Reverse Correlation Research Articles

A Stochastic Dynamic Operator framework that improves the precision of analysis and prediction relative to the classical spike-triggered average method, extending the toolkit.

Here we test the Stochastic Dynamic Operator (SDO) as a new framework for describing physiological signal dynamics relative to spiking or stimulus events. The SDO is a natural extension of existing spike-triggered average (STA) or stimulus-triggered average techniques currently used in neural analysis. It extends the classic STA to cover state-dependent and probabilistic responses where STA may fail. In simulated data, SDO methods were more sensitive and specific than the STA for identifying state-dependent relationships. We have tested SDO analysis for interactions between electrophysiological recordings of spinal interneurons, single motor units, and aggregate muscle electromyograms (EMG) of major muscles in the spinal frog hindlimb. When predicting target signal behavior relative to spiking events, the SDO framework outperformed or matched classical spike-triggered averaging methods. SDO analysis permits more complicated spike-signal relationships to be captured, analyzed, and interpreted visually and intuitively. SDO methods can be applied at different scales of interest where spike-triggered averaging methods are currently employed, and beyond, from single neurons to gross motor behaviors. SDOs may be readily generated and analyzed using the provided SDO Analysis Toolkit We anticipate this method will be broadly useful for describing dynamical signal behavior and uncovering state-dependent relationships of stochastic signals relative to discrete event times.Significance Statement Here the authors introduce new tools and demonstrate data analysis using a new probabilistic and state-dependent technique, which is an expansion and extension of the classical spike-triggered average, the Stochastic Dynamic Operator. Stochastic Dynamic Operator methods extend application into domains where classical spike-triggered averages fail, capture more information on spike correlations, and match or outperform the spike-triggered average when generating predictions of signal amplitude based on spiking events. A data and code package toolkit for utilizing and interpreting Stochastic Dynamic Operator methods is provided together with example simulated and physiological data analyses. Both the method and the associated toolkit are expected to be broadly useful in research domains where the spike triggered average is currently used for analysis, and beyond.

Assessment of Healthcare Service Quality and Patient Satisfaction Using the SERVQUAL Questionnaire in Khuzestan Province During 2022 - 2023

Background: Hospital service quality is the primary predictor of a hospital's success, and any decrease in patient satisfaction is a cause for concern for the organization. Objectives: This study aimed to evaluate the service quality of Golestan Hospital in Ahvaz, Iran, based on patient satisfaction measured using the SERVQUAL questionnaire. Methods: This cross-sectional study was conducted in 2022 - 2023. Patients over 18 years old who visited the emergency department at Golestan Hospital were evaluated, with the exception of those with mental or multiple chronic disorders. Data collection tools included demographic and SERVQUAL Questionnaires. The data were analyzed using SPSS software, with a significance level set at less than 0.05. Results: A total of 200 subjects participated in the study, comprising 124 females (62%) and 76 males (38%). The results of the SERVQUAL Questionnaire indicated that the highest score was in the tangibility dimension (4.35), while the lowest score was in the assurance dimension (1.38). Negative gaps between perception and expectation were observed in the responsiveness (-0.99) and empathy (-1.22) dimensions. The mean total scores for expectation and perception were 99.55 ± 5.06 and 92.85 ± 5.5, respectively, with the highest scores observed for reliability. No significant association was found between expectation and perception (P-value > 0.05). However, the reliability of the gap and expectation in males was significantly higher (P-value < 0.05). A direct correlation was found between age and tangibility, Assurance, and total score of gaps (P-value < 0.05). Conversely, a reverse correlation was observed between age and tangibility and the total score in perception (P-value < 0.05). Post-hoc analysis revealed that the Assurance and total score of gaps and expectations were significantly higher in married patients compared to single patients (P-value < 0.05). Conclusions: This study revealed a negative gap between patients' expectations and perceptions, highlighting the need for adjustments and improvements in hospital service quality by addressing all five dimensions of service quality.

Mapping models of V1 and V2 selectivity with local spectral reverse correlation

Mapping models of V1 and V2 selectivity with local spectral reverse correlation

Correction to: A statistical significance test for spatio-temporal receptive field estimates obtained using spike-triggered averaging of binary pseudo-random sequences

Correction to: A statistical significance test for spatio-temporal receptive field estimates obtained using spike-triggered averaging of binary pseudo-random sequences

Sarcopenia Is Associated with Neoplasm of Bone and Articular Cartilage: Findings from Mendelian Randomized Study.

Exploring the causal relationship between sarcopenia and neoplasm of bone and articular cartilage (NBAC) by bidirectional Mendelian randomization (MR). Genome-wide association study (GWAS) data on sarcopenia-associated traits including appendicular lean mass, low handgrip strength (including criteria from the European Working Group on Sarcopenia in Older People and the Foundation for the National Institutes of Health), and usual walking speeds were obtained from the UK Biobank. GWAS data for NBAC (benign and malignant) were provided by the Finnish Genetic Database. Three different methods of MR analysis, including inverse-variance weighted, Mendelian randomized Egger regression, and weighted median methods, were utilized. MR analysis showed that high appendicular lean mass was positively associated with the risk of developing benign NBAC (odds ratio and 95% confidence interval = 1.236 (1.026,1.489), p = 0.025). At the same time, there is no statistically significant association was found between traits related to sarcopenia and malignant neoplasm of bone and articular cartilage. There was also no reverse causal correlation between NBAC and traits related to sarcopenia. In European populations, better appendicular lean body mass is positively associated with the risk of benign neoplasm of bone and articular cartilage, representing the possibility that sarcopenia may be a protective factor against neoplasm of bone and articular cartilage.

What is a compassionate face? Avoided negative affect explains differences between U.S. Americans and Chinese

ABSTRACT While a compassionate face for Germans mirrors others’ suffering, for U.S. Americans, a compassionate face is one that expresses a slight smile, partly because U.S. Americans want to avoid feeling negative (“avoided negative affect”; ANA) more than do Germans. The present work examines what people in a non-WEIRD (i.e. Chinese) cultural context think a compassionate face looks like. Additionally, it investigates whether an individually-measured cultural variable (i.e. ANA) can explain differences in conceptualisations of compassion between Chinese and U.S. Americans. Participants in China and the U.S. selected the face that most resembles a compassionate face in a reverse correlation task and completed a measure of ANA. As predicted, Chinese mental representations of a compassionate face included more sadness and less happiness compared to U.S. American mental representations of a compassionate face, and Chinese participants wanted to avoid feeling negative less than did U.S. Americans. Finally, ANA mediated the cultural differences in conceptualisations of compassion. We discuss how ANA and conceptualisations of compassion might be related to how people view the experience versus the expression of different emotions. This work has important implications for therapeutic settings and the meaning of compassion in an increasingly globalised and connected world.

Introducing the brief reverse correlation: An improved tool to assess visual representations

AbstractThe reverse correlation is an innovative method to capture visual representations (i.e., classification images, CIs) of social targets. However, this method necessitates many trials to compute high‐quality CIs, which poses important practical and economic challenges. We introduce a new version of the reverse correlation method, namely, the Brief‐RC. By increasing the number of stimuli (i.e., noisy faces) presented at each trial, the Brief‐RC improves the quality of individual (and average) CIs and lowers the overall task length. In two experiments, assessments by external judges confirmed that the new method delivers equally good (Experiment 1) or higher‐quality (Experiment 2) outcomes than the traditional method for the same number of trials, time length and number of stimuli. The informational values of CIs were also compared using a more objective metric (infoVal). Because the Brief‐RC facilitates the production of higher‐quality individual CIs, social psychology researchers may more easily address a series of relevant research questions.

Association between rheumatoid arthritis and chronic respiratory diseases in a Japanese population: A Mendelian randomization study.

Past observational studies have documented an association between rheumatoid arthritis (RA) and chronic respiratory diseases. Undertaking the approach of Mendelian randomization (MR) analysis, this research aims to delve deeper into the probability of a causal connection between RA and chronic respiratory diseases. Collated genome-wide association study data covering RA with 4199 cases against 208,254 controls, asthma comprising 8216 cases versus 201,592 controls, and chronic obstructive pulmonary disease (COPD) detailing 3315 cases in contrast to 201,592 controls were derived from the repository of the Japanese Biobank. A selection of 10 RA-related, 8 asthma-related, and 4 COPD-related single nucleotide polymorphisms notable for their statistical significance (P < 5 × 10-8) were identified as instrumental variables. The primary analytical technique was the inverse variance-weighted (IVW) method, alongside the MR-Egger protocol, weighted median, and weighted mode to reinforce the validity and solidity of the principal results. For scrutinizing possible implications of horizontal pleiotropy, we harnessed the MR-Egger intercept examination and the Mendelian Randomization Pleiotropy REsidual Sum and Outlier test. Employing the inverse variance-weighted technique, we established a positive correlation between genetic predispositions for RA and actual occurrences of asthma (odds ratios [OR] = 1.14; 95% confidence intervals [CI]: 1.04-1.24; P = .003). This correlation remained strong when testing the results utilizing various methods, including the MR-Egger method (OR = 1.32; 95% CI: 1.09-1.60; P = .023), the weighted median (OR = 1.16; 95% CI: 1.06-1.26; P < .001), and the weighted mode (OR = 1.21; 95% CI: 1.11-1.32; P = .002). Furthermore, our findings from the inverse variance-weighted method also demonstrated a positive association between genetically predicted RA and COPD (OR = 1.12; 95% CI: 1.02-1.29; P = .021). However, no such link was discerned in supplementary analyses. In a shifted perspective-the reverse MR analysis-no correlation was identified between genetically predicted instances of asthma (IVW, P = .717) or COPD (IVW, P = .177) and RA. The findings confirm a causal correlation between genetically predicted RA and an elevated risk of either asthma or COPD. In contrast, our results offer no support to the presumed causal relationship between genetic susceptibility to either asthma or COPD and the subsequent development of RA.

Loss of histone deubiquitinase Bap1 triggers anti-tumor immunity.

Immunotherapy using PD-L1 blockade is effective in only a small group of cancer patients, and resistance is common. This emphasizes the importance of understanding the mechanisms of cancer immune evasion and resistance. A genome-scale CRISPR-Cas9 screen identified Bap1 as a regulator of PD-L1 expression. To measure tumor size and survival, tumor cells were subcutaneously injected into both syngeneic WT mice and immunocompromised mice. The phenotypic and transcriptional characteristics of Bap1-deleted tumors were examined using flow cytometry, RNA-seq, and CUT&Tag-seq analysis. We found that loss of histone deubiquitinase Bap1 in cancer cells activates a cDC1-CD8+ T cell-dependent anti-tumor immunity. The absence of Bap1 leads to an increase in genes associated with anti-tumor immune response and a decrease in genes related to immune evasion. As a result, the tumor microenvironment becomes inflamed, with more cDC1 cells and effector CD8+ T cells, but fewer neutrophils and regulatory T cells. We also found that the elimination of Bap1-deleted tumors depends on the tumor MHCI molecule and Fas-mediated CD8+ T cell cytotoxicity. Our analysis of TCGA data further supports these findings, showing a reverse correlation between BAP1 expression and mRNA signatures of activated DCs and T-cell cytotoxicity in various human cancers. The histone deubiquitinase Bap1 could be used as a biomarker for tumor stratification and as a potential therapeutic target for cancer immunotherapies.

When houses wear faces: Reverse correlation applied to architectural design

Reverse correlation (RC) is a data-driven method from social psychology that has been effectively shown to visualize the mental representations that humans hold regarding facial attributes. The method helps to understand what features are relevant in terms of the evaluation of faces, such as dominance or submissiveness. To the best of our knowledge, RC has solely been applied to faces within the area of psychology until this point. However, there are many other areas where it is of interest to understand how humans evaluate and visualize content, one of them being the evaluation of house facades. With this work, we extended the application of RC to architectural design, specifically focusing on the evaluation of house facades with respect to the psychological attributes of facelikeness, invitingness, and likeability. Furthermore, we propose a novel approach to create the base image, by utilizing a generative adversarial network. In an online study with a between-subject design, 121 participants completed the RC task, with 40 to 41 participants assigned to each of the three attributes. The resulting classification images (CIs) from the RC task unveil face-related features for the attribute facelikeness, signifying the potential extension of the RC methodology beyond the established domain of facial analysis to other domains, such as architectural design.

Blue-Light-Excitable Red-Emitting Organic Antimony Halides as a Reversible Humidity Sensor.

Zero-dimensional organic antimony halides have attracted significant attention recently due to their structural variety, tunable optical properties, and high luminescence efficiency. Here, a new series of antimony bromide hybrid structures with seesaw [SbBr4] and pyramidal [SbBr5] geometries are reported with low band gaps and blue-light excited red emissions. Their luminescence is attributed to self-trapped excitons with a broadband emission of a large Stokes shift. Their photoluminescence signal is sensitive to water molecules, with a reversible positive correlation in a relative humidity range of 30-90%, enabling them as potential materials for real-time, self-consistent humidity sensors.

Breast cancer diagnostics by the intelligent analysis of white blood cells’ interaction with target cancer cells using convolutional neural networks

Interaction of immune system and cancer cells plays a crucial role in defining the physical and chemical characteristics of the tumor microenvironment. Consequently, monitoring and analyzing these interactions may prove essential for cancer diagnosis and prognosis. While standard techniques assessing cellular interaction are technically complicated and usually expensive, engineering solutions can be employed to introduce novel methods and effective techniques. In this paper, we presented a new blood-based breast cancer hallmark for people suspected of breast tumor disease (BTD) by time-lapse microscopy imaging from the interaction between the patient’s blood and MDA-MB-231 breast cancer cell lines. The detection protocol is based on the quantifying invasion of the WBCs to the breast cancer cell line. Many cytological, molecular, and immunofluorescent assays were carried out to approve the hypothesis. Blood immune cells showed meaningful invasion patterns to breast cancer cell lines in reverse correlation by the cancerous stage of the patients. Hence, we believe that the immune system is cognizant of the neoplastic nature of breast tumor disease. To eliminate all the human-related limitations, a convolutional neural network (CNN) architecture was used for invasion recognition. The proposed CNN architecture showed an accuracy of approximately 86%, making it a reliable, fast, and easy way for intelligent detection of invasion patterns to decide on the tumor stage. Results made us present the hypothesis that people with more aggressive breast cancer tumors have less strong immune cells to invade cancer cells which could be a start in the clinical use of the cellular-based immune system for cancer investigation. As WBCs were isolated from the blood with no pre-processing, this method would shed new light as a simple complementary method for better clarification of tumor nature.

Deletions of conserved extracytoplasmic function sigma factors-encoding genes in Streptomyces have a major impact on secondary metabolism

BackgroundEthanol shock significantly affects expression of over 1200 genes in Streptomyces venezuelae NRRL B-65,442, including those involved in secondary metabolite biosynthesis and a cryptic gene pepX, which encodes a 19-amino acid peptide with an unknown function.ResultsTo establish a possible correlation between the PepX peptide and secondary metabolism in S. venezuelae, its gene was deleted, followed by analyses of the transcriptome and secondary metabolome of the mutant. Although the secondary metabolome of the pepX mutant was not strongly affected, pepX deletion, similar to ethanol shock, mostly resulted in downregulated expression of secondary metabolite biosynthesis gene clusters (BGCs). At the same time, there was a reverse correlation between the expression of certain extracytoplasmic function sigma factors (ECFs) and several BGCs. Individual deletions of three selected ECF-coding genes conserved in Streptomyces that were upregulated upon both pepX deletion and ethanol shock, had a profound positive effect on the expression of BGCs, which also correlated with the overproduction of specific secondary metabolites. Deletion of one such ECF-coding gene in a marine sponge-derived Streptomyces sp. also significantly altered the secondary metabolite profile, suggesting an important role of this ECF in the regulation of secondary metabolism.ConclusionsThese findings pave the way for the activation or upregulation of BGCs in Streptomyces bacteria harboring genes for ECFs homologous to those identified in this study, hereby assisting in the discovery of novel bioactive secondary metabolites.

Life’s Essential 8, Genetic Susceptibility, and Incident Cardiac Arrhythmias: A Population-Based Prospective Cohort Study

BackgroundIdeal cardiovascular health (CVH) has been associated with reduced cardiovascular disease risk and mortality, but its association with cardiac arrhythmias was still unsettled. In this prospective cohort study, we investigated the relationship between CVH and subsequent arrhythmias risk, including atrial fibrillation (AF)/flutter, ventricular arrhythmias, and bradyarrhythmias. MethodsData from 287,264 participants initially free of arrhythmias in the UK Biobank were included in the analysis. Cox regression models were used to examine the relationship between CVH levels calculated by the American Heart Association’s Life’s Essential 8 (LE8) metrics, with cardiac arrhythmias risk. ResultsDuring a median follow-up period of 12.8 years, 16,802 incident AF, 2186 incident ventricular arrhythmias, and 4128 incident bradyarrhythmias were identified. After adjustment for confounding factors, participants with high initial CVH levels had significantly lower risks for AF (hazard ratio [HR], 0.63; 95% confidence interval [CI], 0.59-0.68), ventricular arrhythmias (HR, 0.48; 95% CI, 0.40-0.59), and bradyarrhythmias (HR, 0.64; 95% CI, 0.55-0.74) compared with those with low CVH levels. Furthermore, each standard deviation (SD) increase in LE8 scores was associated with a 15% lower risk of AF, 21% for ventricular arrhythmias, and 13% for bradyarrhythmias, respectively. In addition, a significant interaction was observed between CVH levels and the genetic risk of AF (P for interaction, 0.021). The reverse correlation seemed to be more noticeable in individuals with a lower genetic susceptibility to AF. ConclusionsWe concluded that higher levels of CVH, estimated by the LE8 metrics, were associated with significantly reduced risks of AF, ventricular arrhythmias, and bradyarrhythmias.

An After-Hours Telemedicine Urgent Care Service May Not Improve Access to Care for Underserved Populations.

Background: After-hours telemedicine services for emergency care are thought to offer a solution for patients who live at a distance from traditional face-to-face emergency services. This study evaluates such a service in a Health Maintenance Organization, focusing on the differences between central and peripheral populations. Methods: In this cross-sectional database study, we collected data regarding the encounter and patient characteristics, including prescriptions, referrals for further evaluation in a traditional emergency department (ED), and the distance from a traditional ED. Other outcome measures included health care utilization after the encounter such as primary care physician (PCP) encounters, additional telemedicine encounters, ED visits, and hospitalization. Results: In total, 45,411 patient visits were analyzed. Medication was prescribed in 25% of the encounters, and a referral to an ED was given in 22%. In total, 17.7% of the patients visited an ED within 24 h of the index encounter. In total, 64.8% of patients visited a PCP in the following 30 days. No further care was needed in 32.4% of the encounters. In multivariable logistic regression, the odds of using the service were lower for low socio-economic status groups and inhabitants of the periphery than the central areas. A weak reverse correlation was observed in Jewish sectors regarding distance from traditional ED, whereas no correlation was found in the Arab sector. Conclusion: It is commonly believed that telemedicine overcomes geographical barriers. The results of this research do not support this hypothesis.

Unsupervised Transfer Learning Across Different Data Modalities for Bearing's Speed Identification

Recent advancements in transfer learning have revolutionized predictive maintenance, enabling cross-domain generalization for components with varying characteristics and operating under different conditions. While traditional transfer learning approaches require labeled data in both source and target domains, unsupervised transfer learning strives for a more cost-effective alternative for which only labels are available in the source domain. This study investigates adversarial transfer learning between two different sensor modalities: vibration and acoustic. The goal is to enable bearing monitoring using microphones, which are, in general terms, cheaper and easier to deploy than vibration sensors; and without the need to label data in the target domain. The research goal is to identify the operating speed of a bearing testbed. The source domain data correspond to vibration measurements taken from an attached sensor, while the target domain uses a microphone array at distance. Artificial Neural Networks are used as the base architecture. Transferability is assessed with two unsupervised adversarial learning techniques: gradient reversal and deep correlation alignment. Their performance is compared to traditional supervised transfer learning via fine-tuning. Experimental results demonstrate that gradient reversal outperforms deep correlation alignment and is able to achieve results similar to those obtained with supervised transfer learning. These findings highlight the feasibility of speed identification using a microphone array and establish a baseline for future condition monitoring research with such sensors. Conclusion. These findings highlight the feasibility of speed identification using a microphone array and establish a baseline for future condition monitoring research with such sensors.

Correlation Between Age, Initial Body Mass Index (BMI) with Excessive Weight Loss in Very Early Postoperative Period

Introduction. As a major outcome of bariatric surgery, weight loss can be affected by many factors, such as sociodemographic, behavioral problems, genetics, patient status, and the surgical technique. However, limited data were available. This research aimed to seek a correlation between age and BMI with excessive weight loss after bariatric surgery. Method. Cross–sectional study design from 2 bariatric centers in Jakarta, using data from 2018–2022. Percentage Excessive Weight Loss (%EWL) 3 months was an outcome measurement tool. Results. Of 87 subjects enrolled with male to female ratio was 1:4. Age ranged from 14–62 years (median 39 years). Type 1 obesity, type 2 obesity, and type 3 were 37.9%, 20.6%, and 28.7%, respectively. Bariatric surgeries include gastric balloon (10.3%), endoscopic sleeve gastrectomy (ELSG) (8%), laparoscopic sleeve gastrectomy (LLSG) (41.3%), sleeve gastrectomy with duodenojejunal bypass (1.1%), Roux en Y gastric bypass (RYGB) (31%), single anastomosis duodeno–ileal bypass (SADI) (8%). In the 3rd month postoperative, it was found 29.8% of participants with %EWL ≥50%: mean %EWL LLSG 46.7% (41.6–51.9%), mean %EWL RYGB 45.5% (40.5–50.7%). Correlation analysis showed a reverse correlation between BMI with %EWL (r = –0.294, p 0.006) and age showed a weak correlation to %EWL (r = 0.063, p 0.565) Conclusion. In the 3rd month, the higher the BMI, the lower %EWL found. Age barely correlates with weight loss.

The Effect of Substance Abuse on Domestic Violence

find out the relationship between drug abuse and domestic violence . descriptive study design. A sample of (50) couples were introduced. A two questionnaire self-report w used to gather data from drug users and abused women .data were gathered in 2024 between January and March The results indicate that the average age of the male is 27±4, then 24 ±4 female, are married, and (38%) were graduated from secondary school while 36% of their wives are graduated from intermediate schools. 82% of clients with substance use are working with free works while 78% of their wives are housewives. 42% of participants are within monthly income of 601000 – 900000 Iraqi dinars. 60% of wives betrayed by their clients with substance use problems. there is positive significant relationship between substance use among clients and domestic violence among their wives at p-value= .037.Among substance abuse and domestic violence are positive correlated, as shown by significant reverse correlation with p-valy67uue=. 037. Domestic abuse is prevalent and unacceptable in both lifetime and present times. Regardless of age, economic standing, or educational attainment, women will at some point in their lives become victims of abuse. Abuse of drugs increases the chance of violence. Spreading the culture of the danger of drugs and treatment from them by opening rehabilitation centers in various cities and villages Focus on protecting women and developing work to protect them from the risk of violence in coordination with community police.

Evaluation of the predictors and frequency of silent hypoxemia in COVID-19 patients and the gap between pulse oximeter and arterial blood gas levels: A cross-sectional study.

Silent hypoxemia is when patients do not experience breathing difficulty in the presence of alarmingly low O2 saturation. It could cause rapid deterioration and higher mortality rates among patients, so prompt detection and identifying predictive factors could result in significantly better outcomes. This study aims to document the evidence of silent hypoxemia in patients with COVID-19 and its clinical features. A total of 78 hospitalized, nonintubated patients with confirmed COVID-19 infection were included in this study. Their O2 saturation was measured with a pulse oximeter (PO), and arterial blood gas (ABG) was taken. Demographic and clinical features were recorded. The Borg scale was used to evaluate dyspnea status, and patients with a score of less than two accompanied by O2 saturation of less than 94% were labeled as silent hypoxic. Univariate analysis was utilized to evaluate the correlation between variables and their odds ratio (OR) and 95% confidence interval (CI). Silent hypoxemia was observed in 20 (25.6%) of the participants. The average difference between the PO and ABG methods was 4.36 ± 3.43. Based on regression analysis, dyspnea and respiratory rate demonstrated a statistically significant correlation with the O2 saturation difference between PO and ABG (OR: 2.05; p = 0.026; 95% CI: 0.248-3.847 and OR: 0.144; p = 0.048, 95% CI: 0.001-0.286). Furthermore, the Borg scale (OR: 0.29; p = 0.009; 95% CI: 0.116-0.740) had a significant reverse correlation with silent hypoxia. Silent hypoxemia can be a possible complication that affects some COVID-19 patients. Further care should be bestowed upon the younger population and those with underlying neurological or mental illnesses. Furthermore, the respiratory rate, pulse oximeter, and arterial blood gas O2 levels should be considered alongside each other.

The Correlation between Sustainable Development and Digitalization in the Post-Pandemic Era

Abstract This study contains both a qualitative and a quantitative approach regarding the correlation between digitalization and sustainable development and the significance level of the impact that digitalization might have on sustainable development. In order to conduct the research, the dependent and independent variables were selected. We selected as a dependent variable representing the sustainable development, the Social Progress Index and as independent variables, representing the digitalization area, the share of enterprises turnover on e-commerce and share of Individuals who have never used the internet. The database was created for 24 European countries for a period of 6 years (2016, 2017, 2019, 2020, 2021 and 2022). The main conclusion of the study indicates to a strong direct correlation between the Social Progress Index and the share of enterprises turnover on e-commerce and a strong and reverse correlation between the Social Progress Index and the share of Individuals who have never used the internet. Also, based on the linear regression model, we can affirm that for the selected period of time and for the 24 European countries, the increase with one unit of the social progress index, the enterprises turnover on e-commerce (%) increases with 2.06 units. As well, at the increase with one unit of the social progress index, the percentage of the individuals who never used the internet increases with 0.18 (decreases). However, the current model has its own limitations based on the restricted number of variables and time period considered in the database.