UNASSIGNED: In this study, mental and physical illnesses, types of traumatic events, frequency of recurrence and sociodemographic characteristics of patients with Posttraumatic Stress Disorder (PTSD) were examined.
UNASSIGNED: The study included the files of 179 patients over the age of 18 who were admitted to the psychiatry outpatient clinic between 01.12.2010 and 31.01.2023 and diagnosed with PTSD. The data was obtained from the hospital automation system and national database.
UNASSIGNED: Of the 44 patients diagnosed with a single comorbid mental illness, 45.5% had mixed anxiety and depressive disorder and 36.4% had a depressive disorder. The rate of patients with comorbid mental illness in PTSD was 51.4%, and chronic physical illness was observed in 59.8%. In our study, sexual trauma and domestic violence had the highest recurrence rates among traumatic events (80%).
UNASSIGNED: Comorbid mental and physical illnesses are common in PTSD. The lack of adequate examination time and an appropriate therapeutic environment causes this diagnosis to be missed by clinicians and prevents patients from getting an ideal health service. In order to prevent recurrences of sexual traumas and domestic violence, the competent authorities must make practices of protecting socially disadvantaged groups more effective and act in accordance with international conventions.

UNASSIGNED: Repetitive transcranial magnetic stimulation (rTMS) therapy could be improved by more accurate and earlier prediction of response. Latent class mixture (LCMM) and non-linear mixed effects (NLME) modeling have been applied to model the trajectories of antidepressant response (or non-response) to TMS, but it is not known whether such models are useful in predicting clinically meaningful change in symptom severity, i.e. categorical (non)response as opposed to continuous scores.
UNASSIGNED: We compared LCMM and NLME approaches to model the antidepressant response to TMS in a naturalistic sample of 238 patients receiving rTMS for treatment resistant depression, across multiple coils and protocols. We then compared the predictive power of those models.
UNASSIGNED: LCMM trajectories were influenced largely by baseline symptom severity, but baseline symptoms provided little predictive power for later antidepressant response. Rather, the optimal LCMM model was a nonlinear two-class model that accounted for baseline symptoms. This model accurately predicted patient response at 4 weeks of treatment (AUC = 0.70, 95% CI = [0.52 - 0.87]), but not before. NLME offered slightly improved predictive performance at 4 weeks of treatment (AUC = 0.76, 95% CI = [0.58 - 0.94], but likewise, not before.
UNASSIGNED: In showing the predictive validity of these approaches to model response trajectories to rTMS, we provided preliminary evidence that trajectory modeling could be used to guide future treatment decisions.

BACKGROUND: Depression and anxiety have become increasingly prevalent across the globe. The rising need for treatment and the lack of clinicians has resulted in prolonged waiting times for patients to receive their first session. Responding to this gap, digital mental health interventions (DMHIs) have been found effective in treating depression and anxiety and are potentially promising pretreatments for patients who are awaiting face-to-face psychotherapy. Nevertheless, whether digital interventions effectively alleviate symptoms for patients on waiting lists for face-to-face psychotherapy remains unclear.
OBJECTIVE: This review aimed to synthesize the effectiveness of DMHIs for relieving depression and anxiety symptoms of patients on waiting lists for face-to-face therapy. This review also investigated the features, perceived credibility, and usability of DMHIs during waiting times.
METHODS: In this systematic review, we searched PubMed, PsycINFO, Cochrane, and Web of Science for research studies investigating the effectiveness of DMHIs in reducing either depression or anxiety symptoms among individuals waiting for face-to-face psychotherapy. The search was conducted in June 2024, and we have included the studies that met the inclusion criteria and were published before June 6, 2024.
RESULTS: Of the 9267 unique records identified, 8 studies met the eligibility criteria and were included in the systematic review. Five studies were randomized controlled trials (RCTs), and 3 studies were not. Among the RCTs, we found that digital interventions reduced depression and anxiety symptoms, but the majority of interventions were not more effective compared to the control groups where participants simply waited or received a self-help book. For the non-RCTs, the interventions also reduced symptoms, but without control groups, the interpretation of the findings is limited. Finally, participants in the included studies perceived the digital interventions to be credible and useful, but high dropout rates raised concerns about treatment adherence.
CONCLUSIONS: Due to the lack of effective interventions among the reviewed studies, especially among the RCTs, our results suggest that waiting list DMHIs are not more effective compared to simply waiting or using a self-help book. However, more high-quality RCTs with larger sample sizes are warranted in order to draw a more robust conclusion. Additionally, as this review revealed concerns regarding the high dropout rate in digital interventions, future studies could perhaps adopt more personalized and human-centered functions in interventions to increase user engagement, with the potential to increase treatment adherence and effectiveness.

BACKGROUND: Fibromyalgia syndrome (FMS) affects 2% to 4% of people, with increasing prevalence in Saudi Arabia reaching 13.4%. FMS can occur in adolescents, known as juvenile-onset fibromyalgia (JFM) with comorbidities including depression, anxiety, and psychological stress. Our patient presented to the child and adolescent psychiatry clinic at King Saud University Hospital Medical City. A year before coming to our clinic, at the age of 15 she was initially diagnosed with JFM followed by a comorbid persistent depressive disorder.
METHODS: As a novel treatment method, a combination treatment approach was used, including a pharmacological intervention with Duloxetine, and a non-pharmacological intervention with interpersonal psychotherapy for adolescents. She completed 16 weeks of therapy while monitoring for duloxetine response and side effects.
RESULTS: Depressive symptoms were in remission by treatment\'s end and continued to be in her first month posttreatment follow-up, and the FMS symptoms were also controlled.
CONCLUSIONS: Our present case highlights a combined approach to treat depression and JFM in adolescents as a novel intervention method thus we strongly recommend utilizing it for similar cases.

Evidence shows that the composition of the gut microbiota (GM) is associated with depression and anxiety disorders. However, the causal relationship between them remains controversial. To investigate the potential causal relationship between the GM and depression/anxiety disorders and to identify specific bacterial taxa, we conducted a 2-sample Mendelian randomization (MR) analysis on the gut microbiome implicated in depression and anxiety disorders. We incorporated summary data from genome-wide association studies (GWAS) of the microbiome derived from 7738 individuals in the Dutch Microbiome Project and 18,340 individuals in the MiBioGen consortium as our exposure variable. Concurrently, the GWAS of depression and anxiety disorders was employed as our outcome variable. The principal estimates were procured using the inverse-variance weighted test complemented by 4 robust methods: MR Egger, weighted median, simple mode, and weighted mode. In addition, we performed comprehensive sensitivity and directionality analyses. The results showed that 5 bacterial taxa were positively correlated with depression, 6 were negatively correlated; 5 were positively correlated with anxiety disorders, and 11 were negatively correlated. This study provides new insights into the connection between the GM and the pathogenesis of depression and anxiety disorders and offers new perspectives for the diagnosis and treatment of these disorders.

BACKGROUND: The prevalence of major depressive disorder (MDD) poses significant global health challenges, with available treatments often insufficient in achieving remission for many patients. Digital health technologies, such as SMS text messaging-based cognitive behavioral therapy, offer accessible alternatives but may not reach all individuals. Email communication presents a secure avenue for health communication, yet its effectiveness compared to SMS text messaging in providing mental health support for patients with MDD remains uncertain.
OBJECTIVE: This study aims to compare the efficacy of email versus SMS text messaging as delivery platforms for supporting patients with MDD, addressing a critical gap in understanding optimal digital interventions for mental health care.
METHODS: A randomized noninferiority pilot trial was conducted, comparing outcomes for patients receiving 6-week daily supportive messages via email with those receiving messages via SMS text message. This duration corresponds to a minimum of 180 days of message delivery. The supportive messages maintained consistent length and structure across both delivery methods. Participants (N=66) were recruited from the Access 24/7 clinic in Edmonton, Alberta, among those who were diagnosed with MDD. The outcomes were measured at baseline and 6 months after enrollment using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and the World Health Organization Well-Being Index (WHO-5).
RESULTS: Most of the participants were females (n=43, 65%), aged between 26 and 40 years (n=34, 55%), had high school education (n=35, 58%), employed (n=33, 50%), and single (n=24, 36%). Again, most participants had had no history of any major physical illness (n=56, 85%) and (n=61, 92%) responded \"No\" to having a history of admission for treatment of mood disorders. There was no statistically significant difference in the mean changes in PHQ-9, GAD-7, and WHO-5 scores between the email and SMS text messaging groups (mean difference, 95% CI: -1.90, 95% CI -6.53 to 2.74; 5.78, 95% CI -1.94 to 13.50; and 11.85, 95% CI -3.81 to 27.51), respectively. Both supportive modalities showed potential in reducing depressive symptoms and improving quality of life.
CONCLUSIONS: The study\'s findings suggest that both email and SMS text messaging interventions have equivalent effectiveness in reducing depression symptoms among individuals with MDD. As digital technology continues to evolve, harnessing the power of multiple digital platforms for mental health interventions can significantly contribute to bridging the existing treatment gaps and improving the overall well-being of individuals with depressive conditions. Further research is needed with a larger sample size to confirm and expand upon these findings.
BACKGROUND: ClinicalTrials.gov NCT04638231; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552095/.

OBJECTIVE: To assess the effectiveness of Internet-based self-help interventions in treating depression in adolescents and young adults.
METHODS: A systematic search was conducted across six databases, including PubMed, to identify randomized controlled trials (RCTs) that satisfied the specified inclusion and exclusion criteria. The intervention measure consisted of Internet-based self-help interventions.
RESULTS: A total of 23 randomized controlled trials (RCTs) were included in this analysis. Meta-analysis indicated that Internet-based self-help therapies significantly reduced depression scores in adolescents and young adults. (OR = -0.68, 95%CI [-0.88, -0.47], P < 0.001). We examined the effects of patient recruitment from various regions, medication usage, therapist involvement, weekly intervention time, and intervention duration. Patients selected from school, primary healthcare centers, clinics and local communities had better results. Intervention lasting 30 to 60 min and 60 to180 minutes per week were effective in the short term.
CONCLUSIONS: The internet-based self-help intervention can be effective in treating depression in adolescents and young adults. However, factors such as patient recruitment locations, medication usage, Therapists\' involvement, weekly intervention time, and intervention duration interacted with the outcome. Subgroup analysis on potential adverse effects and gender was impossible due to insufficient data from the included studies.

Objective: While collaborative care is known to improve depressive and anxiety symptoms in primary care, comparative effectiveness studies of virtual collaborative care versus virtual specialty psychiatry treatment in real world settings are lacking. This study examined patient depressive and anxiety symptoms over 6 months in collaborative care versus specialty psychiatry.
Methods: This was an observational study with target trial emulation in a large, community-based, integrated health care system. Participants were ≥18 years old with mild-moderate depressive or anxiety symptoms measured by the Patient Health Questionnaire-9 or Generalized Anxiety Disorder-7 Scale. Exclusion criteria included acute suicide risk. Patients were assigned to collaborative care or specialty psychiatry, and symptoms were measured 6 months after treatment initiation using linear mixed-effects regression with inverse probability of treatment weighting.
Results: There were N = 10,380 patients (n = 1,607 in collaborative care; n = 8,773 in specialty psychiatry) with depressive disorders and N = 2,935 (n = 570 in collaborative care; n = 2,365 in specialty psychiatry) with anxiety disorders. Model effects at 6 months showed significant symptom improvement for patients in collaborative care (adjusted mean difference [AMD] = -9.0, 95% CI, -9.7, -8.4 for depression; -5.4, 95% CI, -6.2, -4.7 for anxiety) and in specialty psychiatry (AMD = -5.0, 95% CI, -5.6, -4.5 for depression; -2.8, 95% CI, -3.6, -2.1 for anxiety), with patients in collaborative care showing significantly greater improvement compared to those in specialty psychiatry (AMD = -4.0, 95% CI, -4.7, -3.3, P < .0001 for depression; AMD = -2.6, 95% CI, -3.4, -1.8, P < .0001 for anxiety).
Conclusions: Virtual collaborative care was at least as effective as specialty psychiatry for depression and anxiety. Collaborative care implementation can support national guidelines regarding depression and anxiety screening and treatment.

OBJECTIVE: There is a large treatment gap for mental health conditions in sub-Saharan Africa where most patients who receive any care do so from lay primary health care workers (PHCW). We sought to examine the experiences of PHCW who provide care for older people with depression in Nigerian primary health care (PHC) settings.
METHODS: Qualitative study design. A total of 24 PHCW participated. Using in-depth key informant interviews (KIIs), we explored the views of 15 PHCW selected from 10 rural and urban PHCs in South-Western Nigeria. An additional focus group discussion comprising nine participants was also conducted to discuss emerging themes from KIIs. Data were analysed using thematic analysis.
RESULTS: Three overall themes were identified: views about depression, treatment options, and community outreach implications. Participants perceived depression in older people as being characterised by a range of mood, behavioural, and cognitive symptoms which made clinical assessments particularly challenging. Common treatment options used by PHCW included general advice and counselling, as well as frequent need to prescribe mild analgesics, vitamins and occasional sedatives in line with patients\' expectations. Antidepressants were rarely used even though PHCW are authorised. While home visits are part of their expected work schedule, PHCW rarely implemented these due to non-availability of transport facilities. Mobile technology was identified as a possible way of overcoming this constraint to providing community based mental healthcare for older people.
CONCLUSIONS: PHCWs perceived that patients\' poor cognitive performance, expectations to prescribe sedatives, analgesics and vitamins, as well as non-existence of community-based services were existing barriers to providing evidenced based continued care for older people with depression in the study settings.

Depression is a major public health problem worldwide and is closely related with systemic inflammatory responses. Additionly, physical activity (PA) is thought to be associated with lower levels of depression and inflammatory markers. This study aimed to elucidate the complex interactions between PA, depression, and inflammatory markers. Based on the National Health and Nutrition Examination Survey (NHANES), various logistic regression were applied to analyze the pairwise correlations among the three. Restrictive cubic splines were constructed to explore the nonlinear relationship between PA and depression. Mediation models were used to identify the mediating role of inflammatory markers. The findings revealed a positive link between depression and inflammatory marker, whereas PA was inversely correlated with both inflammatory marker and depression. Particularly, we noticed the greatest reduction in the risk of depression when the level of PA was between 1200 and 1722 MET-min/week. Besides, we demonstrated that inflammatory markers mediate the potential effects of physical inactivity on depression, ranging from 1.72 % to 6.25 %. In conclusion, PA appear to protect against depression, in which inflammatory markers may play a mediating role. Moreover, we determined the optimal dosage of PA to minimize the likelihood of depression, thereby offering valuable guidance for managing depression.