1. Introduction

1.1. Environmental Psychology

Environmental psychology is a branch of psychology that studies the mutual relationships and interactions between human behaviour (including experience and action) and its surroundings (material, social, and cultural),(Xu et al 2021)(Tam et al 2020). There are multiple pieces of evidence showing environmental psychology could be considered a psycho-social approach to people’s environmental relationships (Bonnes, M., & Secchiaroli, G., 1995)( (Russell Veitch & Daniel Arkkelin,1995) (Pronello, C. et al 2018) Space perception (Russell Veitch & Daniel Arkkelin,1995) (Nesma Sherif et al 2023) and utilization (Russell Veitch & Daniel Arkkelin,1995)( Feng, H.&, Yang, F. 2023) and recycling behaviour (Russell Veitch & Daniel Arkkelin,1995)( Nurliyana Jekria &Salina Daud 2016) environmental stress, valuation of public goods (Pelgrims, I., et al 2021) and Alzheimer’s disease, landscape aesthetics environmental cognition, behaviour in the natural environment, health behaviour change helping behaviour (Paul Bell et al,1996)on stress related to toxic exposure. community psychology, stress, coping & health (Tony Cassidy 1997). Population & Environment (Robert Gifford,1997) enclosing behaviour and method in environmental and behaviour (Robert Bechtel, 1997) multi-disciplinary centre for environmental strategy (Jonathan Sime,1999). Cross-cultural environmental psychology since-human–environment interactions are culture-bound(Tam et al 2020). Thus each of these scientists mentioned a parameter effect on the psycho-social approach of environmental psychology.

Therefore Environmental psychology (EP) is many things it is something which is seen and felt more as an area of overlap between psychology and several disciplines or domains (Jonathan D.Sime,1999) and EP is not only an area within psychology but interdisciplinary suggests the need to develop a coherent core for EP and recognize its applied context. The most relevant definition for environmental psychology used in this paper was defined as a “multidisciplinary behavioural science, both basic and applied in orientation, whose foci are the systematic interrelationships between the physical and social environments and individual human behaviour and experience” (Veitch, Russell 1995). In other words, environmental psychology is the study of interactions between humans and their surroundings. Because human-environment interactions are culturally determined (Tam et al 2020). There are multiple ecological models used by other researchers to determine the linkage and relationships among multiple factors affecting health, as an ecological model by (Gruenewald et al., 2014). but here we design a model to identify parameters of environmental psychology and relate them to active design approaches through physical activity categories. Figure 1 shows that environmental psychology is equal to context(environment) plus content (people-environment relation) which most of them emphasise social. For instance, the environmental psychology of campus built environment is equal to context (campus environment) and content (student-environment relation).

Figure 1. Environmental psychology model for determining its parameters (Authors).

Figure 1. Environmental psychology model for determining its parameters (Authors).

1.2. Healthy Campus as a New Trend

In general, campus master plans prescribe a set of design and planning actions to achieve a university’s goals and objectives as a higher education institution. It start in medieval Europe and modern universities evolved in America. Some of the best university campuses developed in the 19^th century and early 20^th century in the USA follow certain typologies such as the quadrangle campus, picturesque campus and beaux-art campus but after world war II emphasize freestanding buildings than on-campus master plan (Coulson et al., 2010; Turner, 1984; Dober, 1996). The quality of the campus built environment determines the health of users thus most design focused on micro-scale design rather than macro-scale design therefore an index proposed by (Hajrasouliha, A., 2017) called campus score measures the main physical qualities of universities campus which are composed of three latent variables representing urbanism, greenness and on-campus living with 10 indicators. University campuses can address this wide range of issues and concerns in different ways. Coulson et al. (2014) discuss ‘‘trends’’ in contemporary campus design which are adaptive reuse of buildings and facilities, starchitecture, hub buildings, interdisciplinary science research buildings, commercial urban development, large-scale campus expansions, and revitalizing master plans. But today for modern society the new trend is a healthy built environment with a new approach as the "Healthy Campus framework" which is formulated by the American College Health Association lately presented multiple student health targets, including a requirement to "create social and physical environments that promote good health for all" to "support efforts to increase academic success, productivity, student and faculty/staff retention, and life-long learning." (American College Health Association 2023). The ecological model of (McLeroy et al. 1988) was explained by the American College Health Association’s (2015a) Healthy Campus 2020 initiative and composed of five factors intrapersonal, interpersonal processes and primary groups, institutional factors, community factors and the last public policy for creating healthy campus.

The architectural design of the campus built environment is the main factor for creating a healthy built environment for students and staff. The new trends of design by AIA and UK Sport England introduced active design for promoting physical activity in built environments to get a healthy built environment and achieve a healthy community.( (Bloomberg, M. et al.2010; Sport England- Jennie Price 2015; Sport England 2005; Sallis J. et al. 2005; Sport England 2015; Gebel, K. et al 2005; Silver, L. et al. 2023; Robbins, J.L.2023; Fit City 2 ,2007; Lacasse, M.& Nienaber, S.2015; Bustler FitCity 10 2015; Public Health England,2015; Michael R. B et al. 2010). Figure 2 illustrates the chronological trend of a healthy campus by (the American College Health Association (2015a) and active design by Sport Englan and AIA. The start f a healthy campus from 1979 till now continued and developed. But the start of active design after the growth of chronic disease and obesity among people since 2005. The chronological combination between the two trends when and where started since the active design approach will be used to show it’s a way of achieving a healthy campus and improving the environmental psychology of campus.

Figure 2. Significant moments in healthy campus history data from American College Health Association 2023 with the active design approach. Timeline diagram (by the authors).

Figure 2. Significant moments in healthy campus history data from American College Health Association 2023 with the active design approach. Timeline diagram (by the authors).

1.3. Active Design and Physical Activity

1.3.1. Classification of Physical Activity in Terms of the Active Design Approach

The definitions for active design in U.K. and U.S.A. are similar in that both promote physical activity to create a healthy environment and society. Likewise, Physical activity is the primary variable of active design, so the last updated definition for the active method is by Piggin J (2020) defined physical activity as "people moving, acting and performing within culturally specific spaces and contexts, and influenced by a unique array of interests, emotions, ideas, instructions, and relationships." There is overwhelming evidence corroborating the definition of physical activity from Caspersen et al. 1985, reviewed from different sources, which cover all aspects as cerebral, social, situated, and political. The last updated definition by Piggin (2020) was accepted, studied and analyzed by being categorized into three categories by the author (Figure 3):

• Physically active: such as the person moving, acting and performing to achieve physical wellness in the built environment could be adopted as indoor staircases and outdoor walkways encourage more physical activity on campus .etc.
• Mentally active: influenced by a unique array of interests, emotions, and ideas to achieve mental health in a built environment could be adopted as walkways that wind through quiet outdoor areas offer students calm spaces in which to relax before and after classes (DeClercq, C., 2016) (WHO)
• Socially active: within culturally specific spaces and contexts to achieve social well-being in a built environment could be adopted as Designing community spaces within high-traffic areas encourages students to socialize with their peers.

In the end, the new approach active design its definition studied, analyzed and categorized (Azeez, S.A. et al. 2023). This categorization was used to full fill the purpose and goal of this research paper.

Figure 3. Active design definitions and indicators (Authors’ analysis).

Figure 3. Active design definitions and indicators (Authors’ analysis).

1.3.2. Types of Physical Activity and its Measurement

Physical activity is typically characterized as the following in the still-evolving subject of physical exercise and public health "Physical activity involves people moving, acting and performing within culturally specific spaces and contexts and influenced by a unique array of interests, emotions, ideas, instructions, and relationships." (Piggin 2020)Based on this definition physically active is categorized into three categories the individual is either physically active, mentally active or socially active (Azeez, S.A. et al 2023). Despite this easy definition, physical activity has many forms and intensities, making it a complicated habit. Physical activity can be divided into other categories, such as types of movement (such as walking or skipping), sports (such as soccer or badminton), living contexts (such as at school, home, or when travelling), or primary physiological effects (e.g., cardiorespiratory conditioning, muscle strengthening). Regardless of the classification system, physical exercise affects many health outcomes through various physiologic routes. Aerobic activities are the most popular and have the largest physiologic and physiological benefits, although physical activity is characterized and addressed in various ways. Based on the rate of energy expenditure, aerobic activities are frequently characterized as being sedentary, mild, moderate, or vigorous. Physical activity has been quantified in a variety of methods, including self-reported measures (such as surveys and activity logs), instrumental measurements (such as pedometers and accelerometers), which are sometimes referred to as "objective" measures, and direct observation, none of which are entirely adequate. (Kohl III, H.W. and Cook, H.D. eds., 2013). (See Figure 4) illustrate how physical activity could be measured and data collection will be based on this diagram.

Figure 4. The Diagram Indicates Physical Activity (types, intensity, measuring, and amount), (Designed by authors).

Figure 4. The Diagram Indicates Physical Activity (types, intensity, measuring, and amount), (Designed by authors).

Overall, if a place becomes active built environment should enhance physical activity and identify its types, intensity, amount, and measuring tool; this will help to know the amount of physical activity and active design in the built environment and identify its ratio of active living and lifestyle.

2. Materials and Methods

3. Results

3.1. Demographic Survey

The questionnaire survey was distributed over 428 student participants from 10 university campuses in the Kurdistan region. The participation rate takes out based on the total student number in university campuses with 10% (Table 1). The questionnaires were randomly distributed to students from different colleges. The female participants were more than males, 58.8% and 41.2% respectively. About age from 18 years old to 33 years old, the fresh student’s first-year stage rate is 4.8%. The students who have more than one year of experience on campus rate is 79.3% which is the maximum rate of participants. Other participants are those who went to university after the age of 24 years old 15% and 1% respectively. The weight of students ranged from 40kg to 140 kg. Most students have a normal weight between 41-60kg and 61-80 kg, their rates are 48.2 %and 36.6%. the overweight students are categorized as 81-100kg rate is 12.1%, 101-120 kg rate is 2.2% and 121-140 kg is 0.2%. this indicates a low percentage of students are overweight. For material status, most students are single rate is 91.7%. Most of the students live with family in the house its rate is 78.8%, and only 18.6% live in the dormitory. A small rate of students living with their friends in rented apartment rate is 2.6%. Only 10.6 % of students suffer from chronic (thyroid, arthritis, chronic kidney disease, liver disease, diabetes and depression). For sports, 58.2% of students do sports and 41.8 % are not interested in doing sports, the result is nearly the same. The percentage of hours doing sport per week maximum is ≤ 1-hour rate is 42% and minimum ≥4 rate is 13.7%. Most students are interested to do sports outside campus its rate is 74.6%, only 19.7% do sports inside the university campus, and 5.7% who are boys do sports inside and outside the campus. This is parallel to (von Sommoggy J,2020) conclusion in that “campuses discouraged students from being physically active by missing out on opportunities—indoors and outdoors— campuses discouraged students from being physically active by missing out on opportunities—indoors and outdoors—for fostering movement, such as designating the greens for games or walks or providing sufficient lockers for biking gear. The results can serve as a basis to plan custom-made public health interventions”. The number decreased after COVID-19 (Wong, M.-Y.C. et al 2023) (Mir IA et al. 2023). In addition, 50% do exercise inside the building, 43.9% outside of the building and only a small number 6.1% do sport in and out of the building.

Table 1. Demographic survey.

Table 1. Demographic survey.

Demographic Survey	Count	Table N %
University Campus	Case 1 = University of Dohuk	141	32.9%
	Case 2 = University of Sulaimani	67	15.7%
	Case 3 = University of Zakho	29	6.8%
	Case 4 = Koya University	28	6.5%
	Case 5 = Cihan University - Erbil	43	10.0%
	Case 6 = University of Tishk-Erbil	40	9.3%
	Case 7 = The Lebanese French University-Erbil	25	5.8%
	Case 8 = Knowledge University-Erbil	25	5.8%
	Case 9 = Nawroz University -Dohuk	18	4.2%
	Case 10 = Catholic University -Erbil	12	2.8%
Gender	Male	176	41.2%
	Female	251	58.8%
Age (Binned)	<= 18	20	4.8%
	19 - 23	334	79.3%
	24 - 28	63	15.0%
	29 - 33	4	1.0%
	34+	0	0.0%
Weight (Binned)	<= 40	3	0.7%
	41 - 60	199	48.2%
	61 - 80	151	36.6%
	81 - 100	50	12.1%
	101 - 120	9	2.2%
	121 - 140	1	0.2%
	141+	0	0.0%
Material status	Single	387	91.7%
	Married	35	8.3%
Living arrangement	Home	335	78.8%
	Dormitory	79	18.6%
	with a friend to rent a house/apartment	11	2.6%
Having chronic disease	Yes	45	10.6%
	No	379	89.4%
Do sport (any kind)	Yes	245	58.2%
	No	176	41.8%
Hours of exercise per week	<=1	150	42.0%
	2	108	30.3%
	3	50	14.0%
	>=4	49	13.7%
Location (doing sport)	Inside University Campus	66	19.7%
	Outside University Campus	250	74.6%
	Both	19	5.7%
Fixed setting (doing sport)	Indoor (building)	157	50.0%
	Outdoor (site plan)	138	43.9%
	Both	19	6.1%

3.2. Missing

There are some answers in the questionnaire survey, that are either not answered by students or the answers are not clear for the reliability and accuracy of results they are excluded as shown in Table (2). The maximum percentage of answers in the mentally active 99.5% included, and the Socially active range between 91.6%-93.5% answers included. Physical activity answers included a rate between 84.6%-85.3%. Overall the total average from 428 participants was only 9.7% unbailable answers excluded.

Table 2. The percentage of included and excluded participants who answer in the study.

Table 2. The percentage of included and excluded participants who answer in the study.

Case Processing Summary
	Cases
	Included		Excluded		Total
	N	Per cent	N	Per cent	N	Percent
Physical activity (Frequency) * University campus	364	85.0%	64	15.0%	428	100.0%
Physical activity (Duration) * University campus	362	84.6%	66	15.4%	428	100.0%
Physical activity (Intensity) * University campus	365	85.3%	63	14.7%	428	100.0%
Mentally active (Emotion) * University campus	426	99.5%	2	0.5%	428	100.0%
Socially active(Frequency) * University campus	396	92.5%	32	7.5%	428	100.0%
Socially active(Duration) * University campus	392	91.6%	36	8.4%	428	100.0%
Socially active(Importance) * University campus	400	93.5%	28	6.5%	428	100.0%

3.3. Physical Activity Categories

3.3.1. Physical Activity

The physical activity types included are football, basketball, tennis, swimming, running, fitness/gym, walking, bicycling, exercise physiology (aerobic, yoga), and work performance (university activity participation). The result showed that physical activity such as football, walking and work performance was done by most students inside university campuses other activities were done outside of campus based on individual interest. Most of the students give importance to exercise physiology, swimming, and fitness/gym to shape their body and look good, activities such as bicycling and running are done by some students who are interested in it doing these activities one time for an hour per week. Table 1 showed just 19.7% of students active on campus which is very less, the reason behind it return to most of the campuses did not have the opportunity for students to be active, another reason is that the students who have a lab and practical lectures they do not have time for doing activities inside the campus also (Salonee Jambusaria et al 2020) find out students that do not work out the reasons are the lack of time, energy, and inspiration to work out, a study by (Wu, Y. et al 2023) managing schedule of education for promoting physical activity is crucial. In addition, students engage in higher sedentary time in university for instance sitting in lectures for a long time(Castro, O. et al 2020). Campus universities such as Case 1, case 2, case 3, and Case 4 since having College of physical education and Sport Sciences have all the physical activities but Case 5, case 6 and Case 10 just have a football stadium that could be used for basketball and running too. Case 9 has a basketball and tennis field that can be used by students whenever interested to do so, but the last cases 6 and case 8 do not have any physical activities inside campuses in future they plan to add these activities. In a study by (Melissa L. deJonge et al . 2021), the findings have implications for adopting physical activity programs on campus as a mental health and well-being intervention. Statistically, there is a significant reduction in anxiety symptoms, depressive symptoms, and psychological distress before and after the program. Therefore finding and other research studies indicate that there is a strong relationship between physical activity and mental health (Rodríguez-Romo, G et al.2023, Shahadan, S.Z. et al 2022, Zhang, Z. et al 2023), thus physical activity interventions are crucial for the campus to improve the mental health of their students. For this study, the statistical descriptive includes the number of the sample (N), mean, 95% confidence interval for the mean, standard deviation with minimum and maximum for physical activities (frequency: repetition of activity per week), (duration: number of hours spend each time on the activity) with what intensity do (light, moderate and vigorous). Table (3) The mean for total physical activity frequency for case 1, case 9 and case 10 are 3.2, 3.6, and 3.4 times respectively which is the standard minimum number of activities done 3 times per week. But for other case studies less than this range. For the duration which is several hours for doing these exercises each time the mean for all cases is nearly the same starting from 1.32 hours for each time to 1.9 hours. With 95% coefficient intervals of mean of an hour less than one hour to two hours maximum, most of the students spend time on physical activities. Furthermore for physical activity intensity for all cases nearly the same intensity from light to moderate with a low number in vigorous-intensity especially in sports and fitness/gym. Its mean range is from 1.2 to 1.9.

Table 3. Descriptive statistics for the physical activity category.

Table 3. Descriptive statistics for the physical activity category.

Descriptives statistics
		N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
						Lower Bound	Upper Bound
Physical activity (Frequency)	Case 1	116	3.2059	1.88316	0.17485	2.8596	3.5523	1	7
	Case 2	48	1.8771	1.19052	0.17184	1.5314	2.2228	1	5
	Case 3	28	2.5493	1.49646	0.28281	1.9691	3.1296	1	5
	Case 4	17	1.4765	0.9763	0.23679	0.9745	1.9784	1	3.5
	Case 5	42	2.4901	1.64798	0.25429	1.9765	3.0036	1	7
	Case 6	39	1.7465	0.45192	0.07237	1.6	1.893	1	3.75
	Case 7	25	1.178	0.26657	0.05331	1.068	1.288	1	2
	Case 8	24	2.5357	1.10814	0.2262	2.0678	3.0036	1	4.75
	Case 9	15	3.6756	1.36785	0.35318	2.9181	4.433	1.5	6
	Case 10	10	3.4567	1.59831	0.50543	2.3133	4.6	1	7
	Total	364	2.5032	1.60788	0.08428	2.3375	2.669	1	7
Physical activity (Duration)	Case 1	115	1.6391	0.80329	0.07491	1.4907	1.7875	1	4
	Case 2	47	1.7259	1.29861	0.18942	1.3446	2.1072	1	7
	Case 3	29	1.908	1.32667	0.24636	1.4034	2.4127	1	6
	Case 4	16	1.3688	0.69447	0.17362	0.9987	1.7388	1	3
	Case 5	42	1.7286	0.50822	0.07842	1.5703	1.887	1	3
	Case 6	39	1.4774	0.40715	0.0652	1.3454	1.6094	1	2.5
	Case 7	25	1.3219	0.29562	0.05912	1.1999	1.4439	1	2
	Case 8	24	1.6657	0.77699	0.1586	1.3376	1.9938	1	4
	Case 9	15	1.5744	0.56851	0.14679	1.2596	1.8893	1	2.5
	Case 10	10	1.5633	0.9326	0.29491	0.8962	2.2305	1	3.5
	Total	362	1.628	0.84941	0.04464	1.5402	1.7158	1	7
Physical activity (Intensity)	Case 1	116	1.9253	0.5733	0.05323	1.8198	2.0307	1	3
	Case 2	49	1.6095	0.53709	0.07673	1.4553	1.7638	1	3
	Case 3	29	1.7836	0.57828	0.10738	1.5637	2.0036	1	3
	Case 4	17	1.584	0.44265	0.10736	1.3564	1.8116	1	2
	Case 5	42	1.5935	0.479	0.07391	1.4442	1.7427	1	2.5
	Case 6	39	1.45	0.52432	0.08396	1.28	1.62	1	3
	Case 7	25	1.1295	0.20258	0.04052	1.0459	1.2131	1	1.6
	Case 8	23	1.2479	0.38154	0.07956	1.0829	1.4129	1	2
	Case 9	15	1.6333	0.44633	0.11524	1.3862	1.8805	1	2
	Case 10	10	1.65	0.53547	0.16933	1.2669	2.0331	1	2.5
	Total	365	1.6501	0.56258	0.02945	1.5921	1.708	1	3

3.3.2. Mentally Active

There are nine questions asked about their emotion as to how they feel by doing physical activity and daily routine including being socially active with a Likert scale of either agree with the statement or not. Out of 428 participants, just 2 participants were excluded, and 426 answered positively. Table (4) illustrates among these numbers case 1, case 4 and case 9 same mean are 4. This indicates they agree and feel safe, comfortable, motivated, and expend energy when they are active. Seven out of ten cases nearly have the same mean which is 3.8. This showed that all have nearly the same opinion and agree with these statements. A the end of the questionnaire survey they asked open-ended questions even though they have a positive perception about physical activity will affect mental health (Rodríguez-Romo, G et al.2023, Shahadan, S.Z. et al 2022, Zhang, Z. et al 2023, LaBelle, B.2023), they claimed they do not have enough time to do it on campus but they are more socially active they feel good and satisfied. In addition, mental health is the main parameter of environmental psychology.

Table 4. Descriptive statistics for the mentally active category.

Table 4. Descriptive statistics for the mentally active category.

Descriptives statistics
		N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
						Lower Bound	Upper Bound
Mentally active (Emotion)	Case 1	140	4.1008	0.49119	0.04151	4.0187	4.1828	3	6.5
	Case 2	67	3.7299	0.628	0.07672	3.5768	3.8831	1	4.88
	Case 3	28	4.0079	0.48574	0.0918	3.8195	4.1962	3.13	5
	Case 4	28	3.8386	0.37015	0.06995	3.6951	3.9822	3.25	4.63
	Case 5	43	3.8343	0.40341	0.06152	3.7102	3.9585	3	4.63
	Case 6	40	3.8469	0.50676	0.08013	3.6848	4.0089	2.63	4.63
	Case 7	25	3.685	0.59852	0.1197	3.4379	3.9321	1.88	4.88
	Case 8	25	3.8721	0.63768	0.12754	3.6089	4.1354	1.75	5
	Case 9	18	4.0625	0.56107	0.13225	3.7835	4.3415	2.88	4.75
	Case 10	12	3.9896	0.42459	0.12257	3.7198	4.2594	3.38	4.75
	Total	426	3.9258	0.53567	0.02595	3.8748	3.9768	1	6.5

3.3.3. Socially Active

There are six social activities spending time with friends including the survey as leisure time (cafeteria, restaurant), public spaces (green area, park, benches), library, event hall spaces, theatre and shopping market kiosk. They are asked about frequency (how many times they visit this location), duration (how much they spend time when they visit these spaces) and how much this social activity is important for them. The result showed that the frequency means for visiting the social location on campuses in Case 8, case 9 and Case 10 is nearly the same between 3-3.5 times. For case 1, case 2, case 3, case 4, case 5, and case 6 mean is from 1.7 to 2.2 times which is nearly the same except case 7 has a minimum mean is 1.2 times per week. (time spend at social location). The duration means for all groups is somehow the same starting from 1.39 to 2.1 hours for each time. The break time for all universities same they have a lunch break starting from 12:00 till 13.30 nearly a 1.5-hour small break between lectures from 10-15 minutes. Also, a study by (Ingy Ibrahim El-Darwish 2021) claimed that universities must integrate more outdoor space to encourage social interaction. Social contact on university campuses can improve student’s sense of belonging and well-being and the study emphasizes the necessity of student involvement in creating appropriate social interaction sites, pathways, and routes on campuses that satisfy their requirements. This show that they spend all their break time on social activity more than physical activity. For the rate of the importance of social activity as shown in Table (5) the minimum mean is case 7 (1.32) and the maximum mean is case 2 (1.78) the other cases between them. This indicates that all of them give importance to social activity during break time at university campuses.

Table 5. Descriptive statistics for the socially active category.

Table 5. Descriptive statistics for the socially active category.

Descriptives statistics
		N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Min	Max
						Lower Bound	Upper Bound
Socially active (Frequency)	Case 1	132	2.2109	1.11347	0.09692	2.0191	2.4026	1	8
	Case 2	57	1.7497	1.16049	0.15371	1.4418	2.0576	1	7
	Case 3	25	1.9567	1.57253	0.31451	1.3076	2.6058	1	7
	Case 4	24	1.8153	0.87774	0.17917	1.4446	2.1859	1	4.33
	Case 5	40	1.8854	0.80801	0.12776	1.627	2.1438	1	4
	Case 6	40	1.7846	0.38993	0.06165	1.6599	1.9093	1	2.67
	Case 7	25	1.266	0.33494	0.06699	1.1277	1.4043	1	2.25
	Case 8	24	3.2569	0.89108	0.18189	2.8807	3.6332	1.5	5
	Case 9	18	3.5139	1.3661	0.32199	2.8345	4.1932	1	6
	Case 10	11	3.0848	0.98819	0.29795	2.421	3.7487	1.2	4.5
	Total	396	2.1158	1.14925	0.05775	2.0022	2.2293	1	8
Socially active (Duration)	Case 1	132	1.954	0.84987	0.07397	1.8077	2.1004	1	6.33
	Case 2	55	2.0909	1.01312	0.13661	1.817	2.3648	1	6
	Case 3	24	2.0354	2.02444	0.41324	1.1806	2.8903	1	10
	Case 4	23	1.4312	0.62293	0.12989	1.1618	1.7005	1	3.67
	Case 5	40	2.1004	1.43208	0.22643	1.6424	2.5584	1	10
	Case 6	40	1.5362	0.46975	0.07427	1.386	1.6865	1	2.5
	Case 7	25	1.3933	0.26308	0.05262	1.2847	1.5019	1	1.75
	Case 8	24	1.7014	1.30516	0.26642	1.1503	2.2525	1	6.75
	Case 9	18	1.7824	0.85517	0.20157	1.3571	2.2077	1	4.5
	Case 10	11	1.8682	0.7744	0.23349	1.3479	2.3884	1	3.5
	Total	392	1.8583	1.03942	0.0525	1.7551	1.9615	1	10
Socially active (Importance)	Case 1	132	1.7068	0.44653	0.03887	1.6299	1.7837	1	3
	Case 2	60	1.7869	0.43991	0.05679	1.6733	1.9006	1	2.67
	Case 3	27	1.6407	0.42848	0.08246	1.4712	1.8102	1	2.33
	Case 4	23	1.5022	0.48654	0.10145	1.2918	1.7126	1	2.33
	Case 5	40	1.6767	0.43963	0.06951	1.5361	1.8173	1	2.5
	Case 6	40	1.4254	0.40236	0.06362	1.2967	1.5541	1	2.33
	Case 7	25	1.322	0.37527	0.07505	1.1671	1.4769	1	2.33
	Case 8	24	1.4757	0.4541	0.09269	1.2839	1.6674	1	2
	Case 9	18	1.588	0.40672	0.09586	1.3857	1.7902	1	2
	Case 10	11	1.7636	0.28302	0.08533	1.5735	1.9538	1.33	2.2
	Total	400	1.6298	0.44966	0.02248	1.5856	1.6739	1	3

In the end, the ANOVA test was done for all groups’ physical activity in terms of (frequency, duration and intensity), mentally active and socially active in terms of (frequency, duration and importance) between groups and within groups as shown in Table (6) The F-value in ANOVA has calculated variation between sample mean/ variation within sample The higher F-value the higher the variation between sample mean/variation within samples. The higher the F-value the lower the corresponding p-value. The F- value is high for physical activity (frequency and intensity). (F(21,2)=9.9,p=0.000) and (F(2.4,0.2)=9.1, p=0.000) which is significant but for physical activity duration (F(0.8,0.7)=1.1, p=0.31) which is not significant since the p-value is not less than 0.05. this means the variation between samples is not high enough relative to the variation within samples, to reject the null hypothesis. On the other hand, for mentally active and socially active (frequency, duration and importance) F-value is high enough so it’s significant.

Table 6. ANOVA statistical test for showing the effect of activity between groups and within the groups.

Table 6. ANOVA statistical test for showing the effect of activity between groups and within the groups.

ANOVA
		Sum of Squares	df	Mean Square	F	Sig.
Physical activity (Frequency)	Between Groups	190.059	9	21.118	9.989	.000
	Within Groups	748.397	354	2.114
	Total	938.455	363
Physical activity (Duration)	Between Groups	7.585	9	.843	1.173	.311
	Within Groups	252.876	352	.718
	Total	260.461	361
Physical activity (Intensity)	Between Groups	21.652	9	2.406	9.129	.000
	Within Groups	93.553	355	.264
	Total	115.205	364
Mentally active (Emotion)	Between Groups	9.773	9	1.086	4.027	.000
	Within Groups	112.177	416	.270
	Total	121.951	425
Socially active (Frequency)	Between Groups	112.964	9	12.552	11.853	.000
	Within Groups	408.739	386	1.059
	Total	521.704	395
Socially active (Duration)	Between Groups	21.729	9	2.414	2.302	.016
	Within Groups	400.703	382	1.049
	Total	422.432	391
Socially active (Importance)	Between Groups	7.568	9	.841	4.486	.000
	Within Groups	73.107	390	.187
	Total	80.675	399

3.3.4. Factor Analyses for Physical Activity, Mentally Active and Socially Active

The factor analysis and statistics were used to show the most activity done by students (behaviour observation) and the most related activity to each other. Factor Analysis is a statistical method that looks at how lots of different observations correlate and determines how many theoretical constructs could most simply explain what you see (Ahmed, R.M et al. 2022). In other words, as follows:

• Physical activity extraction:

In the questionnaire, the physical activity asked for ten activities (Football, basketball, tennis, Swimming, running, fitness/gym, walking, bicycling, exercise physiology(aerobic, yoga), and work performance (university activity participation).

The scree plot method is used to determine the number of factors for physical activity. The y-axis shows the total eigenvalue and the x-axis number of components (physical activity). The scree plot orders the eigenvalues from largest to smallest. The first three factors have eigenvalues of more than 1, extracted three components. From largest to smallest (3.091), (1.455) and (1.053) respectively as shown in scree plot Figure (5).

The eigenvalues change less markedly when more than 9 factors are used. Therefore, 4–9 factors appear to explain most of the variability in the data. The percentage of variability explained by factor 1 is 3.091 or 30.91%. The percentage of variability explained by Factor 3 is 1.053 or 10.53%. The scree plot shows that the first three factors account for most of the total variability in data. The remaining factors account for a very small proportion of the variability and are likely unimportant.

Figure 5. Scree Plot to determine the number of factors for physical activity.

Figure 5. Scree Plot to determine the number of factors for physical activity.

Table 7 rotated component matrix extracted the 10 factors into three components and the relation of each factor with each other component 1 composed of 6 factors are swimming, tennis, basketball, working performance, exercise physiology and football. This indicates that out of six factors only two of them students have done. this means students are more active outside of university campuses. The second components have three factors are (walking, running and fitness/gym), walking also another factor students do inside university campuses the last components just have one factor which is bicycling which has done just by a few students outside the campus as an interest for doing this activity. The reason students do not use is the transportation system does not have a bicycle lane therefore there is no safety for students. The other students come from the countryside which is far away from university campuses. The dormitory students by walking they go to buildings.

Table 7. Extraction components of physical activity.

Table 7. Extraction components of physical activity.

Rotated Component Matrixa					Rotated Component Matrixa				Factor Matrixa
Physically active	Component				Mentally active	Component			Socially active	Factor
	1	2	3			1	2			1
Swimming	0.8				I feel anxiety every 4 weeks.	0.676			Leisure time (cafeteria, restaurant)	0.484
Tennis	0.747				I feel depressed when I am not active	0.622			Public spaces (green area, park, benches)	0.714
Basketball	0.663				I feel safer when I am doing physical activities.	0.602			Library	0.753
Working performance (university activity participants)	0.611				Emotionally I feel good when I am physically active	0.509			Event-Hall spaces	0.959
Exercise physiology (aerobic, yoga)	0.539				I feel comfortable everyday walking	0.454			Theatre	0.943
Football	0.517				I expend energy on daily activities.		0.792		Shopping- market- kiosk	0.761
Walking		0.78			I feel good about my Skeletal muscles and health		0.611		Extraction Method: Principal Component Analysis.
Running		0.734			My mood motivates me to move.		0.567		a. 1 factor extracted. 5 iterations required.
Fitness/gym		0.693			Extraction Method: Principal Component Analysis.				Only one factor was extracted. The solution cannot be rotated.
8-Bicycling			0.8		Rotation Method: Varimax with Kaiser Normalization. a
Extraction Method: Principal Component Analysis.					a. Rotation converged in 3 iterations.
Rotation Method: Varimax with Kaiser Normalization. a
a. Rotation converged in 5 iterations.

2.

Mentally active extraction

There are eight questions asked in the questionnaire survey about how they feel about doing activities related to being physically active and socially active. The scree plot method is used to determine the number of factors for being mentally active. The y-axis shows the total eigenvalue and the x-axis number of components (mentally active). The scree plot orders the eigenvalues from largest to smallest. in scree plot (Figure 6). As shown have extracted two components more than 1. The eigenvalues change less markedly when 8 factors are used. Therefore, 8 factors appear to explain most of the variability in the data. The percentage of variability explained by factor 1 is 2.270 or 22.7 %. The percentage of variability explained by Factor 2 is 1.150 or 11.5%. The scree plot shows that the first two factors account for most of the total variability in data. The remaining factors account for a very small proportion of the variability and are likely unimportant.

Figure 6. Scree Plot to determine the number of factors for mentally active.

Figure 6. Scree Plot to determine the number of factors for mentally active.

This can be shown in Table (7) in Component 1 they feel anxiety every four weeks and depression when they are not active at the first point in open-ended questionnaires they mention social activity and during exams, they have such emotions. The other two factors they feel good when they are physically active and comfortable by walking. The second component factors are they spend energy on daily activities such as assignments and exams with socially active, and the two last one is their emotion about their health and motivation. This indicates that students give time more to assignments and exams than social activity and the last one even though they know that physical activities are good for their health but they give less importance to them.

3.

Socially active extraction

There are six questions have been asked in the questionnaire survey public space on the frequency and duration they spend on social activity with friends with the importance level of this activity to them. The scree plot method is used to determine the number of factors for being socially active. The y-axis shows the total eigenvalue and the x-axis number of components (socially active). The scree plot orders the eigenvalues from largest to smallest. in scree plot (Figure 7). As shown have extracted one factor which is more than 1.

Figure 7. Scree Plot to determine the number of factors for Social activity.

Figure 7. Scree Plot to determine the number of factors for Social activity.

The eigenvalues change less markedly when 6 factors are used. Therefore, just one factor appears to explain most of the variability in the data. The percentage of variability explained by factor 1 is 4.007 or 40.07 %. There is we have only one factor then that suggests all of the items fit onto a single theoretical construct. As an operational definition, that means they’re one dimension/scale. The remaining factors account for a very small proportion of the variability and are likely unimportant. This can be shown in Table 7 as only one factor and can not be rotated this factor include all social activities leisure time (cafeteria, restaurant), public spaces (green area, park, benches), theatres, event halls, shopping market- kiosks, and libraries. If we compared it to the open-ended questionnaire survey, most of the students interested to enjoy their free time at the restaurant, café and public spaces such as gardens, parks resting on benches, then shopping-market- kiosks, after that library and the last place are event halls and theatres. In the end, we can say that social activity could be counted under the theoretical concept of environmental psychology.

4. Discussion

Figure 8. Environmental psychology relation with active design approach result.

Figure 8. Environmental psychology relation with active design approach result.

5. Conclusions

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