared to all other SSRIs (HRs 1.85-2.93). Searches following citalopram were associated with significantly higher rates of later impotence queries compared to all other SSRIs (HRs 5.11-7.76), except fluvoxamine. Fluvoxamine was associated with a significantly higher rate of health related searches than all other SSRIs (HRs 2.11-2.36)., Conclusions: Our study reveals new insights into the varying SSRI impacts, suggesting distinct symptom profiles. This novel use of large-scale, naturalistic search data contributes to pharmacovigilance efforts, enhancing our understanding of intra-class variation among SSRIs, potentially uncovering previously unidentified drug effects., Competing Interests: Declaration of competing Interest NCJ has a received grant from Boehringer-Ingelheim. NCJ has edited a book through Academic Press and receives book royalties, and NCJ also receives speaking fees related to his research. MVH has worked as a paid consultant for Artisight and ChatNexus. EYT was previously employed by Microsoft Research., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Mental health disorders are highly prevalent, yet few persons receive access to treatment; this is compounded in rural areas where mental health services are limited. The proliferation of online mental health screening tools are considered a key strategy to increase identification, diagnosis, and treatment of mental illness. However, research on real-world effectiveness, especially in hard to reach rural communities, is limited. Accordingly, the current work seeks to test the hypothesis that online screening use is greater in rural communities with limited mental health resources. The study utilized a national, online, population-based cohort consisting of Microsoft Bing search engine users across 18 months in the United States (representing approximately one-third of all internet searches), in conjunction with user-matched data of completed online mental health screens for anxiety, bipolar, depression, and psychosis (N = 4354) through Mental Health America, a leading non-profit mental health organization in the United States. Rank regression modeling was leveraged to characterize U.S. county-level screen completion rates as a function of rurality, health-care availability, and sociodemographic variables. County-level rurality and mental health care availability alone explained 42% of the variance in MHA screen completion rate (R 2  = 0.42, p < 5.0 × 10 -6 ). The results suggested that online screening was more prominent in underserved rural communities, therefore presenting as important tools with which to bridge mental health-care gaps in rural, resource-deficient areas., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Individuals with body dysmorphic disorder (BDD) suffer from distressing or impairing preoccupations with perceived imperfections in their appearance. This often-chronic condition is associated with significant functional impairment and elevated rates of psychiatric comorbidity and morbidity, including depression, substance use disorders, and suicidality. Cognitive behavioral therapy (CBT) for BDD has been shown to be efficacious. However, this intervention is long (up to 24 weeks) relative to many manualized approaches for other related conditions, there is a significant shortage of clinicians trained in CBT for BDD, and some patients drop out of treatment and/or do not respond. Thus, there is great interest in understanding and predicting who is most likely to respond, to better allocate clinical resources. This secondary data analysis of participants enrolled in prior uncontrolled and controlled studies of CBT for BDD explored whether early response to CBT, operationalized as percentage change in symptom severity within the first four weeks and the first 12 weeks of this 24-week treatment, predicts clinical outcomes for patients with BDD (n = 90). The findings indicated that minimal early symptom change was not indicative of eventual non-response. This suggests that patients and clinicians should not be discouraged by limited early improvement but should instead continue with a full course of treatment before reevaluating progress and alternative interventions. Overall, the results support the view that treatment success is more likely if a longer CBT protocol is followed. More work is needed to understand mechanisms of change and thus match optimal interventions to patient characteristics., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Introduction: Most people with psychiatric illnesses do not receive treatment for almost a decade after disorder onset. Online mental health screens reflect one mechanism designed to shorten this lag in help-seeking, yet there has been limited research on the effectiveness of screening tools in naturalistic settings., Material and Methods: We examined a cohort of persons directed to a mental health screening tool via the Bing search engine (n = 126,060). We evaluated the impact of tool content on later searches for mental health self-references, self-diagnosis, care seeking, psychoactive medications, suicidal ideation, and suicidal intent. Website characteristics were evaluated by pairs of independent raters to ascertain screen type and content. These included the presence/absence of a suggestive diagnosis, a message on interpretability, as well as referrals to digital treatments, in-person treatments, and crisis services., Results: Using machine learning models, the results suggested that screen content predicted later searches with mental health self-references (AUC = 0·73), mental health self-diagnosis (AUC = 0·69), mental health care seeking (AUC = 0·61), psychoactive medications (AUC = 0·55), suicidal ideation (AUC = 0·58), and suicidal intent (AUC = 0·60). Cox-proportional hazards models suggested individuals utilizing tools with in-person care referral were significantly more likely to subsequently search for methods to actively end their life (HR = 1·727, p = 0·007)., Discussion: Online screens may influence help-seeking behavior, suicidal ideation, and suicidal intent. Websites with referrals to in-person treatments could put persons at greater risk of active suicidal intent. Further evaluation using large-scale randomized controlled trials is needed., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objective: Although recent research has begun to examine the impact of elevated anxiety on evolutionary fitness, no prior research has examined anxiety across a continuum. Such research is important as the effect of traits across a continuum on fertility hold important implications for the levels and distribution of the traits in later generations., Method: In a three-generational sample (N = 2657) the linear and quadratic relationship between anxiety and the number of children, grandchildren, and great-grandchildren 15 years later was examined., Results: The findings suggested that anxiety had a positive quadratic relationship with the number of children, grandchildren, and great-grandchildren 15 years later. These relationships were not significantly moderated by sex. Moreover, most of the variance between anxiety and the number of great-grandchildren was explained by anxiety's influence on the number of children and grandchildren, as opposed to anxiety having an independent direct impact on the number of great-grandchildren., Conclusion: These findings suggest that extreme values from the mean anxiety are associated with increased evolutionary fitness within the modern environment., (Copyright © 2018. Published by Elsevier Ltd.)