Psych, Volume 5, Issue 3 (September 2023) – 30 articles

Exploratory factor analysis (EFA) is a very widely used statistical procedure in the social and behavioral sciences. This technique features in validity studies, as well as investigations of latent structure underlying observed measurements. A primary aspect of using EFA is determining the number of factors to retain. In addition to theoretical considerations, a variety of statistical tools have been developed and recommended for use in assisting researchers with respect to factor retention. Some research has been conducted to investigate the accuracy of these methods in the case of continuous factor indicators. The purpose of the current simulation study was to extend this earlier work to situations in which the indicator variables are dichotomous, as with questionnaire or test items. Results of this study revealed that an approach based on the combined results of the empirical Kaiser criterion, comparative data, and Hull methods, as well as Gorsuch’s CNG scree plot test by itself, all yielded accurate results with respect to the number of factors to retain. Implications for practice are discussed. Full article

In a planned missing design, the nonresponses occur according to the researcher’s will, with the goal of increasing data quality and avoiding overly extensive questionnaires. When adjusting a structural equation model to the data, there are different criteria to evaluate how the theoretical model fits the observed data, with the root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), comparative fit index (CFI) and Tucker–Lewis index (TLI) being the most common. Here, I explore the effect of the nonresponses due to a specific planned missing design—the three-form design—on the mentioned fit indices when adjusting a structural equation model. A simulation study was conducted with correctly specified model and one model with misspecified correlation between factors. The CFI, TLI and SRMR indices are affected by the nonresponses, particularly with small samples, low factor loadings and numerous observed variables. The existence of nonresponses when considering misspecified models causes unacceptable values for all the four fit indexes under analysis, namely when a strong correlation between factors is considered. The results shown here were performed with the simsem package in R and the full information maximum-likelihood method was used for handling missing data during model fitting. Full article

A crucial challenge in Bayesian modeling using Markov chain Monte Carlo (MCMC) estimation is to diagnose the convergence of the chains so that the draws can be expected to closely approximate the posterior distribution on which inference is based. A close approximation guarantees that the MCMC error exhibits only a negligible impact on model estimates and inferences. However, determining whether convergence has been achieved can often be challenging and cumbersome when relying solely on inspecting the trace plots of the chain(s) or manually checking the stopping criteria. In this article, we present a SAS macro called %automcmc that is based on PROC MCMC and that automatically continues to add draws until a user-specified stopping criterion (i.e., a certain potential scale reduction and/or a certain effective sample size) is reached for the chain(s). Full article

A constituting feature of item response models is that item and person parameters share a latent scale and are therefore comparable. The Person–Item Map is a useful graphical tool to visualize the alignment of the two parameter sets. However, the “classical” variant has some shortcomings, which are overcome by the new RMX package (Rasch models—eXtended). The package provides the RMX::plotPIccc() function, which creates an extended version of the classical PI Map, termed “PIccc”. It juxtaposes the person parameter distribution to various item-related functions, like category and item characteristic curves and category, item, and test information curves. The function supports many item response models and processes the return objects of five major R packages for IRT analysis. It returns the used parameters in a unified form, thus allowing for their further processing. The R package RMX is freely available at osf.io/n9c5r. Full article

The typical state empathy research used perspective-taking instructions and examined the effect of instructions on empathy-related variables. Empathy-arousing processes were generally not measured. The effect of perspective-taking instructions has been questioned recently. Observers could imagine targets’ feelings without such instructions. This study evoked empathy in Japanese undergraduates (N = 157) without instructional procedure, and based on participants’ responses to questionnaires, measured individual differences between antecedent, process, and intrapersonal outcome variables of state empathy, referring to the organizational model and theories of empathy-arousing processes. The purpose of this study was to measure these variables, examine the causal relationship between them using path analysis, and clarify how empathy occurs. In this way, we could suggest through which processes and antecedent factors intrapersonal empathic outcomes are produced. It is probably the first attempt to clarify how empathy occurs using a social psychological study framework and questionnaire method. This research was originally conducted in 2011 based on two similar studies not published internationally, when only some of the variables were used in our analyses. Afterwards, we constructed another analysis method, reanalyzed the data in 2019 and further reanalyzed in 2023 to obtain the final version of the results. Limitations and scientific and practical implications were discussed. Full article

A mantra often repeated in the introductory material to psychometrics and Item Response Theory (IRT) is that a Rasch model is a probabilistic version of a Guttman scale. The idea comes from the observation that a sigmoidal item response function provides a probabilistic version of the characteristic function that models an item response in the Guttman scale. It appears, however, more difficult to reconcile the assumption of local independence, which traditionally accompanies the Rasch model, with the item dependence existing in a Guttman scale. In recent work, an alternative probabilistic version of a Guttman scale was proposed, combining Knowledge Space Theory (KST) with IRT modeling, here referred to as KST-IRT. The present work has, therefore, a two-fold aim. Firstly, the estimation of the parameters involved in KST-IRT models is discussed. More in detail, two estimation methods based on the Expectation Maximization (EM) procedure are suggested, i.e., Marginal Maximum Likelihood (MML) and Gibbs sampling, and are compared on the basis of simulation studies. Secondly, for a Guttman scale, the estimates of the KST-IRT models are compared with those of the traditional combination of the Rasch model plus local independence under the interchange of the data generation processes. Results show that the KST-IRT approach might be more effective in capturing local dependence as it appears to be more robust under misspecification of the data generation process, but it comes with the price of an increased number of parameters. Full article

We investigated the relationship between the prefrontal cortex (PFC) and executive function during a drawing task. Thirty-three participants using pen tablets provided the data for this task. PFC activity was recorded using functional near-infrared spectroscopy (fNIRS) during a simple zig-zag task and a complex periodic line (PL) pattern task. For each task, there was a trace condition and a prediction condition. The Executive Function Questionnaire (EFQ) was used to examine the association between brain-function measurements and executive function during the task. PFC activity was analyzed in the right, middle, and left regions. Oxygenated hemoglobin values measured with fNIRS were converted to z-values and analyzed as a measure of brain activity. Drawing fluency was measured using the line length. In the PL pattern task, the line length was significantly shorter under the prediction condition than under the trace condition. Activity in the right PFC under the prediction condition was significantly higher than that under the trace condition in the PL pattern task, and the score of the EFQ planning subscale was associated with activity in the right PFC. Activity in the right PFC is important for fluent drawing, suggesting that it is also important during drawing activities involving symbols such as letters. Full article

The R packages Dire and EdSurvey allow analysts to make a conditioning model with new variables and then draw new plausible values. This is important because results for a variable not in the conditioning model are biased. For regression-type analyses, users can also use direct estimation to estimate parameters without generating new plausible values. Dire is distinct from other available software in R in that it requires fixed item parameters and simplifies calculation of high-dimensional integrals necessary to calculate composite or subscales. When used with EdSurvey, it is very easy to use published item parameters to estimate a new conditioning model. We show the theory behind the methods in Dire and a coding example where we perform an analysis that includes simple process data variables. Because the process data is not used in the conditioning model, the estimator is biased if a new conditioning model is not added with Dire. Full article

The aim of the present study is to postulate the existence of psychological phenotypes associated with obesity, based on individual history. While metabolic phenotypes have been acknowledged in the field of medicine, the same cannot be affirmed in the realm of psychology. A longstanding tradition in obesity research has sought to identify shared characteristics among individuals affected by obesity, including personality traits. However, research found no adequate empirical evidence to support the existence of a specific psychological and psychopathological profile among individuals with obesity. Recent efforts in the literature have attempted to correlate these findings and ascertain which metabolic phenotype correlates with a diminished quality of life. We propose a novel differentiation between two categories: (1) individuals who affected by obesity since childhood, and (2) individuals who developed obesity following a life event. Further investigations are imperative to amass experimental data that substantiate this hypothesis. Proactively identifying psychological phenotypes is presumed to impact therapeutic outcomes. Full article

Currently, two-level Mokken scale analysis for clustered test data is being developed. This paper contributes to this development by providing model-fit procedures for two-level Mokken scale analysis. New theoretical insights suggested that the existing model-fit procedure from traditional (one-level) Mokken scale analyses can be used for investigating model fit at both level 1 (respondent level) and level 2 (cluster level) of two-level Mokken scale analysis. However, the traditional model-fit procedure requires some modifications before it can be used at level 2. In this paper, we made these modifications and investigated the resulting model-fit procedure. For two model assumptions, monotonicity and invariant item ordering, we investigated the false-positive count and the sensitivity count of the level 2 model-fit procedure, with respect to the number of model violations detected, and the number of detected model violations deemed statistically significant. For monotonicity, the detection of model violations was satisfactory, but the significance test lacked power. For invariant item ordering, both aspects were satisfactory. Full article

Police officers are exposed to several operational and organizational stressors that significantly impact on their mental health. The COVID-19 pandemic was a new stressor that further exacerbated existing stressors, highlighting the need for a better understanding of its impact on the mental health of police officers. This study tested the hypothesis that occupational stressors and PTSD are serial mediators of the relationship between fear of COVID-19 and burnout. Two hundred Portuguese police officers completed an online survey that assessed their fear of COVID-19, exposure to operational and organizational stressors, PTSD, and burnout. The results of the serial mediation analysis indicated that not only do occupational stressors act as mediators between fear of COVID-19 and burnout but also that PTSD is a mediator. The findings of this study underscore the need for interventions to reduce the negative impact of operational and organizational stressors on the mental health of police officers. Furthermore, this study highlights the power of police institutions for prevention and intervention with these professionals. By recognizing the specific stressors that contribute to the development of PTSD and burnout, our study provides a foundation for the development of direct interventions that can help to minimize the adverse effects of these stressors Full article

An important challenge in statistical modeling is to balance how well our model explains the phenomenon under investigation with the parsimony of this explanation. In structural equation modeling (SEM), penalization approaches that add a penalty term to the estimation procedure have been proposed to achieve this balance. An alternative to the classical penalization approach is Bayesian regularized SEM in which the prior distribution serves as the penalty function. Many different shrinkage priors exist, enabling great flexibility in terms of shrinkage behavior. As a result, different types of shrinkage priors have been proposed for use in a wide variety of SEMs. However, the lack of a general framework and the technical details of these shrinkage methods can make it difficult for researchers outside the field of (Bayesian) regularized SEM to understand and apply these methods in their own work. Therefore, the aim of this paper is to provide an overview of Bayesian regularized SEM, with a focus on the types of SEMs in which Bayesian regularization has been applied as well as available software implementations. Through an empirical example, various open-source software packages for (Bayesian) regularized SEM are illustrated and all code is made available online to aid researchers in applying these methods. Finally, reviewing the current capabilities and constraints of Bayesian regularized SEM identifies several directions for future research. Full article

Previous studies have demonstrated an association between low personal protective equipment (PPE) availability and high stress and anxiety among frontline healthcare workers during the COVID-19 pandemic. It is unclear how other factors, such as infection prevention and control (IPC) training and IPC policy support, correlate with workers’ distress. The current study explores these relationships. We conducted a secondary analysis of a public survey dataset from Statistics Canada. Acute care workers’ survey responses (n = 7379) were analyzed using structural equation modeling to examine relationships between features of the IPC work environment and acute care workers’ ratings of their stress and mental health. We found that PPE availability (β = −0.16), workplace supports (i.e., training, IPC policy compliance, and enforcement) (β = −0.16), and support for staying home when sick (β = −0.19) were all negatively correlated with distress. Together, these features explained 18.4% of the overall variability in workers’ distress. Among surveyed acute care workers, PPE availability was related to their distress; however, having workplace support and an emphasis on staying home when sick was also relevant. Overall, the results highlight that, in addition to PPE availability, workplace supports and emphasis on staying home are important. IPC professionals and healthcare leaders should consider these multiple features as they support acute care workers during future infectious disease outbreaks. Full article

The detection of pain in persons with advanced dementia is challenging due to their inability to verbally articulate the pain they are experiencing. Pain Assessment in Advanced Dementia (PAINAD) is an observer-rated pain assessment tool developed based on non-verbal expressions of pain for persons with severe dementia. This study aimed to perform construct validation of PAINAD for pain assessment in persons with severe dementia in Malaysia. This was a prospective cross-sectional study conducted from 27 April 2022 to 28 October 2022 in eight public hospitals in Malaysia. The PAINAD scale was the index test, and the Discomfort Scale—Dementia of the Alzheimer Type (DS-DAT) and Nurse-Reported Pain Scale (NRPS) were the reference tests for construct and concurrent validity assessment. Pain assessment for the study subjects was performed by two raters concurrently at rest and during activity. The PAINAD score was determined by the first rater, whereas the DS-DAT and NRPS were assessed by the second rater, and they were blinded to each other’s findings to prevent bias. PAINAD showed good positive correlations ranging from 0.325 to 0.715 with DS-DAT and NRPS at rest and during activity, with a p-value of <0.05. It also demonstrated statistically significant differences when comparing pain scores at rest and during activity, pre- and post-intervention. In conclusion, the PAINAD scale is a reliable observer-rated pain assessment tool for persons with severe dementia in Malaysia. It is also sensitive to changes in the pain level during activity and at rest, pre- and post-intervention. Full article

The present Special Issue of Psych, which has been now fully released, aimed to highlight the importance of the Mobile Mental Health Units (MMHUs) in delivering services in rural and remote areas in Greece, and to stress their role as an easily accessible setting that provides a wide range of community-based psychosocial interventions, well beyond usual psychiatric care [...] Full article

This study aims to introduce Bayesian Knowledge Tracing (BKT), a probabilistic model used in educational data mining to estimate learners’ knowledge states over time. It also provides a practical guide to estimating BKT models using the pyBKT library available in Python. The first section presents an overview of BKT by explaining its theoretical foundations and advantages in modeling individual learning processes. In the second section, we describe different variants of the standard BKT model based on item response theory (IRT). Next, we demonstrate the estimation of BKT with the pyBKT library in Python, outlining data pre-processing steps, parameter estimation, and model evaluation. Different cases of knowledge tracing tasks illustrate how BKT estimates learners’ knowledge states and evaluates prediction accuracy. The results highlight the utility of BKT in capturing learners’ knowledge states dynamically. We also show that the model parameters of BKT resemble the parameters from logistic IRT models. Full article

In random-effects models, hierarchical linear models, or multilevel models, it is typically assumed that the variances within higher-level units are homoscedastic, meaning that they are equal across these units. However, this assumption is often violated in research. Depending on the degree of violation, this can lead to biased standard errors of higher-level parameters and thus to incorrect inferences. In this article, we describe a resampling technique for obtaining standard errors—Zitzmann’s jackknife. We conducted a Monte Carlo simulation study to compare the technique with the commonly used delete-1 jackknife, the robust standard error in Mplus, and a modified version of the commonly used delete-1 jackknife. Findings revealed that the resampling techniques clearly outperformed the robust standard error in rather small samples with high levels of heteroscedasticity. Moreover, Zitzmann’s jackknife tended to perform somewhat better than the two versions of the delete-1 jackknife and was much faster. Full article

Gratitude has been extensively studied over the past two decades. Among several predictors, aspects of religiosity and spirituality have been consistent predictors of gratitude. To explore the religious motivations and processes that foster the practice of gratitude, we undertook a systematic thematic analysis using interview data from a national qualitative project of 198 highly religious families. Participants (n = 476) included mothers, fathers, and children from various socioeconomic backgrounds and from diverse religious, racial, and ethnic backgrounds in the United States of America. Semi-structured interviews were conducted in the participants’ homes. Data for this study were analyzed using a team-based approach to qualitative analysis. The findings were organized thematically, including: (a) aspects of gratitude, (b) expressions of gratitude, and (c) the influence of gratitude. Two aspects of gratitude were identified: functional—what people were grateful for—and directional—to whom they were grateful. Expressions of gratitude involved participation in regular, gratitude-focused prayers and mutual day-to-day appreciation. The relational context and implications and context of gratitude in religious families were further examined and reported with sub-themes: (a) gratitude prompted positive re-evaluation of relationships and (b) gratitude reinforced religious faith. Implications, strengths, limitations, and future directions are discussed. Full article

In this study, an exploratory mixed-method approach was employed to investigate the attitudes of Iranians and Americans toward each other, specifically focusing on two critical incidents in their modern history. Drawing from quantitative and qualitative data collected in relation to the hostage crisis in 1979, the missile attack on an Iranian passenger plane (Iran Air 655) in 1988, and the travel ban (Executive Order 13780) in 2018, the study aimed to uncover any changes in attitudes over the course of history. Unlike previous research, the majority of participants had a more balanced and less biased viewpoint toward each other and approached the incidents by considering the consequences and ethical aspects associated with each event. These findings challenge the notion of a mirror image effect, which suggests that people tend to adopt their government’s attitude toward other nations. Instead, participants demonstrated a tendency to rely on their own judgment and critically evaluate information, rather than blindly accepting media narratives. Full article

It is now common to see pedestrians looking at their mobile phones while they are walking. Looking at a mobile phone can cause stooped posture, slower gait, and lack of attention to surroundings. Because these walking characteristics have been associated with negative affect, walking while looking at a mobile phone may have negative effects on mood. This study aimed to investigate whether walking while looking at a mobile phone had psychological effects. One hundred and twenty-five adults were randomised to walk in a park either with or without reading text on a mobile phone. Participants wore a fitness tracker to record pace and heart rate, and posture was calculated from video. Self-reported mood, affect, feelings of power, comfort, and connectedness with nature were assessed. The phone group walked significantly slower, with a more stooped posture, slower heart rate, and felt less comfortable than the phone-free group. The phone group experienced significant decreases in positive mood, affect, power, and connectedness with nature, as well as increases in negative mood, whereas the phone-free group experienced the opposite. There was no significant mediation effect of posture on mood; however, feeling connected with nature significantly mediated the effects of phone walking on mood. In conclusion, individuals experience better wellbeing when they pay attention to the environment rather than their phone while walking. More research is needed to investigate the effects of performing other activities on a mobile phone on mood while walking and in other settings. Full article

This paper demonstrates the process of invariance testing in diagnostic classification models in the presence of attribute hierarchies via an extension of the log-linear cognitive diagnosis model (LCDM). This extension allows researchers to test for measurement (item) invariance as well as attribute (structural) invariance simultaneously in a single analysis. The structural model of the LCDM was parameterized as a Bayesian network, which allows attribute hierarchies to be modeled and tested for attribute invariance via a series of latent regression models. We illustrate the steps for carrying out the invariance analyses through an in-depth case study with an empirical dataset and provide JAGS code for carrying out the analysis within the Bayesian framework. The analysis revealed that a subset of the items exhibit partial invariance, and evidence of full invariance was found at the structural level. Full article

The Cognitive Scale of the Development Support in Childcare (CSDSC) developed in 2023 has adequate reliability and validity. However, it has some limitations in terms of its factor structure. Thus, we re-examined the structural factors, reliability, and validity of the scale using the same data (513 valid responses) as in the original study. In contrast to the two-factor model of the original scale, the revised scale has a one-factor structure. The scale’s Cronbach’s α value was 0.83. A confirmatory factor analysis used to assess whether a one- or two-factor structure was more appropriate for the scale demonstrated that the one-factor model was a better fit, and the revised scale had a higher degree of validity than the original one. The results indicate that the revised and shortened CSDSC has sufficiently high levels of reliability and validity, suggesting that the scale is appropriate for evaluating nursery teachers’ values regarding child development support in childcare. Full article

(1) Background: The dermatillomania and trichotillomania disorders in this study refer to the subcategory of obsessive-compulsive disorders (OCDs) that are medication-induced. Patients with typical dermatillomania or trichotillomania disorder generally present with other OCD symptoms, although this is not present in the cases of medication-induced skin picking or hair pulling disorders found in the current literature. This paper serves to investigate the prevalence and treatment methods of medication-induced excoriation disorders. (2) Methods: The PubMed database was queried for cases of medication-induced dermatillomania or trichotillomania. The database search resulted in 80 results, 7 of which were full-length case reports in English with acceptable detail on clinical course, yielding nine patients. (3) Results: All patients who discontinued their offending agent had complete resolution of symptoms. Patients who continued their medications saw a resolution of symptoms when treated with an additional medication. Atypical antipsychotics and SSRIs were also noted to have been the offending agent in some cases but a successful treatment in other cases. (4) Conclusion: Patients who discontinued their offending agent or added additional pharmacotherapy for dermatillomania or trichotillomania had the best outcomes. Abnormal serotonin and dopamine levels are thought to be connected to the pathology of this disease. Full article

Most questionnaires for somatic symptoms focus either on occurrence, frequency, or severity, and in doing so, they might not be able to comprehensively assess the burden that symptoms present to patients. For example, a symptom might occur at a high frequency but only a minimal severity, so that it is less likely to be a burden on a patient; whereas a symptom that has both a high frequency and severity is more likely to be negatively impacting a patient. Study 1 examined frequency and severity scores for classic Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) symptoms among patients with ME/CFS versus a control group. Findings in Study 1 indicate there were more frequency/severity discrepancies for individuals with ME/CFS versus the control group. Study 1 concluded that collecting data on both measures of symptom burden provides unique indicators that can better assess the burden of the symptoms on patients. In a separate data set, Study 2 reported reliability data on slight differences in the time period and the way the severity was assessed. Study 2 findings indicated high levels of reliability for these changes in the time period and the way questions were asked. These studies provide important psychometric properties that could lead to more reliable and valid assessments of patients with post-viral illnesses. Full article

Background: Leadership during the COVID-19 pandemic often manifested as a command-and-control style of leadership which had detrimental emotional impacts on staff, particularly the nursing workforce. Leadership can have detrimental effects on staff wellbeing, or it can greatly boost their ability to handle a crisis. We sought to explore the interrelationship between leadership and nurses’ wellbeing in an inner-city university hospital during the initial wave of the pandemic. Methods: We conducted secondary analyses of interview data collected during a hospital-wide evaluation of barriers and facilitators to changes implemented to support the surge of COVID-19 related admissions during wave one. Data were collected through semi-structured video interviews during May–July 2020. Interviews were analysed using Framework analysis. Results: Thirty-one nurses participated, including matrons (n = 7), sisters (n = 8), and specialist nursing roles (n = 16). Three overarching themes were identified: the impact on nurses, personal factors, and organisational factors. The impact on nurses manifested as distress and fatigue. Coping and help-seeking behaviours were found to be the two personal factors which underpinned nurses’ wellbeing. The organisational factors that impacted nurses’ wellbeing included decision-making, duty, and teamwork. Conclusions: The wellbeing of the workforce is pivotal to the health service, and it is mutually beneficial for patients, staff, and leaders. Addressing how beliefs and misconceptions around wellbeing are communicated and accessing psychological support are key priorities to supporting nurses during pandemics. Full article

There have been increased calls to address the growing mental health concerns of postsecondary students in Canada. Health promotion focuses on prevention and is needed as part of a comprehensive approach to student mental health support, with an emphasis on not just the individual but also the sociocultural environment of postsecondary institutions. The aim was to conduct a scoping review of the literature pertaining to the associations between postsecondary institutional factors and student wellbeing. The review included a comprehensive search strategy, relevance screening and confirmation, and data charting. Overall, 33 relevant studies were identified. Major findings provide evidence that institutional attitudes, institutional (in)action, perceived campus safety, and campus climate are associated with mental wellbeing, suggesting that campus-wide interventions can benefit from continued monitoring and targeting these measures among student populations. Due to the large variability in reporting and measurement of outcomes, the development of standardized measures for measuring institutional-level factors are needed. Furthermore, institutional participation and scaling up established population-level assessments in Canada that can help systematically collect, evaluate, and compare findings across institutions and detect changes in relevant mental health outcomes through time. Full article

Human trafficking is a complex global problem that demands current and scientifically grounded knowledge capable of coordinating interventions among various sectors of society. To address this issue, a systematic collection of scientific articles was conducted in two databases (Web of Science and Scielo) using keywords in both English and Portuguese. After screening 267 articles based on title, abstract, and full text, an 11-article sample was analyzed for quality. The results revealed that conceptual inconsistency is a challenge in signaling human trafficking, particularly in cases of sexual exploitation of women where it may be associated with prostitution, pimping, or migration—all of which are activities tied to financial gain. Addressing human trafficking requires action from concept to practice, including strengthened policies for sanctions and necessary support for victims. Full article

Interest in the human microbiome in terms of mental health has increased with the rise in psychiatric diseases and disorders. The digestive system, the immune system, the brain, and the autonomic nervous system can all suffer from long-term lack of sleep and relaxation brought on by stress. There is little doubt that stress affects the human intestinal microbiota’s health and encourages problems with its composition, according to scientific studies. Chronic stress exposure raises the risk of both physical and mental illnesses. Therefore, this review’s goal was to support the theory that diseases including anxiety and stress are influenced by microbiome patterns. A total of 8600 sources directly relevant to this study’s topic were chosen from the 236,808 records returned by the literature search, and those with the highest scientific value were then selected based on bibliometric impact factors, language, and year of publication. A total of 87 sources, the most recent scientific output, were finally used for the literature review’s final analysis. The small number of studies on the subject indicates that it is still a developing problem, according to the literature study. Full article