Implementation Cost Research Articles

Structural behaviour of built-up I-shaped CFS columns

The utilization of cold-formed thin-walled members as structural members has gained significant popularity due to their advantages in fabrication, cost-effectiveness, and transportation convenience. However, the reduced thickness of the used sections poses challenges such as global, local, and distortional member buckling, leading to a decrease in their axial strength. This study focuses on addressing these challenges by connecting the channels together using screws as an alternative to welding, considering the cost, time, and ease of implementation. Conducting finite element analysis on structural columns built-up from cold-formed double C steel channels and subjected to axial loads, this paper verifies the numerical models used against experimental tests known from the literature. A comparison of experimental results with nonlinear FEA and AISI & AS/NZ standards reveals commendable agreement, particularly in predicting the buckling behavior of the built-up I-shaped CFS columns. While the results of the finite element analysis show an overestimation of approximately 3.6% compared to the experimental tests, the AISI and AS/NZS standards demonstrate a conservatism of about 3.0%. Furthermore, the current study investigates the influence of screw spacing on axial strength of built-up cold-formed steel columns. The findings are derived from 175 finite element experiments, evaluating seven different cross-sectional profiles with twelve distinct screw spacings. These spacings correspond to the half-wavelength of local, distortional, and global buckling, divided by values ranging from one to four. The screw spacing determined by half the local buckling half-wavelength along the webs’ centerline resulted in enhancements of 22%, 7%, 13%, and 11% in the critical elastic local, distortional, and global column buckling loads, as well as the nominal axial strength, respectively. These increases were even more pronounced for double-lane fasteners with the same spacing, yielding improvements of 25%, 46%, 17%, and 12%, respectively. For economic considerations, it is advisable to utilize single-lane fasteners with a half-wavelength equal to half the local buckling half-wavelength.

Technological Innovation for Sustainable Supply Chain Management in the Food Industry

This study explores the critical role of technological innovations—specifically blockchain, Internet of Things (IoT), and artificial intelligence (AI)—in enhancing sustainable supply chain management within Malaysia's food industry. As the industry faces increasing pressure to adopt sustainable practices due to environmental concerns, regulatory demands, and consumer expectations, these technologies offer significant potential for improving traceability, reducing waste, and optimizing operational efficiency. The research highlights how blockchain enhances transparency and ethical sourcing, IoT enables real-time monitoring to minimize waste, and AI optimizes demand forecasting and inventory management, reducing overproduction and resource waste. However, the study also identifies substantial barriers to the adoption of these technologies, particularly for small and medium-sized enterprises (SMEs). These challenges include high implementation costs, a shortage of skilled labor, and concerns over data security and privacy. To address these issues, the study recommends starting with pilot projects to mitigate risks, investing in continuous workforce training, enhancing data security measures, and leveraging government support and industry collaborations. By overcoming these challenges, Malaysia's food industry can effectively integrate these innovations, leading to more sustainable, efficient, and resilient supply chains. This research underscores the importance of strategic planning and continuous improvement in fully realizing the benefits of technological advancements, thereby positioning Malaysia’s food industry as a leader in sustainable practices within the global market.

Artificial Intelligence-Powered Risk Assessment in Supply Chain Safety

The increasing complexity and globalization of supply chains necessitate robust risk management strategies to ensure safety and resilience. Traditional risk assessment methods often fall short in dynamically adapting to the rapidly changing conditions and voluminous data inherent in modern supply chains. This study explores the potential of Artificial Intelligence (AI)-powered risk assessment to address these limitations in the context of Malaysia's supply chain industry. By employing AI technologies such as machine learning, IoT, and predictive analytics, organizations can significantly enhance their risk management capabilities, improving predictive accuracy, real-time monitoring, and overall operational efficiency. Through a qualitative analysis involving in-depth interviews with supply chain managers, AI experts, and technology vendors, the study identifies the strategies employed for AI integration, the perceived effectiveness of these technologies, and the challenges faced in implementation. The findings highlight the importance of robust data governance, the development of explainable AI models, and continuous skill development to overcome barriers related to data quality, model interpretability, and high implementation costs. The study concludes with recommendations for fostering a safer and more resilient logistics environment in Malaysia, emphasizing the need for comprehensive AI adoption frameworks and scalable solutions for small and medium-sized enterprises.

Evaluating the Subject to Tax Rule in Nigeria: Implications, Challenges and Strategic Considerations Amid Global Tax Reforms

The OECD’s two-pillar solution addresses the tax challenges of digitalization, with the Subject to Tax Rule (STTR) and GloBE Rules ensuring minimum taxation. This article explores the application of the STTR in Nigeria, assessing its potential for generating revenue while considering the high costs of implementation and the country’s strategic alternatives.

Assessing Technical Inefficiency in Ecosystem Service Provision from an Input Perspective in the Cross Timbers region, United States.

We modeled the efficiency of ecosystem service provision-specifically timber production, carbon sequestration, and water yield-in the Cross Timbers region of the United States using stochastic frontier analysis from an input perspective. Inputs considered included natural capital and control variables such as temperature, precipitation, soil moisture, and natural disturbances, among others, that impact ecosystem service production. Inefficiency was modeled as a function of factors such as ownership, forest productivity, and natural disturbances. We utilized forest plot-level data obtained from the Forest Inventory and Analysis (FIA) program between 2008 and 2019. Our results indicated that ecosystem service production increased with higher levels of natural capital, higher temperatures, mesic soils, the presence of oaks, and damage caused by abiotic factors. We found evidence of technical inefficiency in the simultaneous provision of ecosystem services. From an input perspective, our findings revealed that, on average, 15.9% more input is used due to technical inefficiency in the Cross Timbers region. Specifically, private ownership and damage caused by abiotic factors resulted in excess input use of 16.4% and 14.3%, respectively, due to technical inefficiency. Managing the encroachment of invasive species like eastern redcedar can enhance ecosystem service production in the region, despite the high implementation costs. Collaboration among multidisciplinary extension professionals can help create comprehensive land management plans for the Cross Timbers, while landowners can also utilize cost-share programs to lower management expenses.

Qualitative and optimal control analysis of a two-serotype dengue model with saturated incidence in co-infection

ABSTRACT The arboviral disease dengue is a life-threatening global public health problem due to its high prevalence rate, morbidity and mortality. Recent studies suggest that morbidity during secondary dengue infection is higher than during primary infection. To deepen our understanding, we have explored a two-serotype co-infected dengue model with bilinear incidence for primary infection and saturated incidence for secondary infection. In the model, we have also included four control measures: mosquito bite prevention control, treatment control, vaccine control and mosquito killing control. The existence and local stability of the disease free, serotype II free, serotype I free and endemic equilibrium points have been studied. The effect of inhibitory or awareness factors on disease dynamics has also been exhaustively examined. By using sensitivity analysis we have identified and quantified the most influential parameters to prevent as well as to control the dengue outbreak. To optimize our strategies, we have characterized the time-dependent optimal control to reduce dengue prevalence and the total implementation cost of the aforementioned controls. Efficiency analysis has been done to identify the best effective combination of the applied controls to reduce dengue infection. Mosquito bites with treatment control is the most effective combined strategy to control dengue infection.

Water Leak Detection: A Comprehensive Review of Methods, Challenges, and Future Directions

This paper provides a comprehensive review of the methods and techniques developed for detecting leaks in water distribution systems, with a focus on highlighting their strengths, weaknesses, and areas for future research. Given the substantial economic, social, and environmental impacts of undetected leaks, timely detection and precise location of leaks are critical concerns for water authorities. This review categorizes existing methods into traditional approaches, such as manual sounding, and modern techniques involving smart water management and sensor technologies. A multidimensional bibliometric analysis was employed to systematically identify, select, and evaluate 600 scholarly articles on water leak detection, sourced from the Scopus database over a 23-year period (2000–2023). The paper evaluates each method based on leak sensitivity, burst detection, continuous monitoring, alarm accuracy, and implementation costs. Novel insights include an analysis of emerging smart water technologies and their integration into real-world water distribution networks, offering improved efficiency in leak detection. The paper also identifies key gaps in current research and suggests future directions for advancing the accuracy and cost-effectiveness of these technologies.

Cost-Effectiveness of a Shock Team Approach in Refractory Cardiogenic Shock.

Multidisciplinary Shock Teams have improved clinical outcomes for cardiogenic shock, but their implementation costs have not been studied. This study's objective was to compare costs between patients treated with and without a Shock Team and determine if the team's implementation is cost-effective compared with standard of care. We examined patients with refractory cardiogenic shock treated with or without a Shock Team at a tertiary academic hospital from 2009 to 2018. Real-world hospital data were used to compare costs and outcomes, including survival at discharge, 1-year survival, and quality-adjusted life years gained at 1 year. Incremental cost-effectiveness ratios were calculated over a 1-year time horizon, with parameter uncertainty evaluated through probabilistic sensitivity analysis using 1000 second-order Monte Carlo simulations. The study involved 244 patients, with 123 treated by the Shock Team and 121 receiving standard of care. Patients were predominantly male (77.5%), with a mean age of 58 (18-92) years. The Shock Team approach improved survival rates at hospital discharge and 1-year follow-up (61.0% versus 47.9%; P=0.04 and 55.0% versus 40.5%; P=0.03, respectively). The incremental cost-effectiveness ratio for increases in survival probability at discharge for the multidisciplinary Shock Team compared with standard of care was $102 088. The incremental cost-effectiveness ratio for increases in survival probability at 1-year was estimated at $96 152 and at $127 862 per 1 quality-adjusted life year gained. Probabilistic sensitivity analysis estimates showed that the Shock Team was cost-effective in the majority of simulations using a willingness-to-pay threshold of $150 000, while it was also dominant in almost one-third of the simulations. The Shock Team approach for treating refractory cardiogenic shock may be a cost-effective alternative to traditional standard of care. These findings can help prioritize the implementation of Shock Team initiatives to further improve cardiogenic shock outcomes.

Sputum and tongue swab molecular testing for the in-home diagnosis of tuberculosis in unselected household contacts: a cost and cost-effectiveness analysis.

Delayed and missed diagnosis are a persistent barrier to tuberculosis control, partly driven by limitations associated with sputum collection and an unmet need for decentralized testing. Household contact investigation with point-of-care testing of non-invasive specimens like tongue swabs are hitherto undescribed and may be a cost-effective solution to enable community-based active case finding. In-home, molecular point-of-care testing was conducted using sputum and tongue specimens collected from all household contacts of confirmed tuberculosis cases. A health economic assessment was executed to estimate and compare the cost and cost-effectiveness of different in-home, point-of-care testing strategies. Incremental cost effectiveness ratios of strategies utilizing different combination testing algorithms using sputum and/or tongue swab specimens were compared. The total implementation cost of delivering the standard of care for a 2-year period was $84 962. Strategies integrating in-home point-of-care testing ranged between $87 844 - $93 969. The cost-per-test for in-home, POC testing of sputum was the highest at $20·08 per test. Two strategies, Point-of-Care Sputum Testing and Point-of-Care Combined Sputum and Individual Tongue Swab Testing were the most cost-effective with ICERs of $543·74 and $547·29 respectively, both below a $2,760 willingness-to-pay threshold. An in-home, point-of-care molecular testing strategy utilizing combination testing of tongue swabs and sputum specimens would incur an additional 10.6% program cost, compared to SOC, over a 2-year period. The increased sample yield from tongue swabs combined with immediate result notification following, in-home POC testing would increase the number of new TB cases detected and linked to care by more than 800%. Evidence before this study: We searched PubMed for original research published between January 1, 1950 and June 30, 2024 that evaluated the cost-effectiveness of in-home POC molecular testing, as part of HCI strategies for tuberculosis. PubMed search terms used included ["household contact investigation" OR "household contact tracing"] AND "tuberculosis" AND "cost-effectiveness". The search revealed 8 studies, of which one was removed as HCIs were leveraged for the provision of short course preventative therapy and not tuberculosis testing. None of the studies were conducted in South Africa. All seven remaining studies relied on a hub-and-spoke model of sputum collection and transportation with sputum tested at a centralized laboratory facility. Although active case finding strategies like HCIs are endorsed by the WHO to improve early case detection and treatment initiation, limited research has been done to assess its cost-effectiveness in low- and middle-income countries.Added value of this study: To our knowledge, this is the first example of in-home molecular point-of-care (POC) testing as part of HCI. The use of primary data to estimate and compare the incremental cost effectiveness of different combination, in-home testing strategies utilizing alternative sample types equips policy makers with a selection of strategy options to choose from. The tradeoff between sample types with high collection yield and those with increased accuracy becomes evident in the economic analysis, highlighting the need to consider both yield and accuracy in effective clinical decision making and use-case development. The success of in-home, POC tongue swab testing of all contacts, irrespective of symptom presentation shows great promise for universal testing programs.Implications of all available evidence: Results from our economic modeling provide evidence in support for the integration of in-home, POC tuberculosis (TB) testing during HCI. The use of less invasive tongue swab samples to increase sample yield in the absence of sputum expectoration highlights the value of combination testing strategies. Immediate result notification resulting from rapid, in-home POC testing shows great promise for increasing early case detection and improving treatment uptake. In-home, POC testing strategies, when incorporated into HCI could curb ongoing community transmission and reduce the overall burden of TB. Considerations for adopting novel POC testing strategies in future active case finding programs like HCI should strongly be considered. We evaluated the cost-effectiveness of in-home, point-of-care TB testing of household contacts. The findings indicate that combined testing strategies using tongue swab and sputum specimens could significantly increase TB case detection, with modest additional program costs.

Active Acoustics with a Phase Cancelling Modal Reverberator

Active acoustics (AA) systems are used to electronically modify the acoustics of a room (e.g., in live music venues). AA systems have an inherent feedback component and can suffer from instability and coloration artifacts resulting from too high feedback gains. State-of-the-art methods can improve system stability and coloration, usually at the cost of complex implementations and long parameter-tuning sessions. They can also cause sound artifacts due to time-varying components, limiting the enhancement at low frequencies. This work proposes a time-invariant feedback attenuation method for low frequencies based on a modal reverberator. The attenuation is achieved through destructive acoustic interference, obtained via phase shifts between the input and output signals. The analyzed frequency range is 0–500 Hz, where the room transfer functions are considered highly invariant over time. The results show a gain-before-instability increase of more than 5 dB for a modal reverberator with high mode density in this frequency range. The improvement is also stable for low-magnitude changes in the room transfer functions over time. The proposed method provides a robust AA system with artificial reverberation for the low-frequency range and can be used alongside other established methods.

Strategic innovation in business models: Leveraging emerging technologies to gain a competitive advantage

This review paper critically examines the role of strategic innovation in business models, with a focus on how emerging technologies can be leveraged to gain a competitive advantage. By synthesizing existing literature, the paper explores the transformative potential of technologies such as artificial intelligence, blockchain, and the Internet of Things (IoT) on traditional and contemporary business models. The review identifies key patterns and trends in how businesses across various industries are integrating these technologies to enhance their value propositions, streamline operations, and create new revenue streams. The findings suggest that companies that successfully incorporate emerging technologies into their business models are better positioned to outpace competitors and adapt to the rapidly changing market landscape. The paper also discusses the challenges and barriers to technology adoption, such as high implementation costs, skill gaps, and organizational inertia, offering insights into strategies that can mitigate these obstacles. The paper underscores the importance of strategic innovation as a critical driver of sustained competitive advantage in the digital era. It highlights that leveraging emerging technologies is not merely an option but a strategic necessity for businesses aiming to thrive amidst ongoing technological disruption. By embracing these innovations, companies can significantly transform their business models, unlock new opportunities, and secure long-term success. Keywords: Business Model Innovation, Emerging Technologies, Sustainable Practices, Strategic Innovation, Partnerships, Open Innovation, Circular Economy, Organizational Agility, Continuous Improvement, Competitive Advantage, Digital Transformation, Market Adaptation, Technological Integration, Collaborative Innovation, Resilient Business Models.

Visionary constructs: revolutionizing students internships through BIM and extended reality synergy

ABSTRACT This study investigates the integration of Building Information Modeling (BIM) and Extended Reality (XR) technologies in construction education, focusing on their application in internship programs. Traditional internships often face limitations such as restricted exposure to complex scenarios and geographical constraints. To address these challenges, this research examines how BIM-XR technologies can bridge the gap between theoretical knowledge and practical application in the Architecture, Engineering, and Construction (AEC) disciplines. A mixed-methods approach was employed, combining qualitative data from interviews with students, educators, and industry professionals alongside quantitative survey data. This comprehensive methodology enabled an in-depth assessment of BIM-XR's impact on student learning outcomes and operational efficiency. The findings revealed that BIM-XR integration significantly enhances educational experiences by providing immersive simulations that help students visualize complex construction processes. This leads to better preparedness for real-world challenges, increased engagement, and more effective internships. Additionally, BIM-XR offers practical benefits for industry practices, such as improved project planning, real-time decision-making, and enhanced stakeholder collaboration. However, the study also highlights challenges, including the steep learning curve, limited access to necessary technologies, and high implementation costs. These limitations point to the need for comprehensive training programs, affordable technology options, and institutional support to ensure broader adoption. Looking ahead, the study suggests that further integration of BIM-XR with emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) could further enhance educational outcomes and industry practices.

Time-Domain Fault Detection and Location Scheme for Flexible DC Distribution Networks

Accurately detecting and locating the fault point of the DC line is significant for eliminating the fault and restoring the power supply of the flexible DC distribution network as soon as possible. Firstly, a direction pilot protection scheme for a complex DC distribution network is proposed based on the integral of the current superposition to identify the fault direction. Then, an online time-domain fault location method based on the least square (LS) method to solve the overdetermined equations is proposed by analyzing the fault loop circuit after the DC line fault. The proposed location scheme utilizes fault data at both ends of the line to eliminate the theoretical impact of fault resistance, and the calculation of the current difference method is discussed to reduce the location error of whether the fault current-limiting reactor (CLR) exists. Finally, various simulations by PSCAD/EMTDC V4.5 demonstrate that the proposed scheme has high protection reliability and location results after different fault positions and resistances. The proposed scheme has low requirements for the sampling rate, fault data length, and implementation costs, which can meet practical application requirements.

Magnetic Resonance Imaging of the Heart is a Robust Method for Diagnosing Myocardial Lesions with Low Availability in Emergency Cardiology Departments

This article discusses the problem of underuse, low availability of modern imaging techniques such as magnetic resonance imaging of the heart (MRI). This technique is characterized by high accuracy and uniqueness in the diagnosis of myocardial lesions of various genesis. The widespread introduction of this technique in emergency cardiology departments can improve the accuracy of diagnosis and the effectiveness of patient therapy. Despite the high costs of implementation and current use, modern diagnostic methods can save healthcare resources by reducing hospital stays and improving treatment outcomes.

Effectiveness and costs of the recruitment strategies used in the MetA-Bone trial, a randomized clinical trial to test the effects of soluble corn fiber supplementation for 1 year in children

Background: Pediatric recruitment into clinical trials is very challenging. A recruitment plan was designed to recruit healthy children (9–14 years) in a trial testing the 1-year effect of corn soluble fiber supplementation on bone mass. We evaluated the effectiveness and costs of the recruitment strategies used in this trial. Methods: The recruitment plan included “Traditional” (mailings, flyers, posters, visits, snowball, etc.) or “Online” (email campaigns, social media, website, etc.) strategies. All strategies led to the pre-screening online form, which asked how they learned about the study. This analysis includes the number of pre-screenings and enrollment (consents signed), ineligibility, socio-demographics, and costs per strategy. Differences were analyzed using ANOVA or chi-square. Results: 649 individuals completed the pre-screening; 37.1 % came from “Traditional”, 46.7 % from “Online”, 2.6 % from “Other”, and 13.6 % from “Unknown” strategies. The most successful strategies were related to Florida International University (posting flyers around campus and email campaigns). The main reasons for ineligibility were obesity (38.9 %) or outside the age range (22.7 %). A total of 48.4 % of the children enrolled came from “Traditional”, 50.2 % from “Online”, and 1.4 % from “Other” strategies. The cost per screened participant was $1112 for “Traditional” and $512 for “Online” strategies, and the cost per enrolled participant was $2704 for “Traditional” and $1454 for “Online” strategies. The highest costs were staff salary. Conclusion: “Online” strategies were more effective and had a lower implementation cost than “Traditional” strategies, although these were also important in achieving the recruitment goal. Future pediatric trials should consider some of these strategies and their costs.ClinicalTrials.gov registry number: NCT02916862

Increasing the speed of digital devices using the ASMD-FSMD method using non-blocking operators

The ASMD-FSMD method for designing digital devices is considered, which consists of constructing a block diagram of an algorithmic state machine with a data path (ASMD), which describes the behavior of the device, and creating project code in Verilog in the form of a finite state machine with a data processing path. (finite state machine with datapath – FSMD). One of the directions for the development of the ASMD-FSMD methodology is the use of features of the hardware description language (HDL). A hypothesis has been put forward: in the ASMD-FSMD technique, it is possible to apply several non-blocking assignment operators to the same variable in one synchronization cycle, which will lead to an increase in device performance. The hypothesis put forward was investigated in the design of synchronous multipliers that implement the classical multiplication algorithms c and d. Experimental studies have confirmed the validity of the put forward hypothesis, while the speed of the multipliers increases two to three times, and the cost of implementation in most cases decreases compared to the traditional approach.

Preliminary experimental study of low salinity effect on organic polar compounds desorption in Hassi Messaoud field-Algeria

Low salinity water (LSW) injection is a well-recognized enhanced oil recovery method that has proved to increase oil recovery. Despite its simple implementation and low cost, no experimental investigations have been reporting its application in Algeria’s oil fields. The present work investigates the impact of LSW injection and identifies the role of organic polar compounds on oil trapping in Hassi Messaoud oil field. The study involves adsorption/desorption experiments using acid/amine organic polar compounds dissolved in non-polar refined oil while employing rock drilling cuttings. Subsequent validation of desorption data is performed by employing crude oil in both Amott tests and micro-model displacement tests using various water salinity ranges. It was evident that at water salinities ranging from 1000 to 2000 ppm, the interfacial tension decreased to 10−2 mN/m, leading to favorable rock wetting behavior and increased oil recovery of 9.18% and 20.07% for amine and acid compounds, respectively. The wettability alteration mechanism was proposed as the main contributor since the actual interfacial tension of natural surfactant might not significantly impact oil recovery. The implementation of LSW injection in Algerian fields presents fresh prospects for future enhanced oil recovery projects.

Extraction of Soybean Oil with Pressurized Ethanol: Prospects for a New Processing Approach with an Analysis of the Physical Properties of Crude Oil and Implementation Costs through Scale-Up in an Intermittent Process

New environmentally friendly methods for extracting vegetable oils are in development, with a focus on pressurized liquid extraction (PLE) in an intermittent process. Ethanol, a renewable and generally recognized as safe (GRAS) solvent, is gaining prominence in this process. It is crucial for these methods to maintain the physicochemical characteristics of the extracted oils and be economically viable on a large scale. Using SuperPro Design software v 8.5, a simulation of PLE scaled up to industrial levels was conducted. Measurements of oils extracted with pressurized hexane and ethanol showed minimal density variations, with slightly higher viscosity for ethanol-extracted oil. Accelerated oxidative degradation revealed a longer induction period for hexane-extracted oil, indicating that ethanol-extracted oil degrades more easily. The antioxidant activity of the oil extracted with hexane was lower than that with ethanol. In the differential scanning calorimetry analysis, the oils extracted with hexane and ethanol presented onset melting point temperatures of −43.2 and −36.1 °C, respectively. The economic assessment considered 16 scenarios, showing a return on investment ranging from 9.0 to 133.5% in the first year and payback times from 0.7 to 11.1 years. Scenario 8, involving two 5000 L extractors, ethanol recycling, and an annual production of 3,325,300 L of soybean oil at USD 1.25/L, demonstrated the best return on investment (133.5%) in less than one year. Overall, this study suggests that industrial-scale soybean oil extraction via PLE in an intermittent process can be more cost-effective than conventional methods, making implementation feasible.

Challenges and recommendations for collecting and quantifying implementation costs in practice: a qualitative interview study

BackgroundThe cost of implementation is typically not accounted for in published economic evaluations, which determine the relative value for money of health innovations and are important for allocating scarce resources. Despite key papers outlining relevant implementation costs, they continue to be under reported in the literature and often not considered in practice. This study sought to understand and outline current practices for capturing the costs associated with implementation efforts, with examples from the digital health setting.MethodsA qualitative study of semi-structured interviews with purposefully sampled experts in implementation science, health economics and/or digital health was conducted. The interview guide was informed by a literature review and was pilot tested. Interviews were digitally recorded and transcribed. A hybrid inductive/deductive framework analysis was conducted using thematic analysis to elicit key concepts related to the research question.ResultsInterviews were conducted with sixteen participants with specialist expertise in implementation science (n = 8), health economics (n = 6), and/or digital health (n = 8). Five participants were experienced in more than one field. Four key themes were elicited from the data: difficulty identifying and collecting implementation cost data; variation in approaches for collecting implementation cost data; the value of implementation costs; and collaboration enables implementation costing. Broadly, while interviewees recognised implementation costs as important, only some costs were considered in practice likely due to the perceived ill-defined boundaries and inconsistencies in terminology. A variety of methods were used to collect and estimate implementation costs; the most frequent approach was staff time tracking. Multidisciplinary collaboration facilitated this process, but the burden of collecting the necessary data was also highlighted.ConclusionsIn current practice, standardised methods are not commonly used for data collection or estimation of implementation costs. Improved data collection through standardised practices may support greater transparency and confidence in implementation cost estimates. Although participants had industry exposure, most were also academic researchers and findings may not be representative of non-academic industry settings.

The Reach, Effectiveness, Adoption, Implementation, and Maintenance of Digital Mental Health Interventions for College Students: A Systematic Review.

We evaluated the impact of digital mental health interventions (DMHIs) for college students. We organized findings using the RE-AIM framework to include reach, effectiveness, adoption, implementation, and maintenance. We conducted a systematic literature review of recent findings from 2019-2024. Our search identified 2,701 articles, of which 95 met inclusion criteria. In the reach domain, student samples were overwhelmingly female and White. In the effectiveness domain, over 80% of DMHIs were effective or partially effective at reducing their primary outcome. In the adoption domain, studies reported modest uptake for DMHIs. In the implementation and maintenance domains, studies reported high adherence rates to DMHI content. While recruitment methods were commonly reported, adaptations and costs of implementation and maintenance were rarely reported. DMHIs for college students are effective for many psychological outcomes. Future work should address diversifying samples and considering implementation in a variety of college settings.