Goals are constant facets of everyday life that influence decisions in response to the environment. If an individual is confronted with circumstances making it difficult to achieve a goal, the individual may respond with goal disengagement (GD) after a certain period of time. This chapter addresses the question of how this time to GD is distributed. In this respect, a reanalysis was conducted on data from a study that used a digital, card-based game where the goal was to form as many sextuples of cards as possible. The analysis revealed a difference between the mean time to the first GD and the mean time to a subsequent GD. Additionally, the probability distributions of these two categories of GD are best represented by a log-normal mixture distribution. This finding suggests that the data may include two types of GD-populations showing different GD behavior, which could be beneficial for future research, particularly in the development of digital twins with respect to GD.

BACKGROUND:Traditional, Complementary, and Integrative Medicine (TCIM) has been established in the academic context of universities. In recent years, strategies have been developed worldwide to strengthen the role of TCIM in supporting the health of the population. Online databases are a common way for obtaining evidence-based information. This article is an update of a former systematic review from 2010 on published databases resources for TCIM. METHODS:The databases CINAHL, CAMbase, Web of Science, MEDLINE/PubMed, and Google Scholar search engine were searched for databases related to TCIM published in peer-reviewed journals between 2010 and November 2024. All included databases were visited online, and information on the origin, content, and scope of the database was extracted. RESULTS:A total of 6579 articles were identified through the literature search. After exclusion of irrelevant articles, full-text screening of 127 articles yielded 37 new databases. Together with 16 still available old databases, these mainly contained information on herbal therapies (n = 15) and Traditional Chinese Medicine (n = 11) from 18 different countries. Newly identified medicinal plant databases offer various scientific resources such as crude drugs, indigenous plants, and structures for natural and phytochemical components with molecular biological content. CONCLUSIONS:This literature review illustrates the dynamic development in the database landscape over the last 15 years. While the number of bibliographic databases is shrinking, databases in the field of medical plants/herbal therapy content are on the rise, which might be due to advances in plant genomics and molecular biology.

Dealing with relational data is an important and challenging topic not only in life science, as in the characterization of dynamics of living systems, but also in psychology and social sciences, as in the examination of interpersonal behavior. In this context, stochastic process models are often used for the mathematical description of system dynamics and transition processes. In this observational study, interpersonal attachment of 96 participants (74 females and 22 males, mean age of 23.94 ± 4.16 years) measured by a digital application was represented and analyzed as Discrete Time Markov Chains (DTMCs) after the participants formed 48 dyads. For each participant, 100 DTMCs were formed based on a single measurement by continuously increasing the interval between two states and tested for Markov property as well as for homogeneity with their counterpart within a dyad. The results show, firstly, that the majority of the DTMCs satisfy the Markov property and can therefore actually be interpreted as DTMCs and, secondly, that the DTMCs of a dyad can be both homogeneous and heterogeneous, with the middle intervals appearing to be the most suitable in the two tests. Nonetheless, the results should be further investigated by either optimizing the methodology itself or supporting it with additional measures of interpersonal behavior, e.g., by observing interpersonal interactions or by eye-tracking measurements.

People make countless decisions every day. We explored the self-regulatory function of decisions and assumed that the very act of making a decision in everyday life enhances people’s mood. We expected that this decision related mood change would be more pronounced for intuitive decisions than for analytical ones. The ease of making a decision and the feeling of rightness were expected to mediate the effect of intuitive (vs. analytical) decisions on participants' mood. In a preregistered experimental experience sampling study participants from the general population were asked to report when they were about to make an everyday decision over the course of 14 days (N = 256 participants, 6,779 decisions). For each decision, participants were randomly instructed to decide either based on their intuition or based on careful analysis. We assessed several variables before and immediately after the decision. Participants also reported retrospectively on their choices in voluntary follow-up assessments. Making a decision per se immediately enhanced participants’ mood. This mood enhancement was stronger for intuitive compared to analytic decisions and persisted until follow-up. Ease of decision, but not feeling of rightness, mediated this effect. Intuitive compared to analytic decisions were more likely to be implemented and led to greater satisfaction and pleasantness of the chosen option. Having more options for a particular decision led to generally higher mood improvement and satisfaction. This is the first empirical demonstration showing that using one’s gut has beneficial effects in everyday life. Study limitations and implications for theory and practice are discussed.

Introduction: Drawing tasks are an elementary component of psychological assessment in the evaluation of mental health. With the rise of digitalization not only in psychology but healthcare in general, digital drawing tools (dDTs) have also been developed for this purpose. This scoping review aims at summarizing the state of the art of dDTs available to assess mental health conditions in people above preschool age. Methods: PubMed, PsycInfo, PsycArticles, CINAHL, and Psychology and Behavioral Sciences Collection were searched for dDTs from 2000 onwards. The focus was on dDTs, which not only evaluate the final drawing, but also process data. Results: After applying the search and selection strategy, a total of 37 articles, comprising unique dDTs, remained for data extraction. Around 75 % of these articles were published after 2014 and most of them target adults (86.5 %). In addition, dDTs were mainly used in two areas: tremor detection and assessment of cognitive states, utilizing, for example, the Spiral Drawing Test and the Clock Drawing Test. Conclusion: Early detection of mental diseases is an increasingly important field in healthcare. Through the integration of digital and art-based solutions, this area could expand into an interdisciplinary science. This review shows that the first steps in this direction have already been taken and that the possibilities for further research, e.g., on the optimized application of dDTs, are still open.

Germany has a long tradition of health libraries. From their origin in monasteries, they became centres of knowledge and education. In modern times, this tradition has been continued by the Central Library of Medicine. In addition, as a specialty in Germany, special collection areas and special libraries that focus on one topic were established. Those services were transformed to specialized information services and portals as part of the digital transformation process. One of such projects is OPEN-CAM, which provides literature on integrative medicine in a specialist library and hosts the literature database CAMbase. Based on this example, we show how digital transformation has influenced the library landscape and its structures in Germany.

The Hierarchical Taxonomy of Psychopathology (HiTOP) provides a comprehensive description of psychopathology and maladaptive personality traits but does not include etiological theorizing. Psychodynamic theory offers such theorizing, describing motivational conflicts that can be processed either in active (progressive) or passive (regressive) modes. We related motivational conflicts to HiTOP dimensions for the first time. Two studies (four samples, N = 580) showed replicable associations: passive conflict processing displayed stronger and more distributed associations with psychopathology, whereas active processing was associated with lower, yet more specific psychopathology. Particular symptoms were associated with different conflicts, showing that different etiological factors may underlie similar psychopathological signs. Motivational dynamics offer guidance for diagnosis and treatment of psychopathology.

: Cancer is one of leading causes of mortality worldwide. According to GLOBOCAN database, 19.3 million new cancer cases and 10 million cancer deaths worldwide were counted in 2020. Thus, there is an absolute necessity for statistical data on cancer incidence and treatments. This is mainly done by cancer registries, which aim at collecting, managing, and analyzing health and demographic data on individuals diagnosed with cancer. As more and more patients make use of integrative oncology to optimize their health and quality of life during and after cancer treatment, it is important to gather clinical registry data of complementary as well as conventional cancer care. The INTREST registry is the first approach that aims to identify predictors of treatment-response in women undergoing individualized, integrative breast cancer treatment. This article reports on the technical realization and representativity of the registry based on 3,341 eligible women and 885 cases included in interim statistical analysis. The analyses show that the INTREST sample of women suffering from breast cancer does not significantly differ from population-based registries and pragmatic trial data of breast cancer patients in Germany with respect to main sociodemographic and clinical cancer data. However, completeness, particularly in tumor classification, currently is a major limitation.

Despite the increase in scientific publications in the field of integrative medicine over the past decades, a valid overview of published evidence remains challenging to get. The online literature database CAMbase (available at https://cambase.de ) is one of the established databases designed to provide such an overview. In 2020, the database was migrated from a 32-bit to a 64-bit operating system, which resulted in unexpected, technical issues and forced the replacement of the semantic search algorithm with Solr , an open-source platform that uses a score ranking algorithm. Although semantic search was replaced, the goal was to create a literature database that is essentially no different from the legacy system. Therefore, a before-after analysis was conducted to compare first the number of retrieved documents and then their titles, while the titles were syntactically compared using two Sentence-Bidirectional Encoder Representations from Transformers (SBERT) models. Analysis with a paired t-test revealed no significant overall differences between the legacy system and the final system in the number of documents ( t =− 1.41 , d f = 35 , p = 0.17 ), but an increase in performance ( t = 4.13 , d f = 35 , p < 0.01 ). Analysis with a t-test for independent samples of the values from the models also revealed a high degree of consistency between the retrieved documents. The results show that an equivalent search can be provided by using Solr , while improving the performance, making this technical report a viable blueprint for projects with similar contexts.

: Although there is a steady increase of scientific publications in integrative medicine, it is still difficult to get a valid overview of published evidence. The open accessible bibliographical database CAMbase 3.0 (available at https://cambase.de) hosted by Witten/Herdecke University is one of such established databases in this field. In 2020, CAMbase 2.0 was migrated to a newer 64-bit operating systems, resulting in a variety of issues. A promising solution of keeping and accessing the data of CAMbase 2.0 was to replace the business logic with the open-source platform Solr, which uses a score ranking algorithm instead of a semantic-syntactic interpretation of search queries as in CAMbase 2.0. As a result, the before-after analysis with T-tests showed mainly no significant differences in the equality of the queried titles after applying SBERT, not even in the number of search hits ( t = 1.43 , df = 35 , p = 0.17) , but in query times ( t = 4.2 , df = 35 , p < 0.01 ). While search hits remained stable as the speed increases, the approach with Solr is more efficient, making this technical report a possible blueprint for similar bibliography-based databases projects.

INTRODUCTION:While virtual reality (VR) is an emerging paradigm in a variety of research contexts, VR-based embodiment effects on behavior and performance still lack in sufficient evidence regarding to bias in cognitive performance assessment.METHODS:In this methodological observational study, we compare the VR measurement of cognitive performance with a conventional computer-based testing approach in real life (RL) in younger and older adults. The differences between VR and RL scenarios are investigated using the background of two theoretical models from cognitive psychology. Furthermore, data assessment reliability and validity are analyzed, concerning the feasibility of technological and ergonomic aspects.RESULTS:A within-group comparison showed no change in information processing speed in either one of the two age groups, i.e., both groups perform equally well in RL and in a VR testing environment.CONCLUSION:The use of lifelike VR environments for cognitive performance tests seems not to lead to any performance changes compared to RL computer-based assessments, making VR suitable for similar applications. On technical concerns, we recommend the careful use of reaction time paradigms regarding to input hardware and stimuli presentation.

Human attachment describes the establishment of contact between two or more people leading to a closer interpersonal relationship. For measuring attachment, the use of nonverbal assessments tools including art and drawing tasks has been shown to be an alternative to conventional assessment approaches. The present study aims at evaluating the internal criterion validity of a new digital drawing tool for measuring interpersonal attachment. 68 participants took part in this pilot study and were separated in groups of two. After completion of a 10-item subscale of Social Orientation (SO) they were asked to sit opposite to the other and to hold eye contact during a three minute drawing period. Moving the pen to the upper section near the partner stood for thoughts about the other, while moving to the lower section closest to the subject implicated thoughts about oneself. The mean distance of the resulting time series of the two subjects were calculated, using the mean Euclidean distance, and compared with the difference in the SO values via linear regression. Taking all differences together a moderate correlation of r = 0.298 was observed, which however slightly missed the level of significance (p = 0.09). We were able to find small evidence for the criterion validity of IU digital drawing tool. For future studies, other measures of similarity in the time series, i.e. the Manhattan Distance are discussed as an extension to foster the present results.

While virtual reality (VR) emerges in a variety of research contexts, the effects on behavior and performance caused by VR-based embodiment still lack sufficient evidence of changes in affective state.With this feasibility study, we compared the affective states in both younger and older adults, measured after conventional computer-based tests in real life (RL) and after tests in VR.These assessment tests are spread over five time points, two in RL and three in VR, and the differences between the VR and the RL environment are investigated against the backdrop of two theoretical models of cognitive psychology.Results showed no change in affective state in either age group, switching from a RL to a VR environment.In addition, the elderly did not assess their affective state significantly different than that of the younger control group.In conclusion, lifelike VR environments for cognitive testing and other assessment or training purposes do not seem to lead to any systematic influ ence of affective state compared to RL computer-based assessments, making VR an alternative to conventional methods, for instance for cognitive treatments or preventions.Although the results can only be partially generalized due to a small sample size, they show technical stability and suitability for future use of similar applications.

Movement, actions, and intentions are important psychological skills in human behavior. Studies have shown correlations between movement activity and a variety of mental disorders. In this context, planning and designing of gardens and outdoor spaces as an intentional activity might play an important role as a marker for mental health. Thus, in this study, 16 subjects (8 female) aged between 19 and 60 were asked to do a gardening task in an experimentally constructed environment while their movement activity was recorded with a camera from a fixed viewpoint. Movement heatmaps and entropy then was calculated and correlated with mental state measured via the Global Severity Index (GSI) of the Brief Symptom Inventory (BSI-18) questionnaire. After finding an optimal grid size of the heatmaps, we were able to find a moderate negative correlation of r = -0.463 between these quantities in an overall of both genders, explaining 21.4 % of variance. After considering the gender of the test group, a noticeable gender effect could be revealed. We found a significant interaction effect of entropy with gender meaning that a lower movement entropy in a gardening task correlates with a higher mental distress for men, but lower for women. Multivariate regression found that this model explained 77.44 % of variance (R = 0.88). Despite of these promising results, further investigations in this area should overcome some limitations in this pilot study in the field of position tracking and movement feature extraction.

At present, interpersonal attachment has a subordinate role in the field of healthcare, but recent research results assume this as an important parameter, especially in prevention and mental health. Our aim was to develop a digital application that extends the previous approaches with a measurement over a specific time interval. Designed specifically for Windows-based tablets, this application performs a drawing test while capturing the transitions of two mental states, transmitted by the users. The results were collected over a period of three minutes, allowing the application itself, along with the SiZer analysis, to determine how closely the participants were mentally connected. The tablet application has shown its first usefulness to enhance the healthcare, but further investigations are strongly recommended. In addition, its ease to use allows an uncomplicated integration into similar areas.