Recommendations For Future Applications Research Articles

Robustness checks in PLS-SEM: A review of recent practices and recommendations for future applications in business research

For the last decade, scholars have employed partial least squares structural equation modeling (PLS-SEM) extensively in business research. However, when applying PLS-SEM, researchers need to perform various robustness checks before and after model estimation. This study showcases the findings of a review of PLS‐SEM use in business research, by examining papers published between 2016 and 2021 in business journals. The study explores the extent to which researchers have performed robustness checks regarding nonnormality, endogeneity, unobserved heterogeneity, nonlinearity, and heteroskedasticity. The findings highlight that statistical rigor remains a serious problem in business-related studies employing PLS-SEM. Despite some encouraging improvements in the last few years, the vast majority of recent business-related studies using PLS-SEM have systematically overlooked robustness checks. This study calls for continued emphasis on the importance of robustness checks and the correct application of appropriate techniques, providing recommendations and guidelines for future PLS-SEM applications.

Reuse of Industrial By-products in Construction using Geopolymerization

This study explores the reuse of industrial by-products in construction through geopolymerization, positioning it as a sustainable alternative to conventional construction materials. In light of the growing demand for environmentally friendly building practices, this research aims to evaluate geopolymer concrete made with industrial by-products as a viable substitute for traditional concrete. The introduction highlights the importance of sustainable construction and the potential of geopolymer technology in reducing environmental impacts. A comprehensive review of the composition, properties, and previous studies on geopolymer concrete using industrial waste materials is provided. The research methodology outlines the objectives, materials used, experimental framework, and testing protocols. Results on compressive strength, flexural strength, and durability of the geopolymer concrete samples are discussed in detail in the results and analysis section. The discussion interprets the findings, focusing on the enhanced strength and durability achieved through the incorporation of industrial by-products. The study concludes with a summary of key outcomes, implications for the construction industry, and recommendations for future applications and research on geopolymer concrete using industrial waste.

Latent class analysis: A review and recommendations for future applications in health sciences

This article provides an overview of latent class analysis (LCA) and its applications in the field of health sciences. LCA is a statistical method used to identify unobserved subpopulations, or latent classes, within a population based on a set of categorical observed variables. In health sciences, LCA has been used in a variety of applications including identifying subtypes of disease, evaluating treatment effectiveness, and understanding health-related behaviors. The advantages and limitations of LCA are discussed, as well as the methodologies used in LCA. The article also provides examples of LCA applications in health sciences, including identifying subtypes of mental disorders, evaluating treatments for chronic diseases, and understanding health-related behaviors. Additionally, current research trends and future directions for the use of LCA in medicine are discussed.

Algorithms and Predictors for Land Cover Classification of Polar Deserts: A Case Study Highlighting Challenges and Recommendations for Future Applications

The use of remote sensing for developing land cover maps in the Arctic has grown considerably in the last two decades, especially for monitoring the effects of climate change. The main challenge is to link information extracted from satellite imagery to ground covers due to the fine-scale spatial heterogeneity of Arctic ecosystems. There is currently no commonly accepted methodological scheme for high-latitude land cover mapping, but the use of remote sensing in Arctic ecosystem mapping would benefit from a coordinated sharing of lessons learned and best practices. Here, we aimed to produce a highly accurate land cover map of the surroundings of the Canadian Forces Station Alert, a polar desert on the northeastern tip of Ellesmere Island (Nunavut, Canada) by testing different predictors and classifiers. To account for the effect of the bare soil background and water limitations that are omnipresent at these latitudes, we included as predictors soil-adjusted vegetation indices and several hydrological predictors related to waterbodies and snowbanks. We compared the results obtained from an ensemble classifier based on a majority voting algorithm to eight commonly used classifiers. The distance to the nearest snowbank and soil-adjusted indices were the top predictors allowing the discrimination of land cover classes in our study area. The overall accuracy of the classifiers ranged between 75 and 88%, with the ensemble classifier also yielding a high accuracy (85%) and producing less bias than the individual classifiers. Some challenges remained, such as shadows created by boulders and snow covered by soil material. We provide recommendations for further improving classification methodology in the High Arctic, which is important for the monitoring of Arctic ecosystems exposed to ongoing polar amplification.

Ratings and experiences in using a mobile application to increase physical activity among university students: implications for future design.

University students have low levels of physical activity and are at risk of mental health disorders. Mobile apps to encourage physical activity can help students, who are frequent smartphone-users, to improve their physical and mental health. Here we report students' qualitative feedback on a physical activity smartphone app with motivational text messaging. We provide recommendations for the design of future apps. 103 students used the app for 6weeks in the context of a clinical trial (NCT04440553) and answered open-ended questions before the start of the study and at follow-up. A subsample (n = 39) provided additional feedback via text message, and a phone interview (n = 8). Questions focused on the perceived encouragement and support by the app, text messaging content, and recommendations for future applications. We analyzed all transcripts for emerging themes using qualitative coding in Dedoose. The majority of participants were female (69.9%), Asian or Pacific Islander (53.4%), with a mean age of 20.2years, and 63% had elevated depressive symptoms. 26% felt encouraged or neutral toward the app motivating them to be more physically active. Participants liked messages on physical activity benefits on (mental) health, encouraging them to complete their goal, and feedback on their activity. Participants disliked messages that did not match their motivations for physical activity and their daily context (e.g., time, weekday, stress). Physical activity apps for students should be adapted to their motivations, changing daily context, and mental health issues. Feedback from this sample suggests a key to effectiveness is finding effective ways to personalize digital interventions.

Adult offspring's experiences of living with a parent with an alcohol misuse problem

AbstractStudies on the effects of parental alcoholism on adult children of alcoholics (ACOAs) have been mostly quantitative. To acquire a richer and better understanding of this realm in Malta, while outlining concrete recommendations to further contain this problem, a qualitative study was thus employed. Six participants were selected after meeting all inclusion criteria. Data were analysed following interpretative phenomenological analysis (IPA) guidelines. Semi‐structured interviews were audio‐recorded and transcribed verbatim. Three superordinate themes, namely a) psychosocial impact, b) coping strategies, and c) a sense of identity, were elevated. A number of findings resulting from this study may point at the resilient nature and skills exhibited by ACOAs, who move on to lead successful lives, despite their past hard life. Recommendations for future applications are discussed. Overall, recognition of children of parents who misuse alcohol should be prioritised in service planning to ensure that their needs are not overlooked.

An Assessment of Geophysical Survey Techniques for Characterising the Subsurface Around Glacier Margins, and Recommendations for Future Applications

Geophysical surveys provide an efficient and non-invasive means of studying subsurface conditions in numerous sedimentary settings. In this study, we explore the application of three geophysical methods to a proglacial environment, namely ground penetrating radar (GPR), seismic refraction and multi-channel analysis of surface waves (MASW). We apply these geophysical methods to three glacial landforms with contrasting morphologies and sedimentary characteristics, and we use the various responses to assess the applicability and limitations of each method for these proglacial targets. Our analysis shows that GPR and seismic (refraction and MASW) techniques can provide spatially extensive information on the internal architecture and composition of moraines, but careful survey designs are required to optimise data quality in these geologically complex environments. Based on our findings, we define a number of recommendations and a potential workflow to guide future geophysical investigations in analogous settings. We recommend the initial use of GPR in future studies of proglacial environments to inform (a) seismic survey design and (b) the selection of seismic interpretation techniques. We show the benefits of using multiple GPR antenna frequencies (e.g., 25 and 100 MHz) to provide decimetre scale imaging in the near surface (e.g., < 15 m) while also enabling signal penetration to targets at up to ∼40 m depth (e.g., bedrock). This strategy helps to circumvent changes in radar signal penetration resulting from variations in substrate conductivity or abundant scatterers. Our study also demonstrates the importance of combining multiple geophysical methods together with ground-truthing through sedimentological observations to reduce ambiguity in interpretations. Implementing our recommendations will improve geophysical survey practice in the field of glacial geology and allow geophysical methods to play an increasing role in the interpretation of glacial landforms and sediments.

Internet of Things brings Revolution in eHealth: Achievements and Challenges

The medical field has benefited greatly from the technological revolution around our world, as well as the introduction of artificial intelligence (AI) and the Internet of Things (IoT). IoT aims to make life easier and more convenient by bridging the various gaps in connecting various devices that people employ. A wide range of applications and technologies, including wearable device development, advanced care services, personalized care packages, and remote patient monitoring, benefit healthcare professionals and patients. These technologies gave rise to new terms such as the Internet of Medical Things (IoMT), the Internet of Health Things (IoHT), e-Health, and telemedicine. With the advent of technology and the availability of various connected devices, smart healthcare, which has grown in popularity in recent years, has been positively redefined. Through the selection of literature reviews, we systematically investigate how the adoption (and integration) of IoT technologies in healthcare is changing the way traditional services and products are delivered. This paper outlines (i) selected IoT technologies and paradigms related to health care, as well as, (ii) various implementation scenarios for IoT-based models. It also discusses (iii) the various advantages of these applications and finally, (iv) a summary of lessons learned and recommendations for future applications.

Challenges and Recommendations Facing Faculty and Institutions in Delivering Massive Open Online Course (MOOC)

MOOC applications, one of the applications adopted and popular in the age, are not well known in our country. Nevertheless, there is a new educational approach in the world and it is very important to determine the difficulties in MOOC applications with various advantages in terms of eliminating these difficulties. This study examines the difficulties and recommendations faced by faculty and staff teaching at the AtademiX platform in the course of presenting MOOC. In this study, it was aimed to determine the difficulties and suggestions faced by the faculty members and the institution during the MOOC submission process. It was used to describe the case study from qualitative research methods to achieve this goal. The study was carried out in two separate groups. Groups were determined by sampling method. The first working group of the research constitutes 6 faculty members from the administrators and employees who are in charge of the administration and execution of the first MOOC platform of Turkey, AtademiX, and the second group 9 faculty members who teach through the AtademiX platform. Semi-structured interview form was prepared for evaluating the outputs of MOOC applications in terms of faculty members and institutions and data were collected. The collected data were analyzed by content analysis method. Institutions and faculty members have encountered various difficulties while presenting MOOC practice and have made various recommendations for future applications. Challenges faced by the institution can be summarized as difficulties they face due to in-house and faculty members. Difficulties faced by faculty members in the process; Individual difficulties, difficulties arising from participants, and difficulties resulting from interaction.

Latent class analysis in PLS-SEM: A review and recommendations for future applications

With the increasing prominence of partial least squares structural equation modeling (PLS-SEM) in business research, the use of latent class analyses for identifying and treating unobserved heterogeneity has also gained momentum. Researchers have introduced various latent class approaches in a PLS-SEM context, of which finite mixture PLS (FIMIX-PLS) plays a central role due to its ability to identify heterogeneity and indicate a suitable number of segments to extract from the data. However, applying FIMIX-PLS requires researchers to make several choices that, if incorrect, could lead to wrong results and false conclusions. Addressing this concern, we present the results of a systematic review of FIMIX-PLS applications published in major business research journals. Our review provides an overview of the interdependencies between researchers’ choices and identifies potential problem areas. Based on our results, we offer concrete guidance on how to prevent common pitfalls when using FIMIX-PLS, and identify future research areas.

A two-stage drop-the-losers design for time-to-event outcome using a historical control arm.

Phase II immuno-oncology clinical trials screen for efficacy an increasing number of treatments. In rare cancers, using historical control data is a pragmatic approach for speeding up clinical trials. The drop-the-losers design allows dropping off ineffective arms at interim analyses. We extended the original drop-the-losers design for a time-to-event outcome using a historical control through the one-sample log-rank statistic. Simulated trials featured three arms at the first stage, one at the second stage, nine scenarios, eight sample sizes with 5%- and 10%- nominal family-wise error rate (FWER). A numerical algorithm is provided to solve power calculations at the design stage. Our design was compared with a group of three independent single-arm trials (fixed design) with and without correction for multiplicity. Our design allowed strict control of the FWER at nominal levels while the misspecification of survival distribution and fixed design inflated the FWER up to three times the nominal level. The empirical power of our design increased with the sample size, the treatment effect and the number of effective treatments and dropped when more patients were recruited at the second stage. The fixed design with correction showed comparable power, while our design advantageously included more patients to the most promising arm. Recommendations for future applications are given. By taking advantage of the use of historical control data and a time-to-event outcome, the drop-the-losers design is a promising tool to meet the challenge of improving phase II clinical trials in immuno-oncology.

Applications of artificial intelligence/machine learning approaches in cardiovascular medicine: a systematic review with recommendations.

Artificial intelligence (AI) and machine learning (ML) promise vast advances in medicine. The current state of AI/ML applications in cardiovascular medicine is largely unknown. This systematic review aims to close this gap and provides recommendations for future applications. Pubmed and EMBASE were searched for applied publications using AI/ML approaches in cardiovascular medicine without limitations regarding study design or study population. The PRISMA statement was followed in this review. A total of 215 studies were identified and included in the final analysis. The majority (87%) of methods applied belong to the context of supervised learning. Within this group, tree-based methods were most commonly used, followed by network and regression analyses as well as boosting approaches. Concerning the areas of application, the most common disease context was coronary artery disease followed by heart failure and heart rhythm disorders. Often, different input types such as electronic health records and images were combined in one AI/ML application. Only a minority of publications investigated reproducibility and generalizability or provided a clinical trial registration. A major finding is that methodology may overlap even with similar data. Since we observed marked variation in quality, reporting of the evaluation and transparency of data and methods urgently need to be improved.

Workshop methodology design: Innovation-oriented participatory processes for sustainability

Workshop methodologies based on overarching knowledge structures are necessary for a shift of the tourism sector towards sustainability. We adopted a participatory action research approach and designed a workshop methodology based on the main tenets and tools of the theory of change, design thinking, and sustainable business models. We tested this methodology within a project initiated by a destination management organisation to promote innovation during the covid-19 crisis and used the results to identify improvements and recommendations for future applications. Although further tests are needed, the study proved that the developed methodology has great potential for promoting the systemic change, creativity, collaboration, empathy, and empowerment that are necessary for a sustainability shift.

English K-12 Teacher Experiences in Saudi Arabia in the Pandemic Era: A Follow-up Study of One Khbrat University Program

A mixed-methods study examines the impact of the pandemic-driven move to virtual learning on K-12 (kindergarten through twelfth grade) English teacher experiences in Saudi Arabia to inform future development of the teaching of English in the country. Research is limited in K-12 English instruction in the country, and it is just emerging on the pandemic’s impact on education in the MENA region. The 35 subjects were English educators who completed the Saudi government-sponsored professional development program, Khbrat, at one U.S. university. Contextualized within the literature on technology in instruction, leadership frameworks, and Vision 2030 education reforms, the study explores the convergence of technological, institutional, and socio-cultural factors affecting innovation in English education to address the research question of how the pandemic has impacted Khbrat graduates as EFL teachers and as change agents in their country. Integrated analysis of survey and interview data reveals patterns of both acceleration and constraint. Findings suggest pathways to leverage virtual technology and acquired knowledge and skills of Khbrat English teacher graduates to deliver EFL professional development with a more pedagogical focus and to build coalitions among EFL educators to sustain the forward movement of innovation in English education in post-pandemic Saudi Arabia. The study concludes with recommendations for future applications.

Digital Public Archaeology at Must Farm: A Critical Assessment of Social Media Use for Archaeological Engagement

Digital public archaeology is increasingly exploring social networks as platforms for online outreach initiatives. Despite a growing body of literature concerning archaeological engagement on social media there are few examinations of such applications in practice. This research critically assesses the current discussions surrounding archaeological social media use before exploring commercial digital outreach at Must Farm, Cambridgeshire. Quantitative examinations of the project's Facebook metrics and qualitative comment analyses are employed to assess whether audiences were meaningfully engaged by these online strategies. The research concludes there is substantial value in using social networks to communicate archaeology and provides recommendations for future applications.

Measuring stress in Australia: validation of the perceived stress scale (PSS-14) in a national sample

BackgroundIn Australia, the stress levels have increased over the years, impacting on the physical and mental health of the general population. The aim of the present study was to evaluate the validity and reliability of the PSS-14 in an Australian population.MethodsThe PSS-14 was applied to a large national sample comprising 3857 Australians in the population-based cross-sectional study Australia’s National Survey of Adult Oral Health 2004–2006. The psychometric properties analyzed with the Rasch model and Graphical Log-linear Rasch models were: model fit, item fit, local dependence, differential item functioning, unidimensionality, reliability, targeting and criterion validity.ResultsThe PSS-14 did not fit the pure RM (χ2 (55) = 3828.3, p = < 0.001) and the unidimensionality of the whole scale was rejected (p = < 0.001). The Perceived Stress (χ2 (27) = 1409.7, p = < 0.001) and Perceived Control (χ2 (27) = 713.4, p = < 0.001) subscales did not fit the pure RM. After the deletion of two items, the Perceived Stress subscale (χ2 (96) = 94.4, p = 0.440) fitted a GLLRM, while the Perceived Control scale (χ2 (55) = 62.50, p = 0.224) fitted a GLLRM after the exclusion of four misfitting items.ConclusionsThe Perceived Stress subscale displayed adequate psychometric properties after the deletion of two items; however, the majority of problems centered around the Perceived Control subscale. The presence of differential item functioning among four items indicates that adjustment of total scores is required to avoid measurement bias. Recommendations for future applications in Australia are provided.

Beyond Lithium-Based Batteries.

We discuss the latest developments in alternative battery systems based on sodium, magnesium, zinc and aluminum. In each case, we categorize the individual metals by the overarching cathode material type, focusing on the energy storage mechanism. Specifically, sodium-ion batteries are the closest in technology and chemistry to today’s lithium-ion batteries. This lowers the technology transition barrier in the short term, but their low specific capacity creates a long-term problem. The lower reactivity of magnesium makes pure Mg metal anodes much safer than alkali ones. However, these are still reactive enough to be deactivated over time. Alloying magnesium with different metals can solve this problem. Combining this with different cathodes gives good specific capacities, but with a lower voltage (<1.3 V, compared with 3.8 V for Li-ion batteries). Zinc has the lowest theoretical specific capacity, but zinc metal anodes are so stable that they can be used without alterations. This results in comparable capacities to the other materials and can be immediately used in systems where weight is not a problem. Theoretically, aluminum is the most promising alternative, with its high specific capacity thanks to its three-electron redox reaction. However, the trade-off between stability and specific capacity is a problem. After analyzing each option separately, we compare them all via a political, economic, socio-cultural and technological (PEST) analysis. The review concludes with recommendations for future applications in the mobile and stationary power sectors.

A review of using partial least square structural equation modeling in e‐learning research

AbstractPartial least squares structural equation modeling (PLS‐SEM) has become a key multivariate statistical modeling technique that educational researchers frequently use. This paper reviews the uses of PLS‐SEM in 16 major e‐learning journals, and provides guidelines for improving the use of PLS‐SEM as well as recommendations for future applications in e‐learning research. A total of 53 articles using PLS‐SEM published in January 2009–August 2019 are reviewed. We assess these published applications in terms of the following key criteria: reasons for using PLS‐SEM, model characteristics, sample characteristics, model evaluations and reporting. Our results reveal that small sample size and nonnormal data are the first two major reasons for using PLS‐SEM. Moreover, we have identified how to extend the applications of PLS‐SEM in the e‐learning research field.

Silico-Aluminophosphate and Alkali-Aluminosilicate Geopolymers: A Comparative Review

Chemically activated materials (often termed as geopolymer) have received attracting attentions in civil, material and environmental research fields as a toolkit alternative to traditional Portland cement in specific applications. This paper presents a state-of-the-art review on silico-aluminophosphate (SAP) geopolymers in terms of definition, chemistries involved during geopolymerization, mechanical and durability performance, environmental impacts, and their potentials in applications as compared to conventional alkali-aluminosilicate (AAS) geopolymers. Recommendations for future applications are also highlighted. It is found that S-A-P gels with six-coordinated aluminum environment dominate in SAP geopolymers, while the aluminum in N-A-S-H gels formed in the AAS geopolymers is characterized by four-coordinated features. Besides, the slow performance development of SAP geopolymer matrix under ambient temperature curing can be compensated through incorporating additional countermeasures (e.g., metal sources) which allow the tailored design of such geopolymers for certain in-situ applications, i.e., calcium-bearing C-(A)-S-H gels co-existed with N-A-S-H gels are dominant in AAS geopolymers, while S-A-P gels enhanced by phosphate-containing crystalline/amorphous phases are the main products in SAP geopolymers. Another advantage of SAP geopolymers is their environmental friendliness relative to the AAS geopolymers due to the utilization of phosphate activators that require lower production energy relative to silicate-containing activators. However, the higher cost of phosphate activators may confine the applications of SAP geopolymers in some exquisite or special fields.

Test-Retest Reliability of "High-Order" Functional Connectivity in Young Healthy Adults.

Functional connectivity (FC) has become a leading method for resting-state functional magnetic resonance imaging (rs-fMRI) analysis. However, the majority of the previous studies utilized pairwise, temporal synchronization-based FC. Recently, high-order FC (HOFC) methods were proposed with the idea of computing “correlation of correlations” to capture high-level, more complex associations among the brain regions. There are two types of HOFC. The first type is topographical profile similarity-based HOFC (tHOFC) and its variant, associated HOFC (aHOFC), for capturing different levels of HOFC. Instead of measuring the similarity of the original rs-fMRI signals with the traditional FC (low-order FC, or LOFC), tHOFC measures the similarity of LOFC profiles (i.e., a set of LOFC values between a region and all other regions) between each pair of brain regions. The second type is dynamics-based HOFC (dHOFC) which defines the quadruple relationship among every four brain regions by first calculating two pairwise dynamic LOFC “time series” and then measuring their temporal synchronization (i.e., temporal correlation of the LOFC fluctuations, not the BOLD fluctuations). Applications have shown the superiority of HOFC in both disease biomarker detection and individualized diagnosis than LOFC. However, no study has been carried out for the assessment of test-retest reliability of different HOFC metrics. In this paper, we systematically evaluate the reliability of the two types of HOFC methods using test-retest rs-fMRI data from 25 (12 females, age 24.48 ± 2.55 years) young healthy adults with seven repeated scans (with interval = 3–8 days). We found that all HOFC metrics have satisfactory reliability, specifically (1) fair-to-good for tHOFC and aHOFC, and (2) fair-to-moderate for dHOFC with relatively strong connectivity strength. We further give an in-depth analysis of the biological meanings of each HOFC metric and highlight their differences compared to the LOFC from the aspects of cross-level information exchanges, within-/between-network connectivity, and modulatory connectivity. In addition, how the dynamic analysis parameter (i.e., sliding window length) affects dHOFC reliability is also investigated. Our study reveals unique functional associations characterized by the HOFC metrics. Guidance and recommendations for future applications and clinical research using HOFC are provided. This study has made a further step toward unveiling more complex human brain connectome.