Evaluation Of Impact Research Articles

Evaluation of noise pollution impact on health in Dhaka city, Bangladesh

ObjectivesThe purpose of this research was to look at the interrelation between adult health issues in Dhaka and noise pollution.MethodsThe methodology involved a cross-sectional survey conducted in five different land use categories, with a sample size of 1,016 individuals. A validated questionnaire that focused on sources of perceived noise pollution and health issues related to noise was used to gather subjective data for the study. Objective noise pollution was evaluated using equivalent continuous sound pressure level (LAeq).ResultsFindings revealed noise generated from road traffic are the predominant source of noise pollution, with Thursday evenings during the end of office hours being the noisiest period in Dhaka. All areas in Dhaka exceeded permissible noise levels, posing significant health risks to residents and workers. The study identifies critical gaps in existing noise regulation policies and enforcement.ConclusionOverall, this study underscores the urgent need for comprehensive noise pollution mitigation strategies, including innovative technologies, real-time monitoring systems, and public awareness campaigns. Further studies in diverse urban contexts are recommended to enhance the understanding of noise pollution’s long-term impacts on vulnerable populations.

Integration of cone beam computed tomography for interdisciplinary diagnosis and treatment planning

Cone-beam computed tomography (CBCT) has revolutionized dental imaging by providing precise three-dimensional visualization of hard tissue structures with minimal radiation exposure compared to conventional CT. This review explores the integration of CBCT in interdisciplinary diagnosis and treatment planning across various fields of dentistry. CBCT offers versatile applications including assessment of impacted teeth, airway analysis, temporomandibular joint evaluation, detection of jaw pathologies, and precise diagnosis of dento-maxillofacial fractures. Its ability to generate static and rotational 3D images aids in surgical planning and treatment outcome prediction. Furthermore, CBCT plays a crucial role in orthodontics for localization of impacted teeth and evaluation of craniofacial anomalies such as cleft lip and palate. In periodontics and implantology, CBCT facilitates detailed assessment of periodontal structures, bone defects, and precise implant placement. Additionally, CBCT assists in maxillofacial prosthetics by enabling virtual surgical planning and custom prosthetic fabrication. This paper underscores CBCT as an indispensable tool in modern dental practice, enhancing diagnostic accuracy, treatment precision, and patient outcomes across diverse clinical scenarios.

The ARIS Broader Impacts Toolkit: An Online Guide to Support Broader Impact Project Development and Evaluation for Researchers and BI Professionals

The Center for Advancing Research Impacts in Society (ARIS) Broader Impacts (BI) Toolkit is a collection of online, interactive tools focused on the generation of broader impacts activity plans that satisfy the criteria of proposals submitted to the National Science Foundation (NSF). The BI Toolkit includes a set of ARIS Guiding Principles, a Planning Checklist, the BI Wizard, and the BI Rubric. Over a three-year period, the ARIS BI Toolkit was pilot-tested with BI professionals located within ten institutions geographically distributed across the United States. The participating institutions represented a range of R1 and R2 institutions, Land-Grant Institutions, and Minority Serving Institutions with BI professionals serving in centralized and decentralized capacities within the institutions. This paper discusses the development of the ARIS BI Toolkit, its evolution through usability testing, a description of the BI Toolkit as it currently exists, and goals for future expansion.

Association between coordinated counseling from both ASHA and Anganwadi Workers and maternal health outcomes: A cross-sectional study from Madhya Pradesh and Bihar, India.

Community Health Workers (CHWs) play crucial roles in health promotion and services in rural India. Previous research investigating the effectiveness of coordinated health promotion by different community health workers (CHWs) cadres on health practices is scarce. This study examines the effectiveness of coordinated health promotion by different CHW cadres, specifically Accredited Social Health Activists (ASHA) and Anganwadi Workers (AWW), on maternal health outcomes. Using endline data from a 2019 impact evaluation of 6635 mothers with children <12 months in Madhya Pradesh and Bihar, we compared the association between standalone and coordinated counseling by ASHA and AWW on various maternal health practices. Outcomes included four or more antenatal care visits, birth preparedness, institutional delivery, postnatal care visits, and contraceptive uptake. Fixed effects logistic regression with robust standard errors, corrected for multiple hypothesis tests, was used for analysis. Results showed that 39.6% of women received four or more ANC visits, 31.2% adopted birth preparedness practices, 79.6% had institutional deliveries, 23.3% received postnatal care, and 19.5% adopted a postpartum contraceptive method. Coordinated counseling from both ASHA and AWW was associated with a greater prevalence of four outcomes (birth preparedness, institutional delivery, PNC visit, and contraception) compared to standalone counseling from either ASHA or AWWs. These findings suggest that health promotion by AWW complements that of ASHA, collectively associated with improved health outcomes. This study underscores the effectiveness of coordinated health promotion and highlights the need for multisectoral and coordinated efforts among different CHW cadres at the community level. The results emphasize the importance of integrating various CHW roles to enhance maternal health practices and outcomes in rural India. Trial registration number: https://doi.org/10.1186/ISRCTN83902145. Date of registration: 08/12/2016.

OGC SO11 - Impact Evaluation of Endoscopic Mucosal Resection in the Foregut in a Tertiary Centre in the United Kingdom (UK)

Abstract Background Endoscopic mucosal resection (EMR) has emerged as a crucial technique for managing early-stage lesions in the oesophagus and stomach, encompassing precancerous and cancerous conditions.1 With fewer complications and excellent 5-year survival rates, EMR has shown potential as a less-invasive alternative to surgical resections.1 EMR achieves higher accuracy with its ability to obtain more profound and better quality tissue samples compared to conventional biopsies, which facilitates multidisciplinary team (MDT) discussions regarding treatment decisions.1 This study aims to evaluate the impact of EMR performed in an Oesophago-Gastric Cancer tertiary centre in the UK. Method This is a retrospective service evaluation of patients who underwent EMR from March 2021 to March 2024. A sample size of 73 EM (n=73) is identified. Data were collected from medical and endoscopic records, which includes patient’s demographics, American Society of Anaesthesiologists (ASA) grade, EMR indication, histology report and MDT outcome. EMRs performed were categorised into oesophageal, gastric and duodenal. Three main referral indications were identified; ‘polyp’, ‘dysplastic nodule in Barrett’s oesophagus’ and ‘possible early malignancy’. MDT outcomes were analysed thematically. Results Of the seventy-three patients identified, 78% is male and mean age at 71 years. Most patients (81%) are classified as ASA Grade 2. Polyp is identified in 37 patients (51%), making up the most common referral indication. 49% of the EMR were gastric, with remaining being oesophageal (41%) and duodenal (11%). 26% of histology results showed benign disease, 40% dysplastic disease, and 34% malignant. From histology reports, 47% of the EMRs achieved complete clearance margins. 28 patients (38%) were discharged with no further interventions and 12 patients (16%) received repeat EMR. 4 main themes were identified from MDT outcomes, with 43.8% patients needing surveillance endoscopy, 16.7% patients recommended for surgical intervention and repeated EMR each. Conclusion EMR has shown to be effective as a reference for further treatment decisions, especially for MDT discussions. It has been proven that EMR can be therapeutic in providing complete resection, particularly for benign and early dysplastic diseases.

Evaluating the Dynamic Comprehensive Resilience of Urban Road Network: A Case Study of Rainstorm in Xi’an, China

Rainstorms and flooding are among the most common natural disasters, which have a number of impacts on the transport system. This reality highlights the importance of understanding resilience—the ability of a system to resist disruptions and quickly recover to operational status after damage. However, current resilience assessments often overlook transport network functions and lack dynamic spatiotemporal analysis, posing challenges for comprehensive disaster impact evaluations. This study proposes an SR-PR-FR comprehensive resilience evaluation model from three dimensions: structure resilience (SR), performance resilience (PR), and function resilience (FR). Moreover, a simulation model based on Geographic Information System (GIS) and Simulation of Urban MObility (SUMO) is developed to analyze the dynamic spatial–temporal effects of a rainstorm on traffic during Xi’an’s evening rush hour. The results reveal that the southwest part of Xi’an is most prone to being congested and slower to recover, while downtown flooding is the deepest, severely affecting emergency services’ efficiency. In addition, the road network resilience returns to 70% of the normal values only before the morning rush the next day. These research results are presented across both temporal and spatial dimensions, which can help managers propose more targeted recommendations for strengthening urban risk management.

Production of Biodiesel from Industrial Sludge: Recent Progress, Challenges, Perspective

This study investigated biodiesel production from industrial sludge, focusing on the feasibility and sustainability of converting waste materials into renewable energy sources. This study combines a comparative analysis of various sludge-based biodiesel production methods, highlighting both their environmental benefits and economic potential. Utilizing physical, chemical, and biological pre-treatments, this study optimizes biodiesel yield while assessing the impact of each method on the overall production efficiency. Key findings revealed that industrial sludge provides a viable feedstock, contributes to waste reduction, and reduces greenhouse gas emissions. The novel contributions of this study include a detailed economic assessment of biodiesel production from sludge and a comprehensive environmental impact evaluation that quantifies the potential sustainability benefits. Limitations related to scale-up processes are identified, and solutions to overcome these issues are discussed to improve industrial feasibility. Furthermore, the integration of sludge-based biodiesel production with other renewable energy systems has been explored as a future avenue to enhance energy efficiency and sustainability. This research contributes to a significant scientific niche by addressing scalability challenges and proposing future perspectives for sustainable biodiesel production from industrial waste.

BIOM-52. THE DYNAMIC GLIOMA CSF PROTEOME: IMPACT OF LOCATION AND RESECTION FOR DISEASE MONITORING

Abstract While serial sampling of glioma tissue is rarely performed before recurrence, cerebrospinal fluid (CSF) can be acquired serially to evaluate candidate monitoring and pharmacodynamic biomarkers in patients with gliomas. However, the impact of key variables to consider in longitudinal CSF, including anatomical location and post-surgical changes, remains unknown. To that end, pre- versus post-resection intracranial CSF samples from patients with gliomas were obtained at early (1-16 days; n=20) or delayed (86-153 days; n=11) timepoints, as well as lumbar-versus-intracranial glioma CSF samples (n=14). Using aptamer-based proteomics, we identified significant differences in the glioma CSF proteome between lumbar, subarachnoid, and ventricular CSF. Indeed, intracranial CSF in paired lumbar/intracranial samples had nearly 1600 unique aptamers, regardless of which intracranial location was compared to the paired lumbar CSF, including in enrichment style analyses that evaluated the overlap between protein states. Importantly, resection had a significant, evolving longitudinal impact on the CSF proteome, with subsets of proteins associated with early versus delayed post-resection changes, many of which were enriched for inflammatory-related pathways. Interestingly, despite increased contamination from surgical debris, enrichment for plasma-associated proteins decreased with resection (FDR: 0.000), suggesting that a portion of the baseline glioma panel could be derived from plasma-originating analytes due to blood-brain barrier disruption. Despite these challenges, our data still revealed preliminary candidate monitoring biomarkers, such as brevican, that increased with progression (example patient: fold-change of 3.58x and 2.08x through lomustine and bevacizumab, respectively), but not pseudoprogression (Fold change less than 1.5). Serial intracranial CSF samples suggested the early potential for disease monitoring and evaluation of pharmacodynamic impact of targeted therapies, including bevacizumab and pembrolizumab. In conclusion, our available data to date suggest that the intracranial glioma CSF proteome provides an abundant and evolving source of candidate biomarkers to longitudinally discern the impact of resection and systemic treatments.

Human oocyte zona pellucida abnormalities: evaluation of clinical impact for different zona pellucida abnormalities and role of using assisted hatching.

Zona pellucida (ZP) plays an important role in oocyte development and fertilisation, as well as in early embryo development. However, there is currently no exploration of systematic categorising and clinical treatment measures for patients with abnormal ZP, especially the fast and easy method that can be used clinically. In this study, 185 patients with abnormal ZP (ZPA) and 222 patients with normal ZP (ZPN) were enrolled and analysed. Patients with ZPA exhibited altered hormone levels and lower laboratory outcomes in in vitro fertilisation (IVF), such as reduced MII rate, cleavage rate, high-quality embryo rate, and blastocyst formation rate compared to ZPN group. ZPA patients were sub-categorised into ZPA-A/B/C/D group according to the status of oocyte polar body and the width of perivitelline space (PVS). There are also differences in the degree of sperm binding to ZP derived from different ZPA patients and the elasticity of the oocyte membrane. ZPA subgroup analysis revealed further disparities in various IVF parameters and pregnancy outcomes. In addition, by performing different treatments on oocytes derived from ZPA patients, we found that ZP assisted hatching before the first oocyte cleavage on D1 of embryonic development in the ZPA-A/B groups and before blastocyst expansion on D4 of embryonic development in the ZPA-C/D groups were beneficial to improve embryonic development. The degree of the impact on clinical outcomes is correlated with the types of ZPA, and laser-assisted hatching of the ZP helps to improve embryonic development in patients with ZPA.

Evaluation of the Detrimental Impact of Low-Intensity Laser Radiation on the Characteristics of Sperm Movement, Motion, and DNA Damage

It is generally accepted that low-level laser therapy promotes cellular energy production and increases the synthesis of ATP by triggering the mitochondrial electron transport chain's photosensitive cytochrome c oxidase complex. Nevertheless, this investigation aimed to examine the possible adverse impact on sperm function and DNA integrity of low-intensity laser radiation with a wavelength of 980 nm. Following standard analysis, forty semen samples were collected and categorized as either asthenospermic, oligospermic, or normospermic. The remaining semen was subjected to standard semen analysis, and the aliquots were divided into treatment and control groups. A continuous-wave 980 nm laser with an output power of 100 mW and an energy density of 10 J/cm2 was applied to the treated samples for 30 s. Divided samples underwent incubation at 37oC, and semen analysis was used to assess aliquots at 30 s and 2 h intervals. Following the incubation time, each sample was frozen in 250 mL at -80oC until DNA fragmentation was examined using flow cytometry. Thirty minutes after treatment, there was a noticeable increase in sperm movement; the rise was largest in oligospermic and asthenospermic samples (88%) while samples of normal sperm displayed the least increment (7.5%). There was no discernible increase in DNA damage in the treatment samples compared to the control samples. The treatment samples had 21.8% and the control samples had 25.3% of the DNA fragmentation index. The dynamics of sperm motion were noticeably altered. Short-term exposure to low-level laser radiation appeared to improve the motion and movement of treated sperm, and after 2 h, there was no increase in DNA damage. Asthenospermia and mitochondrial dysfunction may be related in some circumstances. To fully understand the ramifications of these results for possible medicinal applications, more research is needed. Our research's conclusions suggest that low-level laser stimulation is a useful and safe technique for identifying viable immotile spermatozoa in a particular sample. It may also cause these spermatozoa to move about, which could have positive therapeutic effects.

Analysis of failure modes and impact resistance factors of PDC cutters

The service life of PDC cutters directly affects the overall drilling performance. In hard and heterogeneous formations, PDC cutters often fail prematurely due to dynamic impacts, leading to short footage and slow penetration rates. Enhancing the dynamic impact resistance of PDC cutters is crucial for achieving one-run drilling and reducing costs. This paper systematically studies the main factors influencing and optimizing the impact resistance of PDC cutters. First, the failure modes of hundreds of returned PDC drill bits were statistically analyzed, revealing that dynamic impact failure, wear failure, thermal damage, and erosion are the primary failure modes. Among these, dynamic impact failure is the most prevalent, with dynamic impact load being the main cause. Following the successful practices of leading international drill bit companies, a set of dynamic impact test and evaluation devices for PDC cutters was designed, and corresponding testing standards were established. Based on this, 19 types of PDC cutters were tested for impact resistance, exploring the effects of cutter diameter, diamond layer thickness, chamfer, cobalt removal, and cutter design on impact resistance. An optimized design methodology to enhance impact resistance was summarized, leading to the proposal of a new arch-axe cutter design. Indoor impact test data verified the superiority of this cutter. The research results indicate that cutter design (non-standard cutters) can significantly improve the dynamic impact resistance of PDC cutters. Additionally, increasing the cutter diameter and chamfer size while reducing the diamond layer thickness also enhances the dynamic impact resistance of PDC cutters. Through the optimization of the arch-ridge design, the independently developed arch-axe cutter improved the dynamic impact resistance by 106.45% and 71.43% compared to flat circular cutters and axe-shaped cutters, respectively.

Enhancing Food Security in an Era of Rising Fertilizer Prices: Evaluation of an Intervention Promoting Mungbean Adoption in Nepal

The improved food security in Asia that has facilitated the region’s development progress depends on nitrogenous fertilizers. Rising prices and shortages of imported fertilizer have prompted countries to explore alternative sources of crop nitrogen, including diversification with legumes. We evaluate an intervention in Nepal that promoted mungbean adoption. Our doubly robust impact evaluation approach accounts for nonrandom patterns of adoption related to livestock rearing, participation in agricultural cooperatives and training, and greater irrigated land use. Adopters growing mungbean for the 2-year study period showed an average increase of 20 kilograms (kg) in their annual consumption of mungbean-based foods, applied almost 40[Formula: see text]kg per hectare (ha) less fertilizers to their rice crops, and obtained an additional 280[Formula: see text]kg in rice yield per ha. Hence, agricultural innovations that use legumes such as mungbean can help promote sustainable intensification of cereal-based production systems, while enhancing food security and reducing balance-of-payments issues for the countries dependent on fertilizer imports.

PP226 Topic: AS21–Post-PICU: Patient and Family Outcomes/Chronic Critical Illness/Post Intensive Care Syndrome in Pediatrics (PICS-p)/Post-discharge Care Delivery Models/Other: RESPONDER. REESTABLISHMENT POST-ICU PROGRAM: EVALUATION OF IMPACT OF A FOLLOW-UP CLINIC IN A PEDIATRIC HOSPITAL IN COLOMBIA

PP226 Topic: AS21–Post-PICU: Patient and Family Outcomes/Chronic Critical Illness/Post Intensive Care Syndrome in Pediatrics (PICS-p)/Post-discharge Care Delivery Models/Other: RESPONDER. REESTABLISHMENT POST-ICU PROGRAM: EVALUATION OF IMPACT OF A FOLLOW-UP CLINIC IN A PEDIATRIC HOSPITAL IN COLOMBIA

Prospective evaluation of impact of adaptive radiotherapy on quality of life in patients with locally advanced head and neck cancers

Prospective evaluation of impact of adaptive radiotherapy on quality of life in patients with locally advanced head and neck cancers

Getting Inspired by Contribution Analysis. Impact Evaluation of the European Commission’s Social Business Initiative

This article addresses the question of how complex interventions can be adequately assessed with limited resources. In 2011, the European Commission presented the Social Business Initiative (SBI), a framework initiative to develop a favourable environment for social enterprises and the social economy. The complexity of the programme stems from its numerous components and the long timeframe for its implementation. The evaluation of the impact of the SBI was commissioned in 2019 and the final report was presented in November 2020. The article presents the study and the evaluation methodology used to analyse the impact contribution influenced by the SBI. A theory-based evaluation approach was chosen, inspired by contribution analysis. The article describes the implementation of the evaluation and discusses the suitability of the chosen method, identifying both its strengths and shortcomings in this specific context.

Predicting tensile and fracture parameters in polypropylene-based nanocomposites using machine learning with sensitivity analysis and feature impact evaluation

This study examines the efficacy of decision tree and AdaBoost algorithms in predicting mechanical and fracture parameters of polypropylene nanocomposites toughened with ethylene-based and propylene-based thermoplastic elastomers and reinforced with fumed silica and halloysite nanotube nanoparticles. The essential work of the fracture approach was utilized to study the fracture parameters, including elastic and plastic works of the blended polymer nanocomposites. The data were divided into 80 % for training and 20 % for testing. AdaBoost consistently achieved superior performance compared to the decision tree model in all variables throughout both the training and testing stages. During the testing phase, the AdaBoost model obtained R2 values of 0.90 for Young's modulus, 0.93 for elongation at break, 0.87 for tensile strength, 0.86 for plastic work, and 0.60 for elastic work. Also, the mean absolute percentage error for the AdaBoost model during the test phase was 3.10 % for Young's modulus, 3.25 % for tensile strength, 10.34 % for elastic work, 13.55 % for plastic work, and 24.78 % for elongation at break. Furthermore, a sensitivity analysis examining the effects of various features such as TPO type, nanoparticles, and nanoparticle type on mechanical properties reveals that TPO has the most significant overall influence. The results also include an analysis of the impact of the key features on each mechanical property based on the sensitivity analysis.

Promote students’ computational thinking in rural areas: The moderating role of gender

The purpose of this study was to assess rural students’ computational thinking abilities. The following proofs were observed: (1) Students’ abstraction affected algorithmic thinking skills; (2) Students’ decomposition influenced algorithmic thinking skills; (3) Students’ abstraction impacted evaluation skills; (4) Students’ algorithmic thinking affected evaluation skills; (5) Students’ abstraction impacted generalization skills; (6) Students’ decomposition impacted generalization skills; (7) Students’ evaluation affected generalization skills. Gender differences were observed in the relationship among the computational thinking factors of junior high school students. This included the abstraction-generalization skills; evaluation-generalization skills; and decomposition-generalization skills relationships, which were moderated by the gender of the students. 258 valid surveys were collected, and they were utilized in the study. Conducting the descriptive, reliability, and validity analyses used SPSS software, and the structural equation modeling (SEM) was also conducted through Smart PLS software to assess the hypothetical relationships. There were gender disparities in the correlation among computational thinking components of the junior high school students’ studying in rural areas. Research has shown that male and female students may have different abstractions, evaluations, and generalizations related to computational thinking, with females being more strongly associated than males in non-programming learning contexts. These results are expected to provide relevant information in subsequent analyses and implement a computational thinking curriculum to overcome the still-existing gender gaps and promote computational thinking skills.

Identifying the active ingredients in payment for performance programmes using system dynamics modelling

Payment for performance (P4P) is not a uniform intervention, with programme effect dependent on several interconnected factors. In this study, a system dynamics model was developed to explore the pathways to improved outcomes and how changes in the design, implementation and context of a P4P programme affected maternal and child health (MCH) service delivery outcomes in Tanzania. A previously developed causal loop diagram of the programme effects was used to inform model development, with further data sources (including an impact evaluation of programme, health surveys, stakeholder feedback and relevant literature) used to build the model. A number of pathways were identified to improved services under P4P, with increased availability of drugs underpinning the content of care outcome (intermittent preventative treatment during ANC), which together with increased supervision, enhanced health worker motivation. This in turn increased perceived quality of care at the facility which improved the coverage of services outcome (facility-based deliveries), and with increased outreach, increased awareness of services also boosted demand. Minor delays in payment reduced provider purchasing power for medicines, with severe delays driving erosion of provider trust and motivation for programme participation. Allocating a larger share of funds for facility operations can enhance performance effects, particularly for those services that rely on efficient drug administration. Contextual factors including limited baseline provision of essential medications, lower community awareness of facility services and dispersed/distant populations reduced programme effect. This paper demonstrates the feasibility and the potential of such models to inform the design of effective health system interventions.

Devising a method for integrated dataset formation and selecting a model for recognizing the technical condition of unmanned aerial vehicle

The object of this study is the process of forming a training dataset for diagnosing the technical condition of unmanned aerial vehicles (UAVs) using machine-learning algorithms. UAV flights are extremely important for various aspects of troop deployment. Combat UAV flights are performed under the influence of negative factors that cause flight special cases (FSC), which hinder the execution of combat missions, lead to mission failures, and result in the aircraft damage or loss. The available capabilities of autopilots are not enough for control under complex conditions, and in certain situations, the human operator cannot timely recognize a flight special case, including evaluation of the destructive impact of enemy’s electronic warfare systems on communication channels and operation of UAV. Therefore, the urgent issue is the intellectualization of onboard control systems, particularly towards recognizing the current technical state of UAV using artificial intelligence methods. To design such systems, labeled datasets are required. The procedure for forming datasets that consider the specificity of UAV construction and their combat use under adversarial conditions is not defined, necessitating the development of an appropriate method. Based on the well-known CRISP-DM methodology, a method for dataset formation has been proposed for subsequent use in artificial intelligence systems that use various machine-learning methods. This method differs from existing ones by considering the specificity of combat mission execution under adversarial conditions, which allowed for an 8.0 % increase in the accuracy of recognizing special cases in UAV flights by the onboard system. It also enabled timely detection of electronic warfare impacts on UAV and evaluation of the effectiveness of radio signal receivers jamming

Best practices for implementing equitable and just large-scale randomized trials in majority world countries.

This article focuses on a widely used method in developmental and education research in majority world countries: large-scale impact evaluations and randomized controlled trials. We build on our experience implementing such programs in majority world countries, primarily in West Africa, and reflect on our experiences to propose a set of best practices in maintaining equity and justice in collaborations between majority and minority world countries. These include prioritizing research-policy-community partnerships, promoting complementary research approaches, considering measurement timescales, and capacity exchange approaches. (PsycInfo Database Record (c) 2024 APA, all rights reserved).