PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, filterJournals=PLoSONE, q=subject:"Neuroscience"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&unformattedQuery=subject:%22Neuroscience%22&sort=Date,+newest+first&filterJournals=PLoSONEAll PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-28T15:20:19ZDesigning Iranian hospital organizational charts: Global comparisonsMostafa Amini-RaraniSomayeh MokhtariMohammad AkbariZahra ZamaniSomayeh Mahdiyan10.1371/journal.pone.03009852024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Mostafa Amini-Rarani, Somayeh Mokhtari, Mohammad Akbari, Zahra Zamani, Somayeh Mahdiyan</p>
Background <p>Hospitals should have effective and efficient organizational charts to face the changing healthcare environment. Thus, for this purpose, the present study seeks to compile an organizational chart for Iranian hospitals.</p> Materials and methods <p>The present study was conducted in two phase overview and qualitative (using focus group discussion). In the overview phase, the organizational charts of hospitals were analyzed in terms of complexity (i.e., degree of horizontal and vertical separations), and the initial hospital organizational chart was developed based on the results. Subsequently, experts were interviewed in a focus group discussion to finalize and validate the initial organizational chart.</p> Results <p>The final organizational chart was designed to contain features such as internal divisions, specialization, reduction of organizational hierarchies, expansion of supervision scope, and moderate-sized organizational pyramid.</p> Conclusion <p>Using designed organizational chart would eliminate the redundant managerial levels since it reduces organizational hierarchies to two levels of management, expands the supervision scopes, fosters a moderate-sized organizational pyramid, and catalyzes communications.</p>Effects of cleft lip on visual scanning and neural processing of infant facesAmanda C. HahnJuergen A. RiedelsheimerZoë RoyerJeffrey FrederickRachael KeeRhiannon CrimminsBernd HuberDavid H. HarrisKelly J. Jantzen10.1371/journal.pone.03006732024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Amanda C. Hahn, Juergen A. Riedelsheimer, Zoë Royer, Jeffrey Frederick, Rachael Kee, Rhiannon Crimmins, Bernd Huber, David H. Harris, Kelly J. Jantzen</p>
Infant faces readily capture adult attention and elicit enhanced neural processing, likely due to their importance evolutionarily in facilitating bonds with caregivers. Facial malformations have been shown to impact early infant-caregiver interactions negatively. However, it remains unclear how such facial malformations may impact early visual processing. The current study used a combination of eye tracking and electroencephalography (EEG) to investigate adults’ early visual processing of infant faces with cleft lip/palate as compared to normal infant faces, as well as the impact cleft palate has on perceived cuteness. The results demonstrated a significant decrease in early visual attention to the eye region for infants with cleft palate, while increased visual attention is registered on the mouth region. Increased neural processing of the cleft palate was evident at the N170 and LPP, suggesting differences in configural processing and affective responses to the faces. Infants with cleft palate were also rated significantly less cute than their healthy counterparts (mean difference = .73, p < .001). These results suggest that infants’ faces with cleft lip/palate are processed differently at early visual perception. These processing differences may contribute to several important aspects of development (e.g., joint attention) and may play a vital role in the previously observed difficulties in mother-infant interactions.A study on smart home use intention of elderly consumers based on technology acceptance modelsChengmin ZhouYawen QianJake Kaner10.1371/journal.pone.03005742024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Chengmin Zhou, Yawen Qian, Jake Kaner</p>
Purpose <p>Smart home devices have great potential to improve the quality of life and independence of older people, positively impacting their health, safety, and comfort. However, Chinese research in this field is still in its early stages. Therefore, more comprehensive and in-depth studies are needed to comprehend the various aspects influencing the acceptance and use of smart homes by older users.</p> Patients and methods <p>This study adopted the Technology Acceptance Model (TAM) and included perceived usefulness, perceived ease of use, usage intention, intergenerational technology support, perceived value, and perceived risk as extension variables to delve deeper into the behavioral intentions of older users in smart home services. The study used a convenience sampling method to randomly distribute 236 questionnaires among older adults over the age of 60 in the school’s community and neighboring urban communities who have experience in smart home use and who can complete human-computer interactions either independently or with the help of others, mainly focusing on the four sections: user characteristics, family situation, experience of use, and usage intention. The study used structural equation modeling (SEM) and factor analysis to analyze the completion of questionnaires. Finally, we conducted a validation analysis of the rationality and scientificity of the model and derived the six dimensions of the model of the influencing factors on the use of smart home products by the elderly and the weight sizes of their corresponding 13 influencing factors.</p> Results <p>The results show that perceived usefulness and perceived ease of use have a positive effect on users’ intention to use smart homes. Perceived ease of use has a positive effect on the perceived usefulness of smart homes. In addition, intergenerational technology support, perceived value, and perceived risk impact users’ perceived usefulness and perceived ease of use of the smart home.</p> Conclusion <p>This research aims to describe the factors influencing older users’ willingness to use smart homes. The findings are not only significant for the elderly in China but also of broad value to other regions and countries facing similar demographic challenges. The development of smart homes not only involves the elderly but is also closely related to all segments of society. The government should increase policy support and guide more social forces to participate in the development of the smart home industry. Service providers and designers should fully understand the demand situation and user experience of target users to develop easy-to-use smart home solutions. At the same time, smart homes, as intelligent products for the elderly, need to focus not only on the basic needs of the elderly such as material life and home safety, but also on the spiritual needs of elderly users. Children or caregivers should always pay attention to the psychological state of the elderly and actively guide them to use smart homes to help them realize their self-worth. We look forward to more research focusing on this area in the future and further exploring the specific issues and solutions involved.</p>Multi-scale object detection in UAV images based on adaptive feature fusionSiqi TanZhijian DuanLongzhong Pu10.1371/journal.pone.03001202024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Siqi Tan, Zhijian Duan, Longzhong Pu</p>
With the widespread use of UAVs, UAV aerial image target detection technology can be used for practical applications in the military, traffic planning, personnel search and rescue and other fields. In this paper, we propose a multi-scale UAV aerial image detection method based on adaptive feature fusion for solving the problem of detecting small target objects in UAV aerial images. This method automatically adjusts the convolution kernel receptive field and reduces the redundant background of the image by adding an adaptive feature extraction module (AFEM) to the backbone network. This enables it to obtain more accurately and effectively small target feature information. In addition, we design an adaptive feature weighted fusion network (SBiFPN) to effectively enhance the representation of shallow feature information of small targets. Finally, we add an additional small target detection scale to the original network to expand the receptive field of the network and strengthen the detection of small target objects. The training and testing are carried out on the VisDrone public dataset. The experimental results show that the proposed method can achieve 38.5% mAP, which is 2.0% higher than the baseline network YOLOv5s, and can still detect the UAV aerial image well in complex scenes.Halofuginone prevents outer retinal degeneration in a mouse model of light-induced retinopathyYukihiro MiwaDeokho LeeChiho ShodaHeonuk JeongKazuno NegishiToshihide Kurihara10.1371/journal.pone.03000452024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Yukihiro Miwa, Deokho Lee, Chiho Shoda, Heonuk Jeong, Kazuno Negishi, Toshihide Kurihara</p>
Photoreceptor cell death can cause progressive and irreversible visual impairments. Still, effective therapies on retinal neuroprotection are not available. Hypoxia-inducible factors (HIFs) are transcriptional factors which strongly regulate angiogenesis, erythropoiesis, intracellular metabolism, and programed cell death under a hypoxic or an abnormal metabolic oxidative stress condition. Therefore, we aimed to unravel that inhibition of HIFs could prevent disease progression in photoreceptor cell death, as recent studies showed that HIFs might be pathologic factors in retinal diseases. Adult male balb/cAJcl (8 weeks old; BALB/c) were used to investigate preventive effects of a novel HIF inhibitor halofuginone (HF) on a murine model of light-induced retinopathy. After intraperitoneal injections of phosphate-buffered saline (PBS) or HF (0.4 mg/kg in PBS) for 5 days, male BALB/c mice were subjected to a dark-adaption to being exposed to a white LED light source at an intensity of 3,000 lux for 1 hour in order to induce light-induced retinal damage. After extensive light exposure, retinal damage was evaluated using electroretinography (ERG), optical coherence tomography (OCT), and TUNEL assay. Light-induced retinal dysfunction was suppressed by HF administration. The amplitudes of scotopic a-wave and b-wave as well as that of photopic b-wave were preserved in the HF-administered retina. Outer retinal thinning after extensive light exposure was suppressed by HF administration. Based on the TUNEL assay, cell death in the outer retina was seen after light exposure. However, its cell death was not detected in the HF-administered retina. Halofuginone was found to exert preventive effects on light-induced outer retinal cell death.Anti-inflammatory potential via the MAPK signaling pathway of <i>Lactobacillus</i> spp. isolated from canine fecesMi Ae ParkMirieom ParkHyun-Jun JangSung Ho LeeYeong Min HwangSoyeon ParkDonghyun ShinYangseon Kim10.1371/journal.pone.02997922024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Mi Ae Park, Mirieom Park, Hyun-Jun Jang, Sung Ho Lee, Yeong Min Hwang, Soyeon Park, Donghyun Shin, Yangseon Kim</p>
Two probiotic candidates, <i>Lactobacillus reuteri</i> C1 (C1) and <i>Lactobacillus acidophilus</i> C5 (C5), which were previously isolated from canines, were evaluated in the present study. <i>L</i>. <i>reuteri and L</i>. <i>acidophilus</i> have anti-oxidant, anti-inflammatory, immune-enhancing, and anti-cancer properties and exhibit various probiotic effects in humans and animals. The strains C1 and C5 demonstrated good tolerance to acid and bile salt exposure, exhibited effective adhesion to HT-29 cell monolayer, and displayed sensitivity to antibiotics, thus affirming their probiotic characteristics. Moreover, C1 and C5 exhibited the ability to downregulate the expression of inducible NO synthase (iNOS), an immunomodulatory factor, leading to a reduction in NO production in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. These strains also demonstrated potent anti-inflammatory effects in LPS-stimulated RAW 264.7 cells, achieved through the augmentation of anti-inflammatory cytokine IL-10 expression and the inhibition of pro-inflammatory cytokine IL-1β expression. These anti-inflammatory effects of C1 and C5 were closely associated with the mitogen-activated protein kinase (MAPK) signaling pathway. The results of the present study suggest that the C1 and C5 probiotic candidates attenuate LPS-induced inflammation via the MAPK signaling pathway and the strains can be used as probiotics considering their anti-inflammatory potential.A machine learning based depression screening framework using temporal domain features of the electroencephalography signalsSheharyar KhanSanay Muhammad Umar SaeedJaroslav FrndaAamir ArsalanRashid AminRahma GantassiSadam Hussain Noorani10.1371/journal.pone.02991272024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Sheharyar Khan, Sanay Muhammad Umar Saeed, Jaroslav Frnda, Aamir Arsalan, Rashid Amin, Rahma Gantassi, Sadam Hussain Noorani</p>
Depression is a serious mental health disorder affecting millions of individuals worldwide. Timely and precise recognition of depression is vital for appropriate mediation and effective treatment. Electroencephalography (EEG) has surfaced as a promising tool for inspecting the neural correlates of depression and therefore, has the potential to contribute to the diagnosis of depression effectively. This study presents an EEG-based mental depressive disorder detection mechanism using a publicly available EEG dataset called Multi-modal Open Dataset for Mental-disorder Analysis (MODMA). This study uses EEG data acquired from 55 participants using 3 electrodes in the resting-state condition. Twelve temporal domain features are extracted from the EEG data by creating a non-overlapping window of 10 seconds, which is presented to a novel feature selection mechanism. The feature selection algorithm selects the optimum chunk of attributes with the highest discriminative power to classify the mental depressive disorders patients and healthy controls. The selected EEG attributes are classified using three different classification algorithms i.e., Best- First (BF) Tree, k-nearest neighbor (KNN), and AdaBoost. The highest classification accuracy of 96.36% is achieved using BF-Tree using a feature vector length of 12. The proposed mental depressive classification scheme outperforms the existing state-of-the-art depression classification schemes in terms of the number of electrodes used for EEG recording, feature vector length, and the achieved classification accuracy. The proposed framework could be used in psychiatric settings, providing valuable support to psychiatrists.How to provide existential and spiritual support to people with mild to moderate dementia and their loved ones. A pilot studyMarc HaufeSaskia TeunissenCarlo Leget10.1371/journal.pone.02987832024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Marc Haufe, Saskia Teunissen, Carlo Leget</p>
Background <p>People with mild to moderate dementia and their loved ones may experience strong existential and spiritual challenges due to the disease. People with dementia could therefore benefit greatly from ongoing conversational support. Within the literature and in supportive practice, there are very few tools that help professionals provide this type of support. Professionals may therefore be unaware of, or uncertain of, how support can be given.</p> Objective <p>To develop and test support approaches that may enable professionals to better conduct conversations with attention for existential and spiritual issues.</p> Methods <p>Participatory action research was conducted with dementia care professionals who spoke to 62 clients and 36 loved ones. Research consisted of two cycles of analyzing support, formulating strategies to try, testing and reflecting on the success of these actions and formulating new ones. The Diamond model for existential and spiritual issues regarding mild to moderate dementia, developed in previous research, was used as a framework.</p> Results <p>Five types of approaches, corresponding to the five fundamental polarities within the basic framework, were found to be helpful in alleviating tensions and bolstering strengths. For issues of self-confidence and -worth, an approach of <i>exploring the felt self</i> was developed; for issues of capacity and adaptability, an <i>exploring daily routines</i> approach; for issues of security and loss, an <i>exploring a trinity of needs</i> approach; for issues of burden and enrichment, an <i>exploring memory</i> approach; and for issues of faith and meaning, an <i>exploring ones’ predicament</i> approach. When exploring these approaches, participants found sets and sequencing of questions and prompts to be helpful and transformative.</p> Conclusion <p>Professionals can use the Diamond framework to provide conversational support to alleviate tension, enhance meaning and bolster strength for clients and loved ones.</p>Triggering Chinese lecturers’ intrinsic work motivation by value-based leadership and growth mindset: Generation difference by using multigroup analysisXiangge ZhaoWalton WiderXinxin ZhangMuhammad Ashraf FauziChee Hoo WongLeilei JiangLester Naces Udang10.1371/journal.pone.02977912024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Xiangge Zhao, Walton Wider, Xinxin Zhang, Muhammad Ashraf Fauzi, Chee Hoo Wong, Leilei Jiang, Lester Naces Udang</p>
This cross-sectional study investigated the effects of value-based leadership and growth mindset on the intrinsic work motivation of Chinese lecturers. In addition, this study used age as a categorical moderator to investigate generational differences between the effects of Millennials and their predecessors. A sample of 518 lecturers from various Chinese universities was used to collect data, and SEM-PLS was used to analyse the data. The results showed that value-based leadership and growth mindset had a significant positive impact on both younger and older lecturers’ intrinsic work motivation, with the effect of value-based leadership on younger lecturers’ intrinsic motivation being significantly stronger than on older lecturers’ intrinsic motivation, whereas the effect of growth mindset on intrinsic work motivation did not differ significantly between the younger and older groups. This study contributes to the existing research literature by contrasting the value-based leadership and growth mindset in relation to lecturers’ intrinsic work motivation across younger and older groups in Chinese higher education settings, where greater heterogeneity between age groups was identified. The findings also provided university administrators with recommendations for boosting the intrinsic work motivation of lecturers, influencing future education policy.Breastfeeding, cognitive ability, and residual confounding: A comment on studies by Pereyra-Elìas et al.Kimmo SorjonenGustav NilsonneMichael IngreBo Melin10.1371/journal.pone.02972162024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Kimmo Sorjonen, Gustav Nilsonne, Michael Ingre, Bo Melin</p>
Recent studies found positive effects of breastfeeding on the child’s cognitive ability and educational outcomes even when adjusting for maternal cognitive ability in addition to a large number of other potential confounders. The authors claimed an important role of breastfeeding for the child’s cognitive scores. However, it is well known that error in the measurement of confounders can leave room for residual confounding. In the present reanalyses, we found incongruent effects indicating simultaneous increasing and decreasing effects of breastfeeding on the child’s cognitive ability and educational outcomes. We conclude that findings in the reanalyses may have been due to residual confounding due to error in the measurement of maternal cognitive ability. Consequently, it appears premature to assume a genuine increasing effect of breastfeeding on the child’s cognitive ability and educational outcomes and claims in this regard may be challenged.Bayesian-knowledge driven ontologies: A framework for fusion of semantic knowledge under uncertainty and incompletenessEugene Santos Jr.Jacob JurmainAnthony Ragazzi10.1371/journal.pone.02968642024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Eugene Santos Jr., Jacob Jurmain, Anthony Ragazzi</p>
The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized or rejected entirely. Because uncertainty is omnipresent in the real world, knowledge engineers are often faced with the dilemma of performing prohibitively labor-intensive research or running the risk of rejecting correct information and accepting incorrect information. It would be preferable if ontologies could explicitly model real-world uncertainty and incorporate it into reasoning. We present an ontology framework which is based on a seamless synthesis of description logic and probabilistic semantics. This synthesis is powered by a link between ontology assertions and random variables that allows for automated construction of a probability distribution suitable for inferencing. Furthermore, our approach defines how to represent stochastic, uncertain, or incomplete subject matter. Additionally, this paper describes how to fuse multiple conflicting ontologies into a single knowledge base that can be reasoned with using the methods of both description logic and probabilistic inferencing. This is accomplished by using probabilistic semantics to resolve conflicts between assertions, eliminating the need to delete potentially valid knowledge and perform consistency checks. In our framework, emergent inferences can be made from a fused ontology that were not present in any of the individual ontologies, producing novel insights in a given domain.GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structureHoyeon JeongYoung-Rae ChoJungsoo GimSeung-Kuy ChaMaengsup KimDae Ryong Kang10.1371/journal.pone.02912232024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Hoyeon Jeong, Young-Rae Cho, Jungsoo Gim, Seung-Kuy Cha, Maengsup Kim, Dae Ryong Kang</p>
Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been primarily used for these prediction models, it is difficult to interpret the models reported thus far as accurately representing the interactions between biomolecules. In this study, we propose the GraphMHC model, which utilizes a graph neural network model applied to molecular structure to simulate the binding between MHC proteins and peptide sequences. Amino acid sequences sourced from the immune epitope database (IEDB) undergo conversion into molecular structures. Subsequently, atomic intrinsic informations and inter-atomic connections are extracted and structured as a graph representation. Stacked graph attention and convolution layers comprise the GraphMHC network which classifies bindings. The prediction results from the test set using the GraphMHC model showed a high performance with an area under the receiver operating characteristic curve of 92.2% (91.9-92.5%), surpassing a baseline model. Moreover, by applying the GraphMHC model to melanoma patient data from The Cancer Genome Atlas project, we found a borderline difference (0.061) in overall survival and a significant difference in stromal score between the high and low neoantigen load groups. This distinction was not present in the baseline model. This study presents the first feature-intrinsic method based on biochemical molecular structure for modeling the binding between MHC protein sequences and neoantigen candidate peptide sequences. This model can provide highly accurate responsibility information that can predict the prognosis of immune checkpoint inhibitors to cancer patients who want to apply it.Can the improvement of the social credit environment enhance corporate ESG scores?Chao HanBaoqi Chen10.1371/journal.pone.03002472024-03-26T14:00:00Z2024-03-26T14:00:00Z<p>by Chao Han, Baoqi Chen</p>
The ESG scores of corporations is a crucial manifestation of their long-term strategic goals, attracting significant attention from society. The impact and underlying mechanisms of the enhancement of the social credit atmosphere on the ESG performance of corporations remain unclear. This study utilizes a sample of Chinese A-share listed companies from 2010 to 2020, employing the Difference-in-Differences (DID) methodology to investigate the relationship of the establishment of the social credit system on company ESG scores. This study reveals that the establishment of the social credit system significantly advances corporate ESG scores. Heterogeneity results indicate that the positive effect is more pronounced in state-owned enterprises or companies having substantial institutional shareholding. Furthermore, the implementation of the social credit system amplifies corporate ESG scores through three key mechanisms: fostering green technology innovation, cultivating ethical and moral corporate cultures, and optimizing the overall business environment. This paper enriches the informal institutional researches about the driving factors of corporate ESG scores, providing valuable insights for policymakers and corporate decision-makers.Towards sensory substitution and augmentation: Mapping visual distance to audio and tactile frequencyPingping JiangChristopher KentJonathan Rossiter10.1371/journal.pone.02992132024-03-26T14:00:00Z2024-03-26T14:00:00Z<p>by Pingping Jiang, Christopher Kent, Jonathan Rossiter</p>
Multimodal perception is the predominant means by which individuals experience and interact with the world. However, sensory dysfunction or loss can significantly impede this process. In such cases, cross-modality research offers valuable insight into how we can compensate for these sensory deficits through sensory substitution. Although sight and hearing are both used to estimate the distance to an object (e.g., by visual size and sound volume) and the perception of distance is an important element in navigation and guidance, it is not widely studied in cross-modal research. We investigate the relationship between audio and vibrotactile frequencies (in the ranges 47–2,764 Hz and 10–99 Hz, respectively) and distances uniformly distributed in the range 1–12 m. In our experiments participants mapped the distance (represented by an image of a model at that distance) to a frequency via adjusting a virtual tuning knob. The results revealed that the majority (more than 76%) of participants demonstrated a strong negative monotonic relationship between frequency and distance, across both vibrotactile (represented by a natural log function) and auditory domains (represented by an exponential function). However, a subgroup of participants showed the opposite positive linear relationship between frequency and distance. The strong cross-modal sensory correlation could contribute to the development of assistive robotic technologies and devices to augment human perception. This work provides the fundamental foundation for future assisted HRI applications where a mapping between distance and frequency is needed, for example for people with vision or hearing loss, drivers with loss of focus or response delay, doctors undertaking teleoperation surgery, and users in augmented reality (AR) or virtual reality (VR) environments.Students’ experience of interpersonal interactions quality in e-Learning: A qualitative researchRita MojtahedzadehShirin HasanvandAeen MohammadiSahar MalmirMehdi Vatankhah10.1371/journal.pone.02980792024-03-26T14:00:00Z2024-03-26T14:00:00Z<p>by Rita Mojtahedzadeh, Shirin Hasanvand, Aeen Mohammadi, Sahar Malmir, Mehdi Vatankhah</p>
Background <p>Online Interaction is a critical characteristic of distance learning, and effective online communication models empower students.</p> Purpose <p>This research aimed to explain students’ experiences on the quality of interpersonal interactions in e-learning.</p> Method <p>This study was conducted from November 2021 to October 2022. The qualitative descriptive design via conventional content analysis was utilized. Purposeful and maximum variation methods recruited sixteen participants from three medical science universities in Iran. The data were collected through semi-structured, in-depth, face-to-face, or online interviews. Interviews were recorded through a digital recorder, and analysis was achieved simultaneously with data collection using Graneheim and Lundman (2004). The Lincoln and Guba criteria, including credibility, dependability, transferability, and confirmability, were used to improve the trustworthiness of the findings.</p> Results <p>The results indicated the importance of different dimensions related to teaching-learning. It seems crucial to develop a comfortable and safe environment to improve interpersonal interactions. Educators should be provided with pedagogical skills to support interactions. In addition, focusing on some learners’ soft skills is also vital. In addition to the significance of the teacher’s inclusive role, the educational content must have critical standards. Constructive feedback and the proper use of simultaneous and non-simultaneous communication tools and social networks are other important issues in strengthening interpersonal relationships. Ultimately, comprehensive and ongoing support of learners improves the quality of interpersonal interactions.</p> Conclusions <p>The results indicated the significance of different dimensions of teaching-learning as facilitating factors of interpersonal interactions. The proper use of simultaneous and non-simultaneous communication tools and social networks are other important issues in strengthening interpersonal relationships. Ultimately, comprehensive and ongoing support of learners improves the quality of interpersonal interactions.</p> Implications <p>The results of this study give teachers the insight to keep essential issues in mind when developing their online courses and students to be aware of their roles in the online learning process. Also, the characteristics of simultaneous and non-synchronous platforms, social messaging networks, and learner support are crucial.</p>