Holger Mauch

Feasibility of Health Services Research in Nursing Home Settings – A SWOT Analysis Using the Example of AroMaDem

Within the framework of the randomized controlled trial, both the feasibility of a standardized intervention (hand and forearm massage with lavender oil)—including a training curriculum—in daily clinical practice, as well as the clinical benefit of the intervention, are evaluated. Opportunities and challenges regarding implementation are summarized in the form of a SWOT analysis

Globally, the demographic shift towards an aging population leads to significant challenges in healthcare systems, specifically due to an increasing incidence of multimorbidity resulting in polypharmacy among the elderly. Simultaneously, sleep disorders are a common complaint for elderly people. A treatment with pharmacological therapies often leads to side effects causing a high potential for dependency. Within this context, there is a high need to explore non-pharmacological therapeutic approaches. The purpose of this study is to evaluate the effectiveness of acupuncture and music therapy, both individually and combined as a multimodal therapy, in the treatment of sleep disorders in individuals aged 70 years and older.
We conduct a confirmatory randomized controlled trial using a two-factorial study design. A total of n = 100 elderly people receive evidence-based standard care information for age-related sleep disorders. Beyond that, patients are randomly assigned into four groups of n = 25 each to receive acupuncture, receptive music therapy with a monochord, multimodal therapy with both acupuncture and music therapy, or no further therapy. The study's primary outcome measurement is the improvement in sleep quality as assessed by the Pittsburgh Sleep Quality Index (PSQI) (global score), at the end of intervention. Additionally, depression scores (Geriatric Depression Scale), health-related quality of life (Short-Form-Health Survey-12), neurovegetative activity measured via heart rate variability, and safety data are collected as secondary outcomes. Using a mixed-methods approach, a qualitative process evaluation will be conducted to complement the quantitative data.
The study is ongoing and the last patient in is expected to be enrolled in April 2024. The results can provide valuable insights into the effectiveness of non-pharmacological interventions for sleep disorders among the elderly, contributing to a more personalized and holistic approach in geriatric healthcare.
German Clinical Trials Register (DRKS00031886).

Accurate assessment and enhancement of health-related skills among oncology patients are pivotal for optimizing cancer care. The Patient Activation Measure (PAM-13), a questionnaire designed to reflect an individual's knowledge, skills, and confidence in self-healthcare management, has been validated across diverse countries and settings. Concerns have been raised regarding the cross-situational applicability, as patients with specific diseases and cultural backgrounds interpret questionnaire items differently. This study aimed to examine the structural validity and psychometric properties of the PAM-13 in an oncological patient cohort.
Baseline data from a longitudinal non-randomized controlled study involving cancer out-patients (n = 1,125) from Comprehensive Cancer Centres in Southern Germany were analysed. The German version of the PAM-13 was employed. With classical test and item response theory methods data quality, reliability, convergent and structural validity, as well as psychometric properties were assessed. Exploratory (EFA) and confirmatory factor analyses (CFA) were employed to investigate the postulated unidimensionality of the underlying construct. With a partial credit model (PCM) we examined item fit, targeting, local independence and differential item functioning.
Participants were predominantly female (73.0%) with a breast cancer diagnosis (41.3%). While items were generally well-accepted, ceiling effects were observed and a high mean PAM-13 score (69.7, SD = 14.2) was noted, potentially compromising responsiveness to interventions. Reliability was adequate (Cronbach's α = 0.81), person and item separation reliability were good to excellent (0.81 and 0.99, respectively). Explorations of the unidimensionality of the construct (EFA, CFA, PCM) yielded inconclusive results, hinting towards a two-factor solution. Item difficulty rankings deviated from the original. No differential item functioning was identified, and local independence was confirmed.
While the PAM-13 serves as a valuable instrument for comprehending and promoting health-related skills in cancer patients, the identification of ceiling effects, disordered item-difficulty rankings, and inconclusive findings regarding unidimensionality contribute to the expanding body of evidence, emphasizing the dependency of PAM-13's validity and reliability on distinctive characteristics within the population under investigation. Future research should prioritize refining or adding PAM-13 items to better capture the specific health-related challenges within diverse populations, paving the way for more effective patient engagement strategies in oncology.
DRKS00021779.

Research has shown that the amount of diversity within project groups has an effect on how well groups perform. In particular, groups that are balanced with respect to gender, race, national origin, and social background tend to be more creative, more productive, and perform better on average than non-diversified groups (Hunt 2015, Hunt 2018). Therefore the assignment of employees to project groups must also take into account the sub-goal of diversification during the decision making process (in addition to hard constraints such as suitable skill level of an employee to even qualify for membership in a group.) The additional constraints this imposes on the optimization problem of finding the best group composition can be a considerable challenge for management. In this paper, we present a new variation of a classical network flow algorithm to solve this problem optimally. We show the results of an application area where optimal groups have been formed that work together. The results have been obtained by the software implementation of our algorithm called "NF Group Diversity".

Pong was a popular table tennis video game originally released in 1972. Pong is often used as the test subject for neural networks and genetic algorithms, often in tandem. Simple games like Pong have been optimized utilizing neural networks and genetic algorithms in order to scale difficulty or to self-sufficiently "beat" the game or human opponent [3]. However, this work attempts to scale difficulty not through behavior but through geometric morphological phenotypes. We have employed an evolutionary algorithm that weighs the performance of various Pong paddle shapes. This is tested and verified in our Pong simulation. This evolutionary algorithm modifies vertex values to generate shapes with weighted probabilities, simulate their performance in the game, establish the fitness of those shapes, and breed the most fit individuals to produce new generations of paddle shapes.

The Quantitative Excellence in Science and Technology (QuEST) Scholars Program facilitates the academic success of transfer students who enter Eckerd College intending a STEM major. Our primary goal is to create and nurture cohorts of STEM transfer students through specifically designed and carefully monitored academic and social-support activities. Transfer students face unique challenges as they transition to a new institution. Each student has completed a unique set of courses, requiring careful faculty mentoring to plan the successful completion of a STEM degree. Transfer students also lack the advantages of a natural cohort of peers, unlike native freshmen who are typically taking the same classes at the same stages throughout their undergraduate careers. To address these issues, we created a Scientific Inquiry Seminar, one course extending over two semesters, for all new QuEST Scholars. The discussion-based course included a wide range of topics, from ethical issues and cutting-edge research in science, to more mundane topics such as graduation requirements, career planning, and resume building. To foster success for all STEM majors, we improved the peer-tutoring program for students struggling with quantitative subjects presented in math and science courses. We unified peer-tutors for computer science, physics, mathematics, and chemistry under one umbrella with a dedicated faculty member to oversee the program and developed an on-line reporting system to track individual sessions. Tutor development seminars were held regularly. Building a learning community among students and tutors was one of the most frequently mentioned positive outcomes of the tutoring program, according to exit interviews with tutors. We are in the fifth year of our NSF grant (S-STEM #1154520) and have provided scholarship support for 28 undergraduates, including 15 who intended to major in Marine Science and one in Geosciences. Average awards are $8,000 per year and are renewable based on continued progress as a STEM major and unmet financial need. Ten students received scholarships until graduating with a bachelor's degree, 10 are still receiving support as STEM majors, and 8 left Eckerd and/or switched to a non-STEM major prior to graduation. We compare these results to those of native freshmen choosing STEM majors.

The Closest String Problem (CSP) is an NP-hard problem, which arises in computational molecular biology and coding theory. This class of problems is to find a string that minimizes the maximum Hamming distance to a given set of strings. In this paper, we present an exact algorithm called Distance First Algorithm (DFA) for three strings of CSP with alphabet size two. For the general CSP, we design a polynomial heuristic which is a combination of our proposed approximation algorithm LDDA ([10] Liu Xiaolan, Fu Keqiang, Shao Renxiang. Largest distance decreasing algorithm for the Closest String Problem. Journal of Information & Computational Science 2004; 1(2): 287–92) and local search strategies. Numerical results show that the proposed heuristic may obtain a nearly optimal value in a reasonable time for small and large-scale instances of the CSP.

Encoding for solutions of combinatorial optimization problems involving permutations or constraints that maintain the generality of operators in evolutionary computation is often difficult. In this paper, we present the Priority Encoding Scheme (PES), a general-purpose encoding scheme that encodes information used to construct solutions rather than directly encoding solutions themselves. We show that not only is PES simple to implement, but that it can be used effectively with Genetic Algorithms (GA) and Simulated Annealing (SA) to find good solutions to the multiple-constraint knapsack problem (MKP) and shows promise for finding good solutions to the traveling salesman problem (TSP).

The closest string problem is an NP-hard problem, which arises in computational molecular biology and coding theory. Its task is to find a string that minimizes maximum Hamming distance to a given set of strings. In this paper, a compounded genetic and simulated annealing algorithm (CGSA) which combines the merits of genetic algorithms and simulated annealing is presented to solve CSP. An adapting two-point crossover operator and a heuristic gene mutation operator designed by us are used in CGSA. In addition, by analyzing the optimal solution's structural features some rules are designed to pretreat the data, which reduces the problem size. We report computational results which show that the CGSA is capable of finding good solutions in a reasonable amount of time.