Monthly Archives: April 2022

Effects of Solar Wind on Earth’s Climate

DOI: 10.31038/GEMS.2022421

Abstract

The mechanism of climate in conventional explanations is caused by the Sun’s irradiation under daily rotation of Earth. However, the effects of solar wind have been ignored. The Earth’s climate depends on the wind. The daily weather moves along latitudes, spreading to the same latitude, and a wide range of weather travels in cycles of several days from west to east along longitude. In Conventional theory of heat convection of air cannot explain why the weather rotates faster than the Earth’s rotation. The solar wind collides with the Earth at an angle corresponding to the state of tilted Earth’s rotation axis. Although magnetic field caused by isolated moving charged particle decreases at the place far from the source, chained magnetic coupling of charged particles with solar wind exist at the surface of rotating Earth. The solar wind passing at high speeds through the east side of the Earth’s atmosphere move the weather from east to west because it has a greater acceleration effect than the western deceleration effect. These facts are the evidence that the solar wind has been affecting the Earth’s climate.

Keywords

Climate change, Solar wind, Trade wind, Westerlies

Introduction

Human-caused global warming is a current phenomenon [1]. The Holocene epoch [2], however, was superimposed on a naturally varying climate. Wind depends on the hourly atmospheric pressure arrangements. As the strike angle of solar wind depends on the tilt of the rotational axis of Earth, seasonal changes in wind not only depend on the irradiation angle of the Sun, but also on solar wind. Milankovitch cycles [3] describe the long-term effects of changes caused by Earth’s movements. These cycles depend on Earth’s orbital eccentricity, axial tilt, and precession. However, none had recognized the importance effects by the solar wind. In conventional terms, solar wind does not reach Earth’s surface owing to the geomagnetic field; this description on the geomagnetic field induces to misunderstand as “the solar wind does not affect the climate of the Earth.” Atmospheric molecules at upper boundary the Earth collide with the solar wind H⁺ to ionize, and there is a locally magnetic interaction among the motioning charged particles. So, the atmosphere links with the solar wind by magnetic coupling among moving charged particles. Solar wind has an escape velocity (V_e = 617.5 km/s) characterized by anti-clockwise motion (V_⊥ = 1.89 km/s) due to the rotation of the Sun. When solar wind collides head-on near the equator, the momentum of V_⊥ provides a driving force in the clockwise direction based on the gear mechanism on the daytime. Thus, solar wind collides with the atmosphere during the daytime and generates trade winds that flows from the east to the west. Atmospheric flow links with the H⁺in solar wind via the magnetic coupling of moving charged particles traveling in parallel. Magnetic coupling occurs for parallel-running charged particles, but it causes a repulsive action for anti-parallel charged particles. Therefore, solar wind that passes through the eastern region of Earth accelerates atmospheric rotation. However, solar wind passing through the west side region of Earth slows atmospheric rotation. The magnetic interaction of solar wind causes a strong acceleration in parallel-running charged particles. So, solar wind drives the westerly wind. Many explanations exist based on the Coriolis effect which can be applied to the movement of rotating objects. As the Coriolis force is perpendicular to the axis of an object, it is zero at the equator. Conventional explanations did not explain the mechanism: “why does weather, characterized by a large quantity of air, rotate faster than Earth’s rotation?”

The Geomagnetic Field that Expands by Magnetic Coupling of Moving Charged Particles

The density peak of hydrogen in the atmosphere of Earth is 10¹³m^–3, and occurs at an altitude of approximately 80 km, while that of the oxygen atom is 10¹⁷ m^–3 at an altitude of 100 km [4]. Although H⁺ escapes from Earth’s gravity, the peak density of H⁺ exists based on a continuous supply of H⁺ via solar wind.

The conventional “bow-shock” concept has frequently been mispresented as “solar wind exhibits a decreasing velocity owing to a repulsive force in the geomagnetic field.” The bow-shock concept results from the collision of particles with solar wind in the upper boundary of the atmosphere. The idea that the geomagnetic field prevents solar wind is incorrect. The magnetic field is the result of line integral from the electric current in a closed circle. Isolated moving electrons in a coil always change the direction. The isolated charged particle in motion affects the local motion of other moving charged particles. According to the Aharonov–Bohm effect [5], the magnetic field (B) is a mathematical entity for contiguously moving electrons and the vector potential (A) physically influences a moving isolated electron. In other words, the A–B effect states that a moving charged particle should be described by A instead of B.

Quantum theory uses the magnetic coupling energy among charged motioning particles via A (B = rot A). Equation (1) indicates that A caused by current j provides energy (E_m) to another current (i). E_m= –A・i (1)

Although there is horizontal magnetic coupling on parallel traveling protons (H⁺), there is repulsive magnetic force between the parallel traveling H⁺and electrons (e^–). This magnetic effect maintains the plasma state of solar wind. The movement of the scalar potential (V) generates vector potential A. The static potential V (E = grad V) and vector potential A have an identical form of distance dependency [6]. The magnetic field decreases at a location far from the source. The H⁺ in solar wind collides with an atom or a molecule in cosmic space; the ionized particles contribute to expansion of magnetic field by the chains of additions due to parallel-moving charged particles. So, the chain of coupled charged particles traveling in parallel expands the magnetosphere of the Planet (Figure 1).

Figure 1: A model of Van Allen belt that is formed via chained magnetic coupling of moving charged particles

As shown in Figure 1, the inner van Allen belt is located at approximately 1.6 R_e (R_e = 6,378km; Earth radius). The Outer van Allen Belt is located at approximately 4.0 R_e. There is a “gap” region between these belts at the distance of 2.2 R_e [7]. The offset mechanism related to the magnetic coupling among charged particles causes this gap region.

Effects of Solar Wind on Planetary Wind

Comparison of the Wind on Planets

The sun emits high-speed H⁺ as solar wind. The rotational component of solar wind, i.e., 1.89 km/s, is perpendicular to a radiation velocity for several hundred kilometers. The charged particles emitted from the Sun travel over a long distance, eventually colliding with each other. Thus, the rotational component of the momentum of solar wind decreases owing to magnetic coupling. The charged particles of solar wind form a disk shape on a plane perpendicular to the Sun’s rotation axis via the magnetic coupling of parallel currents. Comparative planetology has revealed that solar wind drives the atmosphere of a planet. Solar wind passing at high speeds through the eastern region of Earth’s atmosphere pushes weather from the east to west because it has a greater acceleration effect than the western deceleration effect. Figure 2 shows the effects of solar wind on atmospheric flow on Venus, Earth, Jupiter, and Saturn. Mousis et al. describe atmospheric flow on the outer planets [8]. The wind flow on Saturn was overwritten by using illustrated data in [9].

Figure 2: Atmospheric flow on Venus, Earth, Jupiter, and Saturn. Original images of each planet

Effects of Solar Wind on Super Rotation of Venus

Venus rotates in a direction opposite to that of other planets. The rotational period is 243 days, the orbital period is 224.7 days, and the angle of orbital inclination is 3.39°. The rotational speed of Venus’s atmosphere reaches 100 m/s at an altitude of approximately 70 km. Super rotation does not occur by Venus’s rotation itself, because there is little angular momentum. The clockwise rotational velocity of the atmosphere of Venus is explained caused by the collisions of solar wind with anticlockwise rotational velocity of1.89 km/s. However, the atmosphere on the nightside of Venus receives solar wind from the direction opposite to that of the dayside. A large bow-like pattern was captured by the mid-infrared camera (LIR) onboard Akatsuki, the Venus climate orbiter, in December 2015 [10], as shown in Figure 3. This pattern remained in approximately the same place for more than four days. The dayside and nightside continued rotating for more than 100 days. So, the temperature on the dayside increased while that on the nightside decreased. Therefore, the high-temperature atmosphere of the dayside passes through the upper layer of the low-temperature atmosphere on the nightside at the boundary.

Figure 3: Hot temperature atmosphere of dayside on Venus passes through at upper layer of low temperature atmosphere on nightside at the atmospheric boundary

Effects of Solar Wind on Earth’s Winds

Charged Particle in Earth’s Upper Atmosphere

The charged particle density increases at noon owing to ultraviolet rays and light emitted by the Sun. As the mass of electrons is negligible compared with that of H⁺, H⁺ of solar wind moves in a counterclockwise direction, together with ions in the upper earth’s sky. The magnetism caused by the rotating charged particles combines with the geomagnetism caused by the inner core. Auroras occur at a latitude of 75–80° on the daytime side. However, auroras exist at a latitude of approximately 65–70° on the nightside. The difference in the latitudes of auroras between the dayside and night side is due to irradiation from the Sun (Figure 4).

As shown in Figure 4a, the increase in aurora luminescence shifts from the west side to the east side at night, but the decrease in aurora luminescence shifts from the dayside to the nightside. Auroras observed at night are not only caused by the effects of daylight but also by the neutralization of ions by free electrons. As shown in Figure 4b, the trade winds blowing from the east to the west shift the charged particles on the daytime side. The westerlies blow at high latitudes and on the nightside.

Figure 4: Differences between the Sun-facing side and nightside, as observed from the North Pole

Weather in Equatorial Area Related to Solar Wind

Daily Changes in Weather in Equatorial Areas

During the daytime in equatorial areas, where solar irradiation occurs directly from the front, wind is characterized by a clockwise flow as solar wind enters the upper atmosphere. In contrast, solar wind drives the counterclockwise flow of the atmosphere at the nightside. Therefore, rain occurs in the evening along the equator. Madden–Julien oscillation (MJO) is a weather phenomenon in the equatorial region generated in the western Indian Ocean, wherein alternate wet and dry areas move eastward with a slow repetitive cycle of approximately 1~2 months [11]. Th slow speed at which weather migrates east over a wide area in the tropics can be understood as an effect of solar wind. The counterclockwise flow of the atmosphere at nighttime is offset by the effect of trade winds blowing from the east to west.

Mechanism of Typhoon

Typhoons occur in the Pacific Ocean during summer in the northern hemisphere. The most irradiated region during the summer solstice is around northern latitude of 23.4°. In this area, although trade winds blow in the daytime on end of June, westerlies of counterclockwise direction blow on both sides of the trade wind. Since the earth’s axis of rotation tilts at 23.4°, the solar wind has a moving component of north direction. So, when water vapor uprises at the southern region of the trade wind blows in the summer, that is the region where westerlies wind blows, the vapor of water moves northwest with counterclockwise rotation and collides with the trade wind of clock rotation. The collision forms an anticlockwise vortex. In the vortex, water vapor condenses, and rains, causes a tropical cyclone. This tropical cyclone moves northwest in a clockwise trade wind while develops into a typhoon. Then, the typhoon collides with the westerly winds of counterclockwise rotation and travels northeast direction. Figure 5 shows an illustration of the typhoon mechanism.

Figure 5: Typhoon mechanism in the northern hemisphere during summer

Conclusion

Weather and climate rely on the winds blowing over a wide area affected by solar wind. The tilt of Earth causes seasonal changes in the wind owing to solar wind. The flows of atmosphere are linked to solar wind via magnetic coupling among moving charged particles.

This study described effects of solar wind on the weather and the climate of Earth. This will be helpful when discussing research in a wide range of fields such as global warming.

Acknowledgement

I would like to thank Editage (www.editage.com) for English language editing.

References

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Buis A (2020) Milankovitch (Orbital) Cycles and Their Role in Earth’s Climate. NASA’s Jet Propulsion Laboratory.
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Feynman RP, Leighton RB, Sands M, Treiman SB (1964) “The Feynman lectures on physics. Physics Today 17: 45-46.
NASA, The deadly van Allen Belts?
Mousis O, David HA, Richard A, Sushil A, Don B, et al. (2021) In situ exploration of the giant planets. Experimental Astronomy.
García-Melendo E, Pérez-Hoyos S, Sánchez-Lavega A, Hueso R (2011) Saturn’s zonal wind profile in 2004–2009 from Cassini ISS images and its long-term variability. Icarus. 215 (1): 62-74.
Fukuhara T, Masahiko F, George LH, Takeshi H, Takeshi I, et al. (2017) Large stationary gravity wave in the atmosphere of Venus. Nature Geoscience 10 (2): 85-88.
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Role of Alpha Fetoprotein in Hepatocellular Carcinoma

COVID 19 Impact on Medical Students in Jordan, Cross-Sectional, Prospective Study

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DOI: 10.31038/JCRM.2022514

Abstract

Introduction: COVID 19, the global pandemic that was first identified in December 2019 in Wuhan, China, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and adversely affected global life style, was reported in Jordan in March 2020. Due to its high contagious dissemination, the rapid virus spread caused global lifestyle modifications. Medical schools in Jordan as other facilities were highly affected and had alterations related to education. Here we focus, discuss and conclude the final alterations impact according to students impressions to end up with recommendations for future pandemic education.

Methods: This cross sectional, prospective study explores the impact of COVID-19 pandemic on medical students’ academic performance in Jordan from their point of view. A survey questionnaire was developed to investigate the issue related to the study subject and to answer certain questions. Mainly we needed to find out if COVID-19 pandemic affected medical students’ academic performance in Jordan? In which aspects? And in what direction? Due to the nature of this study, and the circumstances during the study period, an online survey questionnaire was conducted through Google Forms and reflected the found outcome.

Results: The study population consists of approximately 6500 representing all medical students in each academic year from the six medical schools in Jordan. Appropriately found formula was used to determine the required sample size. Finalising that most but not all criteria used measures were negatively affected.

Conclusion: All the academic performance components -that we have assumed- have been affected negatively by the pandemic with the exception of medical knowledge. E-learning infrastructure and pre-experience in distance learning might have an improvement effect and may be better outcome than classical learning.

Introduction

COVID 19, the global pandemic that was first identified in December 2019 in Wuhan, China, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and adversely affected global life style, was reported in Jordan in March 2020 [1]. Due to its high contagious dissemination and the variable symptoms from subclinical to severe lethal pneumonia [2,3], the rapid virus spread caused global lifestyle modifications. Most governments worldwide applied new regulations trying to flatten the escalating spread curves caused by the pandemic. Face masks wearing, strict hygiene, social distancing, travel restrictions, borders closing, and closing schools, colleges and Universities physically were all utilized. The higher educational institutions around the world have been fully or partially, closing their campuses to limit the rapid spread of COVID19 infection. All those alterations led to massive disrupt at all educational levels in general [4]. Therefore, such consequences forced the worldwide higher educational institutes to adopt distance learning mode. Taking in consideration that any unforeseen judgment would probably lead to massive derangement in the critical and civilian cervices [5].

Moreover, all students perspectives in general, were distorted due to the misbelief of expected curricula modification to fit for the new so-called remote learning. In addition, remote electronic exams (E-exams) were considered as the new mode of assessment. Distance learning, teaching, and assessment were never the fundamental one applied in Jordan schools of medicine. Lack of experience in both parties of electronic services created an unsecured atmosphere. The issue of having distance learning as being the solely one used in medical schools was growing over and over. Debate started to expand between experts whether distance learning decision was injudicious up to many where others considered it sapient [6].

Concerning students in medical schools in Jordan, there was an apprehension among them about that newly developed assessment mode [7]. The panic was higher between clinical years medical students as medicine studying depends in its majority on clinical, and practical part especially in the last three years. Their fear was understandable as the decision of distance learning was suddenly taken and not gradually as expected to be. Gradual transition was about to be justified especially if proper preparation and precautions were taken in consideration before the complete sudden distance education decision.

However, the unprepared technical infrastructure will always be an obstacle for distance learning indifferent of the educational level. Malfunctions, bugs, connection errors, inability to connect, sudden disconnection, or even video and audio technical problems are all challenges faced by best prepared networks. Dishonesty of either side whether students or lecturers was always considered an addressed issue and taken seriously due to its major and catastrophic consequences. Nevertheless, obscurant credence started to be a new challenge for medical schools to face. That belief of students and parents reached to the extent that many appealed for money refund. Accordingly, proving efficiency and ability to continue online without affecting the quality of learning was a new challenge for all educational institutions to take over. Hybridisation of conventional, as well as online educational programme was applied by many institutions as a way to keep the balance between safety during pandemic and high quality education [8]. For instance, all lectures and presentations which were considered theoretical were given online, while patient based practice sessions were in hospital module of learning, after taking all precautions as per ministry of health instructions.

Nevertheless, medical educational system continued to pursue its utmost efforts to facilitate the informations availability. Undergraduate medical student’s opinions about the modified system attitude were variable, and here we try to focus on their expression and to illustrate their point of view on the newly adopted distance learning era [9-13].

In this article, we have conducted a cross-sectional online survey study among all six years medical schools in Jordan to explore the above mentioned challenges, and the impact of COVID-19 pandemic on medical school students’ academic performance.

Materials and Methods

This cross sectional, prospective study explores the impact of COVID-19 pandemic on medical students’ academic performance in Jordan from their point of view. A survey questionnaire was developed to investigate the issue related to the study subject and to answer certain questions. Mainly we needed to find out if COVID-19 pandemic affected medical students’ academic performance in Jordan? In which aspects? And in what direction? Due to the nature of this study, and the circumstances during the study period, an online survey questionnaire was conducted through Google Forms. The form distributed to the study cohort could have been found at: https://docs.google.com/forms/d/1N0J8hiVVzYw7iV6zcPhvzRy_q_3NvdzxKlrovLVnqCg/prefill?skip_itp2_check=true. The targeted study population is the medical school students in Jordan indifferent in which year, meanwhile, basic and clinical years included. From all medical schools in Jordanian Universities, students were invited to participate in the study by completing the form online. The form was available through an invitation on known web platforms, sites and pages to students. Participation was voluntary and completely anonymous for the period from beginning of February till the end of it same year (2021). The study was approved by the ethical committee, and has IRB approval number 219/132/2020 from Jordan University of Science and Technology (JUST), Irbid, Jordan. The University of Jordan (UJ), Jordan University of Science and Technology (JUST), Mutah University (MU), The Hashemite University (HU), Al-Balqa Applied University (BAU), and Yarmouk University (YU) registered at study time students from medical schools were all eligible to participate in the study.

Variable Selection

The following variables are developed from literature reviews and serve as indicators of students’ academic performance:

1) Academic achievement which includes:

A. Medical knowledge.

B. Laboratory skills which applied for basic science years students only {first to third year}.

C. Clinical skills which applied for clinical science years students only {forth to sixth year}.

2) Attributes of studying which includes:

A. Studying hours

B. Sessions attendance

3) Seasonal grade.

4) Self-Assessment.

Based on the aforementioned variables, diagram 1 represent the operational definition of the impact of COVID-19 pandemic on students’ academic performance.

The reliability of Academic performance as indicated by the reliability coefficient (Cronbach’s Alpha=(0.723)). Indicates adequate reliability.

Hypothesis, test of hypothesis and sampling:

The hypotheses for this research are to test whether there is any significant impact of COVID-19 pandemic on students’ academic performance, and to test whether there is any association between specific demographic characteristics of the students and the impact of COVID-19 on their academic performance.

A. There is no impact of COVID-19 pandemic on students’ academic performance.

A1. There is no impact of COVID-19 pandemic on students’ academic achievement.

A1.1. There is no impact of COVID-19 pandemic on students’ medical knowledge.

A1.2. There is no impact of COVID-19 pandemic on students’ laboratory skills.

A1.3. There is no impact of COVID-19 pandemic on students’ clinical skills.

A2. There is no impact of COVID-19 pandemic on students’ attributes of studying.

A2.1. There is no impact of COVID-19 pandemic on students’ studying hours.

A2.2. There is no impact of COVID-19 pandemic on students’ attendance.

A3. There is no impact of COVID-19 pandemic on students’ grades.

A4. There is no impact of COVID-19 pandemic as self-assessed by students.

B1. There is no association between students’ Gender and the impact of COVID-19 pandemic on students’ academic performance.

B2. There is no association between students’ Academic year and the impact of COVID-19 pandemic on students’ academic performance.

B3. There is no association between students’ High school and the impact of COVID-19 pandemic on students’ academic performance.

B4. There is no association between students’ number of family members and the impact of COVID-19 pandemic on students’ academic performance.

B5. There is no association between students’ monthly family income and the impact of COVID-19 pandemic on students’ academic performance.

Due to the nature of this empirical study, an online survey questionnaire was conducted through Google Forms. The questionnaire was published through social media (multiple website, and platforms like Facebook groups for medical students in Jordan). The respondents were asked to evaluate the selected variables in a three point Likert scale, with 3=positively/increased, 2=neutral/not changed, 1=negatively/decreased.

One sample Student’s t-test is used to test hypotheses (A-A4). A t-test is a statistical hypothesis test in which the test statistic follows a Student’s t distribution if the null hypothesis is supported. It is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic is known. The one sample t-test requires that the dependent variable follow a normal distribution. When the number of subjects in the experimental group is 30 or more, the central limit theorem shows a normal distribution can be assumed. 95% of the t-Tests two tailed probability level was selected to signify the differences between preferences. The estimate value for testing hypotheses in this study is 2, which is neutral/not changed. It shows no differences in academic performance in the presence of the pandemic. A Pearson’s correlation test was run to test hypotheses (B1-B4). The respondents were asked to evaluate the selected variables in three points. One sample Student’s t-test is used to test hypotheses (A-A4). A t-test is a statistical hypothesis test in which the test statistic follows a Student’s t distribution if the null hypothesis is supported. It is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic is known. The one sample t-test requires that the dependent variable follow a normal distribution. When the number of subjects in the experimental group is 30 or more, the central limit theorem shows a normal distribution can be assumed. 95% of the t-Tests two tailed probability level was selected to signify the differences between preferences. The estimate value for testing hypotheses in this study is 2, which is neutral/not changed.

Results

Between Feb 2, 2021 and Feb 27, 2021. A total of 369 sixth year medical students in Jordan responded to the questionnaire, and of those who did, a number of 16 responses were excluded due to lack of accuracy-halo effect/since they answered a question not supposed to be answered. With 353 valid responses for analyses, representing 95% of the total was surveyed.

The study population consists of approximately 6500 representing all medical students in each academic year from the six medical schools in Jordan. The Slovin’s formula was used to determine the required sample size.

Sample Size=N/(1 + N*e22) where: N=population size. e=margin of error.

Solving the formula using e=0.05, N=(6500) sample size of (364) was yielded.

Table 1 presents the distribution of the students according to specific Demographic characteristics:

Table 1: Demographic characteristics

		Frequency	Percent
Gender	Male	179	50.7
Gender	Female	174	49.3
Residence	Central region	207	58.6
	Northern region	97	27.5
	Southern region	49	13.9
University	Al-Balqaʼ Applied University (BAU)	119	33.7
	Jordan University of Science and Technology (JUST)	59	16.7
	Mutah University (MU)	39	11.0
	The Hashemite University (HU)	43	12.2
	The University of Jordan (UJ)	19	5.4
	Yarmouk University (YU)	74	21.0
Academic year	First year	48	13.6
	Second year	83	23.5
	Third year	47	13.3
	Forth year	48	13.6
	Fifth year	73	20.7
	Sixth year	54	15.3
High school	private school	191	54.1
High school	public school	162	45.9
Number of Family members	Small family	142	40.2
	Medium family	188	53.3
	Large family	23	6.5
Monthly family income	Low income	125	35.4
	Moderate income	112	31.7
	High income	116	32.9

Table 2 presents the test results of One-Sample t-Test, with mean differences, t values, degrees of freedom, and two tailed significances of these tests.

Table 2: COVID-19 pandemic effect on medical students’ academic performance and its components

	Test Value = 2
	t*	df**	P value	Mean Difference	95% Confidence Interval of the Difference
	t*	df**	P value	Mean Difference	Lower	Upper
Academic performance	-8.020	352	.000	-.21211	-.2641	-.1601
Academic achievement	-7.725	352	.000	-.23654	-.2968	-.1763
Progress in medical knowledge	.274	352	.784	.01133	-.0699	.0926
Progress in laboratory skills	-8.910	177	.000	-.46629	-.5696	-.3630
Progress in clinical skills	-10.661	174	.000	-.50286	-.5960	-.4098
Attributes of studying	-7.604	352	.000	-.23229	-.2924	-.1722
Average daily studying hours	-2.796	352	.005	-.11898	-.2027	-.0353
Sessions attendance	-9.697	352	.000	-.34561	-.4157	-.2755
Seasonal grade	-2.306	352	.022	-.09632	-.1785	-.0142
Self-assessment	-7.289	352	.000	-.28329	-.3597	-.2069

*t value
**Degree of freedom

The mean for Academic performance score and all of its components – except medical knowledge- scores were statistically significantly lower than the neutral score of 2 (p<0.05). With progress in clinical skills having the highest mean difference of 0.49 and Seasonal grade having the lowest mean difference of -.10. Therefore, we can reject the null hypotheses (A, A1, A1.2, A1.3, A2, A2.1, A2.2, A3, and A4) and accept the alternative hypotheses. And accept the null hypothesis A.1.1.Thus the Academic performance and all of its components except medical knowledge is negatively affected by COVID-19 pandemic.

Table 3 presents the test results of Pearson’s correlation test between specific demographic characteristics and academic performance.

Table 3: Relationship between specific demographic characteristics and impact of COVID-19 pandemic on medical students’ academic performance

		Gender	Residence	University	Academic year	High school	Family member groups	Monthly family income level
Academic performance	Pearson Correlation	-.071	.077	.030	.159^**	.049	-.001	-.026
	p	.183	.150	.579	.003	.363	.983	.624
	N	353	353	353	353	353	353	353

** Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)

There was a very weak, positive correlation between Academic year and Academic performance r=.159, N=353; the relationship was statistically significant (p=.003). However there were no statistically significant relationships between Academic performance and other demographic characteristics (p>.05). Therefore, we can reject the null hypothesis B2 and accept the alternative hypothesis. And accept the null hypotheses (B1, B3 and B4). According to the findings and statistics, the academic performance and all of its components except medical knowledge were negatively affected by COVID-19 pandemic.

Discussion

Since COVID 19 pandemic first appearance in Wuhan city in china, November 2019 and its spread over the world (9, 10, 11), it has been affecting almost all sectors of life and increasing efforts has been made to study that effect (12, 13), lock down have been held worldwide which led to a huge impact on economy, education and most importantly health regardless whether it was physical or mental health [14-17].

In this context, this study was conducted as to observe the impact of COVID 19 on the academic performance of medical students in Jordan Universities, and evaluate the effect on certain parameters like their medical knowledge, laboratory and clinical skills, their attendance, daily studying hours and their grades, and all that was viewed in regards to e-learning which was adopted as the learning method during the pandemic. This study was done on the 6 medical schools in Jordan and the sample was 353 medical students from all years.

Apparently, and according to our results illustrated; COVID19 pandemic has negative impact in all component measured by us of academic performance for medical students in Jordan (attributes of studying, average daily studying hours, sessions attendance, academic achievement, progression in laboratory and clinical skills, grades, and self-assessment) with the exception of medical knowledge progression as found in Tables 2 and 4.

Table 4: Components measured by us of academic performance for medical students in Jordan

		Negative	Neutral	Positive
Total impact on academic performance	Frequency	158	137	58
Total impact on academic performance	Percent	44.76	38.81	16.43
Average daily studying hours	Frequency	136	123	94
Average daily studying hours	Percent	38.53	34.84	26.63
Seasonal grade	Frequency	127	133	93
Seasonal grade	Percent	35.98	37.68	26.35
Attendance	Frequency	161.00	153.00	39.00
Attendance	Percent	45.61	43.34	11.05
Progress in medical knowledge	Frequency	104.00	141.00	108.00
Progress in medical knowledge	Percent	29.46	39.94	30.59
Progress in laboratory skills for (1st – 3rd year)	Frequency	104.00	53.00	21.00
Progress in laboratory skills for (1st – 3rd year)	Percent	58.43	29.78	11.80
Progress in clinical skills (for 4th-6th year)	Frequency	100.00	63.00	12.00
Progress in clinical skills (for 4th-6th year)	Percent	57.14	36.00	6.86

The effect on daily studying hours and sessions attendance could be explained by the probability that students considered e-learning less serious and possibly there are difficulties in dealing with such kind of learning because it is an emerging one in medical schools in Jordan Universities. Moreover, resources limitation such as unavailability of proper internet connection in certain urban areas, and/or smart devices limited access by some students may have played a role and that could be indirectly observed through the participation in our study which is entirely dependant on digital platforms. Most of study participants are from central areas in Jordan (58.6%) where the most reliable internet is. On the contrary, contributors from northern and southern Universities where rural areas are, with unreliable internet connections represented 41.4% (27.5+13.9) as per (Table 1). Taking in consideration that students individual preferences, interests, vary from student to another [18].

Laboratory and clinical skills were the components that have been negatively most affected (mean difference=0.47, 0.5 respectively). We firmly believe that this effect is due to the fact that students have been away from the field of learning. Additionally, the suggested certainty related to the weaknesses of infrastructure in medical schools in Jordan to support appropriate e-learning which they believed it should have been far better that the existing [19]. Although some studies showed that laboratory skills can be acquired away from the lab by video feedback [20], the results we observed were against the results of those studies; and this can be explained by challenges found in Jordan Universities in supporting this kind of learning modality. Students in our study do believe that they substantially need to physically attend and participate in clinical rounds, take history and do physical examination to improve their clinical medical skills [21,22].

In contrast to other components, medical knowledge has shown no relation with the pandemic (p=0.784), we suggest that this is due to students ability to depend on self-studying from other resources outside the University premises. Books, slides, scientific papers, lectures, internet etc. participated to develop student’s medical knowledge. In addition, students platforms availability on the internet which facilitates knowledge sharing, and suggested sites between medical school students and their mentors again played distinguished part in improving faculty members and students medical knowledge [23].

Demographic characteristics in this study showed no relation (p>0.05) on the impact of COVID 19 pandemic on medical students academic performance with the exception of academic year (p=0.003). It showed only a weak positive effect (Pearson correlation=0.159) illustrated clearly in Table 3. The thing which can be explained by the fact that medical students autonomously progress in their years spent in medical schools. They perform more tests and sit for more evaluation exams, so more conjunction of knowledge and skills is met. Nevertheless, more development of cognition that makes them more independent in their self-developing [24]. Good example is that fourth year medical student is more likely to compensate the reduction in the quality and quantity than the second year medical student.

Alsoufi et al. found an accepted level of knowledge in medical students regarding e-learning in Libya in his study. In addition, they were concerned about how e-learning could be applied to provide clinical experience which depends heavily on bedside teaching [25].

Some other studies in other regions, specifically Kingdom of Saudi Arabia have shown acceptance in e-learning during COVID-19, showing better outcomes with promising potentials to prefer e-learning in medical education in the future [26]. As per experts, such findings could be related to better distance learning infrastructure and facilities.

The strength of this study is that it applied multiple measures (medical knowledge, laboratory and clinical skills, session attendance, daily studying hours, grades and self-assessment) to demonstrate and assess academic performance (Figure 1).

Figure 1: Definition of the impact of COVID-19 pandemic on students’ academic performance

Certain limitations of this study could be addressed in future research are (low response, and absence of funding, limited number of studies on this topic).

More studies are still needed to evaluate the impact of distance learning under and free of the influence of certain pandemic.

Conclusion

All the academic performance components -that we have assumed- have been affected negatively by the pandemic with the exception of medical knowledge. E-learning infrastructure and pre-experience in distance learning might have an improvement effect and may be better outcome than classical learning.

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