extfieldsofstudy: Medicine Psychology

text:
Personality and learning styles in relation to attitudes towards interprofessional education: a cross-sectional study on undergraduate medical students during their clinical courses

Background Interprofessional Education (IPE) is now included in curricula in universities worldwide. It is known that there are differences in attitudes towards IPE among students, but less is known regarding how students’ personalities and learnings styles correspond with those attitudes. The aim of this study was to investigate whether personality traits and learning styles have any impact on medical students’ attitudes towards IPE. Methods Seventy nine medical students in their 9th term (63% females, mean age 29 years) were questioned regarding their attitudes towards IPE according to the Interdisciplinary Education Perception Scale questionnaire, the Kolb’s learning style and Big Five Inventory questionnaires. For all three instruments we used the Swedish translated versions. Results When investigated with a logistic regression, adjusting for age and gender, there were no significant associations between Big Five inventory, Kolb’s learning style and IEPS, except for the Reflective-Pragmatic learning style that was moderately associated with a higher IEPS score. Conclusion There was no clear correlation between personality, learning style and attitude towards IPE as measured by the IEPS among medical students in our study population. Further investigations would benefit from a combination of qualitative and quantitative design. Supplementary Information The online version contains supplementary material available at 10.1186/s12909-020-02327-7.

Introduction
Interprofessional collaboration between different health care professionals is a strategy meant to improve patients' medical outcome and increase patient safety. The idea is that when different health care professionals work together in well-functioning teams, they all contribute with specific knowledge adding up to a holistic approach [1]. However, it may be difficult to achieve good interprofessional teamwork. In an attempt to meet this challenge, universities have developed Interprofessional Education (IPE) learning activities to offer students opportunities to train and learn collaboration skills [2,3]. IPE promotes safe patient care (World Healt h [4]) and has been widely implemented [5]. IPE has been defined as "members or students of two or more professions associated with health or social care, engaged in learning with, from and about each other" ( [2], p. 43). IPE is currently included in curricula at many universities worldwide (C. L. [6]); however, "there is no generalizable theory which can explain how, why or when learning through IPE is successful" (C. L. [6], p. 2). Allvin et al. stated in a study protocol from 2020 that IPE includes many aspects of collaboration and learning activities on different levels. This complexity of IPE-field provides a challenge in terms of research and they conclude that previous research consists of contradictory results and that "the effects of IPE on learning outcomes across all health professions are inconclusive" ( [7], p. 2). Although the use of IPE as a teaching method in healthcare education has increased during the last 20 years, it is important to recognize that students' attitudes toward IPE seem to vary [8]. There are gender differences in attitudes [9], as well as differences based on what educational program the students attend. Wilhelmsson et al. [9] concluded that female students were more positive towards IPE/teamwork than male students, regardless of the educational program they were attending. Another finding was that nursing students had a more positive attitude to teamwork and collaboration compared to medical students. Students that participate in courses in IPE ward seem to be more positive to IPE and to collaboration with other professions (C. L. F [10].).
In 2017, Visser et al. carried out a systematic review to identify how IPE was perceived by medical students, residents, and nursing students in a clinical setting. Their conclusion was that there are three levels of explanations for successful IPE activities: the organizational, processual, and individual levels. In their study, Visser [6] identified a need for more research on the individual level. Our article is an attempt fill this knowledge gap by analyzing different factors on a personal level in order to increase the understanding of students´attitudes towards IPE. Learning styles have been discussed as one of the components that can have impact on students' performance [11,12]. Personality is another aspect that is likely to affect learning processes as well as attitudes towards IPE. A recent study [13] from Israel found positive correlations between nursing students´perception of actual cooperation with other professions (IC) and the personality traits; agreeableness, conscientiousness, and openness to new experiences. Regarding medical students there is a lack of previous studies examining the relationship between personality traits and attitudes towards IPE. In two different systematic reviews examining IPE personality traits were not included [14,15]. We would argue that the influence of learning styles as well as personality traits regarding attitudes towards IPE and interprofessional collaboration is a research field with knowledge gaps. To the best of the authors' knowledge, there are no published studies exploring the correlation between learning styles, personality traits and attitudes towards IPE.
The aim of this study was to investigate whether personality traits and learning styles have any impact on medical students' attitudes towards IPE and interprofessional collaboration.

Methods and participants
The curriculum of the medical program at Karolinska Institutet is not designed as interprofessional but some interprofessional activities are included throughout the program. The longest IPE period is a mandatory 2 weeks interprofessional clinical rotation, that takes place during their 8th term at a ward or in an emergency room setting [16]. This rotation is an IPE course with specific learning outcomes related directly to IPE. During these interprofessional clinical rotations students experienced active collaboration with nursing students, and sometimes also with physiotherapist-and occupational therapist students, in real patient care and the students discuss and solve upcoming clinical problems together [17,18]. At the medical program and the other health care related educational programs at Karolinska Institutet IPE is in line with the descriptions made by CAIPE, and they state that IPE is "occasions when two or more professions learn with, from and about each other to improve collaboration and the quality of care" [19].
The null hypothesis of this cross-sectional cohort study was a priori defined as that there is no correlation between personality traits, learning styles and medical students' attitudes towards IPE and interprofessional collaboration. In the fall of 2012 all 6th-semester medical students at Karolinska Institutet were invited to participate in a study that used the Contextual Activity Sampling System (CASS) for data collection using mobile devices [20][21][22]. All students were informed both orally and written, during their first week in 6th semester out of eleven about the research project's aim and design plus what participation would imply. Further they were informed about that participation were voluntary and that they could decline at any time without consequences, neither for their grades nor course participation. Informed consent was obtained by all participants.
When constructing experience-sampling questionnaires it is important to be cautious [23] to avoid reactivity among the respondents concerning frequent sampling. Therefore, the total number and frequency of questionnaires to be used during this study were thoroughly discussed in the research group based on previous research on the topic as described by Van Berkel et al. and Heron et al. [24,25]. After consensus in the study group, questionnaires were decided to be sent via mobile phones with follow-ups every 3rd week during the 6th semester, and this data has been published elsewhere [26]. Background data (gender and age) were also collected through the CASS on the first occasion.
During the 9th semester, students´attitudes towards IPE were investigated by using the Interdisciplinary Education Perception Scale (IEPS) (B [27].). The Kolb's learning style questionnaire [28] and the Big Five Inventory (BFI) questionnaire were used regarding learning styles and personality traits respectively [29]. The IEPS is a tool originally designed to measure attitudes towards interprofessional education [30]. In this study we used the Swedish translated version that has been adapted to consist of three subscales measured with a Likert scale ranging from 1 = strongly disagree to 6 = strongly agree (B [27].). The competency and autonomy subscale refers to respect and trust among professions, positive attitudes about goals and contributions, and attitudes about students' training and competence. The perceived need for cooperation subscale refers to students' attitudes about the need to cooperate and to learn from other professions. The perception of actual cooperation subscale refers to students' attitudes about teamwork, positive interprofessional relationships, and willingness to collaborate with those in other professions. The IEPS total score is a sum of the three subscores. The competency and autonomy subscale is the sum of responses to five questions with a maximum score of 30. The perceived need for cooperation is the sum of responses to two questions with a maximum score of 12, and the perception of actual cooperation subscale is the sum of responses to five questions with maximum score of 30. The maximum total sum score of 72 indicates a more positive response to interprofessional cooperation. For this study, the IEPS results were judged as positive (61-72 points) or negative (51-60 points) towards interprofessional collaboration.
According to Kolb's experiential learning theory, learning is viewed as a four-stage cycle [31]. First, immediate and concrete experiences serve as a basis for observation. Next, the individual reflects on these observations and begins to build a general theory of what this information might mean. In the next step, the learner forms abstract concepts and generalizations based on the hypothesis. Finally, the learner tests the implications of these concepts in new situations. Hereafter, the learning process continues in the four stages as an endless spiral of the experiential process. The learning styles described by Kolb are based on two major dimensions: active/reflective and abstract/concrete. In the Swedish version that we used in this study, these are presented as two partially redefined variables: Emotive-Rational and Reflective-Pragmatic. These two variables are independent of each other and have good reliability, expressed both as homogeneity and stability [28]. Kolb's learning style inventory dimensions of Emotive-Rational and Reflective-Pragmatic have been calculated in this study according to the model defined by Marke and Cesarec [28]. For more information, see Appendix 1 (Additional file 1).
The Big Five Inventory (BFI) is a well-established and validated instrument used to measure personality traits [29]. The major advantages of the BFI is that it is easily understood by respondents because it is derived from ordinary people's vocabulary, it seems to capture humans' personalities in different cultures, and it can be used to predict important life events. Five types of personality traits are used in the model. Extraversion refers to someone who is social, active, and likes to have fun. Agreeableness represents someone who is helpful, forgiving, and honest. Conscientiousness refers to someone who thinks before acting and is good at organizing and prioritizing. Neuroticism refers to someone who feels anxious, nervous, sad, and tense. Openness to experience describes a person who is curious, interested in new things, and intellectual [29]. The BFI has been translated, validated and used in a Swedish context [32]. The BFI consists of 44 items on a 5-point Likert scale, where 1 indicates "I strongly disagree"; 2, "I disagree"; 3, "I neither agree nor disagree"; 4, "I agree"; and 5, "I agree strongly." Each personality dimension's overall score is calculated by summing up the Likert scale scores of the 8-10 assertions specific for each dimension [32].. The personality dimension scores were dichotomized into the following categories with the median value of the whole population defining the cut-off; extraversion 13-28 = no, 29-40 = yes,

Statistics
Statistical analyses were performed using software packages of SPSS version 23. The cohort size was defined by convenience sampling, including one class of medical students. To compare proportions of categorical variables, the Chi Squared test was used. Bonferroni's correction was used for multiple comparisons. To compare numerical values, a Student's t-test was used. All comparisons were considered significant if p < 0.05 in two-sided tests.
The main outcome of IEPS is a numerical ordinal value and was presented as means and corresponding standard deviation. The correlations between IEPS and age, gender, previous experience with IPE, Kolb's learning styles, and personality according to BFI, respectively, were tested in a logistic regression model in all individuals with complete data. Other confounders were not considered in the analysis. Results are presented as crude measures, univariate analysis and multivariable analysis adjusted for age, gender, KOLB, and BFI. The results are presented as odds ratios for crude and adjusted measures for being positive to IPE. Statistical significance is presented as 95% confidence intervals and p-values.

Ethics
This study was performed according to the Helsinki Declaration

Results
Ninety-eight students out of 136 eligible individuals agreed to participate in the study, out of whom 79 responded to the questionnaires and were included in the current analysis. The mean age of the participants was 29 years (SD = 5.3, range 23-46 years) and 62% (n = 50) were females. Table 1 shows the mean scores for the IEPS. Table 2 presents the IEPS subscales. Generally, the scores were relatively high, and the subscale perceived need for cooperation reached almost a maximum score (11.7 of 12 possible). There were no differences between genders. Table 3 summarizes the participants' personality dimensions according to the BFI questionnaire. There were significant differences between genders in three out of five dimensions, with female students scoring significantly higher in the agreeableness, neurotic and conscientiousness dimensions. Table 4 shows the Kolb's learning inventory. Female students had higher scores for the dimension Reflective-Pragmatic compared to male students (p = 0.024).
There were complete data regarding IEPS for 76 students, out of which 49 students (64%) scored 51-60 points on the IEPS, which was interpreted as a negative attitude towards IPE, whereas 27 students (36%) scored 61-72 points, which was considered a positive attitude towards IPE. When investigated using a logistic regression adjusting for age and gender, a moderate association was found between the Reflective-Pragmatic learning style, and a higher IEPS score, as shown in Table 5. No other relationship was found between the main outcome IEPS and Kolb's learning style or BFI in either the univariate or the adjusted analysis.

Discussion
The aim of this study was to investigate associations between learning styles, personality and medical students' attitudes towards IPE and interprofessional collaboration. Table 1 Mean scores of participants on the Interdisciplinary Education Perception Scale in a study investigating personality and learning styles in relation to attitudes towards interprofessional activities among 79 undergraduate medical students The data were collected in 2014 alongside a longitudinal study with medical students at Karolinska Institutet [33,34]. The demographic data showed that the gender distribution was in line with the current malefemale ratio of students in Sweden and at Karolinska Institute where the study was conducted. The sample is representative, and the findings are generalizable from a gender perspective. The participants were all familiar with the CASS method of data collection, and the response rate was relatively high, which further supports the appropriateness and generalizability of the findings.
In several previous studies, gender did seem to play a role in attitudes towards IPE [35,36], showing that female students were more positive towards IPE compared to male students. In contrast, in our study, no difference was found between genders for the IEPS results, a finding supported by a study by Williams et al. (Brett [37]).
In our study, IEPS scores were found to be relatively high, and the subscale "perceived need for cooperation" reached almost a maximum score. The purpose of our study was probably obvious to the study participants, and that may have introduced bias in our findings. Students may have responded to our questions in a manner that they thought would please us, thus producing a higher IEPS score than students normally would achieve. However, the fact that all CASS answers were anonymized minimized the risk of such bias. Moreover, in a population with a generally positive attitude towards IPE, there may exist little differences between groups that are not discernable due to ceiling effects in our measurement tool. A larger study, and/or another study design would be needed to clarify these circumstances. Psychometric robustness of instruments to evaluate IPE has been reported to be questionable [38]. Problems relating to the IEPS involve that use of the IEPS by various authors demonstrates considerable variation in the application of the original test scoring protocol. In some papers, raw scores have been used for analysis rather than factor or subscale scores and total scores [38]. We have used a dichotomized result. The cut-off was arbitrarily set at 60, which may be subject for discussion and/or criticism. Our study aim was to investigate an association between IPE attitudes and learning styles with a quantitative approach. After discussion in the study group, we decided for the current methodology, which has its weaknesses but still represents an inventory of strong associations between different psychometric measures in the population under study.
In a study from Marke and Cesarec [28], females were found to be more emotive in their learning modes  independent of profession and not correlated to age. They also showed that students of social work and psychology were the most emotive and most prone to reflection, while medical students had more pragmatic and rational learning modes. Heffler and Sandell, who studied learning styles among psychotherapy students, found that men were more rational than women.
However, this finding was only significant in one of three cohorts studied [39]. The findings from our study showed that female medical students had a significantly more reflective pragmatic learning style than male students; however, no difference in the Emotive-Rational learning style between genders was observed. The findings regarding relations between gender and learning  Well-established and validated instruments were used to measure students' learning styles, personality traits, and attitudes towards IPE by using the Swedish version of IEPS (B [27].). Even so, there are some limitations to this study that should be recognized. First, the number of participants was relatively low and all participants were medical students from the same semester and from one single university. Future research would benefit from using a larger sample, with students from different educational programs and / or time periods that would allow a comparative approach. Significant associations may have been found using a larger or different sample. Second, although well-established and validated instruments were used to measure learning styles, personality traits, and attitudes towards interprofessional education activities, it should be noted that these are all complex processes that can be difficult to investigate using a quantitative design. Future research would benefit from a combination of quantitative and qualitative research methods.


Microbial pollution of indoor air in Riyadh city government schools

The presence of microorganisms in indoor air represents a dangerous issue with a major impact in the field of health protection and environmental engineering. Low indoor air quality is a major trouble in government schools because of the massive density of students per classroom, inadequate supply of air from outside, as well as weak construction and poor maintenance of school buildings. Evaluation of microbial contamination within the indoor air is important to assess health dangers and establish requirements for tracking indoor air quality. Evaluation of microbial contamination is of notable significance in intensively populated centers as government schools. A study was carried out among a hundred and twenty randomly classrooms of twenty government primary schools of Riyadh city in the academic year 2018/2019. For the determination of microbial pollution, passive air sampling settle plate technique was utilized by exposing a Petri dish of appropriate agar media for one hour. Results showed that the counts of bacteria and fungi were higher in government schools in low socioeconomic districts as compared to those of high socioeconomic districts. The indoor analyses reveal that the concentration of bacteria was higher than counts of fungi. In general, Gram positive microorganisms were the dominant organisms. Gram positive bacteria, Bacillus, Micrococci and Staphylococci were the predominant bacterial strains in the schools under study. Attention has to be paid for controlling the physical factors that assist the growth and reproduction of microbes in indoor air of classrooms to keep the students and teachers healthy.

Introduction
The quality of air in indoors has come to be a significant public health challenge as the general public spends more than ninety percent of their time in interior such as homes, workplaces and educational facilities. Indoor air may be polluted with one or more of the most important microorganism like bacteria and fungi. It was found that about 33% of the indoor air quality claims occurred by the microbial contamination [1] which cause allergy, respiratory and immunetoxic diseases [2]. A large number of studies were carried out on the microbial contaminants in varied indoors of educational establishments [3]. Millions of students are going every day to the educational facilities as schools. The high levels of student's activities led to indoor air pollution with bacteria and fungi. Children are more susceptible to indoor air pollutants than adults as they are exposed to unidentified amount of indoor air pollutants in school environments [4]. Schools are more danger than the other different buildings. This is attributed to the high density of students per classroom, bad sanitation and inadequate outdoor air supply. This danger is aggravated through frequent construction and upkeep of school buildings [5]. The concentration of microbial contamination of schools is a crucial factor because of its effect on the human mentality, physical up growth and students' performance.
A study was carried out among a hundred and twenty randomly classrooms of twenty government primary schools of Riyadh city, Saudi Arabia in the academic year 2018/2019.There are 1883 public schools in Riyadh city, of which 713 are public schools (413 primary schools, 206 middle schools, and 94 secondary schools) and the rest are private schools. Therefore, the aim of the present investigation is to estimate the indoor air pollution in some government primary schools of Riyadh city in two different socioeconomic districts to upgrade knowledge and offer recommendations for better understanding of bacterial content of indoor air quality issues in such type of schools.

Material and methods
A study was carried out to evaluate indoor microbial pollutants and its effect on indoor air quality of government primary schools in Riyadh, capital of Saudi Arabia.

Sample size and sampling procedures
The study was carried out in randomly one hundred twenty classroom of 20 primary government schools of Riyadh city in the academic year 2018/2019, out of those ten schools are located in low socioeconomic districts (there is no ventilation or air condition) and other ten schools are located in high socioeconomic districts (there are 2 air condition in each classroom). The schools located in low socioeconomic districts were built since 30 years ago while, the schools in the high socioeconomic districts were built since only 12 years ago. In each school six classes were used to collect samples during April 2019. Samples were taken five days a week during the studied month. Saudi Arabia has an arid continental climate. The temperature in April ranged between 20.4-33.4°C and the relative humidity in the same month was 28%.
Total counts of bacteria and fungi were determined using the passive air sampling technique; the settle plate method using open Petri-dishes containing different culture media. Microbial contamination assay based totally on the quantity and type of microbial fall directly on Petri dishes left open to the air. The scheme of 1/1/1 (for 1 h, 1m faraway from the ground, at the least 1m far from partitions or any impediment) was used according to [6].
To detect the microbial count with take in consideration the environmental variation, the medium containing petri plates have been exposed at sampling classrooms an hour after the school day ends at 15:00 in the afternoon (Sunday via Thursday). To minimize dilution of air contaminants, doorways and class windows had been closed. Also, during sampling the human motion was restrained to let the air steady and prevent newly fall organisms. Nutrient agar (NA) and Potato dextrose agar (PDA) provided with 10 mg/L chloramphenicol were used for the cultivation of bacteria and fungi, respectively. Three replicates of each of nutrient agar and potato dextrose agar have been used. Nutrient agar plates were left at 37°C for forty-eight hours to let aerobic mesophilic bacteria to grow. Potato dextrose agar dishes have been incubated for 5 days at 25°C to allow the growth of fungal colonies. The mean of colony forming units (CFU) of each of bacteria and fungi turned into calculated and converted to organisms per cubic meter of air (CFU m -3 ) applying the equation of. [7]. N = a * 10000/b * t * 0.2 Where N: Microbial CFU/m 3 of indoor air; a: Number of colonies per Petri dish; b: Dish surface area (cm 2 ); t: Exposure time.
Bacterial colonies had been characterized at the beginning with the aid of morphology and microscopic look, and recognized further via biochemical assessments as mentioned before by Bergey's Manual of Systematic Bacteriology [8]. Each fungal colony was moistly prepared using Lacto phenol cotton-blue solution and examined microscopically. Identification of fungi was done depending on growth colonial appearance, microscopic examination of the spore and hypha traits of the stained preparations [9]. Along with microbial sample collection, indoor temperature, and relative humidity had been measured.

Statistical analysis
The received data have been analyzed statistically applying the general linear version technique of [10]. Mean comparisons had been made with an F-protected LSD at P < 0.05. Table 1 showed that most of the government schools under study have high indoor microbial population counts. The total bacterial counts ranged from 396-3589 and 712-5760 CFU m -3 in the schools of high and low socioeconomic districts, respectively. The overall indoor air bacterial loads were 1881.2 and 3073.6 CFU m -3 in the schools of high and low socioeconomic districts, respectively (Table 1). Potato dextrose agar (PDA) petri plates showed heavy fungal growth when exposed to indoor air in government primary schools of both high and low socioeconomic districts of all sampled schools. The fungal counts in primary government schools were 127-978 and 198-1326 CFU m -3 in high and low socioeconomic districts, in respective order ( Table 1). The overall indoor air fungal loads were 534.7 and 791.4 CFU m -3 in the schools of high and low socioeconomic districts, respectively (Table 1).

Results in
It was obvious that the indoor air bacterial counts in the schools of low standard level districts were significantly higher than indoor air bacterial counts recorded in the schools of high socioeconomic districts Table 1. This is may be due to the absence of ventilation in such types of schools beside they were built since more than 30 years ago, while the schools of high socioeconomic districts have good ventilation and 2 air conditions per classroom and it were built since only 12 years. The variations of the fungal concentration between schools and the level of districts were followed the same trend of the indoor air bacterial concentration. The bacterial concentration was high in all primary schools than fungi regardless the school level and the other environmental factors. One of the most vital investigations to assess indoor air pollution with different microbes is the microbiological quality assessment. Information on the indoor air content of bacteria and fungi is necessary to assess health risks and to establish standards for controlling indoor air quality. The total airborne bacteria and fungi of indoor air environments of government primary schools in Riyadh city was found in the range between 396-3589 and 712-5760 CFU m -3 in the schools of high and low socioeconomic districts, respectively. These results were higher than the findings of other studies [11]. Bacterial load of indoor air might be correlated with indoor temperature. This means that the density of aerosols will increase when the temperature increase. These results are in line with those recorded by [12,13,14]. The difference among the varied government schools on high and low socioeconomic districts might be because of the reality that different environmental factors increase the microbial contamination in school rooms and also the density of school students might also bring about a major biodiversity of high indoor air bacterial load. [15] got the same finding of the present study. The indoor air microbial loads of different buildings are related to the surrounding environmental conditions. Humidity is the health risk indicator for indoor air pollutants as reported by [16]. Therefore, to improve indoor air quality, congestion should be avoided and good ventilation systems designed. The most vital approach for heading off adverse health outcomes is the prevention (or minimization) of persistent humidity and microbial growth on interior surfaces and in schools constructing systems.
Facilities such as good ventilation, daily cleaning of classrooms, and increased student density in classes are responsible for increasing the microbial content of indoor air of schools [17] and [18]. The movement of outdoor air leads to the accumulation of gaseous emissions that enter the classrooms depending on the direction of the wind [19]. This leads to a decrease in the quality of indoor air of the classrooms.
During physical parameter measurement, it was found that all examined classrooms did not have an HVAC (heating, ventilation, and air conditioning) system in the government schools of low socioeconomic districts. However, there were ventilation system and air conditions in each classroom in the schools of high socioeconomic districts. The temperature in April ranged between 20.4-33.4°C and the relative humidity in the same month was 28%. Previous studies have shown that the environmental temperature affects the survival of microorganisms in the air [20] The survivability pattern of airborne bacteria in present study shows that temperature and humidity had effect on survival of most of these airborne bacteria. Since the group of Gram Positive Bacilli and cocci which have mechanism to resist the desiccation factors they were prevalent in all schools under study.

Identification of bacteria and fungi species
Three bacterial species were isolated and identified. They were Bacillus species, Micrococcus species and Staphylococcus species. Bacillus species was predominant in most government primary schools represented 85% of total bacteria presented in indoor air of schools under study ( Table 2). Identification of microorganisms is important issue from the ecological and health point of view. Three bacterial species were isolated and identified. They were Bacillus species, Micrococcus species and Staphylococcus species. Bacillus species was predominant in most government primary schools. The predominant bacterial flora was Gram positive bacteria. Bacillus species are the most dominant Gram positive bacteria. Bacillus is aerobic saprophytic, endospore formers and extensively disbursed within the atmosphere [21]. However, cocci bacteria are normal flora of skin and mucous membranes in human and mammals [22].
In the present study about 85 % of the bacteria isolated were Bacillus species which caused many of human diseases.
On the hand, about 60 % of bacteria isolated were Gram positive cocci belonging to saprophytic micro flora generally associated to human skin and mucosa which can be dispersed through droplets or skin peeling and maintained in air [7] observed a significant increased concentration of bacteria in afternoon as compared to morning in various rooms of a university [23] found the same result, concluding that bacterial contamination into indoor air derives from human presence. The association of airborne microbes and human activity has also been reported by many studies. [17] recorded highest level of bacteriological contamination in corridor and rooms during lessons in a school.
Gram positive bacteria, despite their abundance in the environment are less harmful; however, they have potential to be opportunistic pathogens [24][25]. The finding of isolated bacterial species of the present study partly agrees with the work by [26][27]. It was also harmonized in a study conducted in India [28].
Fungal flora isolated from indoor air of sampled schools showed dominant species like Aspergillus species, Penicillium species and Alternaria species ( Table 2). The prevailing species Aspergillus found in about 60% of total fungal count and detected in indoor air of sampled schools followed by Penicillium species (about 50%) and Alternaria species (about 30%), respectively ( Table 2). Fungal flora isolated from indoor air of sampled schools showed dominant species like Aspergillus species, Penicillium species and Alternaria species. The prevailing species was Aspergillus followed by Penicillium and Alternaria, respectively (Table 2). Aspergillus, Penicillium, Alternaria, and Cladosporium are the dominant fungal flora all over the world; because they can grow in numerous habitats in diverse ways [29]. According to some previous studies the microbiological quality of indoor air is highly influenced by the microbiological composition of outdoor air, which very much influenced by environment, season, the weather and even daytime. In the present study Aspergillus sp. and Alternaria sp. as outdoor molds occurred in a large number in schools under study. This result provided the evidence that high concentration of fungi in atmosphere can influence microbiological indoor air contamination. [30] also noticed that most commonly occurred molds in Norwich schools belonging to the genera: Penicillium, Aspergillus, Cladosporium and Mucor. Fungal flora of the indoor air of school room under study was dominated by Aspergillus sp. The present results are in agreement with those of [31] who found the same results in other indoor setting.

Indoor air quality of government schools
Based on the European sanitary requirements for non-industrial premises, the degree of air pollution via bacteria population in the studied schools ranges among high to extremely high (Table 3). There are not any regularly values regarding concentrations of the air of indoor bacteria, and the obtain results from the present study may be as compared simplest with the values endorsed with the aid of numerous authors or scientific establishments. High socioeconomic district The work conducted by a WHO expert group on assessment of health risks of biological agents in indoor environments suggested that total microbial concentration should not exceed 1000 CFU m -3 [32], whereas other scholars considered that 750 CFU m -3 should be the limit for bacteria [33]. Airborne microbial concentrations ranging from 4500 to 10,000 CFU m -3 also have been suggested as the upper limit for ubiquitous bacterial aerosols [34]. Based on the European sanitary requirements for non-industrial premises, the degree of air pollution via bacteria population in the primary schools under study ranges among high to extremely high polluted. The permissible limits of bacterial load were recorded as ≤ 500 CFU m -3 based on the sanitary standards of the European Commission for non-industrial premises [35]. The bacterial load in indoor education establishments is varied according to environmental factors such as temperature, humidity, and particulate matter concentration. In the present study, however the concentration of bacteria and fungi, had been surpassed the mentioned above value. Therefore, it is of importance to address microbial air pollution in these educational facilities as well as to expand related standards. It was found that more than 14 m 3 of air is daily inhaled by a human adult [36] leads to the conclusion that the airborne microbial intake per day of the occupants of the analyzed building might likely exceed by at least 14-fold the average number of microorganisms expressed above. The control of the microbial load of the surrounding air is thus important to establish the quality and health conditions of the services rendered by any public institution.

Conclusion
An excessive indoor air bacterial load was recorded in government primary schools in Riyadh metropolis in comparison with various indoor air biological requirements specification. Bacillus, Micrococcus and Staphylococcus had been the dominant isolated bacterial species. It should be taken in consideration to controlling the physical factors that support the growth and reproduction of bacteria in the internal environment of the classrooms to maintain the health of students and teachers. The microbial air quality of public facilities is a crucial factor in determining the extent of risk to human health. Undoubtedly, bacterial and fungal content varied with regard to the pupil activity, occupancy density, and ventilation. Government primary schools in Riyadh city recorded the worst quality of the microbiological air, as these educational facilities depend on natural ventilation in addition to the high student density. The indoor air microbial concentration is higher in the government schools, indicating suspected indoor microbial sources. In public instructional facilities, students, teachers and all labors are exposed to excessive microbial contamination. There is an urgent need to establish rules governing the high limits of the different types of airborne microorganisms for all public educational institutions.


extfieldsofstudy: Psychology Medicine

text:
Development of Nomophobia Profiles in Education Students through the Use of Multiple Correspondence Analysis

(1) Background: Nomophobia is a recent behavioural addiction phenomenon. The present study proposes the objective of determining levels of nomophobia in students of Education. In addition, it seeks to find evidence regarding whether cross-tabulating variables produces statistically significant differences and to examine whether the contemplated variables, together with nomophobia levels, can be used to generate a student profile. (2) Methods: A total of 510 students (M = 20.69 years) participated in this study. For the collection of information, we developed a Likert-type ad hoc scale of nomophobia. The quantitative data analysis programmes SPSS v.25 (IBM, Armonk, NY, USA), STATA.v.15 (StatCorp, Spring, TX, USA) and jamovi v.1.2 (The jamovi project, Sidney, Australia) were used to analyse information collected by the previously described scale. (3) Results: The study concludes the existence of three main levels of correspondence. The first is formed by students with a low level of nomophobia. It is associated with students undertaking the first year of a Master’s degree who are older than 24, and in this case, gender does not play a discriminating role. The second describes students with moderate nomophobia. It is associated with females, the degree titles of Pedagogy and Primary Education, undertaking the first or second year of degree study and ages of between 21 and 24. Finally, the third level of correspondence is formed by students with high nomophobia. It is related to the same characteristics as those previously mentioned but ages typically ranging between 17 and 20.

Introduction
Beginning in the last decade and motivated mainly by the technological advances that have taken place in society, young people are typically referred to as digital natives, whilst some older individuals are referred to as digital immigrants, as they have adopted this Information and Communications Technology (ICT) society [1,2]. ICT brought with it an accelerated increase in internet use, social networks, smartphones and videogames. This led to positive consequences and potential advantages that guarantee personal security, knowledge and enable health promotion and better communication [3][4][5]. Unfortunately, it also led to negative consequences, as it increases the power of loneliness and depression [6,7], internet addiction [8] and so on. This could have perverse duration of mobile phone possession nor narcotic substance use were associated with smartphone addiction. Another study by Haug et al. [37] was conducted in Switzerland and indicated that smartphone addiction was more frequent amongst younger adolescents in comparison with young adults. Further, work carried out by Yildiz-Durak [38] in Turkey analysed a set of demographic variables and reached the conclusion that age is the most important predictor, by a long way, of suffering nomophobia to a greater or lesser extent. Finally, work carried out in India by Bartwal and Nath [39] with students of Medicine reported that gender and age were equally the most relevant elements when considering the prevalence of nomophobia.
Although it has been reasonably well-established that young people feel the need to be continually connected to their mobile phones, a solid theoretical basis cannot be found that supports this disorder; neither is there unanimity in the established evaluation instruments [40]. In consideration of this, and bearing in mind that it has been presented by [9] that, up until the date of writing, little empirical evidence exists relating problematic mobile phone use with potential behavioural addictions, the present work proposes the following objectives: (a) To determine the levels of nomophobia (low, medium or high) within a sample of students of Education Sciences, according to their individual scale ratings and the characteristics of the sample being analysed; (b) to examine whether a cross-tabulation of different demographic variables relating to students (gender, age range, degree title and degree year) shows statistically significant differences with regards to the variable describing levels of nomophobia and (c) to check whether the demographic variables previously discussed, together with the variable describing the nomophobia level, produce any type of correspondence that can generate a student profile describing a higher or lower level of nomophobia.

Methods
The methodological design used for the present research corresponds to a descriptive study and, more specifically, to a survey study based on administration of a Likert-type scale on nomophobia to a representative sample of university students.

Participants
The sample size of our research study was N = 510 students from the Faculty of Education Sciences at the University of Granada (mean age was 20.69 years) whose differential traits will now be presented. With regards to gender, 23.7% were male, compared to 76.3% who were female. Relative to degree year, first-year students made up the greatest percentage with 38.2%, second-year students made up 30.8%, third-year students formed only 6.5% of the sample and fourth-year students corresponded to 17.3%, whilst the remaining 7.3% were on the first year of a Master's degree. In reference to degree title, 21.2% of the sample were undertaking Primary Education, 15.9% Infant Education, 33.7% Pedagogy and 22% Social Education, whilst 7.3% were Master's students. Finally, in relation to age, 55.7% were aged between 17 and 20 years, 34.4% were aged between 21 and 24 years and, lastly, the remaining 9.8% were older than 24.
On the other hand, we must highlight that, for the calculation of sample size, the following parameters were taken as a starting point: N = 6000, p = q = 0.5 and 1-α = 0.95, with a sampling error of ±4% calculated from the formula for finite populations propose for Thompson [41]: Using the following online tool: http://www.berrie.dds.nl/calcss.htm. The calculated sample size of this formula was 546 students, while our sample size had, finally, n = 510 students, with a sample loss of 36 participants. Finally, the sampling approach used adhered to proportional stratified probabilistic sampling, taking the variable describing degree title as the only proportional stratum.

Research Variables
A total of five different variables were considered as variables for investigation. On the one hand, four of these corresponded to the individual characteristics of students, these being: (a) gender: males vs. female; (b) degree year: first, second, third or fourth year of a Bachelor's degree and first year of a Master's degree; (c) degree title: Infant Education, Primary Education, Pedagogy, Social Education and Master's; (d) year: 17 to 20 years, 21 to 24 years and older than 24 years and one corresponded to (e) the level of nomophobia: high, medium and low.

Instrument for the Collection of Information and Reliability and Validity
For the collection of information, we developed a Likert-type ad hoc scale of nomophobia through the selection/adaptation of items from other previously standardised instruments that deal with this topic. This instrument is formed by diverse demographic variables of the students, these being: gender, age, degree title and degree year. Further, it includes 28 items with 4 response categories: never, sometimes, frequently and always. Reliability and validity have been considered since the classical test theory (CTT) due to the inability to calculate an item response theory (IRT) model (e.g., 2 parameters, graded response model, nominal response model and modified graded response model). This difficulty in the adjustment of the item response theory (IRT) model to noncognitive tests is consistent with what we found in other researches. One possible explanation for this difficulty is that this type of research has so far been developed mainly on tests designed with CTT and not with ITR, which makes it more difficult to adjust [42].
CTT analysis obtained corrected item-total correlations of r > 0.20 for all items, apart from items 13 and 26. This indicates good general discrimination of the items making up the scale (George and Mallery [43]). However, with the aim of consolidating the results obtained through the CTT, we also submitted the data obtained from the scale to an IRT analysis. To explain in detail, we developed a graded response model (GRM) using the program Stata v.15 (StataCorp, Spring, TX, USA). The GRM is an extension of the Logistic Model of two paremeters (LM2p) and it enables us to identify the ability of items to discriminate between levels of the latent trait Samejima [44]. It is held constant, with item difficulty being established at each "step" of the item or when a response moves from one response category to another. In other words, for a 4-point response scale, as found in the present case, we would have k − 1 steps (b parameters), given that participant responses can move from (a) 1 to 2, (b) 2 to 3, or (c) 3 to 4. Thus, k is the number of response options for a given item. In this way, the model would have 3 b parameters or threshold parameters. The model is structured in terms of cumulative probabilities and differences between accumulated differences. The probability that a participant selects response category k or higher is given by: According to the criteria described by Baker [45], the results obtained (not presented here due to space limitations) indicated that estimated values for discrimination parameters (a) suggested between acceptable (a > 0.65) and high (a > 0.1.34) discrimination for most items, with values of between 1.03 a 1.24 being achieved. Very high (a > 1.69) discrimination was also shown only in the case of items 1, 12, 21, 22, 27 and 28. Further, only three of the 28 items overall obtained values a < 0.65 (items 13, 18 and 26). As can be seen, these outcomes largely coincided with the CTT results obtained. Thus, we can conclude that the items were generally able to discriminate between students with lower vs. higher mayor nomophobia when discrimination criteria were applied. With regards to the threshold parameters (b), these ranged between −2.01 (b 3 item 6) and 12.98 (b 3 item 26), although the majority of values were between −2 and 2. This enabled accurate measurements of the latent trait of nomophobia to be taken within a large range. The distance between b k values was large for 28 of the considered substances. All categories emerged as most likely for some aspect of the measured trait. This appears appropriate for this scale, given that selecting a response option of 4 or 3 requires a much higher level of nomophobia in comparison to 1 or 2. This indicates that the information provided by this scale was more accurate at higher levels of the trait.
We contemplated reliability in terms of internal consistency (given that we included only a single administration of the measurement instrument) through analysis of Cronbach's alpha and obtained a value of α = 0.88. This can be considered a high value, which denotes that high reliability is enjoyed by the scale [46,47].
In addition, we calculated the value of Cronbach's alpha for the whole scale should each one of the 28 items be individually eliminated. In this sense, values of the Cronbach's alpha coefficients for the scale were seen not only to fail to improve the obtained value but actually make it worse (all values below α < 0.88) should the scale items constituting the instrument be individually eliminated. This means that the items contemplated by the present study are necessary and should be maintained by the instrument, given that their suppression would provoke a reduction in the consistency level of the scale [43].
In addition, we also calculated the composite reliability, as well as the average variance extracted (AVE) of each of the factors using the jamovi programme [48] and Excel spreadsheet. For this purpose, we relied on the standardised factor loadings of each item with its reference factor, as well as the residual covariances.
The results obtained are shown in the Table 1: As can be seen in the immediately preceding table, the composite reliability values are all equal to or greater than 0.71, while the AVE values are equal to or greater than 0.34. In the case, of composite reliability, values greater than 0.70 are preferable [49], and all the values obtained meet that condition. Moreover, for average variance extracted values, at least, equal to or greater than 0.5 is acceptable [50]. In our study, that condition is met, except in factor 1.
With regards to validity, we estimated content validity and concurrent criterion validity. Content validity of the instrument sought to guarantee that the items making up the instrument measure the construct that they were developed to measure; in other words, that the instrument measures what it is supposed to measure. In order to certify this validity, we constructed a scale based on three previously standardised instruments. In accordance with this, we have to outline that 8 of the instrument items were taken/translated from the screening for new addictions questionnaire (DENA) [51]. Another 8 of the questionnaire items were previously utilised by Ordoñez et al. [52], and, finally, the 12 remaining items were acquired from the instrument described by Roberts [53]. This left a total of 28 items that were scalar in nature.
We also considered concurrent criterion validity whose usefulness resides in determining the degree of correlation that individually exists between each scale item and the overall scale itself. For this purpose, we implemented the corrected item-total coefficient correlation. The results obtained in this respect indicated the cases in which r < 0.30 (items 20 and 28). For this reason, we can agree with the contributions of Dawson [54] and Salkind and Frey [55], which found that the items individually measured the same thing as the overall scale and, in addition, in the same direction (all of the correlations were positive). Thus, we can assert that the scale demonstrates concurrent criterion validity.
Finally, we estimated the construct validity of the scale. For this purpose, we submitted the 28 items of the scale to the exploratory factor analysis, using the quantitative analysis program SPSS v.25. The estimates used to provide a starting point will now be introduced. Extraction method used: principal component with Kaiser Criterion (λ ≥ 1). Rotation considered: Varimax.
With regards to the statistics prior to development of the factor analysis, a determinant correlation matrix value of |A| = 0.0000935 was achieved. This is to say, close to 0 but not null. This shows that the correlation matrix is not a single matrix and that the linear equations associated to the matrix could have a solution. On the other hand, the value of the Kaiser-Meyer-Olkin (KMO) measure of global adequacy was 0.871. According to Fabrigar and Wegener [56] and Holmes Finch [57], this value can be considered worthy. Measures of individual sampling adequacy (MSA) obtained values of ≥0.80 for all cases, this also being higher than the minimum value of MSA = 0.5 [58]. These results endorse the suggestion that the items' bivariate correlations are more important than the outcomes obtained for the partial correlations. In addition, results for the Bartlett test for sphericity obtained a value of χ 2 = 4497.882 (df = 378; p = 0.000). This means that the correlation matrix obtained is not an identity matrix; in other words, it is not a matrix where the correlations found in the diagonal are perfect (between the items themselves) and are null elsewhere in the square.
In relation to the results of the exploratory factor analysis implemented, we highlighted the presence of 8 factors that, when taken together, explain σ 2 = 64.45%. As we will see later, and following the considerations of Carmines and Zeller [59] and Reckase [60], the first factor extracted does not explain at least 20% of the variance explained by the factorial solution, which is why we cannot consider the presence of unidimensionality on the scale used; however, it can be considered the main factor of the factorial model obtained. The commonalities obtained pertaining to each one of the variables of the scale are all greater than h 2 = 0.5. This denotes that each and every one of the commonalities obtained good representation in the resulting factor solution. With regards to the final factor solution, we should highlight that the factor loadings were saturated at r > 0.35 (at least 10% of explained σ 2 , practical significance criterion).
Given these precedents, we contemplated a first factor comprised of 9 items (explained σ 2 = 14.01%) that seemed to have in common something we call prominence; that is, a behaviour that becomes important when it is deeply integrated into the daily life of surveyed participants. It coincided with factor 2 pertaining to abuse and difficulty in controlling abuse from the scale presented by Meyers et al. [58].
We also had a second factor comprised of 6 items (explained σ 2 = 9.96%), all of which had in common something we can refer to as abstinence symptoms. It coincided with factor 1 (not being able to communicate oneself) from the scale described by Yildirim and Correia [26].
We also found a third factor composed of 4 items (explained σ 2 = 9.30%) related with tolerance of mobile device use. As with the second factor, the third also coincided with factor 1, pertaining to tolerance and abstinence from the scale of Meyers et al. [58].
The fourth factor, for its part, was also organized according to 4 items (explained σ 2 = 7.05%), all of which had something to do with what we can refer to as comfort and euphoria resulting from mobile device use (coincident with factor 4, pertaining to giving up comfort from the scale described by Yildirim and Correia [26]).
The fifth factor was constructed of 3 items (explained σ 2 = 5.64%) that maintained an association with conflicts generated by mobile device use in the family setting. The sixth factor was configured by 2 items (explained σ 2 = 5.52%) that were linked to conflicts produced by mobile device use in the sphere of friendships.
The seventh factor was configured by a single item (explained σ 2 = 5.43%) and was similarly related with conflicts created by mobile phone use at a social level. Finally, an eighth factor was presented that was also formed by a single item (explained σ 2 = 4.47%). This had something to do with engagement in dangerous behaviours and personal integrity, such as mobile device use whilst driving a vehicle. Factors 5, 6, 7 and 8 from our scale could be seen as being reflected in factor 3 from the scale described by Meyers et al. [58], which globally referred to problems brought about by excessive mobile device use.
However, in order to demonstrate that the questionnaire worked similarly on males and females with measurement invariance analyses, we calculated a confirmatory factor analysis (CFA) by the jamovi program through the adjustment for maximum likelihood (ML). The results obtained about fit measures of CFA female vs. male are shown in the Table 2: Confirmatory factor analyses conducted with male and female samples supported an eight-factor structure. In this structure, the obtained factors presented generally satisfactory standardised factor saturations (not presented here due to space limitations), which further provided strong evidence of the existence of factor invariance between studied male and female university students. In this respect, we should highlight that, in relation to CFA, measures of fit can be generally considered for both genders, whilst also appearing to be well-adjusted in both genders. Firstly, upon examination of the incremental fit indices of the comparative fit index (CFI) and the non-normed fix index or Tucker-Lewis index (TLI), values of 0.90-0.95 were obtained for both genders. For this reason, a reasonable fit was considered [61]. Secondly, if we consider the absolute fit measure of the root mean square error of approximation (RMSEA), we can see that both genders obtained higher values than that dictated by the cutt-point criteria of 0.06 advised by Hu and Bentler [62]. Nonetheless, given that this value has a known statistical distribution, confidence intervals can also be calculated (lower-upper) from the level of 90%. In this way, if the lower interval is above 0.05 and the upper value lower than 0.08, we can consider the fit to be reasonably good [63]. Finally, if we consider the parsimony-based fit measure of the Bayesian information criterion (BIC), according to Raftery [64], we can conclude that both considered models are well-adjusted. This is shown through the fact that BIC values >10 denote consistent fit, and, in our particular case, these values are well above this limit.

Ethical Considerations
Study participants gave informed consent before commencing with any type of participation. Participation was entirely voluntary, and participants had the opportunity to withdraw study data at any stage during its development. Information was stored in a secure and protected database, and any information enabling the identification of participants was destroyed.

Data Analysis and Interpretation
We used the quantitative analysis program SPSS v.25 to analyse the collected information. A diverse analysis that was descriptive, inferential and multivariate in nature was implemented in order to address the proposed research objectives.
In order to determine the levels of nomophobia (low, medium or high) within the sample of students, we considered their individual classification in relation to the total obtained for each student and a series of cut scores. These cut scores referred to the three tertiles that can be inferred by dividing all of the scores, which ranged from a minimum of 28 and a maximum of 112, into three equal groups as shown in the Table 3. On the other hand, we show a detailed descriptive analysis of the three groups formed from the incidence of nomophobia (taking, with reference, the total scale) as shown in Table 4. Bearing in mind the aforementioned classification, we present the levels of nomophobia amongst the students who formed the object of this research. Breaking the results down according to the demographic variable being considered-gender, degree year, degree title and age-within a single table in which these variables are nested, determined paths of correspondence are established. Definitively, we present a type of Burt table that is obtained when a multiple correspondence analysis (from now on, a MCA) is implemented. The one we present here is in Figure 1.
Following the observations of the immediately preceding figure (Burt table), different correspondence paths immediately seem to be drawn at a merely descriptive level. In this way, we can appreciate how high levels of nomophobia appear to be more strongly associated with the female gender, those aged between 17 and 20 years, with the degree titles of Primary Education and Pedagogy and undertaking the first years of a degree (first and second). In contrast, the moderate and low levels of nomophobia appear to be related with other ages; that is to say, from 21 to 24 years and older than 24 years. In addition, they are linked to the degree titles of Infant Education and Social Education and to a Master's degree and undertaking the final years of a degree course (third and fourth and first Master's).
Nonetheless, this exclusively descriptive consideration must be empirically considered. With this aim (responding to research objective two), we developed four contingency tables in which we crossed-tabulated the four described variables (gender, degree year, degree title and age) with the nomophobia level, as shown in Table 5.
Bearing in mind the aforementioned classification, we present the levels of nomophobia amongst the students who formed the object of this research. Breaking the results down according to the demographic variable being considered-gender, degree year, degree title and age-within a single table in which these variables are nested, determined paths of correspondence are established. Definitively, we present a type of Burt table that is obtained when a multiple correspondence analysis (from now on, a MCA) is implemented. The one we present here is in Figure 1.   It can be appreciated that, except in the case of the variable describing gender where statistically significant differences were not reported (χ 2 = 1.74; p > 0.05), the three remaining variables achieved χ 2 statistic values that were all associated with a significant p-value (p < 0.05). These results contribute sufficient empirical evidence within the sample of participating students to support the continuing enquiry and the search for profiles capable of characterising a higher or lower incidence of nomophobia. For this objective (research objective three), we will implement the calculation of an MCA through the program SPSS, v.25. The MCA characteristics implemented are as follows: supplementary case range objects, normalisation method (principal variation according to the variables), convergence criteria (0.00001) and maximum iterations (100). The main results obtained are now shown below in Table 6. The summary table of the model permits two inferred dimensions to be appreciated. Given that the eigenvalue considers the proportion of data in the model that is explained by each dimension, we can determine that factor or dimension one is the most important (inertia-associated λ 1 = 2.395 and an explained σ 2 1 of 0.479). Further, it can be seen that factor or dimension two obtained an inertia-associated λ 2 = 1.847 and an explained σ 2 2 of 0.369. This produces a total explained σ 2 t of 0.848; in other words, almost 85% corresponds to an overall eigenvalue (λ t = 4.242). For its part, the Cronbach's α values obtained also indicate the extent of the correlations between the empirical variables (gender, degree year, degree title and age) that compose the latent variables (dimensions one and two). In our specific case, we can see that α 1 = 0.728, whilst α 2 = 0.573. We can, therefore, conclude that there is a greater correlation between the observed variables constituting factor one than those making up factor two.
With regards to the discrimination measures obtained for the different variables included in the analysis, we achieved significant results collected into Table 7 and Figure 2, which we will present next. greater correlation between the observed variables constituting factor one than those making up factor two. With regards to the discrimination measures obtained for the different variables included in the analysis, we achieved significant results collected into Table 7 and Figure 2, which we will present next.  As can be observed, we firstly highlighted that the variable pertaining to gender, in obtaining a parallel position to dimension two (x = 0; y = 0.410), becomes a good discriminating element of that dimension. This can also be said for the variables pertaining to the nomophobia level (x = 0.005; y = 0.101) and age (x = 0.475; = 0.055) with regards to dimension one. For their part, the variables pertaining to degree title (x = 0.902; y = 0.710) and degree year (x = 0.918; y = 0.666) achieved a bisector profile with regards to the equidistant origin, both for dimension one and dimension two. This converts them into discriminating variables of these two dimensions, and, further, as they are found further away from the origin, they possess greater explanatory power. Finally, we present the bio- As can be observed, we firstly highlighted that the variable pertaining to gender, in obtaining a parallel position to dimension two (x = 0; y = 0.410), becomes a good discriminating element of that dimension. This can also be said for the variables pertaining to the nomophobia level (x = 0.005; y = 0.101) and age (x = 0.475; = 0.055) with regards to dimension one. For their part, the variables pertaining to degree title (x = 0.902; y = 0.710) and degree year (x = 0.918; y = 0.666) achieved a bisector profile with regards to the equidistant origin, both for dimension one and dimension two. This converts them into discriminating variables of these two dimensions, and, further, as they are found further away from the origin, they possess greater explanatory power. Finally, we present the bio-spatial correspondence chart for the different levels of the contemplated variables, as shown in Figure 3. As we can appreciate, the correspondence chart of the points from the various categories that form the five variables permits an organised structure to be drawn around three main correspondences. The first one would be composed (correspondence one) of students with low levels of nomophobia. It is associated with students undertaking the first year of a Master's degree and who are older than 24 years of age, whilst gender does not play a discriminating role. The second correspondence is fulfilled by students with moderate nomophobia. It is more associated with females, the degree titles of Pedagogy and Primary Education, undertaking the first or second year of the degree course and individuals aged between 21 and 24 years. Finally, a third correspondence (correspondence three) would come formed by students with high levels of nomophobia. It is also more associated with females, the degree titles of Primary Education and Pedagogy, undertaking the first or second year of the degree course and being aged between 17 and 20 years.

Discussion of study
The main aim of the present research sought to determine the levels of nomophobia within a sample of students of Education Sciences and to determine the potential correspondences between the parameters that formed the object of study. In relation to this, it must be indicated that the present study of nomophobia produced as results outcomes that are in agreement with those found in other consulted studies [33,[65][66][67].
The majority of consulted research works indicate that high levels of nomophobia are associated with variables of a negative nature, such as anxiety, panic, impaired academic performance, lack of attention in class, impaired learning, etc. [67][68][69][70][71].
The results of the study indicated a stronger association of nomophobia with the female gender, As we can appreciate, the correspondence chart of the points from the various categories that form the five variables permits an organised structure to be drawn around three main correspondences. The first one would be composed (correspondence one) of students with low levels of nomophobia. It is associated with students undertaking the first year of a Master's degree and who are older than 24 years of age, whilst gender does not play a discriminating role. The second correspondence is fulfilled by students with moderate nomophobia. It is more associated with females, the degree titles of Pedagogy and Primary Education, undertaking the first or second year of the degree course and individuals aged between 21 and 24 years. Finally, a third correspondence (correspondence three) would come formed by students with high levels of nomophobia. It is also more associated with females, the degree titles of Primary Education and Pedagogy, undertaking the first or second year of the degree course and being aged between 17 and 20 years.

Discussion of Study
The main aim of the present research sought to determine the levels of nomophobia within a sample of students of Education Sciences and to determine the potential correspondences between the parameters that formed the object of study. In relation to this, it must be indicated that the present study of nomophobia produced as results outcomes that are in agreement with those found in other consulted studies [33,[65][66][67].
The majority of consulted research works indicate that high levels of nomophobia are associated with variables of a negative nature, such as anxiety, panic, impaired academic performance, lack of attention in class, impaired learning, etc. [67][68][69][70][71].
The results of the study indicated a stronger association of nomophobia with the female gender, within younger individuals and with the degree titles of Primary Education and Pedagogy. These data confirmed the results found in the studies of Hong et al. [36], Haug et al. [37] and Yildiz-Durak [38]. These pointed to a younger age and gender as relevant elements at the time of identifying and seeking to influence the prevalence of nomophobia.
In this sense, higher indices of socialisation correspond to the aforementioned age range, and mobile phone use constitutes one of the most socialising aspects of young populations [72][73][74]. As a result of this, a link between smartphone dependence and relationships with other individuals is generated. With regards to degree title, some authors indicated that the degrees of Social and Infant Education are highly vocational [75][76][77]. This implies a high capacity of attention towards these types of higher studies relative to the degrees of Primary Education and Pedagogy, which are not so specific or vocational. In a certain way, this enables students to prioritise other elements and could justify the results obtained in the present study.
As has been commented, individuals of a higher age and undertaking their final year of degree study acquire a larger degree of responsibility, and the levels of nomophobia decrease [78][79][80].

Conclusions
In this respect, the study determines three main correspondence levels. The first of these was formed by students with low levels of nomophobia and was associated with first-year Master's students who were older than 24 years of age. Further, gender did not play a discriminating role. These results confirmed that which was indicated by Bragazzi et al. [81] and Yildirim et al. [82], who highlighted that age is a protective factor in the face of nomophobia. This is due to the fact that, as students grow older, they acquire a series of personal, family and working commitments that, in a certain way, replace the addiction to mobile phones. However, we will also see later on that, in profiles where levels of nomophobia are moderate or high, both gender and age play a much more discriminating role.
A second correspondence would be formed by students with moderate nomophobia that is found to be associated with the female gender, in addition to the degree titles of Pedagogy and Primary Education, undertaking the first or second year of degree study and being aged between 21 and 24. Finally, we contemplated a third correspondence formed by students with high levels of nomophobia that were also more associated with the female gender, in addition to the degree titles of Primary Education and Pedagogy, undertaking the first or second year of degree study and being aged between 17 and 20. Thus, sufficient empirical arguments exist for us to conclude that age is a key element with regards to nomophobia, as has been indicated in previous research works [33][34][35].
Finally, and in relation to the purpose at the outset of the present work, we can conclude that, effectively, in our particular case, we found three profiles of students of Education Science that were more or less associated with different levels of nomophobia. In these profiles, age, degree year and gender seem to contribute to a greater extent to the development of profiles outlining the levels of nomophobia. On the other hand, the variable describing degree title maintained a less influential role over the preparation of said profiles.
The data obtained showed the need to continue investigating other university populations and wider age ranges in order to establish correspondences with other psychological factors and establish more detailed profiles relating to the problem of nomophobia.

Limitations and Prospections of the Study
The limitations found in the present study are largely due to the realisation of a cross-sectional study in which data were collected at a specific time point. Another limitation is that the data cannot be generalised to the general university population, as only students of Education Sciences were analysed. It is also important to indicate that the ages involved were somewhat slanted, given that age ranges spanning only 27 years were included (the maximum age was 44 years vs. a minimum age of 17 years), and there existed a strong predominance of individuals with ages between 18 and 21 years.
Finally, another limitation of the study was the excessive presence of the female gender in the sample under investigation. However, this aspect is justified by the feminisation of the degrees studied at the facility under analysis.