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Question: Seed bank sampling remains a critical bottleneck to the quality of studies investigating community patterns in the seed bank. The main cause is a large knowledge gap in two aspects critical to sampling, i.e. spatial autocorrelation and species—area relations. The central question of this study is how the seed bank of a single plot should be sampled, in order to obtain more precise estimates on plot seed bank characteristics, without resorting to a disproportionate investment of available resources. Similar seed bank samples may then enable better plot-based statistical inference of ecological patterns in the seed bank in community ecology studies. Location: Semi-natural habitats in Flanders (Belgium) and northern France. Methods: We investigated the fine-scale spatial structure of individual seed banking species across 12 2.1 m × 2.1 m plots in three widespread habitats: temperate forest, grassland and heathland. Soil core samples (128) were collected in each plot, using a combined systematic (64) and random design (64). This enabled both geostatistical analyses of the fine-scale spatial structure of individual species—plot combinations as well as the calculation of sampled-based species rarefaction curves. Results: Fine-scale (i.e. within plot) spatial seed bank structure was detected in all plots in each habitat, in at least one or usually more plant species. Over half of the species records displayed significant spatial structure — visible as a random distribution of seed clusters — with medium to strong spatial dependence between point observations of a species of ca. 30 cm. Species rarefaction curves did not attain an asymptote at the actual sampling intensity of 128 samples. Seven out of 12 extrapolated species rarefaction curves did reach an asymptote in less than 384 samples. Conclusions: Using these consistent results in spatial structure and species—area relations across habitats, we present a method of how researchers can develop a tailor-made seed bank design to accommodate their individual needs, abiding by simple predefined boundaries. When the tailored design samples ca. 3% of a plot surface area along a systematic grid with a mesh width of at least 30 cm, these studies will potentially significantly increase the comparability among future seed bank community studies in semi-natural habitats.

Background Motivation levels for exercise vary widely among individuals and are influenced by various factors. This study aimed to compare exercise motivation levels and explore influencing factors among university students. Methods A cross-sectional research design targeted university students aged range 18 to 32 years. Participants ( n  = 148) were selected via cluster random sampling. Motivation for exercise was determine by the Exercise Motivation Inventory (EMI-2). EMI-2 comprises fourteen different subscales of motivation, with each subscale containing three to four items. All items were rated on a scale of 0 to 5, with 0 indicating “not at all true for me” and 5 indicating “very true for me.” Statistical analyses included ANOVA and Pearson correlation coefficient to assess differences among demographic variables (year of study, age, gender, marital status, location, and family size) and relationships between motivational aspects. Results The average exercise motivation level among all students was 166.94 ± 32.20. Fifth-year students exhibited the highest motivation 178.33 ± 30.37. No significant gender differences were found ( p  = 0.149). However, age ( p  = 0.024), location ( p  = 0.015), marital status ( p  = 0.050), and family size ( p  = 0.030) significantly influenced exercise motivation. Conclusion University students demonstrate inherent motivation for physical activity, with significant variations observed across demographic factors. These findings underscore the importance of tailored interventions to promote exercise and enhance student well-being. Further research, including longitudinal studies, is warranted to comprehensively understand exercise motivation dynamics in this population.

Smartphone self-monitoring of mood, symptoms, and contextual factors through ecological momentary assessment (EMA) provides insights into the daily lives of people undergoing psychiatric treatment. Therefore, EMA has the potential to improve their care. To integrate EMA into treatment, a clinical tool that helps clients and clinicians create personalized EMA diaries and interpret the gathered data is needed. This study aimed to develop a web-based application for personalized EMA in specialized psychiatric care in close collaboration with all stakeholders (ie, clients, clinicians, researchers, and software developers). The participants were 52 clients with mood, anxiety, and psychotic disorders and 45 clinicians (psychiatrists, psychologists, and psychiatric nurses). We engaged them in interviews, focus groups, and usability sessions to determine the requirements for an EMA web application and repeatedly obtained feedback on iteratively improved high-fidelity EMA web application prototypes. We used human-centered design principles to determine important requirements for the web application and designed high-fidelity prototypes that were continuously re-evaluated and adapted. The iterative development process resulted in Personalized Treatment by Real-time Assessment (PETRA), which is a scientifically grounded web application for the integration of personalized EMA in Dutch clinical care. PETRA includes a decision aid to support clients and clinicians with constructing personalized EMA diaries, an EMA diary item repository, an SMS text message-based diary delivery system, and a feedback module for visualizing the gathered EMA data. PETRA is integrated into electronic health record systems to ensure ease of use and sustainable integration in clinical care and adheres to privacy regulations. PETRA was built to fulfill the needs of clients and clinicians for a user-friendly and personalized EMA tool embedded in routine psychiatric care. PETRA is unique in this codevelopment process, its extensive but user-friendly personalization options, its integration into electronic health record systems, its transdiagnostic focus, and its strong scientific foundation in the design of EMA diaries and feedback. The clinical effectiveness of integrating personalized diaries via PETRA into care requires further research. As such, PETRA paves the way for a systematic investigation of the utility of personalized EMA for routine mental health care.

Background Chronic fatigue with a debilitating effect on daily life is a frequently reported symptom among adolescents and young adults with a history of Q-fever infection (QFS). Persisting fatigue after infection may have a biological origin with psychological and social factors contributing to the disease phenotype. This is consistent with the biopsychosocial framework, which considers fatigue to be the result of a complex interaction between biological, psychological, and social factors. In line, similar manifestations of chronic fatigue are observed in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) and juvenile idiopathic arthritis (JIA). Cognitive behavioral therapy is often recommended as treatment for chronic fatigue, considering its effectiveness on the group level. However, not everybody benefits on the individual level. More treatment success at the individual level might be achieved with patient-tailored treatments that incorporate the biopsychosocial framework. Methods In addition to biological assessments of blood, stool, saliva, and hair, the QFS-study consists of a randomized controlled trial (RCT) in which a single-subject experimental case series ( N=1 ) design will be implemented using Experience Sampling Methodology in fatigued adolescents and young adults with QFS, CFS/ME, and JIA (aged 12–29). With the RCT design, the effectiveness of patient-tailored PROfeel lifestyle advices will be compared against generic dietary advices in reducing fatigue severity at the group level. Pre-post analyses will be conducted to determine relevance of intervention order. By means of the N =1 design, effectiveness of both advices will be measured at the individual level. Discussion The QFS-study is a comprehensive study exploring disrupted biological factors and patient-tailored lifestyle advices as intervention in adolescent and young adults with QFS and similar manifestations of chronic fatigue. Practical or operational issues are expected during the study, but can be overcome through innovative study design, statistical approaches, and recruitment strategies. Ultimately, the study aims to contribute to biological research and (personalized) treatment in QFS and similar manifestations of chronic fatigue. Trial registration Trial NL8789. Registered July 21, 2020.

Dating violence (DV) among young people is increasingly recognized as a significant problem and preventive efforts targeting adolescents and young adults are being mobilized to tackle it. However, an accumulating body of evidence shows that these efforts fail to adequately capture young people’s needs, particularly those from diverse cultures and contexts, and to incorporate their perspectives into practice. The present study aimed to address this gap by exploring young people’s views on how DV can be prevented and what they expect from prevention programs in an urban Turkish context, where DV remains an under-studied issue and preventive efforts are only slowly progressing. Toward this goal, a qualitative research design was employed. Thirty-nine college students, aged 18–25, were recruited through convenience sampling and individually interviewed in a semi-structured manner. The interviews were transcribed and thematically analyzed from a social constructionist perspective. The analysis revealed five main themes that indicated young people’s suggestions for and expectations from DV prevention: 1) setting new dating norms, 2) targeting socialization processes, 3) improving relational competence, 4) improving oneself, and 5) managing obstacles. The findings and practice implications are discussed within a contextual-ecological framework in the changing socio-cultural terrain of Turkey. The study highlights the fact that young people’s views can guide the development of effective, contextually relevant, empowering, and collaborative practices, and indicates the value of listening to young people’s voices in the field of DV prevention.

We used a tailored survey design to obtain a more representative response. Paradata from previous consumer sentiments surveys and register information were used to stratify the sample into groups that differed in contact and co-operation propensity. We approached an experimental sample of 3000 households with a Web—mail—computer-assisted telephone interviewing sequential mixed mode strategy. The choice of initial mode and the subsequent computer-assisted telephone interviewing approach were tailored to the expected contact and co-operation propensities of the sample units. In the computer-assisted telephone interviewing follow-up of non-respondents, co-operation was manipulated by assigning specific interviewers to specific sample units. Contact was manipulated by timing, spacing and prioritizing calls. The tailored fieldwork strategy was successful in significantly increasing representativeness, while maintaining the level of response and costs. Representativeness was determined by R-indicators.

We compared a tailored and a targeted intervention designed to increase genetic testing, clinical breast exam (CBE), and mammography in young breast cancer survivors (YBCS) (diagnosed <45 years old) and their blood relatives. A two-arm cluster randomized trial recruited a random sample of YBCS from the Michigan cancer registry and up to two of their blood relatives. Participants were stratified according to race and randomly assigned as family units to the tailored (n = 637) or the targeted (n = 595) intervention. Approximately 40% of participants were Black. Based on intention-to-treat analyses, YBCS in the tailored arm reported higher self-efficacy for genetic services (p = 0.0205) at 8-months follow-up. Genetic testing increased approximately 5% for YBCS in the tailored and the targeted arm (p ≤ 0.001; p < 0.001) and for Black and White/Other YBCS (p < 0.001; p < 0.001). CBEs and mammograms increased significantly in both arms, 5% for YBCS and 10% for relatives and were similar for Blacks and White/Others. YBCS and relatives needing less support from providers reported significantly higher self-efficacy and intention for genetic testing and surveillance. Black participants reported significantly higher satisfaction and acceptability. Effects of these two low-resource interventions were comparable to previous studies. Materials are suitable for Black women at risk for hereditary breast/ovarian cancer (HBOC).

While completing my PhD in sociology, I did not anticipate spending most of my academic career researching ways to improve methods for doing sample surveys. At that time, I was dedicated to understanding community organization and how people adopt the use of new technologies. This article describes how becoming a new assistant professor just prior to a university crisis turned my academic interests away from organizational behavior toward more than five decades of research to advance survey methodology in step with technological changes transforming the world. This process also turned upside down my thoughts on how to do research. Increasingly I was inspired by the work of survey designers in government and private sector organizations who needed help with improving their survey designs. These experiences led to the creation of a series of innovations: telephone and mail data collection methods, mixed-mode surveying, tailored design for different survey situations, data collection over the internet, unified construction of questionnaires across survey modes, and understanding the differences between answers given to aurally vs. visually delivered survey questions. This sequence of research efforts led to the development and testing of web-push procedures that are now replacing the use of telephone survey methods throughout the world. Yet frequently and at unexpected times, my education in social organization and technology issues provided much needed guidance for thinking beyond the constraints of current survey methods and the possibilities that new methods could provide.

Introduction: A partnership between three Aboriginal Community Controlled Organisations and a mainstream health service was formed to develop, implement and evaluate a comprehensive and culturally appropriate social marketing project which aimed to encourage smokers to quit smoking. The project also supported quit attempts and promoted denormalisation of smoking. Methods: The project was evaluated through baseline (n = 427) and follow-up (n = 611) surveys carried out face-to-face with Aboriginal and/or Torres Strait Islander participants 18 years and older recruited through convenience sampling at community events and venues during 2010-2011 and 2015. Results: The proportion of participants who had made one or more quit attempts increased significantly between baseline and follow-up surveys (54%, 101 out of 187; vs 64%, 189 out of 297; P < 0.05). Participants who had intended to quit within 6 months (AOR, 3.29; 95% CI 1.90-5.68; P < 0.01); and participants disagreeing with the statement \"I don't mind if people smoke inside my home\" (AOR, 1.74; 95% CI 1.06-2.84; P < 0.05) were significantly more likely to have made one or more quit attempts compared to the respective reference groups. Conclusion: Study findings demonstrate that the project was associated with increased quit attempts. Intention to quit and attitude were found to be the predictors of making a quit attempt.

In finance and economics much work has been done on the theoretical modeling and statistical estimation of the yield curve, defined as the relationship between $ - \\frac{1}{\\tau }\\log p_t (\\tau )$ and τ, where pt,(τ) is the time t price of a zero-coupon bond with payoff 1 at maturity date t + τ. Of considerable current interest are models of the yield curve in which a collection of observed and latent factors determine the market price of factor risks, the stochastic discount factor, and the arbitrage-free bond prices. The model is particularly interesting from a statistical perspective, because the yields are complicated nonlinear functions of the underlying parameters (e. g., those appearing in the evolution dynamics of the factors and those appearing in the model of the factor risks). This nonlinearity tends to produce a likelihood function that is multimodal. In this article we revisit the question of how such models should be fit from the Bayesian viewpoint. Key aspects of the inferential framework include (a) a prior on the parameters of the model that is motivated by economic considerations, in particular, those involving the slope of the implied yield curve; (b) posterior simulation of the parameters in ways to improve the efficiency of the MCMC output, for example, through sampling of the parameters marginalized over the factors and tailoring of the proposal densities in the Metropolis-Hastings steps using information about the mode and curvature of the current target based on the output of a simulating annealing algorithm; and (c) measures to mitigate numerical instabilities in the fitting through reparameterizations and square root filtering recursions. We apply the techniques to explain the monthly yields on nine U. S. Treasury Bills (with maturities ranging from 1 month to 120 months) over the period January 1986-December 2005. The model contains three factors, one latent and two observed. We also consider the problem of predicting the nine yields for each month of 2006. We show that the (multi-step-ahead) prediction regions properly bracket the actual yields in those months, thus highlighting the practical value of the fitted model.