Mathematics 2022, 10, x. https://doi.org/10.3390/xxxxx www.mdpi.com/journal/mathematics
Article 1
Development and Initial Validation of the Active School
2Transport Instrument in the Developing Country Context to
3Measure Parental Intentions
4Mukhlis Nahriri Bastam 1,*, Muhamad Razuhanafi Mat Yazid 2,* and Muhamad Nazri Borhan 2 5
1 Research Centre, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Bangi, 6
43600, Malaysia 7
2 Smart and Sustainable Township Research Centre, Faculty of Engineering & Built Environment, Universiti 8
Kebangsaan Malaysia, Bangi, 43600, Malaysia 9
* Correspondence: [email protected] (M.N.B.); [email protected] (M.R.M.Y.) 10 Abstract: An active school transport (AST) instrument to measure parental intentions in a develop- 11 ing country context with 11 latent constructs and 108 measuring items has been created as part of 12 the integration framework: psychological and social cognitive constructs, perceived environmental, 13 and habit constructs. The purpose of the current study is to develop and carry out initial validation 14 of construct items for measuring parental intentions to promote AST in a developing country's con- 15 text. Three experts carried out a content validity index (CVI) by giving agreement to calculate the 16 Item-CVI (I-CVI) and the Scale-level-CVI (S-CVI). A pilot study was conducted to test the validity 17 and reliability of the construct items in Palembang, Indonesia, with 34 parents of school-aged chil- 18 dren returning the instruments to be analyzed using SPSS Version 23. It was discovered that 93 19 items were legitimate since their r values were more extensive than 0.3, and it was determined that 20 11 constructs were reliable because the measuring items had a Cronbach's alpha coefficient range of 21 0.8 – 0.9 (very good) and > 0.9. (excellent). An instrument has met the requirements of good validity 22 and reliability and can contribute as a novel instrument to measure parental intentions towards 23 AST, especially in developing countries in Asia, particularly Indonesia. 24 Keywords: instrument development, school travel, mode choice, active transport, reliability, valid- 25 ity, theory of planned behaviour, perceived environment, social cognitive, habit, active commuting, 26
children, parents, develping country 27
MSC: 28
29
1. Introduction 30
Physical activity (PA) among children is on the decline worldwide, which poses a
31substantial risk to their health. As a result, interventions are required to raise the likeli-
32hood that children will reach the World Health Organization's recommendation of engag-
33ing in 60 minutes of PA per day [1–5]. The overall prevalence of insufficient physical ac-
34tivity in some high-income Western countries such as the United States is 72.0%, Canada
35is 76.3%, the UK is 79.9%, Spain is 76.6%, Australia is 89%, and New Zealand is 88.7% also
36several countries in the Southeast Asian region such as Indonesia 86.4% and neighbours
37Singapore 76.3% and Malaysia 86.2% [1]. Indonesia, with a population of 40% of the total
38population in Southeast Asia or 279.1 million people, is the country with the most popu-
39lation in the region [6]. This statistic will undoubtedly have consequences on children's
40well-being. Physical activity can be defined as any movement of the body that is produced
41by the skeletal muscles and results in the expenditure of energy [7]. The term "physical
42 Citation: Lastname, F.; Lastname, F.;Lastname, F. Title. Mathematics 2022, 10, x. https://doi.org/10.3390/xxxxx Academic Editor: Firstname Last- name
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activity" refers to all types of movement a person engages in, whether to move themselves
43to and from an activity, for recreation or as part of their activity [7]. Children who par-
44ticipate in active school transportation (AST), often known as walking and cycling to
45school, have the opportunity to increase their physical activity levels [8,9]. Many benefits
46of AST will be obtained by children not only reducing the risk of being overweight or
47obese [10–13]. Nevertheless, it also positively influences children's mental and psycholog-
48ical health [14–16]. To promote AST as an increase in PA levels, researchers studied the
49behaviour of children and their parents towards AST, especially in developed countries
50such as the United States, Canada, UK, Spain, Australia, and New Zealand, which are
51otherwise inadequate in developing countries in Asia [17]. As a significant key in AST
52decision-making in children, parental involvement needs to be a primary focus in inves-
53tigating to promote of AST [18,19].
54Behaviour towards AST is influenced by various complex factors related to each
55other at the individual, social, and environmental levels [20,21]. Multiple factors men-
56tioned in the ecological model, including psychological and environmental factors, affect
57health behaviour such as AST [22,23]. However, little research has used established psy-
58chological theories to understand the relationships between psychological factors [24].
59The Theory of Planned Behavior is a socio-psychological model commonly used to explain
60behavioural motivation and successfully explains the mechanism of AST [24–27]. TPB ar-
61gues that intention is the main predictor that shapes individual behaviour and is a medi-
62ator of attitudes, subjective norms, and perceived behavioural control (PBC) [28]. Further
63evidence from recent research reveals that attitudes, social support, parental perceptions,
64and perceived parental barriers toward AST influence their children's transportation
65mode to school [18,29–32]. Barriers that parents consider are related to safety, distance to
66school, and built environment [18]. Self-determination theory [33] assumes that accom-
67plishing basic psychological needs (BPNs) such as autonomy (the need to take responsi-
68bility for one's actions), competence (the desire to achieve desired outcomes) and related-
69ness (the desire for a sense of connection with others) directly leads to an increase in pos-
70itive behavioural outcomes such as interest, attitude, and intention. The SDT has been
71utilized extensively as a research framework concerning PA, whereas the utilization of
72BPNs in connection with AST is currently low [27]. Several previous studies have inte-
73grated TPB and BPNs to explain the mechanism of AST [34,35]. Environmentally nuanced
74factors directly or indirectly affect AST behaviour [27,36,37]. In addition, the habit has a
75significant effect on the behaviour of AST [24] A research framework that integrates psy-
76chological and social cognitive constructs (i.e., TPB, BPN) and perceived environmental
77factors to explain AST was first proposed in New Zealand [20]. The author modifies the
78framework by combining the habit construct as a predictor and applying it to the context
79of developing countries in Asia, especially Indonesia. The current study aims to create
80further, refine, adjust, and initial items validate constructs to measure parental intentions
81to promote AST in developing countries.
822. Materials and Methods 83
2.1. Context 84
The study was conducted in Palembang, a metropolis in a developing country lo-
85cated to the south of the Indonesian island of Sumatra. The city has a population of 1.6
86million people with an area of 400.61 km2 with a population density of 4166 inhabit-
87ants/km2 [38]. The city of Palembang is divided into two parts, namely the Seberang Ilir
88and Seberang Ulu areas. The Musi River is the longest river on the island of Sumatra and
89is among the ten longest rivers in Indonesia. Nine hundred sixty-two schools consisting
90of 488 elementary schools, 253 junior high schools, and 221 high schools spread across 18
91sub-districts in Palembang [39]. Three hundred sixteen thousand eight hundred sixty-five
92students with details of 155,828 elementary school level students, 76,870 junior high school
93level students, and 84,167 high school level students who travel to school every day [40].
94The climate in the study area is a tropical climate consisting of dry and rainy seasons [41].
95The dry season begins in April and ends in August, when the study is conducted. The
96region has no specific intervention to promote AST among school children.
972.2. Procedures and Measures 98
The design of the instrument to measure parental intention variables in this study
99used four general procedures, namely: 1) conceptualization, 2) development, 3) expert re-
100view, and 4) pilot study (Figure 1). The procedure's framework results from modifications
101to instrument development and validation procedures carried out by researchers in vari-
102ous fields [42–45].
103104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119
Figure 1. Instrument development and validation procedure 120
The first stage of the instrument development and validation procedure used in this
121study, conceptualization, consists of two fundamental steps before building a research
122instrument. The step is to formulate a framework or model, followed by identifying and
123defining the construct of the proposed framework or model. In the second stage, the initial
124draft instrument is constructed by selecting, compiling, and adapting the items used as
125indicators in measuring the construct and the grading system of these items. In the third
126stage, the items that have been arranged in the initial draft of the instrument are reviewed
127by experts. The review process includes language and culture adjustments according to
128geographical contexts and the validity of the content of these items. The result of this stage
129is the acceptance, repair, or elimination of items for the implementation of the next stage.
130In the fourth stage, the author conducts a field test of the initial draft of the instrument
131extracted from the previous stage to assess the validity and absolute reliability of the
132measuring instrument.
133134
2.2.1.Conceptualization
135The conceptualization stage is the framework formulation that will be proposed to
136measure parental intentions toward the AST, constructs identification, and definition. The
137authors conducted a systematic literature analysis to summarize key findings from past
138research to establish which constructs will be employed. The theory of planned behaviour
139(TPB) has been successfully applied in previous efforts to understand AST behaviour from
140a parental approach [46–48]. It has been shown that habit has a significant and positive
141effect on all of the other latent variables of TPB in prior studies [24,49]. Self-determination
142theory [50,51] is a well-known paradigm for analyzing the societal and individual factors
143that influence physical activity involvement in children and adolescents [52]. Moreover,
144the number of studies in the AST-specific setting has increased in recent years [53,54]. It
145has been established that perceived environmental barriers and perceived neighbourhood
146environments are related to PA in developed countries, but little is known about them in
147emerging countries of Asia [22,55–58]. TPB is extended to include the constructs of habit,
148perceived environment, and child's psychological needs as parental barriers to encourag-
149ing AST.
150151
2.2.2.Development
152The items used to measure the constructions are selected, created, and modified in
153the development stage. A scoring system was utilized to quantify participant responses
154to the questions. Furthermore, generate an initial draft of the instrument to initiate the
155subsequent stage.
156Theory of Planned Behaviour Subscale 157
A questionnaire was constructed to test the TPB constructs (i.e., attitude, subject
158norm, description norm, perceived behavioural control, and intention) based on the ref-
159erences of [59] and prior research on AST in children [24,27,60–62]. Attitude is measured
160by nine items (i.e. "If my child cycles/walks to school regularly, my child's independence
161will grow well."). Subjective norm (SN) is measured by six items (i.e. "My best friends/ My
162family/ My co-workers/ My neighbours/ My Spouse/ My parents support me letting my
163child bike/walk to school."). Description norm (DN) measured by six items (i.e. "My best
164friends/ My family/ My co-workers/ My neighbours/ My Spouse/ My parents will let their
165child bike/walk to school."). Nine items measure perceived behavioural control (PBC) (i.e.
166"I am confident that I can let my child bike/walk to school every day."). The intention is
167measured by six items (i.e. "I intend to let my child bike/walk to school every day in the
168upcoming school year."). A five-point Likert scale was used to gauge participant agree-
169ment (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree).
170Self Determination Theory Subscale 171
Prior studies have contributed to the involvement of certain items in these constructs
172[27,63]. The self-determination theory in the activity scale, which consists of twenty items,
173was utilized to perform the measuring of autonomy (six items: e.g. “I feel that I have used
174the school travel mode of my choice.”), competence (seven items: e.g. “I am proficient in
175cycling/walking to school.”), Furthermore, relatedness (seven items: e.g. “I feel very com-
176fortable when I go to school with my friends.”). A Likert scale with five points was utilized
177for each participant to report their level of agreement.
178Perceived Environmental Barriers Subscale 179
The Barriers to Active Transport to Educational Centres (BATACE) scale was devel-
180oped to examine people's perceptions of the environmental barriers that hinder the suc-
181cess of AST [64], and recent research [27]. Perceived environmental barriers were meas-
182ured by eighteen items (i.e. "Sidewalks or bike lanes are not available on the road along
183between the house-schools."). Each participant used a Likert scale with five points to re-
184port the degree to which they agreed with the statement.
185Perceived Neighbourhood Environment Subscale 186
A participant's neighbourhood was defined as the region surrounding his or her res-
187idence that could be walked in 10–15 minutes, or roughly 1.5 kilometres [65,66]. The per-
188ceived neighbourhood environment was evaluated using a Spanish adaptation of the AL-
189PHA environmental questionnaire [65,66], and a recent study [27]. Twenty-two items
190were used to measure this construct (i.e. "Due to the high volume of traffic in the neigh-
191bourhood around where I live, walking is not recommended."). A Likert scale with five
192points was given to each participant, and they were instructed to report the degree to
193which they agreed with the statement being made.
194195 196
Habit Subscale 197
Habit as a determinant of intention and behaviour in TPB is studied since the con-
198structs meet Ajzen's criteria for utilizing determinants in other behavioural domains [67–
19969]. Habit also has a significant positive effect on the latent construct in the TPB of chil-
200dren's school travel behaviour [24]. This construct was measured by twelve items adapted
201from Verplanken and Orbell's Self-Report Habit Index (i.e. "Cycling/walking on travel is
202something I frequently do.”) [70]. A Likert scale with five scales is also employed.
203 2042.2.3.Expert Review
205A new investigation must be strictly confirmed to warrant that an instrument is valid
206[71–73]. Quantitative methods are used to evaluate how well items relate to or reflect a
207particular domain, and content validity is one of the measures that can be obtained from
208these evaluations [72–74]. There are many methods to assess content validity. The content
209validity index (CVI), assessed by experts, is used in this study. CVI is the strategy for
210content validity in instrument construction that has received the most significant attention
211from researchers, and it may be computed with the use of the Item-CVI (I-CVI) and the
212Scale-level-CVI (S-CVI) [73,75]. The I-CVI is calculated by taking the number of experts
213rated each item as "very relevant" and dividing that number by the total number of ex-
214perts. The values range from 0 to 1, and if the I-CVI for an item is more significant than
2150.79, then it is relevant; if it is between 0.70 and 0.79, then it requires changes; and if it is
216less than 0.70, then it is removed [73,75]. Similarly, the S-CVI is computed using the num-
217ber of items in an instrument-rated "very relevant" [73,75]. A conservative method, the
218Average CVI (S-CVI/Ave), was used to calculate the S-CVI in this study [73,75]. By divid-
219ing the total number of items by the sum of their I-CVIs, S-CVI/Ave is determined to study
220[73,75]. S-CVI/Ave demonstrates excellent content validity values greater than or equal to
2210.9 [76]. Experts also make cultural or contextual adjustments to items adapted from pre-
222vious studies. The experts who conducted the review process of the instrument items in
223this study were three experts. The first expert is a professional statistician and consumer
224behaviour expert. The second expert is a professional psychologist and lecturer. The third
225expert is a professional media communication expert. These experts have more than ten
226years of experience in their field.
227228
2.2.4.Pilot Study
229A pilot study is an initial stage in the overall study protocol. A pilot study is more
230typical of a small-scale than the main study, and its primary purpose is to assist in the
231planning and adjustment of the full-scale study [77–79]. The preliminary trial, practice
232run, feasibility study, and small-scale study are commonly used to describe pilot study
233[77,80]. The pilot study's purpose is to gather the information that can be used to improve
234the project or determine its feasibility [81–83]. The pilot study is also a statistical test con-
235firming the instrument's validity and reliability for use in full-scale studies. Because test-
236ing the hypothesis is not the primary goal of a pilot study, the sample size is sometimes
237not estimated in these investigations [77]. Some studies propose more than 12 samples for
238each group, while others recommend over 30 samples for each group [77,84,85]. It is nec-
239essary to select a suitable sample size not to provide adequate power for hypothesis test-
240ing but to understand the practicability of participant recruiting or study design [77]. The
241pilot study was carried out from April 2022 to May 2022. A total of 50 instruments were
242distributed to participants, and then 34 instruments were received for analysis using SPSS
243Version 23.
244In order to establish the correct Pearson correlation coefficient (r table value), the de-
245gree of freedom (df) must be determined. The degree of freedom (df) was then set to 32,
246given that there were 34 study participants (degree of freedom = sample size − 2). 0.307 is
247the r table value for 32 degrees of freedom with a significance level of 0.05. Meanwhile,
248the standard of reliability follows the interpretation of Cronbach's alpha coefficient range
249(<0.6 (weak); 0.6 - 0.7 (moderate); 0.7 - 0.8 (good); 0.8 – 0.9 (very good); > 0.9 (excellent))
250[86].
2513. Results and Discussion 252
3.1. Content Validity Index (CVI) 253
A summary of the expert review process is presented in Table 1. The first column
254shows the constructs involved in the study. The second column is the items used to meas-
255ure each construct. There are 11 latent constructs with 108 items spread out, varying each
256construct. The third and the fourth columns indicate the CVI given by the expert and the
257I-CVI of each item. Three experts give a valuation of the relevance of the items. Three
258experts are required for content validation [87]. The last column, the fifth column, inter-
259prets each I-CVI value of each item. Of 108 items assessed by experts, 96 items were rated
260appropriate, 11 items needed revision, and eliminated 1 item based on the reference I-CVI
261value range [73,75]. Items that require revision relate to the adjustment of local culture
262and language. The eleven items that need improvement are five items of the attitude con-
263struct, four items of the perceived environmental barriers construct, and two items of the
264perceived neighbourhood environment construct. While the eliminated item, included in
265the habit construct, is the ambiguous item in terms of language, experts cannot be used in
266the context of this study. After each item is revised and rejected according to the advice of
267experts, the total number of items to be tested for validity and reliability is 107. S-CVI
268calculated at the end of the table shows that the number 0.93 meet the established criteria,
269which means the validity of the content is excellent [76].
270 271Table 1. Calculation of I-CVI and S-CVI/Ave for items of AST 272 273
Constructs Items Expert - CVI I-CVI Interpretation
1 2 3
ATT ATT1 Child's independence 1.00 0.86 1.00 0.95 Appropriate
ATT2 Child's concentration 1.00 0.84 1.00 0.95 Appropriate
ATT3 Child's health 1.00 0.98 1.00 0.99 Appropriate
ATT4 Feel excited and happy 0.80 0.88 0.70 0.79 Need Revision
ATT5 Household expenditure 1.00 0.96 1.00 0.99 Appropriate
ATT6 Safety and security will be vulnerable 0.70 0.94 0.70 0.78 Need Revision ATT7 School trips will take too extended 0.70 0.88 0.80 0.79 Need Revision ATT8 School trips will be boring and unpleasant 0.80 0.80 0.70 0.77 Need Revision
ATT9 Feel tired and depressed 0.80 0.80 0.70 0.77 Need Revision
SN SN1 Friends 1.00 0.90 0.94 0.95 Appropriate
SN2 Family 1.00 0.90 0.94 0.95 Appropriate
SN3 Coworkers 1.00 0.90 1.00 0.97 Appropriate
SN4 Neighbours 1.00 0.90 0.94 0.95 Appropriate
SN5 Couple 1.00 0.96 0.94 0.97 Appropriate
SN6 Parents 1.00 0.96 0.94 0.97 Appropriate
DN DN1 Friends 1.00 0.80 0.94 0.91 Appropriate
DN2 Family 1.00 0.90 0.94 0.95 Appropriate
DN3 Coworkers 1.00 0.80 1.00 0.93 Appropriate
DN4 Neighbours 1.00 0.80 0.94 0.91 Appropriate
DN5 Couple 1.00 0.96 0.94 0.97 Appropriate
DN6 Parents 1.00 0.96 0.94 0.97 Appropriate
274
Table 1. Cont. 275 276
Constructs Items Expert - CVI I-CVI Interpretation
1 2 3
PBC PBC1 I live in a surrounding that allows 1.00 0.96 0.94 0.97 Appropriate
PBC2 I am confident that I can 1.00 0.96 1.00 0.99 Appropriate
PBC3 Giving trust to my child 1.00 0.96 1.00 0.99 Appropriate
PBC4 The child who knows navigation 1.00 0.96 1.00 0.99 Appropriate
PBC5 Could walk/bike to school 1.00 0.96 0.94 0.97 Appropriate
PBC6 Could walk/bike for other activities 1.00 0.96 0.94 0.97 Appropriate
PBC7 It is entirely up to me 1.00 0.96 1.00 0.99 Appropriate
PBC8 It is difficult for my child to 1.00 0.80 0.88 0.89 Appropriate
PBC9 My child has enough time 1.00 0.88 1.00 0.96 Appropriate
PEB PEB1 Availability of Sidewalks or cycle sections 1.00 0.88 1.00 0.96 Appropriate PEB2 The road atmosphere is not interesting 0.96 0.96 0.88 0.93 Appropriate
PEB3 No lighting at night 0.70 0.96 0.70 0.79 Need Revision
PEB4 Dangerous crossroads along home-school 0.95 0.90 0.94 0.93 Appropriate
PEB5 Influence of local weather 1.00 0.80 0.82 0.87 Appropriate
PEB6 Similarities with other children 1.00 0.80 0.94 0.91 Appropriate PEB7 Teenagers' perception of cycling/walking 1.00 0.80 0.94 0.91 Appropriate
PEB8 Carrying heavy loads 0.80 0.80 0.70 0.77 Need Revision
PEB9 The convenience of self-driving and finding a rides 0.98 0.90 0.82 0.90 Appropriate
PEB10 Troublesome preparation 1.00 0.80 0.94 0.91 Appropriate
PEB11 Safe bicycle parking 1.00 0.80 0.94 0.91 Appropriate
PEB12 Presence of wild animals 0.70 0.80 0.70 0.73 Need Revision
PEB13 Distance between home and school 1.00 0.96 0.94 0.97 Appropriate
PEB14 Areas with a high crime rate 1.00 0.90 1.00 0.97 Appropriate
PEB15 Cycling/walking fun 1.00 0.96 0.94 0.97 Appropriate
PEB16 The road contour along the home-school 1.00 0.80 0.88 0.89 Appropriate
PEB17 Traffic situation 1.00 0.80 0.88 0.89 Appropriate
PEB18 Pedestrian abuse of the bicycle lane function 0.70 0.80 0.70 0.73 Need Revision
PNE PNE1 Availability of sidewalks 1.00 0.96 0.94 0.97 Appropriate
PNE2 Availability of pedestrian paths 1.00 0.96 1.00 0.99 Appropriate PNE3 Availability of cycle-only lanes 1.00 0.96 0.94 0.97 Appropriate PNE4 Availability of separated cycle routes 1.00 0.88 0.94 0.94 Appropriate PNE5 Availability of playgrounds or esplanades 1.00 0.96 0.94 0.97 Appropriate
PNE6 Sidewalks condition 1.00 0.96 0.94 0.97 Appropriate
PNE7 Cycle lanes condition 1.00 0.96 0.94 0.97 Appropriate
PNE8 Playgrounds or esplanades condition 1.00 0.96 0.94 0.97 Appropriate
PNE9 Unsafe bicycle parking 1.00 0.80 0.94 0.91 Appropriate
PNE10 Safe points to cross busy streets 0.70 0.80 0.70 0.73 Need Revision
PNE11 Traffic volume and walking 0.97 0.96 0.94 0.96 Appropriate
PNE12 Traffic volume and cycling 0.95 0.96 0.94 0.95 Appropriate
PNE13 Crime rate and security during the day 0.98 0.96 0.88 0.94 Appropriate PNE14 Crime rate and security at night 1.00 0.96 0.88 0.95 Appropriate
PNE15 Cycling experience 1.00 0.80 0.94 0.91 Appropriate
PNE16 Graffiti and garbage litter my neighbourhood street 0.70 0.96 0.70 0.79 Need Revision PNE17 Environments with tree-lined roads 1.00 0.96 0.94 0.97 Appropriate PNE18 Abandoned buildings in the neighbourhood 1.00 0.96 0.88 0.95 Appropriate
Table 1. Cont. 277 278
Constructs Items Expert - CVI I-CVI Interpretation
1 2 3
PNE PNE19 The existence of a shortcut 1.00 0.88 0.94 0.94 Appropriate
PNE20 The fastest mode of cycling during the day 1.00 0.88 0.94 0.94 Appropriate
PNE21 The existence of a crossroads 1.00 0.88 0.94 0.94 Appropriate
PNE22 Ease of cycling/walking and preferred route 1.00 0.96 0.94 0.97 Appropriate
HBT HBT1 I do frequently 1.00 0.96 1.00 0.99 Appropriate
HBT2 I do automatically 1.00 0.80 0.94 0.91 Appropriate
HBT3 I do it without having to remember consciously 1.00 0.80 0.88 0.89 Appropriate HBT4 That makes me feel weird if I do not do it 1.00 0.80 0.94 0.91 Appropriate
HBT5 I do it without thinking 1.00 0.80 0.82 0.87 Appropriate
HBT6 That would require effort not to do it 1.00 0.80 0.94 0.91 Appropriate HBT7 (Daily, weekly, monthly) routine 1.00 0.80 0.94 0.91 Appropriate HBT8 I start doing it before I realize I am doing it 1.00 0.80 0.82 0.87 Appropriate
HBT9 I would find it hard not to do 1.00 0.80 0.94 0.91 Appropriate
HBT10 I do not need to think about doing 1.00 0.80 0.88 0.89 Appropriate
HBT11 That is typical “me” 0.50 0.78 0.60 0.63 Eliminated
HBT12 I have been doing this for a long time 1.00 0.96 1.00 0.99 Appropriate
INT INT1 I want to let my child 1.00 0.80 0.94 0.91 Appropriate
INT2 I intend to let my child 1.00 0.80 0.94 0.91 Appropriate
INT3 I will let my child 1.00 0.96 0.94 0.97 Appropriate
INT4 I am willing to let my child 1.00 0.96 0.94 0.97 Appropriate
INT5 I plan to let my child 1.00 0.88 0.94 0.94 Appropriate
INT6 It is prospective that I will let my child 1.00 0.80 0.94 0.91 Appropriate
ATN ATN1 I feel that I use 1.00 0.96 1.00 0.99 Appropriate
ATN2 I feel that I have the freedom 1.00 0.96 1.00 0.99 Appropriate
ATN3 I feel that my school commute mode is perfectly 1.00 0.96 1.00 0.99 Appropriate ATN4 I feel that my school commute mode parallel 1.00 0.96 0.94 0.97 Appropriate ATN5 I feel that my school commute mode is what 1.00 0.96 1.00 0.99 Appropriate
ATN6 I feel that I can choose 1.00 0.96 1.00 0.99 Appropriate
COM COM1 I am capable to cycle/walk 1.00 0.96 0.94 0.97 Appropriate
COM2 I am competent to cycle/walk 1.00 0.80 0.94 0.91 Appropriate
COM3 I am profecient to cycle/walk 1.00 0.96 1.00 0.99 Appropriate
COM4 I am confident in my ability 1.00 0.96 0.94 0.97 Appropriate
COM5 I am confident in my proficiency 1.00 0.88 0.94 0.94 Appropriate
COM6 I am confident in my expertise 1.00 0.88 0.94 0.94 Appropriate
COM7 I am confident in my competency 1.00 0.88 0.88 0.92 Appropriate
RLT RLT1 I feel tuned in when 1.00 0.96 1.00 0.99 Appropriate
RLT2 I feel I can easily talk when 1.00 0.96 0.88 0.95 Appropriate
RLT3 I feel very comfortable when 1.00 0.96 1.00 0.99 Appropriate
RLT4 I feel incredibly relaxed when 1.00 0.96 0.88 0.95 Appropriate RLT5 I feel I kindly interplay with 1.00 0.96 1.00 0.99 Appropriate RLT6 I feel comfortable talking to 1.00 0.96 1.00 0.99 Appropriate
RLT7 I feel very relaxed with 1.00 0.96 0.88 0.95 Appropriate
S-CVI/Ave 0.93
ATT = Attitude; SN = Subjective Norm; DN = Description Norm; PBC = Perceived Behavioural Control; PEB = Perceived Environmental Barriers; 279 PNE = Perceived Neighbourhood Environment; HBT = Habit; INT = Intention; ATN = Autonomy; COM = Competence; RLT = Relatedness 280
3.2. Validity and Reliability 281
The sociodemographic characteristics of this study's participants are presented in Ta-
282ble 2. The participants that returned the self-reported instruments comprised 34 parents
283with school-aged children aged 6 to 18. Participants consisted of men (55.9%) age range
28426 – 41 or the millennial generation group (58.8%) and dominated by higher education
285(91.2%). Children as school travellers consist of boys (64.7%) with an age range of 6-12
286years (70.6%) or at the level of elementary school students. The characteristics of school
287tips are in the form of distance to school, which is evenly distributed with a distance of
288more than 3 km (35.3%), these children are accompanied to school (82.4%), and the use of
289private vehicles (motorbikes/cars) (88.2%).
290291
Table 2. Sociodemographic characteristics of participants (n = 34) 292 293
%
Gender of parent
Male 55.9
Female 44.1
Age of parent
26 - 41 Millenial 58.8
42 - 56 Gen X 41.2
Education of parent
Middle school education 8.8
Higher education 91.2
Gender of child
Boy 64.7
Girl 35.3
Age of child
6 - 12 70.6
13 - 15 14.7
16 - 18 14.7
Distance to school
0 - 500 m 11.8
>500 - 1 km 11.8
>1 - 2 km 23.5
>2 - 3 km 17.6
>3 km 35.3
School Mobility
Escorted 82.4
Independent Mobility 17.6
School Mode of Transport
Public Transport 2.9
Private Vehicle 88.2
Bicycle 2.9
Walk 6.0
294 295
Table 3 shows the final results of the calculation of the validity and reliability of each
296item from the constructs that have been compiled previously. The items resulting from
297expert reviews continue clustered by type of constructs. Attitude construct (ATT) with
298nine items primarily yielded item ATT9 r = 0.276 < 0.3 (r-table) items ATT8 r = 0.248 < 0.3
299(r-table) this means that these two construct-forming items are not yet valid, so they need
300to be eliminated from their construct. Seven items on ATT have met the validity require-
301ments (> 0.3), and the value of Cronbach's Alpha = 0.875 (very good) indicates that ATT
302with those items is already reliable. Subjective norm (SN) and description norm (DN) at
303the beginning have met the item validity requirements (> 0.3), with each construct con-
304sisting of six items. The values of Cronbach's Alpha, both SN = 0.974 and DN = 0.977, are
305excellent and report that the SN and DN with their items have been reliable. After the
306PBC8 item r = 0.212 < 0.3 (r-table) is eliminated, the Perceived behavioural construct (PBC)
307has the remaining eight items that have met the validity requirement (> 0.3) with a value
308of Cronbach's Alpha = 0.942 (excellent) which indicates the PBC and its items are reliable.
309Perceived environmental barriers (PEB), with eighteen measuring items, eliminate PEB15
310r = 0.278 < 0.3 (r-table) so that the items meet the validity requirement (> 0.3) and reliability
311parameters that is Cronbach's Alpha = 0.944 (excellent). Still with constructs relating to
312the environment, the perceived neighborhood environment (PNE) has eliminated its ten
313items, PNE1 r = 0.200, PNE2 r = 0.189, PNE3 r = 0.214, PNE4 r = 0.223, PNE6 r = 0.245, PNE7
314r = 0.188, PNE8 r = 0.264, PNE9 r = 0.237 > 0.3 (r-table), and PNE5 relating to PNE8, and
315PNE17, to obtain validity values that meet the requirements (> 0.3). PNE, with twelve
316items remaining, has qualified reliability with the value of Cronbach's Alpha = 0.892 (very
317good). Habit (HBT) with 11 items, intention (INT) with six items, autonomy (ATN) with
318six items, competence (COM), and relatedness (TLT) constructs with seven items each
319have met the validity requirements (> 0.3) without having to eliminate. These last five
320constructs have also gained the value of excellent reliability.
321 322Table 3. Overview of items, corrected item-total correlation, Cronbach's alpha, Cronbach's 323
alpha based on standardized items, number of items
324325
Constructs Items (r)
()1 ()2 No.
Items
ATT Child's independence 0.860 0.878 0.875 7
Child's concentration 0.748
Child's health 0.853
Feel happy 0.646
Household expenditure 0.852
Security will be vulnerable 0.329
Trips time will take too extended 0.380
SN Friends 0.930 0.972 0.974 6
Family 0.938
Coworkers 0.924
Neighbours 0.912
Couple 0.882
Parents 0.887
DN Friends 0.970 0.976 0.977 6
Family 0.920
Coworkers 0.936
Neighbours 0.927
Couple 0.892
Parents 0.897
Table 3. Cont. 326 327
Constructs Items (r) ()1 ()2 No.
Items
PBC I live in a surrounding that allows 0.831 0.942 0.942 8
I am confident that I can 0.918
Giving trust to my child 0.895
The child who knows navigation 0.844
Could walk/bike to school 0.785
Could walk/bike for other activities 0.821
It is entirely up to me 0.532
My child has enough time 0.730
PEB Availability of Sidewalks or cycle sections 0.769 0.945 0.944 17
The road atmosphere is not interesting 0.649
Road signs along home-school 0.739
Dangerous crossroads along home-school 0.825
Influence of local weather 0.733
Similarities with other children 0.753
Teenagers' perception of cycling/walking 0.564
Carrying a heavy school bag 0.699
The convenience of self-driving and finding a rides 0.646
Troublesome preparation 0.619
Safe bicycle parking 0.628
Presence of stray dogs 0.527
Distance between home and school 0.748
Areas with a high crime rate 0.812
The road contour along the home-school 0.351
Traffic situation 0.764
Misuse of the sidewalk function 0.854
PNE Availability of crossings 0.609 0.893 0.892 12
Traffic volume and walking 0.645
Traffic volume and cycling 0.625
Crime rate and security during the day 0.661
Crime rate and security at night 0.814
Cycling experience 0.357
Garbage litter my neighbourhood street 0.637 Abandoned buildings in the neighbourhood 0.662
The existence of a shortcut 0.643
The fastest mode of cycling during the day 0.389
The existence of a crossroads 0.692
Ease of cycling/walking and preferred route 0.496
HBT I do frequently 0.827 0.945 0.944 11
I do automatically 0.807
I do it without having to remember consciously 0.789 That makes me feel weird if I do not do it 0.706
I do it without thinking 0.684
That would require effort not to do it 0.501
(Daily, weekly, monthly) routine 0.812
Table 3. Cont. 328 329
Constructs Items (r) ()1 ()2 No.
Items I start doing it before I realize I am doing it 0.827
I would find it hard not to do 0.809
I do not need to think about doing 0.744 I have been doing this for a long time 0.797
INT I want to let my child 0.901 0.978 0.978 6
I intend to let my child 0.927
I will let my child 0.945
I am willing to let my child 0.923
I plan to let my child 0.921
It is prospective that I will let my child 0.947
ATN I feel that I use 0.737 0.920 0.927 6
I feel that I have the freedom 0.716
I feel that my school commute mode is perfectly 0.820 I feel that my school commute mode parallel 0.768 I feel that my school commute mode is what 0.883
I feel that I can choose 0.787
COM I am capable to cycle/walk 0.874 0.980 0.981 7
I am competent to cycle/walk 0.931
I am profecient to cycle/walk 0.911
I am confident in my ability 0.960
I am confident in my proficiency 0.970
I am confident in my expertise 0.925
I am confident in my competency 0.928
RLT I feel tuned in when 0.794 0.948 0.949 7
I feel I can easily talk when 0.839
I feel very comfortable when 0.805
I feel incredibly relaxed when 0.828
I feel I kindly interplay with 0.839
I feel comfortable talking to 0.834
I feel very relaxed with 0.839
r = Item Correlation ; 1 = Cronbach's Alpha; 2 = Cronbach's Alpha Standardized 330
4. Conclusions 331
TPB has been a successful theory for understanding parental intentions on AST be-
332haviour in developed countries. The extension of this theory enhances habit, perceived
333environmental barriers, perceived neighbourhood environment, and self-determination
334theory as an addition to aspects of children's assessment in parental decisions. These pro-
335posed constructs are a unified instrument for understanding AST in developing countries,
336especially Indonesia. In this study, the author proposed 11 constructs and 108 measure-
337ment items. Experts panel have evaluated the items as constructs, resulting in the I-CVI >
3380.79 and S-CVI/Ave > 0.9, which can be considered measurement instruments with elimi-
339nation and adjustment procedures. In this process, only one item was eliminated and
340eleven items required revision. Validity and reliability tests are conducted on constructs
341and items that have passed the preceding procedure. In conclusion, 93 items were deter-
342mined to be valid based on their r values being more significant than 0.3, and the reliability
343of 11 constructs was determined based on the measurement items having a Cronbach's
344alpha coefficient range of 0.8 – 0.9 (very good) and > 0.9. (excellent). In conjunction with
345these findings, this study can contribute to the development of a validated instrument for
346measuring the psychological factors parents consider when deciding whether to allow
347their children to walk or cycle to school, particularly in developing countries in Asia.This
348section is not mandatory but can be added to the manuscript if the discussion is unusually
349long or complex.
350351 Author Contributions: Conceptualization, M.N.B.1 and M.R.M.Y.; methodology, M.N.B.1; software, 352 M.N.B.1; validation, M.N.B.1, M.R.M.Y. and M.N.B.2.; formal analysis, M.N.B.1. and M.R.M.Y.; inves- 353 tigation, M.N.B.1.; resources, M.N.B.1; data curation, M.N.B.2; writing—original draft preparation, 354 M.N.B.1, M.R.M.Y.; writing—review and editing, M.N.B.1, M.R.M.Y. and M.N.B.2; visualization, 355 M.N.B.2; supervision, M.R.M.Y. and M.N.B.2.; project administration, M.R.M.Y.; funding acquisi- 356 tion, M.R.M.Y. All authors have read and agreed to the published version of the manuscript. 357 Funding: This research was sponsored by the Universiti Kebangsaan Malaysia (UKM) and The Min- 358
istry of Higher Education Malaysia through project GUP-2021-014 359
Data Availability Statement: All the necessery data are contained this paper. 360 Acknowledgments: The author would like to acknowledge all parties who have assisted in this 361 research, especially each reviewer who has provided improvements to this work 362 Conflicts of Interest: The authors declare no conflict of interest. 363
References 364
1. Guthold, R.; Stevens, G.A.; Riley, L.M.; Bull, F.C. Global Trends in Insufficient Physical Activity among Adolescents: A Pooled 365 Analysis of 298 Population-Based Surveys with 1.6 Million Participants. Lancet Child Adolesc. Heal. 2020, 4, 23–35, 366
doi:10.1016/S2352-4642(19)30323-2. 367
2. Larouche, R.; Mammen, G.; Rowe, D.A.; Faulkner, G. Effectiveness of Active School Transport Interventions: A Systematic 368 Review and Update. BMC Public Health 2018, 18, 206, doi:10.1186/s12889-017-5005-1. 369 3. Villa-González, E.; Barranco-Ruiz, Y.; Evenson, K.R.; Chillón, P. Systematic Review of Interventions for Promoting Active 370 School Transport. Prev. Med. (Baltim). 2018, 111, 115–134, doi:10.1016/j.ypmed.2018.02.010. 371 4. Buliung, R.; Faulkner, G.; Beesley, T.; Kennedy, J. School Travel Planning: Mobilizing School and Community Resources to 372
Encourage Active School Transportation. J. Sch. Health 2011, 81, 704– 373
5. Witten, K.; Kearns, R.; Carroll, P.; Asiasiga, L.; Tava’e, N. New Zealand Parents’ Understandings of the Intergenerational De- 374 cline in Children’s Independent Outdoor Play and Active Travel. Child. Geogr. 2013, 11, 215–229, 375
doi:10.1080/14733285.2013.779839. 376
6. World Population Review ASEAN Countries | Association of Southeast Asian Nations 2022 Available online: https://worldpop- 377
ulationreview.com/country-rankings/asean-countries (accessed on 17 July 2022). 378
7. World Health Organization Physical Activity Available online: https://www.who.int/news-room/fact-sheets/detail/physical-ac- 379
tivity (accessed on 16 July 2022). 380
8. Larouche, R.; Saunders, T.J.; Faulkner, G.E.J.; Colley, R.; Tremblay, M. Associations between Active School Transport and Phys- 381 ical Activity, Body Composition, and Cardiovascular Fitness: A Systematic Review of 68 Studies. J. Phys. Act. Health 2014, 11, 382
206–227, doi:10.1123/jpah.2011-0345. 383
9. Van Sluijs, E.M.F.; Fearne, V.A.; Mattocks, C.; Riddoch, C.; Griffin, S.J.; Ness, A. The Contribution of Active Travel to Children’s 384 Physical Activity Levels: Cross-Sectional Results from the ALSPAC Study. Prev. Med. (Baltim). 2009, 48, 519–524, 385
doi:10.1016/j.ypmed.2009.03.002. 386
10. Adom, T.; De Villiers, A.; Puoane, T.; Kengne, A.P. Prevalence and Correlates of Overweight and Obesity among School Chil- 387 dren in an Urban District in Ghana. BMC Obes. 2019, 6, 85–89, doi:10.1186/s40608-019-0234-8. 388 11. Bere, E.; Oenema, A.; Prins, R.G.; Seiler, S.; Brug, J. Longitudinal Associations between Cycling to School and Weight Status. 389
Int. J. Pediatr. Obes. 2011, 6, 182–187, doi:10.3109/17477166.2011.583656. 390
12. Ramírez-Vélez, R.; García-Hermoso, A.; Agostinis-Sobrinho, C.; Mota, J.; Santos, R.; Correa-Bautista, J.E.; Amaya-Tambo, D.C.; 391 Villa-González, E. Cycling to School and Body Composition, Physical Fitness, and Metabolic Syndrome in Children and Ado- 392
lescents. J. Pediatr. 2017, 188, 57–63, doi:10.1016/j.jpeds.2017.05.065. 393
13. Mendoza, J.A.; Cowan, D.; Liu, Y. Predictors of Children’s Active Commuting to School: An Observational Evaluation in 5 U.S. 394
Communities. J. Phys. Act. Heal. 2014, 11, 729–733, doi:10.1123/jpah.2012-0322. 395
14. Stark, J.; Singleton, P.A.; Uhlmann, T. Exploring Children’s School Travel, Psychological Well-Being, and Travel-Related Atti- 396 tudes: Evidence from Primary and Secondary School Children in Vienna, Austria. Travel Behav. Soc. 2019, 16, 118–130, 397
doi:https://doi.org/10.1016/j.tbs.2019.05.001. 398
15. Fusco, C.; Moola, F.; Faulkner, G.; Buliung, R.; Richichi, V. Toward an Understanding of Children’s Perceptions of Their 399 Transport Geographies: (Non)Active School Travel and Visual Representations of the Built Environment. J. Transp. Geogr. 2012, 400
20, 62–70, doi:10.1016/j.jtrangeo.2011.07.001. 401
16. Kleszczewska, D.; Mazur, J.; Bucksch, J.; Dzielska, A.; Brindley, C.; Michalska, A. Active Transport to School May Reduce Psy- 402 chosomatic Symptoms in School-Aged Children: Data from Nine Countries. Int. J. Environ. Res. Public Health 2020, 17, 1–12, 403
doi:10.3390/ijerph17238709. 404
17. Bastam, M.N.; Mat Yazid, M.R.; Borhan, M.N. School Travel Behavior Research Milestone (1979-2021): A Bibliometric Review 405
Analysis. Int. Trans. J. Eng. 2022, 13, 1–16, doi:10.14456/ITJEMAST.2022.90. 406
18. Aranda-Balboa, M.J.; Huertas-Delgado, F.J.; Herrador-Colmenero, M.; Cardon, G.; Chillón, P. Parental Barriers to Active 407 Transport to School: A Systematic Review. Int. J. Public Health 2020, 65, 87–98, doi:10.1007/s00038-019-01313-1. 408 19. Forsberg, H.; Rutberg, S.; Mikaelsson, K.; Lindqvist, A.-K. It’s about Being the Good Parent: Exploring Attitudes and Beliefs 409 towards Active School Transportation. Int. J. Circumpolar Health 2020, 79, 1798113, doi:10.1080/22423982.2020.1798113. 410 20. Ikeda, E.; Hinckson, E.; Witten, K.; Smith, M. Assessment of Direct and Indirect Associations between Children Active School 411 Travel and Environmental, Household and Child Factors Using Structural Equation Modelling. Int. J. Behav. Nutr. Phys. Act. 412
2019, 16, 32, doi:10.1186/s12966-019-0794-5. 413
21. Mandic, S.; Hopkins, D.; García Bengoechea, E.; Flaherty, C.; Williams, J.; Sloane, L.; Moore, A.; Spence, J.C. Adolescents’ Per- 414 ceptions of Cycling versus Walking to School: Understanding the New Zealand Context. J. Transp. Heal. 2017, 4, 294–304, 415
doi:https://doi.org/10.1016/j.jth.2016.10.007. 416
22. Bauman, A.E.; Reis, R.S.; Sallis, J.F.; Wells, J.C.; Loos, R.J.F.; Martin, B.W. Correlates of Physical Activity: Why Are Some People 417 Physically Active and Others Not? Lancet (London, England) 2012, 380, 258–271, doi:10.1016/S0140-6736(12)60735-1. 418 23. Sallis, J.F.; Bull, F.; Guthold, R.; Heath, G.W.; Inoue, S.; Kelly, P.; Oyeyemi, A.L.; Perez, L.G.; Richards, J.; Hallal, P.C. Progress 419 in Physical Activity over the Olympic Quadrennium. Lancet (London, England) 2016, 388, 1325–1336, doi:10.1016/S0140- 420
6736(16)30581-5. 421
24. Jing, P.; Wang, J.; Chen, L.; Zha, Q. fen Incorporating the Extended Theory of Planned Behavior in a School Travel Mode Choice 422 Model: A Case Study of Shaoxing, China. Transp. Plan. Technol. 2018, 41, 119–137, doi:10.1080/03081060.2018.1407508. 423 25. Stark, J.; Berger, W.J.; Hössinger, R. The Effectiveness of an Intervention to Promote Active Travel Modes in Early Adolescence. 424 Transp. Res. Part F Traffic Psychol. Behav. 2018, 55, 389–402, doi:https://doi.org/10.1016/j.trf.2018.03.017. 425 26. Abrahamse, W.; Steg, L.; Gifford, R.; Vlek, C. Factors Influencing Car Use for Commuting and the Intention to Reduce It: A 426 Question of Self-Interest or Morality? Transp. Res. Part F Traffic Psychol. Behav. 2009, 12, 317–324, 427
doi:https://doi.org/10.1016/j.trf.2009.04.004. 428
27. Zaragoza, J.; Corral, A.; Ikeda, E.; García-Bengoechea, E.; Aibar, A. Assessment of Psychological, Social Cognitive and Perceived 429 Environmental Influences on Children’s Active Transport to School. J. Transp. Heal. 2020, 16, 100839, 430
doi:10.1016/j.jth.2020.100839. 431
28. Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211, 432
doi:https://doi.org/10.1016/0749-5978(91)90020-T. 433
29. Mandic, S.; Hopkins, D.; García Bengoechea, E.; Flaherty, C.; Coppell, K.; Moore, A.; Williams, J.; Spence, J.C. Differences in 434 Parental Perceptions of Walking and Cycling to High School According to Distance. Transp. Res. Part F Traffic Psychol. Behav. 435
2020, 71, 238–249, doi:https://doi.org/10.1016/j.trf.2020.04.013. 436
30. Woldeamanuel, M. Younger Teens’ Mode Choice for School Trips: Do Parents’ Attitudes toward Safety and Traffic Conditions 437 along the School Route Matter? Int. J. Sustain. Transp. 2016, 10, 147–155, doi:10.1080/15568318.2013.871664. 438 31. Rothman, L.; Buliung, R.; To, T.; Macarthur, C.; Macpherson, A.; Howard, A. Associations between Parents Perception of Traffic 439 Danger, the Built Environment and Walking to School. J. Transp. Heal. 2015, 2, 327–335, doi:10.1016/j.jth.2015.05.004. 440 32. Mah, S.K.; Nettlefold, L.; Macdonald, H.M.; Winters, M.; Race, D.; Voss, C.; McKay, H.A. Does Parental Support Influence 441 Children’s Active School Travel? Prev. Med. Reports 2017, 6, 346–351, doi:10.1016/j.pmedr.2017.04.008. 442 33. Ryan, R.; Deci, E. Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. 443
Am. Psychol. 2000, 55, 68–78, doi:10.1037/0003-066X.55.1.68. 444
34. Silva, K.S.; Pizarro, A.N.; Garcia, L.M.T.; Mota, J.; Santos, M.P. Which Social Support and Psychological Factors Are Associated 445 to Active Commuting to School? Prev. Med. (Baltim). 2014, 63, 20–23, doi:https://doi.org/10.1016/j.ypmed.2014.02.019. 446 35. Kinnafick, F.-E.; Thøgersen-Ntoumani, C.; Duda, J.L.; Taylor, I. Sources of Autonomy Support, Subjective Vitality and Physical 447 Activity Behaviour Associated with Participation in a Lunchtime Walking Intervention for Physically Inactive Adults. Psychol. 448 Sport Exerc. 2014, 15, 190–197, doi:https://doi.org/10.1016/j.psychsport.2013.10.009. 449 36. Scheiner, J.; Huber, O.; Lohmüller, S. Children’s Mode Choice for Trips to Primary School: A Case Study in German Suburbia. 450
Travel Behav. Soc. 2019, 15, 15–27, doi:10.1016/j.tbs.2018.09.006. 451
37. Arvidsson, D.; Kawakami, N.; Ohlsson, H.; Sundquist, K. Physical Activity and Concordance between Objective and Perceived 452
Walkability. Med. Sci. Sport. Exerc. 2012, 44. 453
38. Badan Pusat Statistik Kota Palembang Palembang Municipality in Figures 2022; Palembang, 2022; 454 39. Kementerian Pendidikan dan Kebudayaan Jumlah Data Satuan Pendidikan (Sekolah) Per Kabupaten/Kota : Kota Palembang 455 Available online: https://referensi.data.kemdikbud.go.id/index11.php?kode=116000&level=2 (accessed on 12 March 2022). 456 40. Kementerian Pendidikan dan Kebudayaan Jumlah Data Peserta Didik (NISN) Per Kabupaten/Kota : Kota Palembang Available 457 online: https://referensi.data.kemdikbud.go.id/pd_index.php?kode=116000&level=2 (accessed on 28 September 2021). 458
41. Badan Meteorologi Klimatologi dan Geofisika Prakiraan Awal Musim Kemarau/Hujan Available online: 459
https://iklim.bmkg.go.id/ (accessed on 1 April 2022). 460
42. Schmiedel, T.; vom Brocke, J.; Recker, J. Development and Validation of an Instrument to Measure Organizational Cultures’ 461 Support of Business Process Management. Inf. Manag. 2014, 51, 43–56, doi:https://doi.org/10.1016/j.im.2013.08.005. 462 43. Bass, K.M.; Drits-Esser, D.; Stark, L.A. A Primer for Developing Measures of Science Content Knowledge for Small-Scale Re- 463 search and Instructional Use. CBE Life Sci. Educ. 2016, 15, doi:10.1187/cbe.15-07-0142. 464 44. Almutairi, A.F.; Dahinten, V.S. Factor Structure of Almutairi’s Critical Cultural Competence Scale. Adm. Sci. 2017, 7. 465 45. Davis, A.E. Instrument Development: Getting Started. J. Neurosci. Nurs. J. Am. Assoc. Neurosci. Nurses 1996, 28, 204–207, 466
doi:10.1097/01376517-199606000-00009. 467
46. Pang, B.; Rundle-Thiele, S.; Kubacki, K. Can the Theory of Planned Behaviour Explain Walking to and from School among 468 Australian Children? A Social Marketing Formative Research Study. Int. J. Nonprofit Volunt. Sect. Mark. 2018, 23, e1599, 469
doi:https://doi.org/10.1002/nvsm.1599. 470
47. Schuster, L.; Kubacki, K.; Rundle-Thiele, S. A Theoretical Approach to Segmenting Children’s Walking Behaviour. Young Con- 471
sum. 2015, 16, 159–171, doi:10.1108/YC-07-2014-00461. 472
48. Schuster, L.; Kubacki, K.; Rundle-Thiele, S. Understanding Caregivers’ Intentions for Their Child to Walk to School: Further 473 Application of the Theory of Planned Behavior. Health Mark. Q. 2016, 33, 307–320, doi:10.1080/07359683.2016.1240521. 474 49. Bamberg, S.; Ajzen, I.; Schmidt, P. Choice of Travel Mode in the Theory of Planned Behavior: The Roles of Past Behavior, Habit, 475 and Reasoned Action. Basic Appl. Soc. Psych. 2003, 25, 175–187, doi:10.1207/S15324834BASP2503_01. 476 50. Deci, E.L.; Ryan, R.M. Intrinsic Motivation and Self-Determination in Human Behavior; Springer, 1985; 477 51. Ryan, R.M.; Deci, E.L. Self-Determination Theory: Basic Psychological Needs in Motivation, Development, and Wellness.; The 478 Guilford Press: New York, NY, US, 2017; ISBN 978-1-4625-2876-9 (Hardcover); 978-1-4625-2877-6 (PDF). 479 52. B. Owen, K.; Smith, J.; Lubans, D.R.; Ng, J.Y.Y.; Lonsdale, C. Self-Determined Motivation and Physical Activity in Children and 480 Adolescents: A Systematic Review and Meta-Analysis. Prev. Med. (Baltim). 2014, 67, 270–279, doi:https://doi.org/10.1016/j.yp- 481
med.2014.07.033. 482
53. Burgueño, R.; González-Cutre, D.; Sevil-Serrano, J.; Herrador-Colmenero, M.; Segura-Díaz, J.M.; Medina-Casaubón, J.; Chillón, 483 P. Understanding the Motivational Processes Involved in Adolescents’ Active Commuting Behaviour: Development and Vali- 484 dation of the Behavioural Regulation in Active Commuting to and from School (BR-ACS) Questionnaire. Transp. Res. Part F 485 Traffic Psychol. Behav. 2019, 62, 615–625, doi:https://doi.org/10.1016/j.trf.2019.02.016. 486 54. White, R.L.; Parker, P.D.; Lubans, D.R.; MacMillan, F.; Olson, R.; Astell-Burt, T.; Lonsdale, C. Domain-Specific Physical Activity 487 and Affective Wellbeing among Adolescents: An Observational Study of the Moderating Roles of Autonomous and Controlled 488 Motivation. Int. J. Behav. Nutr. Phys. Act. 2018, 15, 87, doi:10.1186/s12966-018-0722-0. 489 55. Uddin, R.; Burton, N.; Khan, A. Perceived Environmental Barriers to Physical Activity in Young Adults in Dhaka City, Bangla- 490
desh—Does Gender Matter? Int. Health 2018, 10, doi:10.1093/inthealth/ihx057. 491
56. Chiang, C.-C.; Chiou, S.-T.; Liao, Y.-M.; Liou, Y.M. The Perceived Neighborhood Environment Is Associated with Health-En- 492 hancing Physical Activity among Adults: A Cross-Sectional Survey of 13 Townships in Taiwan. BMC Public Health 2019, 19, 493
524, doi:10.1186/s12889-019-6848-4. 494
57. Liou, Y.M.; Lee, H.-L.; Chien, L.-Y.; Kao, W.-Y.; Chiang, C.-C.; Wang, D.-Y. Daily-Life Physical Activity and Related Factors 495 Among Patients With Cancer Receiving Chemotherapy in Taiwan. Cancer Nurs. 2011, 34. 496 58. Hsueh, M.-C.; Lin, C.-Y.; Huang, P.-H.; Park, J.-H.; Liao, Y. Cross-Sectional Associations of Environmental Perception with 497 Leisure-Time Physical Activity and Screen Time among Older Adults. J. Clin. Med. 2018, 7. 498 59. Fishbein, M.; Ajzen, I. Predicting and Changing Behavior: The Reasoned Action Approach; Psychology press, 2011; ISBN 499
0203838025. 500
60. Murtagh, S.; Rowe, D.A.; Elliott, M.A.; McMinn, D.; Nelson, N.M. Predicting Active School Travel: The Role of Planned Behavior 501 and Habit Strength. Int. J. Behav. Nutr. Phys. Act. 2012, 9, 65, doi:10.1186/1479-5868-9-65. 502 61. Forsberg, H.; Lindqvist, A.K.; Forward, S.; Nyberg, L.; Rutberg, S. Development and Initial Validation of the PILCAST Ques- 503 tionnaire: Understanding Parents’ Intentions to Let Their Child Cycle or Walk to School. Int. J. Environ. Res. Public Health 2021, 504
18, doi:10.3390/ijerph182111651. 505
62. Banyong, C.; Jomnonkwao, S.; Ratanavaraha, V. Factors Influencing Mode Of Travel To School: A Case Study Of Nakhon 506
Ratchasima. Suranaree J. Sci. Technol. 2020, 27, 1–10. 507
63. Burgueño, R.; González-Cutre, D.; Sevil-Serrano, J.; Herrador-Colmenero, M.; Segura-Díaz, J.M.; Medina-Casaubón, J.; Chillon, 508 P. Validation of the Basic Psychological Need Satisfaction in Active Commuting to and from School (BPNS-ACS) Scale in Span- 509 ish Young People. J. Transp. Heal. 2020, 16, 100825, doi:https://doi.org/10.1016/j.jth.2020.100825. 510 64. Molina-García, J.; Queralt, A.; Estevan, I.; Álvarez, O.; Castillo, I. Barreras Percibidas En El Desplazamiento Activo Al Centro 511 Educativo: Fiabilidad y Validez de Una Escala. Gac. Sanit. 2016, 30, 426–431, doi:https://doi.org/10.1016/j.gaceta.2016.05.006. 512 65. García-Cervantes, L.; Martinez-Gomez, D.; Rodriguez-Romo, G.; Cabanas-Sanchez, V.; Marcos, A.; Veiga, O.L. Reliability and 513 Validity of an Adapted Version of the ALPHA Environmental Questionnaire on Physical Activity in Spanish Youth. Nutr. 514
Hosp. 2014, 30, 1118–1124, doi:10.3305/nh.2014.30.5.7769. 515
66. Spittaels, H.; Verloigne, M.; Gidlow, C.; Gloanec, J.; Titze, S.; Foster, C.; Oppert, J.-M.; Rutter, H.; Oja, P.; Sjöström, M.; et al. 516 Measuring Physical Activity-Related Environmental Factors: Reliability and Predictive Validity of the European Environmental 517 Questionnaire ALPHA. Int. J. Behav. Nutr. Phys. Act. 2010, 7, 48, doi:10.1186/1479-5868-7-48. 518
67. Ajzen, I. The Theory of Planned Behaviour: Reactions and Reflections. Psychol. Health 2011, 26, 1113–1127, 519
doi:10.1080/08870446.2011.613995. 520
68. Rivis, A.; Sheeran, P. Descriptive Norms as an Additional Predictor in the Theory of Planned Behaviour: A Meta-Analysis. Curr. 521
Psychol. 2003, 22, 218–233, doi:10.1007/s12144-003-1018-2. 522
69. Gardner, B. Modelling Motivation and Habit in Stable Travel Mode Contexts. Transp. Res. Part F Traffic Psychol. Behav. 2009, 523
12, 68–76, doi:https://doi.org/10.1016/j.trf.2008.08.001. 524
70. Verplanken, B.; Orbell, S. Reflections on Past Behavior: A Self-Report Index of Habit Strength1. J. Appl. Soc. Psychol. 2003, 33, 525
1313–1330, doi:https://doi.org/10.1111/j.1559-1816.2003.tb01951.x. 526
71. Collins, D. Pretesting Survey Instruments: An Overview of Cognitive Methods. Qual. Life Res. 2003, 12, 229–238, 527
doi:10.1023/A:1023254226592. 528
72. Saw, S.M.; Ng, T.P. The Design and Assessment of Questionnaires in Clinical Research. Singapore Med. J. 2001, 42, 131–135. 529 73. Rodrigues, I.B.; Adachi, J.D.; Beattie, K.A.; MacDermid, J.C. Development and Validation of a New Tool to Measure the Facili- 530 tators, Barriers and Preferences to Exercise in People with Osteoporosis. BMC Musculoskelet. Disord. 2017, 18, 540, 531
doi:10.1186/s12891-017-1914-5. 532
74. Carmines, E.; Zeller, R. Reliability and Validity Assessment 1979. 533
75. Zamanzadeh, V.; Ghahramanian, A.; Rassouli, M.; Abbaszadeh, A.; Alavi-Majd, H.; Nikanfar, A.-R. Design and Implementation 534 Content Validity Study: Development of an Instrument for Measuring Patient-Centered Communication. J. caring Sci. 2015, 535
4, 165–178, doi:10.15171/jcs.2015.017. 536
76. Shi, J.; Mo, X.; Sun, Z. Content Validity Index in Scale Development. Zhong Nan Da Xue Xue Bao. Yi Xue Ban 2012, 37, 152–155, 537
doi:10.3969/j.issn.1672-7347.2012.02.007. 538
77. In, J. Introduction of a Pilot Study. Korean J. Anesthesiol. 2017, 70, 601–605, doi:10.4097/kjae.2017.70.6.601. 539 78. Arnold, D.M.; Burns, K.E.A.; Adhikari, N.K.J.; Kho, M.E.; Meade, M.O.; Cook, D.J. The Design and Interpretation of Pilot Trials 540 in Clinical Research in Critical Care. Crit. Care Med. 2009, 37, S69-74, doi:10.1097/CCM.0b013e3181920e33. 541 79. Thabane, L.; Ma, J.; Chu, R.; Cheng, J.; Ismaila, A.; Rios, L.P.; Robson, R.; Thabane, M.; Giangregorio, L.; Goldsmith, C.H. A 542 Tutorial on Pilot Studies: The What, Why and How. BMC Med. Res. Methodol. 2010, 10, 1, doi:10.1186/1471-2288-10-1. 543 80. Flight, L.; Julious, S.A. Practical Guide to Sample Size Calculations: An Introduction. Pharm. Stat. 2016, 15, 68–74, 544
doi:10.1002/pst.1709. 545
81. Smith, L.J.; Harrison, M.B. Framework for Planning and Conducting Pilot Studies. Ostomy. Wound. Manage. 2009, 55, 34–48. 546 82. Polit, D.F.; Beck, C.T.; Hungler, B.P. Essentials of Nursing Research: Methods, Appraisal, and Utilization; Lippincott, 2001; ISBN 547
9780781725576. 548
83. Polit-O’Hara, D.; Polit, D.F.; Hungler, B.P. Nursing Research: Principles and Methods; Nursing Research: Principles and Meth- 549
ods; Lippincott, 1999; ISBN 9780781715621. 550
84. Julious, S.A. Sample Size of 12 per Group Rule of Thumb for a Pilot Study. Pharm. Stat. 2005, 4, 287–291, 551
doi:https://doi.org/10.1002/pst.185. 552
85. Browne, R.H. On the Use of a Pilot Sample for Sample Size Determination. Stat. Med. 1995, 14, 1933–1940, 553
doi:10.1002/sim.4780141709. 554
86. Hair, J.F.; Money, A.H.; Samouel, P.; Babin, B. Essentials of Business Research Methods; Wiley, 2003; ISBN 9780471271369. 555 87. Lynn, M.R. Determination and Quantification of Content Validity. Nurs. Res. 1986, 35, 382–385. 556