This study builds on the work by Rehman et al (2022) who argued that transcranial magnetic stimulation (TMS) treatment not only helps treat depression but also decreases sleep problems such as difficulty falling asleep,staying asleep, and waking too early. The present study further explores differences in sleep onset latency, meaning the time it takes to fall asleep, and duration of sleep per night in the pre and post treatment phases of rTMS. The information regarding major attributes of sleep is critical because recent research shows that about 90% of patients with major depressive disorder (MDD) also struggle with sleep disorders (Li et al., 2022), and sleeping for less than seven hours may eventually lead to sleep deprivation (Hirshkowitz et al., 2015), with increased risk of physical and mental health problems (Sheehan et al, 2019). Sleep onset latency estimates vary from individual to individual but typical sleep latency is considered between 10 to 20 minutes (Jung et al, 2013). As it has been shown that overall sleep problems improve with rTMS, we hypothesized that self-reported sleep onset latency will decrease, and sleep duration will increase.

All participants met inclusion criteria for MDD diagnosis and completed a full course of TMS treatment (N=470; Mean age=53.45, SD=13.73). The sample was mostly male (81%) and ethnically diverse: 77.7% non-Hispanic White, 13.3% Black Americans, 1.9% Asian, 0.2 % Asian Indian, and 1.9% other ethnicities. Sleep problems were assessed using the following questions at the pre and post treatment stages: the number of minutes it takes to fall asleep and duration of sleep each night.

A Wilcoxon matched-pairs signed-rank test was conducted to determine whether there was a difference in sleep onset latency and hours of sleep per night between pre and post intervention. The results indicated a significant difference in time to fall asleep between pre and post treatment (pre-treatment M = 1.19, SD = 0.99, post-treatment M = 0.93, SD = 0.91; z = -5.01, p < .001. In addition, there was a significant increase in the minutes of sleep per night in pre (M = 6.11, SD = 2.07) compared to the post treatment (M = 6.32, SD = 1.77), z = -2.56, p = .010.

Reduced sleep is known to negatively impact mood, cognitive ability, work performance, and immune function (Besedovsky et al., 2012; Killgore, 2010; Massar et al, 2019; Vandekerckhove & Wang, 2018). Similarly, longer sleep onset latency can cause an individual to enter the first sleep stage later than expected and complete fewer sleep cycles. The results of the present study show the effectiveness of rTMS in decreasing sleep onset latency and increasing the duration of sleep. Given the comorbidity and bidirectionality between sleep disturbances and mood disorders (Fang et al., 2019; Palagini et al., 2019), further researching treatments such as rTMS to improve sleep as a means to also improve mood is crucial. We propose acquiring knowledge about sleep attributes as an essential part of clinicians’ work early on in the rTMS treatment in order to monitor an individual’s global functioning level in light of improved sleep.

Police officers are important gatekeepers in suicide prevention, but at the same time, cases of suicidal behaviour and suicides are, among other deaths, one of the most stressful parts of their job. Police trustees are a special group of police officers who offer support to their colleagues in ambiguous or stressful cases.

The objective of this study was to educate and train the police trustees on suicide prevention and help them dealing with the suicide related situations. Besides, we aimed to evaluate the effects of the intervention.

13 police trustees (Mage = 39,23 years; SDage = 16,23) participated in our 1-day workshop. We used a pre-post evaluation design with both quantitative and qualitative questions. We used Perceived Stress Scale PSS (Cohen et al., 1983), and additional questions on self-perceived competence and anxiety regarding suicide related situations as evaluation tools.

Preliminary results show that according to the questionnaire's norms, four participants reported slightly higher level of perceived stress prior to our training. Further on, most common answers on self-perceived competence questions were either moderately or quite competent in suicide related situations, but participants also feel moderately to severely anxious in these situations. Our workshop met the expectations of a vast majority (86%) of attendees.

In our opinion, preliminary results show a great need for further cooperation with the police in suicide prevention initiatives. Follow up evaluation will serve as an indicator of the workshop's efficacy and will serve as guideline for its improvement.

A number of scales are used to estimate the severity of depression. However, differences between self-report and clinician rating, multi-dimensionality and different weighting of individual symptoms in summed scores may affect the validity of measurement. In this study we examined and integrated the psychometric properties of three commonly used rating scales.

The 17-item Hamilton Depression Rating Scale (HAMD-17), the Montgomery–Asberg Depression Rating Scale (MADRS) and the Beck Depression Inventory (BDI) were administered to 660 adult patients with unipolar depression in a multi-centre pharmacogenetic study. Item response theory (IRT) and factor analysis were used to evaluate their psychometric properties and estimate true depression severity, as well as to group items and derive factor scores.

The MADRS and the BDI provide internally consistent but mutually distinct estimates of depression severity. The HAMD-17 is not internally consistent and contains several items less suitable for out-patients. Factor analyses indicated a dominant depression factor. A model comprising three dimensions, namely ‘observed mood and anxiety’, ‘cognitive’ and ‘neurovegetative’, provided a more detailed description of depression severity.

The MADRS and the BDI can be recommended as complementary measures of depression severity. The three factor scores are proposed for external validation.