Classification Of Problems Research Articles

Problematising menstrual tracking apps: presenting a novel critical scoping review methodology for mapping and interpreting research literature

Objectives To showcase a novel, theoretically informed methodology for conducting scoping reviews by operationalising critical theory. And to advance the field of women’s digital health by applying this critical scoping review methodology (CSR) to research on menstrual tracking apps (MTAs). Methods and measures 116 articles published in English, between November 2015 and November 2023, focusing on MTAs, and/or user’s experiences of MTAs, were thematically analysed through the Foucauldian concept of problematisation and analytics from critical psychology. This method examined what was produced as a problem, and the underpinning discourses, subject positions, paradigms, desired outcomes, and absences within these problem categories. Results Four problematisations were identified, (1) the problem of data privacy (subproblems: type of data, consent, abortion surveillance); (2) the problem with efficacy (subproblems: evaluating efficacy, accuracy, useability); (3) the problem of regulation (subproblems: self-surveillance, normative femininity, hormonal imperative, cycle regularity imperative, menstrual stigma); and (4) the problem of women (subproblems: health literacy, technology use, medically unknown, hard to design for). Conclusion MTA researchers would benefit from understanding their field through these problematisations. The CSR offers an important theoretically informed methodology for mapping and interpreting a research literature, which can identify, and expand, possibilities for research thought and practice.

Considering the dual role of intermediate weights in fuzzy network systems by genetic algorithms

Purpose Many researchers and analysts are interested in evaluating the performance of a system with a network structure as a decision-making unit. In this regard, fuzzy network data envelopment analysis (FNDEA) is a noticeable and worthy method for evaluating the efficiency of a system with fuzzy data. Based on the structure of a fuzzy network system, which consists of at least two serial stages, an intermediate factor has an output nature for the first stage and an input nature for the second stage. Hence, it is inappropriate to allocate the same weight for each stage using this factor. Unfortunately, contrary to real-world conditions, all previous conventional FNDEA studies have considered the same role for intermediate factors to linearize or simplify models. For the first time, this study attempts to determine the upper and lower bounds of the overall efficiencies of a fuzzy two-stage series system and its subprocesses with unequal intermediate product weights. Design/methodology/approach The proposed model remains in its original nature as a complex combinatorial problem in the nonlinear programming category of NP-hard problems. A genetic algorithm (GA) is utilized as a metaheuristic algorithm, and a novel hybrid GA-FNDEA algorithm is presented to solve the problem. Findings The findings of the study outlined several theoretical contributions and practical implications, including as compensatory property of DEA, determining upper and lower bounds, improving efficiency in nonlinear systems, reducing computational burden, enhancing evolutionary algorithms and retaining real-world conditions. Originality/value Contrary to real-world conditions, all previous conventional FNDEA studies have considered the same role for intermediate factors to linearize or simplify models. For the first time, this study attempts to determine the upper and lower bounds of the overall efficiencies of a fuzzy two-stage series system and its subprocesses with unequal intermediate product weights.

A novel approach for solving bi-level mono-objective and multi-objective programming problems using evolutionary algorithms

Bi-level programming problems (BLP) constitute an important class of non-convex optimization problems, which makes it challenging to find a global optimal solution. In this article, we propose an efficient technique to solve this category of problems. We reformulated the initial problem as a single-level optimization problem using the optimal value function of the lower-level problem. To solve the latter, we employed a technique based on -dense curves to approximate the value function of the lower-level problem. Two evolutionary algorithms were then used to solve the reformulated problem. Furthermore, we extended our method to address multi-objective bi-level programming problems with a single objective at the upper level and multiple objectives at the lower level, known as a semi-vectorial bi-level programming problem. Several numerical experiments on nonlinear BLP show the outstanding efficiency of our approach.

ANALISIS PERMASALAHAN YANG MEMPENGARUHI PELAKSANAAN PROYEK GEDUNG BPKB POLRES PATI

Project Management is planning, organizing, leading and controlling company resources to achieve predetermined short-term goals. Project Management can also be interpreted as activities to achieve goals that have been clearly defined and determined as efficiently and effectively as possible (Soeharto, 2010). Construction project management has characteristics, is unique, involves a lot of resources, and requires organization. The data processing results of this research were taken as a whole from all incoming data, as many as 40 respondents. But before taking the overall data analysis, it can be seen from the completeness of the data based on work items that influence the construction implementation method of a BPKB building project, namely planning factors, material factors, labor factors, equipment factors, financial factors, relationship factors with the government, contract factors. , supervisory consultant factors, contractor factors, environmental factors, so the results of this questionnaire are divided into 3 categories of problems that influence the implementation of the BPKP Pati grunge construction project, namely the high category, the medium category and the low category.

Set Covering Routing Problems: A review and classification scheme

Cyclic routing problems are a well-researched category of combinatorial problems in Operations Research (OR). They involve finding an optimal cycle (route), starting from an initial point (e.g., depot), visiting some nodes (e.g., customer or demand points), and returning to the starting point while adhering to constraints and optimizing a specific objective. These problems are categorized into two main types: (i) Hamiltonian routing problems: All customer nodes must be visited (must be on a cycle), such as the Traveling Salesman Problem (TSP), seeking the shortest possible cycle visiting each node once. (ii) Non-Hamiltonian routing problems: At least one customer node is not on a route. This work mainly focuses on classifying one of the main sub-problems of non-Hamiltonian routing problems, known as Set Covering Routing Problems (SCRPs), in which customers may be directly visited or covered by another node on the cycle or route. The SCRPs also incorporate Steiner nodes (transition points) to cover the customers who are not directly visited, integrating covering and routing decisions. SCRPs have wide-ranging applications in logistics, transportation planning, healthcare, telecommunication network design, and disaster response, making them vital for theoretical exploration and practical solutions. This work reviews the studies on SCRPs, presenting a classification scheme and a generic mathematical model for these problems, enabling a unified analysis and comparison. Finally, the study gaps, future research directions, and the limitations and implications for practical applications are discussed.

Identifikasi Drug Related Problems Pada Pasien Penyakit Ginjal Kronis Di Rumah Sakit Prof. dr. Chairuddin Panusunan Lubis Tahun 2023

Chronic kidney disease (CKD) is an abnormality of kidney structure or function, present for ≥ 3 months, with implications for health. The high number of medications used by CKD patients can increase the potential for Drug-Related Problems (DRPs) which can interfere with desired health outcomes. This study aimed to determine the occurrence of DRPs in chronic kidney disease patients admitted to Prof. dr. Chairuddin Panusunan Lubis Hospital in 2023. This study was a descriptive retrospective cross-sectional study conducted. Data were obtained from the medical records of CKD inpatients in 2023 (n=51). The sampling technique used was total sampling. The occurrence of DRPs was identified based on the Pharmaceutical Care Network Europe (PCNE) V9.1 classification, which includes problems categories (P1-P3) and causes (C1-C6). There were 28 females (54.90%) and 23 males (45.10%), with an average age of 46.8±11.5 years. The highest stage of CKD was stage 5 (78.43%). The most common comorbid condition was anemia (84.31%), with the most frequently used medication being antihypertensives in the Calcium Channel Blocker class (88.24%). Among the 51 medical records, 21 (41,17%) showed the occurrence of DRPs, consisting of 26 Problems (P) categorized under P1. Treatment effectiveness (46,15%) and P2. Treatment safety (53,85%), and 26 Causes (C) categorized under C1. Drug selection (57,69%) and C3. Dose selection (42,31%). Drug-Related Problems (DRPs) occurred in chronic kidney disease patients admitted to Prof. dr. Chairuddin Panusunan Lubis Hospital in 2023.

Pediatric masks of obstructive sleep apnea syndrome

A number of factors contribute to the occurrence of chronic otolaryngological diseases in children at an early age, which often acquire a long, undulating course with exacerbations, relapses and complications. The increasing aggressiveness of environmental factors, the growth of allergization of the population, the formation of strains of microorganisms resistant to the action of medicines, lead to a steady increase in diseases of the nasopharyngeal tonsils and a worsening of their course, especially among children, both in our country and abroad. At the same time, the adenotonsillar problem has long gone beyond ENT pathology and attracts the attention of a wide range of medical resea. The aim of the work: to analyze the literature data on clinical manifestations, laboratory and instrumental diagnostic methods and the prevalence of OSA in children. The analysis of publications using PubMed, EMBASE and Web of Science search engines in the period from January 1970 to March 2024 related to research on epidemiological, pathogenetic, clinical and laboratory aspects of OSA in children and adults was carried out. rchers. Sleep respiratory disorder is a term covering various clinical diagnoses from primary snoring to obstructive sleep apnea. This clinical symptom is registered in at least one in nine children, which makes it one of the most frequently diagnosed sleep disorders and puts it in the category of serious social problems. The most compelling evidence relates to hyperactivity, inattention, and social problems: decreased social competence, increased problematic behavior, and decreased memory scores. Despite the growing body of evidence suggesting cognitive impairment in children with snoring, many results have been contradictory. The availability of pediatric sleep laboratories, even in countries with advanced health systems, is limited, which encourages the search for less complex and more convenient testing methods. Timely detection of the development of the disease allows you to prevent complications and improve the quality of life. The article also describes clinical cases of late diagnosis of obstructive sleep apnea in children.

Competition of tribes and cooperation of members algorithm: An evolutionary computation approach for model free optimization

Metaheuristic algorithms are a series of intelligent algorithms that are inspired by natural phenomenon and achieve the optimal searching via utilizing behaviors from nature. The rising complexity and dimensions of practical engineering problem in reality, a significant number of metaheuristic algorithms are promoted and applied in various of fields. Inspired by ancient tribes competition and members cooperative behavior, this paper proposes the Competition of Tribes and Cooperation of Members Algorithm (CTCM). Subsequent experiments are conducted on 23 benchmark test functions and exhaustively compared with other state-of-the-art algorithms, including particle swarm optimization (PSO), grey wolf optimizer (GWO), sparrow search algorithm (SSA), egret swarm optimization (ESOA), beetle antennae search (BAS) and whale optimization (WOA). The standard deviation and average, as well as statistic test are utilized to compare the performance of each algorithms, which reveal that CTCM outperforms in most kinds of problem. And from the result of Wilcoxon and Friedman rank test, the CTCM achieve the first place in all categories of problems, which indicate that CTCM possesses strong global optimization search capability and stability, and has faster convergence speed. The superiority of CTCM is then proofed on practical engineering optimization problems, in which CTCM achieve all the optimal solution for each engineering problem.

On a Hybrid Class of $p$-Laplacian Initial Value Problems with Modified Mittag-Leffler Kernel

In this work, we establish key results on the existence theory for a category of initial value problems (IVPs) involving hybrid fractional integro-differential equations (HFIDEs) with a $p$-Laplacian operator, utilizing the modified Mittag-Leffler kernel. By employing Krasnoselskii and Banach fixed point theorems (FPTs), we determine the conditions required for the existence of solutions. Additionally, we examine the Hyers-Ulam (H-U) stability of the problem. Lastly, we present an example to confirm our theoretical results.

Analisis Usability Website PT. Perkebunan Nusantara (PTPN IX) Untuk Menunjang Industri Kreatif di Era Global

Technology is rapidly advancing in society and the workplace. PT Perkebunan NusantaraIX (PTPN IX), which operates in the management and marketing of plantationcommodities, has utilized technology to facilitate the presentation of downstream productinformation through a dynamic website. The PTPN IX website plays a crucial role inpresenting the company's latest information. However, the PTPN IX website has neverundergone a usability testing process. Therefore, this study aims to analyze the quality ofthe website in supporting its role and functions. The results of the observations indicate thatseveral users experience problems when accessing the website. To analyze these issues,heuristic evaluation methods were used to identify usability problems on the website, andthe System Usability Scale (SUS) to assess the system's feasibility. This method involved3 evaluators and 100 users to evaluate the website based on 10 heuristic aspects, whichwere mapped into sub-aspects according to their severity levels. The overall evaluationresults indicated categories of cosmetic issues and minor usability problems. This studyidentified 10 problems and provided recommendations for improving the PTPN IXwebsite. The improvement recommendations aim to optimize the website system to betterfulfill its role and function as an information provider platform related to local commodityproducts for all elements of society.

Research on Dynamic Evaluation Method of Tourist Destination Accessibility Based on Interpretive Structure Model

Because of its core role in the process of tourism, tourism destination has always been the focus of discussion among the industry, but the comprehensive evaluation of tourism destination is rarely mentioned. This paper selects tourism destination as the focus of investigation, gives the evaluation method of tourism destination, adapts to the trend of tourism modernization, and discusses the quantifiable model of tourism destination evaluation. This paper first selects several tourism destinations as samples, collects and combs the information related to spatial equity of tourism destinations, and determines the main problem categories of spatial equity of tourism destinations. Then, through the summary of relevant data and case analysis, a framework of tourism target accessibility risk factors is formed. At the same time, considering the interaction between risk factors, we then give a method to determine the weight that can improve granular computing. First, we use this method to obtain the quotient space family with hierarchical characteristics through the similarity relationship between data, and then we can calculate the importance of each feature in the quotient space family, so as to obtain the corresponding weight between different influence indexes. Finally, the paper takes the tourism destination spatial equity problem as the main research goal, and through the dynamic evaluation of the tourism destination spatial equity risk impact structure using the interpretive structure model, and describes the schematic diagram of its impact structure, so as to find out the direct, source, process and other factors that cause the problem.

Unlocking the learning in formal complaints: the development of an end-of-life care complaint analysis tool

Background/Aims End-of-life care is a targeted area of healthcare service reform. Complaints are increasingly recognised as a valuable source of evidence for evaluating practice and informing service improvement work. This project aimed to develop a tool to support the standardised coding, categorisation and organisational use of formal complaint data concerning end-of-life care for adults. Methods A service evaluation was conducted using existing data. Deductive analysis was conducted with 59 letters of formal complaint submitted to an NHS trust in the Midlands, UK. A published healthcare complaints analysis tool served as a thematic framework for use in conjunction with framework analysis. The project was carried out in two stages: the first comprised preliminary work to produce a template of end-of-life care concerns; the second involved pilot testing the face validity of the template when used as a coding and categorising scheme. Results An initial template of 20 subcategories of end-of-life care concerns were developed from the data during preliminary work. This template was deemed to enable the analyst to focus on predefined areas of interest, organise concerns into relevant themes, concisely present the data in a summarised form and provide meaningful objective conclusions. During pilot testing, 185 complainant concerns were coded and categorised, over half of which fell into the domain of ‘relationship problems’ (n=99; 53.5%). Within this domain, the most common problem categories were ‘communication’ (n=44) and ‘respect and rights’ (n=44). A total of five new subcategory concerns were also derived and added to the template. Collectively, the outcomes of complaint data analysis informed the structure of a dedicated end-of-life care complaint analysis tool comprising 25 subcategories of end-of-life care concerns and accompanying exemplar indicators, together with criteria that were meaningful to identifying the context of the care concerns. Conclusions A systematic approach to analysing and reporting complainants' experiences of end-of-life care has the potential to support organisational learning, quality monitoring and bespoke service improvements in response to collective complaints and concerns.

A Task-Guided, Implicitly-Searched and Meta-Initialized Deep Model for Image Fusion.

Image fusion plays a key role in a variety of multi-sensor-based vision systems, especially for enhancing visual quality and/or extracting aggregated features for perception. However, most existing methods just consider image fusion as an individual task, thus ignoring its underlying relationship with these downstream vision problems. Furthermore, designing proper fusion architectures often requires huge engineering labor. It also lacks mechanisms to improve the flexibility and generalization ability of current fusion approaches. To mitigate these issues, we establish a Task-guided, Implicit-searched and Meta-initialized (TIM) deep model to address the image fusion problem in a challenging real-world scenario. Specifically, we first propose a constrained strategy to incorporate information from downstream tasks to guide the unsupervised learning process of image fusion. Within this framework, we then design an implicit search scheme to automatically discover compact architectures for our fusion model with high efficiency. In addition, a pretext meta initialization technique is introduced to leverage divergence fusion data to support fast adaptation for different kinds of image fusion tasks. Qualitative and quantitative experimental results on different categories of image fusion problems and related downstream tasks (e.g., visual enhancement and semantic understanding) substantiate the flexibility and effectiveness of our TIM.

Multi-Split Configuration Design for Fluid-Based Thermal Management Systems

Abstract High power density systems require efficient cooling to maintain their thermal performance. Despite this, as systems get larger and more complex, human expertise and insight may not suffice to determine the desired thermal management system designs. To this end, a framework for automatic architecture exploration is presented in this article for a class of single-phase, multi-split cooling systems. For this class of systems, heat generation devices are clustered based on their spatial information, and flow splits are added only when required and at the location of heat devices. To generate different architectures, candidate architectures are represented as graphs. From these graphs, dynamic physics models are created automatically using a graph-based thermal modeling framework. Then, an optimal fluid flow distribution problem is solved by addressing temperature constraints in the presence of exogenous heat loads to achieve optimal performance. The focus in this work is on the design of general multi-split heat management systems. The methods presented here can be used for diverse applications in the domain of configuration design. The multi-split algorithm can produce configurations where splitting can occur at any of the vertices. The results presented include three categories of problems and are discussed in detail.

Implementation of Problem-Based Learning Model to Improve High School Students' Problem-Solving Ability on Physics Materials

This research aims to see whether there is an influence of the problem-based learning model on students' problem-solving abilities in physics material at SMAN 9 Gowa. This research is Pre-Experimental research using One Group Pretest-Posttest Design so that only one class without control class. The population of this study were students of class XI MIPA 1 until XI MIPA 5. The research sample was taken using a simple random class technique, namely class XI MIPA 5 SMAN 9 Gowa. The research instrument is a test instrument for students' physics problem solving abilities in the form of 6 selected essays that use the valid criteria. The research results showed that the physics solving abilities of class XI MIPA 5 students before being taught by applying the problem based learning model were in the low problem category as indicated by the average score of 42.5. Problem solving ability of students before the application of the PBL model is 64% in the medium category, 32% in the low category and 4% in the very low category. The ability to solve physics problems of class XI MIPA 5 students after being taught by applying the problem based learning model is in the high category as shown by the average score of 61.7. Problem solving ability of students after applying the PBL model is 56% in the high category, and 44% in the medium category and nothing student have low and very low problem solving ability. In the pretest, problem solving ability has the lowest score is 19, the highest score is 47 and the average score is 42.5 which is in the medium category with a standard deviation is 6.7, while in the posttest, the lowest score is 50, the highest score is 75, and the average score is 61.7 which is in the high category with a standard deviation is 6.8. There was a significant increase in the physics problem solving abilities of class XI MIPA 5 students after being taught using the problem-based learning model with the N-Gain category = 0.34 (medium criteria).

A Giza Pyramids Construction metaheuristic approach based on upper bound calculation for solving the network reliability problem

Network reliability optimization is an optimization problem that focuses on finding an optimal solution for a reliable network design. In network reliability optimization, the goal is to maximize network reliability so that the overall cost of the network is reduced at the same time. The discussion of the reliability of various systems in the field of industry and engineering is of great importance, that's why reliability optimization has received a lot of attention in recent decades. Since this problem is included in the category of NP-Hard problems, the use of soft computing methods will be highly effective in solving it. In this paper, an approach based on the Giza Pyramids Construction (GPC) metaheuristic algorithm is proposed to solve the network reliability problem. For this purpose, two independent single objective functions with constraints are defined, and then the reliability of the network is calculated through optimistic estimation using the upper bound method. In order to compare the performance, 12 types of diverse and complex network models have been generated and the proposed algorithm has been compared with 10 popular and state-of-the-art algorithms. Statistical analysis has been used to find significant differences in the performance of algorithms. Also, a real model of the university network has been generated, investigated, and solved as a case study. The results of experiments, statistical analysis, and observations show that the proposed algorithm has a better performance than other metaheuristic algorithms and the proposed approach in solving reliability is an effective and low-cost approach.

Use of Creative Frameworks in Health Care to Solve Data and Information Problems: Scoping Review.

Digitization is vital for data management, especially in health care. However, problems still hinder health care stakeholders in their daily work while collecting, processing, and providing health data or information. Data are missing, incorrect, cannot be collected, or information is inadequately presented. These problems can be seen as data or information problems. A proven way to elicit requirements for (software) systems is by using creative frameworks (eg, user-centered design, design thinking, lean UX [user experience], or service design) or creative methods (eg, mind mapping, storyboarding, 6 thinking hats, or interaction room). However, to what extent they are used to solve data or information-related problems in health care is unclear. The primary objective of this scoping review is to investigate the use of creative frameworks in addressing data and information problems in health care. Following JBI guidelines and the PRISMA-ScR framework, this paper analyzes selected papers, answering whether creative frameworks addressed health care data or information problems. Focusing on data problems (elicitation or collection, processing) and information problems (provision or visualization), the review examined German and English papers published between 2018 and 2022 using keywords related to "data," "design," and "user-centered." The database SCOPUS was used. Of the 898 query results, only 23 papers described a data or information problem and a creative method to solve it. These were included in the follow-up analysis and divided into different problem categories: data collection (n=7), data processing (n=1), information visualization (n=11), and mixed problems meaning data and information problem present (n=4). The analysis showed that most identified problems fall into the information visualization category. This could indicate that creative frameworks are particularly suitable for solving information or visualization problems and less for other, more abstract areas such as data problems. The results also showed that most researchers applied a creative framework after they knew what specific (data or information) problem they had (n=21). Only a minority chose a creative framework to identify a problem and realize it was a data or information problem (n=2). In response to these findings, the paper discusses the need for a new approach that addresses health care data and information challenges by promoting collaboration, iterative feedback, and user-centered development. Although the potential of creative frameworks is undisputed, applying these in solving data and information problems is a minority. To harness this potential, a suitable method needs to be developed to support health care system stakeholders. This method could be the User-Centered Data Approach.

Termination and Universal Termination Problems for Nondeterministic Quantum Programs

Verifying quantum programs has attracted a lot of interest in recent years. In this paper, we consider the following two categories of termination problems of quantum programs with nondeterminism, namely: (1) (termination) Is an input of a program terminating with probability one under all schedulers? If not, how can a scheduler be synthesized to evidence the nontermination? (2) (universal termination) Are all inputs terminating with probability one under their respective schedulers? If yes, a further question asks whether there is a scheduler that forces all inputs to be terminating with probability one together with how to synthesize it; otherwise, how can an input be provided to refute the universal termination? For the effective verification of the first category, we over-approximate the reachable set of quantum program states by the reachable subspace, whose algebraic structure is a linear space. On the other hand, we study the set of divergent states from which the program terminates with probability zero under some scheduler. The divergent set also has an explicit algebraic structure. Exploiting these explicit algebraic structures, we address the decision problem by a necessary and sufficient condition, i. e. the disjointness of the reachable subspace and the divergent set. Furthermore, the scheduler synthesis is completed in exponential time, whose bottleneck lies in computing the divergent set, reported for the first time. For the second category, we reduce the decision problem to the existence of invariant subspace, from which the program terminates with probability zero under all schedulers. The invariant subspace is characterized by linear equations and thus can be efficiently computed. The states on that invariant subspace are evidence of the nontermination. Furthermore, the scheduler synthesis is completed by seeking a pattern of finite schedulers that forces all inputs to be terminating with positive probability. The repetition of that pattern yields the desired universal scheduler that forces all inputs to be terminating with probability one. All the problems in the second category are shown, also for the first time, to be solved in polynomial time. Finally, we demonstrate the aforementioned methods via a running example — the quantum Bernoulli factory protocol.

A numerical approach for a category of piecewise fractional variational problems depending on an indefinite integral

The primary focus of this study is to introduce some kinds of piecewise fractional derivatives (PFDs). These derivatives are defined using fractional derivatives in both the Atangana–Baleanu and Caputo senses. They are considered to generate a novel collection of fractional variational problems that rely on an indefinite integral. A numerical method established on the piecewise Chebyshev cardinal functions (as a suitable family of basis functions for such situations) is utilized to solve these problems. To this end, some operational matrices for PFDs of the expressed cardinal functions are derived and used to generate the presented method. Using the proposed technique, solving the desired problems is converted into solving associated algebraic systems. The effectiveness of the procedure is checked by solving some illustrative examples.

Longitudinal changes in coping strategies across midlife and older adulthood: findings from the midlife in the United States study.

Most studies examining age differences in coping across adulthood come from cross-sectional studies and focus on the broader categories of problem- and emotion-focused coping. We aimed to establish a factor structure for coping items used in a national, longitudinal study of aging (MIDUS) and examine age patterns in coping strategies over 10 years. We performed exploratory and confirmatory factor analysis, and factorial invariance testing. Next we conducted a series of multilevel models for each coping factor with participants from waves II and III of the MIDUS study (N = 2,661, Mage = 55, 58% women, 84% White). We found a four-factor solution: instrumental action; denial/disengagement; positive reappraisal; focus and venting of emotions. Invariance was established across time and age. At baseline, age was positively associated with the use of three strategies, though younger adults used more focus and venting of emotions. There was an overall decrease over 10 years in use of all strategies, which was moderated by age. Positive reappraisal declined more steeply among midlife participants, whereas the remaining strategies declined more for older participants. Results highlight the multi-dimensionality of MIDUS coping items and underscores the import of age in understanding changes in coping across midlife and older adulthood.