Does a Brief Mindfulness Training Enhance Heartfulness in Students? Results of a Pilot Study

(1) Background: There is robust evidence that mindfulness trainings enhance mindfulness as operationalized in Western psychology, but evidence about their effect on aspects of heartfulness is sparse. This study seeks to test whether a brief mindfulness training enhances heart qualities, including self-compassion, gratitude, and the generation of feelings of happiness. (2) Methods: Eighteen students enrolled in a mindfulness training that was offered as part of an interdisciplinary class. The training consisted of five training sessions and four booster sessions of 45 minutes each over the course of nine weeks. Mindfulness was measured with the Five Facet Mindfulness Questionnaire-Short Form (FFMQ-SF) and self-compassion was measured with the Self-Compassion Scale Short Form (SCS-SF). In addition, two items were drawn from the Caring for Bliss Scale (CBS) measuring gratitude and the generation of feelings of happiness in the present moment. Assessments were conducted before the training (pre), after the training (post), and four weeks after the training (follow-up). (3) Results: Results showed that mindfulness, general self-compassion, and generating feelings of happiness increased from pre to post, whereas self-critical attitudes decreased and that these changes were maintained at follow-up. Gratitude increased from pre to post and then decreased from post to follow-up. (4) Conclusions: A brief mindfulness training seems to be beneficial for students to improve mindfulness and aspects of heartfulness, but further research is needed to investigate the effectiveness of the training relative to a cohort or active control group

Mindfulness and acceptance-based trainings for fostering self-care and reducing stress in mental health professionals: A systematic review

This review summarizes the effectiveness of Mindfulness-Based Stress Reduction (MBSR), Mindfulness-Based Cognitive Therapy (MBCT), Mindful Self-Compassion (MSC), and Acceptance and Commitment Therapy (ACT) to foster self-care and reduce stress in mental health professionals. Twenty-four quantitative articles from PsycInfo and PubMed were identified that focused on mindfulness, self-compassion, psychological flexibility, stress, burnout, or psychological well-being. All MBSR and MBCT studies lacked active control conditions, but some of the ACT studies and one MSC study included an active control. Most studies support evidence that all training programs tend to improve mindfulness and some also self-compassion. In addition, psychological flexibility was measured in the ACT studies and tends to improve over time. Further, MBSR, MSC, and ACT tend to reduce stress or burnout. The results were less supportive for psychological well-being. The value of the various training adaptations as well as directions for future research are discussed

Assessing associations in multi-member multi-group data: An actor-partner interdependence

Data from groups often have a multimember multigroup (MMMG) structure. Examples are two-parent families with a female or male child (three members, two groups), two same-gender and opposite-gender peers of different status (two members, four groups), or gay, lesbian, and heterosexual couples (two members, three groups). To analyze such data, a framework called MMMG actor – partner interdependence model (MMMG APIM) is presented considering group composition. Three models are discussed in detail: the three-member two-group APIM, the two-member four-group APIM, and the two-member three-group APIM. Structural equation modeling and cross-sectional and longitudinal data are used to illustrate the approach. To ease the interpretation of APIM findings, a proposal of a general classification scheme is made

Kann die Symptombelastung einen regulären oder irregulären Behandlungsabschluss bei Substanzkonsumstörungen vorhersagen?

Ziel der Studie Das Ziel der vorliegenden explorativen Studie war zu untersuchen, ob die subjektive Symptombelastung vor und während der Behandlung von PatientInnen mit einer Substanzkonsumstörung einen Einfluss darauf hat, ob die Behandlung regulär (d. h. in gegenseitigem Einverständnis zwischen Therapeut und Patient) oder irregulär (d. h. Therapeut oder Patient bricht ab) beendet wird. Methodik In der vorliegenden, retrospektiven Untersuchung wurden 54 PatientInnen einer Drogenentzugs- und Entwöhnungsstation untersucht. Die Informationen zur Art des Behandlungsabschlusses wurden der Basisdokumentation und zur Symptombelastung der Brief-Symptom-Checkliste (BSCL) entnommen. Ergebnisse Die Ergebnisse der binären logistischen Regressionsanalysen zeigten, dass eine allgemeine Reduktion der Symptombelastung während der Behandlung mit einem regulären statt einem irregulären Behandlungsabschluss einherging. Die Analysen der Subskalen der BSCL ergaben signifikante Effekte für eine Abnahme der Ängstlichkeit und des Paranoiden Denkens während der Therapie zugunsten eines regulären Behandlungsabschlusses. Des Weiteren sagten hohe Werte der Zwanghaftigkeit zu Behandlungsbeginn einen regulären Behandlungsabschluss vorher. Schlussfolgerung Bei der Behandlung von PatientInnen mit Substanzkonsumstörungen erscheint es sinnvoll, die allgemeine subjektive Symptombelastung während der Behandlung zu erfragen, um Therapieabbrüche zu vermeiden. Insbesondere sollten die Ängstlichkeit und das Paranoide Denken in den Fokus der Behandlung rücken, da diese in der vorliegenden Studie einen regulären Behandlungsabschluss vorhersagten. Purpose The aim of the present exploratory study was to investigate whether the subjective symptom burden before and during the treatment of patients with a substance use disorder has an influence on whether the treatment is terminated regularly (i. e. by mutual agreement between the therapist and the patient) or irregularly (i. e. the therapist or the patient discontinues). Methods In the present retrospective study 54 patients of a drug withdrawal and weaning ward were examined. The information on the type of treatment termination was taken from the basic documentation and the symptom burden of the Brief-Symptom-Checklist (BSCL). Results The results of the binary logistic regression analyses showed that a general reduction of the symptom burden during treatment was predictive for a regular rather than an irregular treatment termination. The analyses of the subscales of the BSCL showed significant effects for a decrease in anxiety and paranoid thinking during therapy in favour of a regular treatment termination. Furthermore, high values of obsessive-compulsivity at the beginning of treatment predicted a regular treatment termination. Conclusion In the treatment of patients with substance use disorders, it seems reasonable to ask for the general subjective symptom burden during treatment in order to avoid discontinuation of therapy. In particular, anxiety and paranoid thinking should be in the focus of the treatment, as these predicted a regular completion of treatment in the present study

Analytical strategies for the determination of amino acids: Past, present and future trends

This review describes the analytical methods that have been developed over the years to tackle the high polarity and non-chromophoric nature of amino acids (AAs). First, the historical methods are briefly presented, with a strong focus on the use of derivatization reagents to make AAs detectable with spectroscopic techniques (ultraviolet and fluorescence) and/or sufficiently retained in reversed phase liquid chromatography. Then, an overview of the current analytical strategies for achiral separation of AAs is provided, in which mass spectrometry (MS) becomes the most widely used detection mode in combination with innovative liquid chromatography or capillary electrophoresis conditions to detect AAs at very low concentration in complex matrixes. Finally, some future trends of AA analysis are provided in the last section of the review, including the use of supercritical fluid chromatography (SFC), multidimensional liquid chromatography and electrophoretic separations, hyphenation of ion exchange chromatography to mass spectrometry, and use of ion mobility spectrometry mass spectrometry (IM-MS). Various application examples will also be presented throughout the review to highlight the benefits and limitations of these different analytical approaches for AAs determination

Evaluation of Prototype CE-MS Interfaces

Capillary electrophoresis–mass spectrometry (CE-MS) coupling is a powerful analytical solution bringing together the separation power of CE and the wealth of chemical information afforded by MS. Nevertheless, interfaces making the hyphenation of both techniques possible have always been the subject of a quest for improvement by their users in search for more sensitive and robust setups. This fact has led to numerous technical developments and new interface designs claiming to outrival existing approaches in different aspects. Nevertheless, the task of evaluating and comparing a new interface to previous solutions is not always straightforward. Issued from our own experience in the field, we herein propose a protocol to optimize the operation parameters of a new CE-MS interface design, assess its analytical performance, and compare it to a reference interface if desired. Electrospray stability, sensitivity, reproducibility, and robustness are practically evaluated as key elements of the process.</p

High-throughput identification of monoclonal antibodies after compounding by UV spectroscopy coupled to chemometrics analysis

Monoclonal antibodies (mAbs) compounded into the hospital pharmacy are widely used nowadays. Their fast identification after compounding and just before administration to the patient is of paramount importance for quality control at the hospital. This remains challenging due to the high similarity of the structure between mAbs. Analysis of the ultraviolet spectral data of four monoclonal antibodies (cetuximab, rituximab, bevacizumab, and trastuzumab) using unsupervised principal component analysis led us to focus exclusively on the second-derivative spectra. Partial least squares-discriminant analysis (PLS-DA) applied to these data allowed us to build models for predicting which monoclonal antibody was present in a given infusion bag. The calibration of the models was obtained from a k-fold validation. A prediction set from another batch was used to demonstrate the ability of the models to predict well. PLS-DA models performed on the spectra of the region of aromatic amino acid residues presented high ability to predict mAb identity. The region corresponding to the tyrosine residue reached the highest score of good classification with 89 %. To improve the score, standard normal variate (SNV) preprocessing was applied to the spectral data. The quality of the optimized PLSDA models was enhanced and the region from the tyrosine/tryptophan residues allowed us excellent classification (100 %) of the four mAbs according to the matrix of confusion. The sensitivity and specificity performance parameters assessed this excellent classification. The usefulness of the combination of UV second-derivative spectroscopy to multivariate analysis with SNV preprocessing demonstrated the unambiguous identification of commercially available monoclonal antibodies

The Reynolds Intellectual Assessment Scales (RIAS): Measurement and structural invariance across four language groups.

The Reynolds Intellectual Assessment Scales (RIAS) measures general intelligence and its two main components, verbal and nonverbal intelligence, each comprising of two subtests. The RIAS has been recently standardized in Denmark, Germany, Switzerland, and Spain. Using the standardization samples of the U.S. (n = 2,438), Danish (n = 983), German (n = 2,103), and Spanish (n = 1,933) versions of the RIAS, this study examined measurement invariance across these four language groups for a single-factor structure, an oblique two-factor structure with a verbal and nonverbal factor, and a bifactor structure with a general, a verbal, and a nonverbal factor. Single-group confirmatory factor analysis (CFA) supported the oblique two-factor and bifactor structure for each language group but not the single-factor structure. The bifactor analysis revealed that the general factor accounted for the largest proportion of common variance in each language group, while the amount of variance accounted for by the two specific factors was small and their reliabilities low. Multiplegroup CFA supported scalar invariance in both, the oblique two-factor and bifactor structure

New insights into the conversion of electropherograms to the effective electrophoretic mobility scale

CE–MS is increasingly gaining momentum as an analytical tool in metabolomics, due to its ability to obtain information about the most polar elements in biological samples. This has been helped by improvements of robustness in peak identification by means of mobility-scale representations of the electropherograms (mobilograms). As a necessary step toward facilitating the use of CE–MS for untargeted metabolomics data, the authors previously developed and introduced ROMANCE, a software automating mobilogram generation for large untargeted datasets through a simple and self-contained user interface. Herein, we introduce a new version of ROMANCE including new features such as compatibility with other types of data (targeted MS data and 2D UV-Vis absorption-like electropherograms), and the much needed additional flexibility in the transformation parameters (including field ramping and the use of secondary markers), more measurement conditions (depending on detection and integration modes), and most importantly tackling the issue of quantitative peak conversion. First, we present a review of the current theoretical framework with regard to peak characterization, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. Then, the new version of the software is presented and validated experimentally. We contrast the multiple marker mobility transformations with previous results, finding increased peak position precision, and finally we showcase an application to actual untargeted metabolomics data