Search

BackgroundMental health problems among workers cause enormous losses to companies in Japan. However, workers have been considered to have limited access to psychological support because of time constraints, which makes it difficult for them to engage in face-to-face psychological support interventions. ObjectiveThis study aimed to present an intervention protocol that describes a randomized controlled trial to examine whether brief guided mindfulness meditation (MM) or self-compassion meditation (SCM) provided by a smartphone app is effective for mental health and work-related outcomes among workers. MethodsThis is an open-label, 3-arm randomized controlled trial. The participants will be recruited through an open call on relevant websites with the following inclusion criteria: (1) employees who are working more than 20 hours per week, (2) between the ages of 18 and 54 years, (3) not on a leave of absence, (4) not business owners or students, and (5) not currently diagnosed with a mental disorder and have a Kessler Psychological Distress Scale-6 score below 13 points. We will include 200 participants and randomly assign them to an SCM course (n=67), an MM course (n=67), and a waitlist group (n=66). The intervention groups (SCM and MM) will be instructed to engage in daily guided self-help, self-compassion, and MMs lasting 6-12 minutes per day over 4 weeks. Primary outcomes will include psychological distress and job performance, and secondary outcomes will include somatic symptoms, cognitive flexibility, self-esteem, self-compassion, perceived stress, well-being, emotion regulation, work engagement, anger, psychological safety, and creativity. All procedures were approved by the ethics committee of the University of Tokyo (22-326). All participants will be informed of the study via the websites, and written informed consent will be collected via web-based forms. ResultsThe recruitment of participants began in December 2022, and the intervention began in January 2023. As of September 2023, a total of 375 participants have been enrolled. The intervention and data collection were completed in late October 2023. ConclusionsThis study will contribute to the development of effective self-care intervention content that will improve mental health, work performance, and related outcomes and promote mindful and self-compassionate attitudes when faced with distress. Trial RegistrationUniversity Hospital Medical Information Network Clinical Trials Registry UMIN000049466; https://tinyurl.com/23x8m8nf International Registered Report Identifier (IRRID)DERR1-10.2196/53541

The octanol/water partition coefficient, P (logP), is a hydrophobicity index and is one of the determining factors of the pharmacokinetics of chemical compounds. LogP values obtained from in silico software, open chemistry databases, and in vitro liquid chromatography retention factors may vary. Some chemicals (boscalid, etoxazole, and permethrin) have up to four-order-magnitude differences in in silico/in vitro P values. This study aimed to evaluate the effects of logP values of these three compounds, along with bisphenol A, 1,2-dibromobenzene, tetrabromobisphenol A, trazodone, and triazolam, on the input parameters and output plasma/hepatic concentration–time profiles of simple physiologically based pharmacokinetic (PBPK) models. Although the blood-to-plasma concentration ratios (~0.9–0.6) were slightly affected by variations in logP values, logarithmic plasma unbound fraction values and liver-to-plasma partition coefficients (Kp,h) were, respectively, inversely and linearly correlated with logP values (Kp,h was stable at ~6.7 for logP > 4). LogP was among the input parameters for previously established machine learning systems; consequently, the resulting logarithmic intrinsic clearance values were correlated with logP values in the range 2–8. However, the bioavailability, absorption rate constants, and volumes of distribution were not affected. PBPK-modeled plasma and hepatic maximum concentrations and areas under the concentration–time curves after virtual oral doses were mostly within ~0.5- to ~2-fold ranges, except for substances with low in vitro logP values, e.g., etoxazole and permethrin. These results suggest that in silico logP values are generally suitable for pharmacokinetic modeling; nevertheless, caution is needed for compounds with low in vitro logP values of ~2. [ABSTRACT FROM AUTHOR]

The octanol/water partition coefficient P (logP) is a hydrophobicity index and is one of the determining factors for the pharmacokinetics of orally administered substances because it influences membrane permeability. To illustrate the wide-ranging variety of compounds in the chemical space, a two-dimensional data plot consisting of 25 blocks was previously proposed based on a substance’s in silico chemical descriptors. The logP values of approximately 200 diverse chemicals (test plus reference compounds covering all 25 blocks of the chemical space) were estimated experimentally using retention times in reverse-phase liquid chromatography; these values were compared with those of authentic reference compounds with established logP values (available for 17 of 60 reference substances in the Organization for Economic Co-operation and Development Test Guideline 117). The logP values of 140 of 165 chemicals successfully estimated using four different mobile phase conditions (pH 2, 4, 7, and 10 for molecular forms) correlated significantly with those calculated using the in silico packages ChemDraw and ACD/Percepta (r > 0.72). Although substances that neighbored authentic compounds in the chemical space had precisely correlated logP values estimated experimentally and in silico, some compounds that were more distant from authentic substances showed lower logP values than those estimated in silico. These results indicate that additional authentic reference materials with wider ranging chemical diversity and their logP values from reverse-phase liquid chromatography should be included in the international test guidance to promote simple and reliable estimation of octanol/water partition coefficients, which are important determinant factors for the pharmacokinetics of general chemicals. [ABSTRACT FROM AUTHOR]