Search Results (17)

Migraine is a common disabling primary headache disorder with significant personal and socio-economic impacts. A combination of medication and non-pharmacological therapies is essential for migraine management. Outpatient multidisciplinary headache therapy has not yet been evaluated in Switzerland. This study evaluates the effectiveness of the headache management program at Inselspital, Bern University Hospital, in improving headache-related disability in migraine patients. This open-label pilot study used prospectively assessed routine data from our headache registry. Participants aged 18 years or older with a diagnosis of migraine, confirmed by a headache specialist, were included. The program consisted of seven weekly sessions, each with a 50 min educational lecture and a 30 min progressive muscle relaxation (PMR) exercise. Primary outcomes were headache-related impact and disability, measured by the Headache Impact Test 6 (HIT-6) and Migraine Disability Assessment (MIDAS). Secondary outcomes included symptoms of anxiety, measured by the Generalized Anxiety Disorder 7-item scale (GAD-7), and symptoms of depression, assessed using the eight-item Patient Health Questionnaire depression scale (PHQ-8). Data were analysed using paired t-test and Wilcoxon signed rank tests. Significant improvements were observed in HIT-6 scores (pre-program: 65.2; post-program: 61.9; p = 0.012) and MIDAS scores (pre-program: 38; post-program: 27; p = 0.011), while PHQ-8 also showed a statistically significant reduction. Although the GAD-7 scores improved numerically, this change was not statistically significant. These findings suggest that the headache management program may reduce headache burden and disability; however, further research with larger samples is needed to confirm these preliminary results. Full article

This investigation explores the application of supervised machine learning regression approaches to predict various responses, including penetration, bead width, bead height, hardness, ultimate tensile strength, and percentage elongation in autogenous TIG-, A-TIG-, and TIG-welded joints of SS304H, which is considered as an advanced high-temperature resistant material. The machine learning (ML) models were constructed based on the data gathered from 50 experimental runs, considering eight key input variables: gas flow rate, torch angle, filler material, welding pass, flux application, root gap, arc gap, and heat input. A total of 80% of the collected dataset was used for training the models, while the remaining 20% was reserved for testing their performance. Six ML algorithms—Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting Regression (GBR), and Extreme Gradient Boosting (XGBoost)—were implemented to assess their predictive accuracy. Among these, the XGBoost model has demonstrated the highest predictive capability, achieving R² scores of 0.886 for penetration, 0.926 for width, 0.915 for weld bead height, 0.868 for hardness, 0.906 for ultimate tensile strength, and 0.926 for percentage elongation, along with the lowest values of RMSE, MAE, and MSE across all responses. The outcomes establish that machine learning models, particularly XGBoost, can accurately predict welding characteristics, marking a significant advancement in the optimization of TIG welding parameters. Consequently, integrating such predictive models can substantially enhance the precision, reliability, and overall efficiency of welding processes. Full article

Background: While cardiac rehabilitation (CR) primarily focuses on restoring physical strength, preventing relapse, and reducing rehospitalization rates, psychological interventions play a complementary role by supporting mental health, which is crucial for patients’ long-term adherence and overall recovery. The effectiveness of psychological interventions in CR is debated, and while technologies like virtual reality (VR) therapy show promise, they have limitations for patients with coronary artery disease (CAD). Therefore, this study examines non-sleep deep rest (NSDR) relaxation, a novel and easily implementable technique, and compares its impact on depression, anxiety, and stress with VR therapy and standard care. Methods: Forty-five CAD patients undergoing CR in ambulatory conditions were divided into three groups: the NSDR group, which received eight sessions of NSDR relaxation as part of their rehabilitation; the VR group, which received eight sessions of VR therapy as part of their rehabilitation; and the control group, which received standard care including Schultz Autogenic Training (SAT). The outcomes were measured using the Hospital Anxiety and Depression Scale (HADS) and the Perception of Stress Questionnaire (PSQ). Results: Both NSDR relaxation and VR therapy were effective in reducing the HADS total score, anxiety levels, the PSQ general score, and emotional tension. No significant differences were observed between the two treatment approaches. However, SAT was found to be insufficient for effectively improving the mental state of cardiac patients. Conclusions: This study suggests that NSDR relaxation is an effective psychotherapeutic intervention in CR. NSDR and VR therapy showed similar benefits, offering promising alternatives to traditional methods. Integrating these techniques could enhance patient outcomes and adherence in CR. Further research is needed to refine these interventions and optimize their clinical application. Full article

This study explores the application of machine learning techniques for predicting generic mill liner wear in semi-autogenous grinding (SAG) mills used in mineral processing. Various models were developed and compared using data from 143 liner measurements across 36 liner cycles from ten different SAG mills. The research initially focused on individual mill modeling, employing simple linear regression, first-order kinetic approach, Multiple Linear Regression (MLR), tree-based methods (Decision Trees, Random Forests, XGBoost), and Multilayer Perceptron (MLP). Results showed that simple linear regression provided sufficient accuracy, with other methods only slightly improving performance. This study then developed a combined model using data from multiple mills. MLR and advanced machine learning techniques were applied for this generic model, with XGBoost emerging as the most successful. In the interpolation scenario involving a mill similar to those in the training data, the XGBoost model achieved a mean absolute percentage error (MAPE) of 5.27%. For the extrapolation scenario, with a mill larger than those in the training set, the MAPE increased slightly to 6.12%. These results demonstrate the potential of machine learning approaches in creating effective generic models for mill liner wear prediction. However, this study also highlights the potential for improving predictive models by incorporating additional key parameters such as liner and ball material properties. Full article

Reliable monitoring of mineral process systems is key to more efficient plant operation. Multivariate statistical process control based on principal component analysis is well-established in industry but may not be effective when dealing with dynamic nonlinear or transient processes, where process behavior may change rapidly from time to time. Although a large variety of nonlinear models have been proposed to address these problems, the monitoring of complex dynamic process systems remains challenging. Isolation forests are unsupervised machine learning models that provide an interesting approach to process monitoring that has not been explored extensively yet. In this investigation, this approach is compared with traditional multivariate statistical process monitoring based on principal component models. Three real-world case studies are considered. The first case study is based on coal flotation, the second is based on features extracted from a platinum group metal flotation froth; and the third is based on data from an industrial semi-autogenous grinding circuit. In each case, the models were trained on data representing normal operating conditions and then tested on new process data that were generally different from the training data to test their ability to identify these data as out-of-control. The isolation forest models performed better than the principal component models when the data were nonlinear, but not when the data associated with normal operation and faulty conditions were linearly separable, as was the case with the flotation data. Full article

Headache disorders are a significant global health burden, leading to reduced quality of life. While vast pharmacological treatments are available, they may be associated with adverse effects or inadequate efficacy for some patients, therefore there is a need for exploring alternate treatment strategies. This review gives a brief explanation and evaluation of some established and emerging non-pharmacological approaches for headache management, focusing on nutraceuticals and diet, acupuncture, cognitive behavioral therapy (CBT), biofeedback, relaxation techniques, autogenic training, and neuromodulation. Special consideration is given to psychological interventions as they increase patient self-efficacy and provide strategies for managing chronic pain. Future research should focus on optimizing these therapies, identifying patient-specific factors influencing their effectiveness, and integrating them into holistic headache management strategies. Full article

Background: Teaching is recognized as a highly challenging profession. Experience of chronic stress is a risk factor for poor mental and physical well-being, and burnout. There is limited knowledge regarding optimal interventions to address stress and burnout among teachers. Objective: To undertake a scoping review of the literature in the last five years to determine various psychological interventions to address stress and burnout among teachers. Method: The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews was followed. Relevant search terms were used to determine different interventions adopted to reduce teachers’ stress and burnout. Articles published between 2018 and 2022 were identified using five bibliographic databases. Relevant articles were extracted, reviewed, collated, and thematically analyzed, and findings s were summarized. Results: Forty studies conducted in Asia, North America, Oceania, Europe, and Africa, met the inclusion criteria. Sixteen kinds of burnout and stress-reduction interventions were identified. The most popularly studied intervention were Mindfulness-Based Interventions alone or in combination with yoga or Cognitive Behavioural Therapy (CBT), followed by Rational Emotive Behavioral Therapy (REBT). Mindfulness-Based Interventions led to decreased overall Teacher Stress Inventory (TSI) and emotional exhaustion subscale scores. REBT, primarily used with special education teachers, especially in Africa, has also shown positive results. Other interventions reporting positive outcomes include Inquiry-Based Stress Reduction (IBSR), the Stress Management and Resiliency Training Program (SMART), Cyclic Meditation, Group Sandplay, Progressive Muscle Relaxation, Autogenic Training, Sport-Based Physical Activity, Emotional Intelligence Ability Models and Christian Prayer and Prayer-Reflection. Conclusions: Stress and burnout can have a negative impact on teachers and, very often, on the students they teach. Implementing suitable school-based interventions is necessary to improve teachers’ stress-coping ability, reduce the likelihood of burnout and improve general well-being. Policymakers, governments, school boards and administrators should prioritize the implementation of school-based awareness and intervention programs. Full article

Autogenic training (AT) is a well-established self-induced relaxation technique based on autosuggestion. From the past two decades, an increasing number of AT studies strongly suggests the practical usefulness of psychophysiological relaxation in the area of medicine. Despite this interest, to date, limited critical clinical reflection on the application and effects of AT in mental disorders exists. The present paper reviews psychophysiological, psychopathological, and clinical aspects of AT in persons with mental disorders with emphasis on implications for future research and practice. Based on a formal literature search, 29 reported studies (7 meta-analyses/systematic reviews) were identified that examined the effects and impact of AT on mental disorders. The main psychophysiological effects of AT include autonomic cardiorespiratory changes paralleled by central nervous system activity modifications and psychological outputs. Studies demonstrate consistent efficacy of AT in reducing anxiety and medium range positive effects for mild-to-moderate depression. The impact on bipolar disorders, psychotic disorders, and acute stress disorder remains unexplored. As an add-on intervention psychotherapy technique with beneficial outcome on psychophysiological functioning, AT represents a promising avenue towards expanding research findings of brain–body links beyond the current limits of the prevention and clinical management of number of mental disorders. Full article

Painful post-traumatic trigeminal neuropathy (PTTN) is a known complication of dental implant therapy. Patients with PTTN develop sensory abnormalities in the orofacial region, which may be a psychosocial aspect, and dentists should assess somatosensory testing and psychosocial factors. The patients were assessed using quantitative sensory testing (QST). A 64-year-old female presented with allodynia of the left lower lip that occurred after a surgical implant procedure. Persistent pain started 4 months after the placement of two dental implants in the mandible. Sensory testing of these areas revealed warm hyposensitivity and mechanical hypersensitivity of the mandibular region. We also assessed PTTN-related perceived injustice using the Injustice Experience Questionnaire. The patient refused medication therapy such as pregabalin; therefore, autogenic training was adopted as an alternative management strategy. We conclude that for expensive dental procedures, such as implant placement, sufficient consensus should be obtained preoperatively before proceeding with surgery. Full article

Despite the growing popularity of relaxation training, the effectiveness of an autogenic training (AT) as a method of dealing with sleep problems in group of student athletes is unknown. Therefore, this study aimed to fill this gap. University athletes with decreased sleep quality (selected from 209 participants) were randomly assigned to the experimental (EG, n = 11) and control (CG, n = 11) groups similar in terms of sleep quality, age, gender, type of sport discipline and sport experience. During the 14 days dedicated to performing relaxation training in the form of an audio recording, electronic daily logs and actigraphy were used to monitor the athletes’ sleep and daily activity. The EG listened to the recording with suggestions based on AT and CG only to the background music. Pre- and post-measurements of sleep quality by means of the Pittsburg Sleep Quality Index (PSQI) and physiological stress reactions by biofeedback device were performed. In EG and CG, the parameters of sleep and daily activity obtained by actigraphy and daily logs as well as physiological indicators of emotional reactivity did not differ. Sleep quality in PSQI significantly increased after AT usage in EG. AT seems to be an effective method for university athletes in improving subjective sleep quality, but further studies are necessary. Full article

Introduction: People with depression often complain of dysfunction in cognitive processes, particularly attention. Pharmacotherapy is one of the most commonly used methods of treating depressive disorders and related attention difficulties. Patients also benefit from various forms of psychotherapy and frequently support themselves with alternative therapeutic methods. The purpose of this study was to examine whether a 15-min-long relaxation training session could improve the efficiency of attention and perceptiveness in individuals diagnosed with depressive disorders. Methods: Forty-two individuals participated in the study, including 20 individuals diagnosed with recurrent depressive disorder (rDD) and 22 healthy subjects (comparison group, CG). The so-called continuous performance test in the Polish version (Attention and Perceptiveness Test, APT) was applied in the study. In the first stage, the participants completed the 6/9 version of the APT test and then took part in a 15-min relaxation training session (autogenic training developed by the German psychiatrist Johannes Heinrich Schultz). The next step of the study was to perform APT again (parallel version—3/8). Results: The analyses showed statistically significant differences (p < 0.001) in the results obtained in the two versions of APT between the studied groups (rDD versus CG) in terms of the perceptual speed index. These differences were seen both before and after the introduction of the relaxation training. There was a statistically significant difference in the value of the perceptual speed index before and after the applied relaxation training for the subjects with depression (p = 0.004) and for the whole study group (p = 0.008). A significant correlation of illness symptom severity with decreased attentional efficiency was observed in the rDD group (perceptual speed index)—both before (r = −0.864; p < 0.001) and after the relaxation training (r = −0.785; p < 0.001). Conclusions: The continuous performance test (APT) is a reliable indicator of impaired attention efficiency among patients with depressive symptoms compared to healthy subjects. 15-min-long one-time relaxation exercise has a beneficial effect on attention efficiency measured by APT in people with depression. Full article

Background: Mind-body interventions may support the development of adolescents’ self-regulation and provide a protective effect against maladaptive outcomes, e.g., internalizing and externalizing problems. The present study aimed at evaluating the effects of mindfulness-oriented meditation training (MOM) and autogenic training (AT) on a group of healthy Italian adolescents’ character dimensions, emotional and behavioral difficulties. Methods: 72 adolescents were randomly assigned to MOM/AT conditions and tested before and after the 8-week trainings through self-report measures (Temperament and Character Inventory 125, TCI; Strengths and Difficulties Questionnaire for Adolescents, SDQ-A). Main analyses involved robust and repeated measures ANOVAs, carried out separately for character TCI and SDQ-A scales. Results: After trainings, we found increased levels of cooperativeness and reduced emotional symptoms. Changes in these dimensions were negatively correlated: the more participants increased in their cooperativeness the greater decrease they showed in emotional symptoms. Conclusion: Both MOM and AT enhanced a cooperative attitude in adolescents and helped reducing their emotional problems. Therefore, it may be useful to apply these mind-body interventions in school settings as they can have a protective effect on the well-being and psychosocial adjustment of youths, through fostering their character maturity and helping them to better regulate their emotions. Full article

The coronavirus disease 2019 (COVID-19) pandemic has become an unprecedented threat to humanity worldwide, including healthcare workers (HCWs). Mind–body modalities have been used to improve the mental health, well-being, quality of life, and physical health of clinical and general populations, and may also be used to improve the mental health of HCWs during COVID-19. The objective of this review is to analyze the effectiveness of mind–body modalities for the mental health of HCWs in the COVID-19 era. Six electronic bibliographic databases were comprehensively searched to find intervention studies using mind–body modalities, including meditation, mindfulness-based intervention, autogenic training, yoga, tai chi, qigong, breathing exercise, music therapy, guided imagery, biofeedback, prayer, and faith-based techniques for HCWs. All intervention studies conducted from December 2019 to August 2021 will be included. Quality assessment will be performed according to study type, and Cochrane Collaboration’s Risk of Bias tool will be used for randomized controlled clinical trials (RCTs). If sufficient homogeneous data from RCTs exist, a meta-analysis will be performed. Dichotomous data and continuous data are presented as risk ratios and mean differences with their 95% confidence intervals, respectively. The results of this systematic review will be disseminated through the publication of a manuscript in a peer-reviewed journal or by presentation at a conference. Full article

Background and Objectives: Cardiovascular disease (CVD) has become increasingly prevalent in women, and it is also in this group that the risk of developing depression is the highest. The most commonly applied therapeutic intervention in cardiac rehabilitation is Schultz’s autogenic training, which has proven to be of little efficacy in reducing depression and anxiety disorders. At the same time, a growing number of scientific reports have been looking at the use of virtual reality (VR) to treat mental health problems. This study aimed at assessing the efficacy of virtual therapy in reducing levels of depression, anxiety, and stress in female CVD patients. Materials and Methods: The study included 43 women who were randomly divided into two groups: experimental group (N = 17), where eight-week cardiac rehabilitation was enhanced with VR-based therapeutic sessions, and control group (N = 26), where the VR therapy was replaced with Schultz’s autogenic training. Mental state parameters were measured using the Perception of Stress Questionnaire and Hospital Anxiety and Depression Scale (HADS). Results: In the experimental group, the sole parameter which failed to improve was HADS-Anxiety, which remained at the baseline level. In the control group, there was a deterioration in nearly all tested parameters except for HADS-Depression. Statistically significant differences in the efficacy of rehabilitation were recorded in relation to the level of stress in the sub-scales: emotional tension (p = 0.005), external stress (p = 0.012), intrapsychic stress (p = 0.023) and the generalized stress scale (p = 0.004). Conclusions: VR therapy is an efficient and interesting complement to cardiac rehabilitation, with proven efficacy in reducing stress levels. Full article

The aim of this study was to assess the efficacy of virtual reality (VR)-enhanced cardiac rehabilitation (CR) in reducing the intensity of depression and anxiety symptoms in patients undergoing phase II of CR in ambulatory conditions. One hundred participants (mean age 65.7 years) were divided randomly into two groups. Both groups took part in eight sessions of standard CR (three times per week). The experimental group was additionally supported by eight sessions of VR therapy using the VR TierOne device and the control group by eight sessions of Schultz Autogenic Training. The Hospital Anxiety and Depression Scale (HADS) was used as the primary outcome measure. The Perception of Stress Questionnaire was used as the secondary outcome measure. The data from 77 participants were subject to analysis. Post-intervention, in the experimental group, the overall HADS score was statistically significantly reduced by 13.5%, HADS-Depression by 20.8%, and the general stress level by 12.8% (p < 0.05). In the control group, the scores of the HADS, HADS-Anxiety and the general stress level were statistically significantly higher, by 4.8%, 6.5%, and 4.9%, respectively. VR-enhanced CR for individuals with cardiovascular disease reduced the level of anxiety and depression symptoms compared to standard CR. Full article