研究背景：
足量身體活動可預防許多慢性疾病，已被世界衛生組織列為重要的健康行為之一。大學階段為個人健康行為發展定型的關鍵時期，及早培養足量身體活動習慣有助降低成人期罹患慢性病之風險。現今促進大學生身體活動多為個人方案之策略，以網站社交媒體搭配身體活動監測器(如計步器或加速器)為主，成效驗證多檢測步數的多寡。然而環境是人活動的空間，為重要因素，若能將校園環境納為大學生促進身體活動之一環，並以激發達中高等身體活動強度的行為為目標，進而促進心肺適能之健康成效。如何設計此等健康促進方案與策略，將是校園健康專業人員的一大挑戰。

研究目的：
本研究主要探討結合校園環境健走地圖之兩種不同策略促進中高強度身體活動方案，在執行一周後可達到以下相關指標效能的差異：(1)達足量身體活動比率；(2)足量身體活動者其中等強度身體活動之累積時間；(3)足量身體活動者其費力身體活動之累積時間；(4)足量身體活動者執行方案一周前後心肺耐力(體力指數)之變化。

研究方法：
(一)研究設計：可行性研究。
(二)研究對象：研究場域為南部某大學校園，對象為該校之大學生。
(三)研究架構：依據邏輯模式，輸入、過程、輸出及結果為方案發展架構與依循步驟。
(四)研究過程：(1)輸入-需求評估：評估相關政策與資源，以了解發展健走地圖與促進身體活動相關策略所需的軟硬體資源；(2)過程-方案發展：透過「校園健走環境評分表」評估校園環境健走路線，建置健走地圖，提供社會認知理論為策略發展依據，由學生討論並設計促進身體活動相關策略；(3)輸出-方案產出：產出健走地圖與促進身體活動相關策略之兩種方案；(4)結果-方案測試：共招募86名大學生(方案一：小雞養成 46人；方案二：Out Walking 40人)。
(五)成效指標：透過分別執行兩種方案一周，並評價其達到足量身體活動比率、達足量身體活動者其活動強度之差異與體力指數的變化。
(六)研究工具：(1)測量身體活動程度依方案有不同，方案一為免費手機應用程式Pacer，方案二為本研究所發展之手機應用程式Out Walking；(2)體力指數為透過測量心肺耐力三分鐘登階測驗計算得之。
(七)統計分析：資料分析以百分比、平均值及標準差描述資料特徵，進一步以獨立樣本t檢定、卡方檢定與共變數分析，比較本研究所發展出的兩種方案執行一周後，對中高強度身體活動促進效能之差異。

研究結果：
兩種方案執行一周後，對促進身體活動與體力指數有以下的結果：足量身體活動比率，以方案二達80%顯著高於方案一的45.7%；在足量身體活動者達中等強度身體活動，平均每人一周累積時間以方案一215.6分鐘顯著高於方案二11.6分鐘；而足量身體活動者達費力身體活動，平均每人一周累積時間以方案二191.4分鐘顯著高於方案一28.1分鐘；足量身體活動者對心肺耐力健康效果，以方案二之體力指數前後測進步11.36分顯著高於方案一的2.74分，且體力指數以達全國常模排名前40百分位數為達標分類，方案二後測達標或前後維持達標者有65.6%，顯著高於方案一的52.4%。

結論：
本研究發展兩種促進中高強度身體活動方案，經執行一周的測試，其中方案二 「Out Walking」比方案一「小雞養成」，可明顯促進該組參與者一周之高強度身體活動累積時間及心肺功能之效能。而方案一「小雞養成」則促進中等強度身體活動累積時間。Out Walking乃結合校園健走環境與網路社交平台，應用社會認知理論來設計APP，其功能具身體活動目標、提供即時回饋健走資訊與即時獎勵特點，透過遊戲過程，促進健走動機，以達中高等強度活動與心肺適能之健康成效。建議未來仍需透過實驗性研究驗證Out Walking方案促進中高強度身體活動之成效。進一步亦可推廣至其他年齡族群參與者，以及其他場域如社區，擴大驗證其應用成效。

This feasibility study was to test the effects of two newly developed internet-based programs on promoting higher levels of physical activity (PA). This study was under the logic model to develop two internet-based programs, combined with walking maps, hypothesized the two programs can promote moderate PA (MPA) or vigorous PA (VPA). The strategies of the two programs based on social cognitive theory were designed by 90 college-students in a health promotion class. Further, 86 college-students were invited to participate in the programs for 7-days, 46 of which applied for the free App program and 40 applied for the outwalking program to test the effects of two programs in promoting PA.Outcome measures included PA and cardiovascular fitness levels. The PA were respectively measured for two programs' participants by using its device including the free application (Apps) and the outwalking Apps. Chi-square test, t-test and ANCOVA were used to test the outcome measurements. Results show that participants using the outwalking program were more effective than those using the free app program achieving sufficient levels of PA weekly. Among those participants with sufficient levels of PA, the effects of achieving cumulated time of VPA for 7-days and cardiorespiratory fitness in the outwalking program was significantly higher than in the free Apps program. However, participants in the free Apps program had significantly longer MPA accumulation than participants in the outwalking program. This is a feasibility study; thus, an experimental study should be applied to examine the effectiveness of promoting PA in the future.

內政部營建署(2018，11月)．都市人本交通道路規劃設計手冊(第二版)。
https://myway.cpami.gov.tw/wiki/wikimain
林建得、陳坤檸、洪睿聲（2004）。登階測驗與身體組成預測最大攝氧量。台灣醫學，
8(2)，175-183。https://doi.org/10.6320/FJM.2004.8(2).03
國民健康署(2017，11月)．全民身體活動指引。https://www.hpa.gov.tw/Pages/EBo
ok.aspx?nodeid=1411
國民健康署(2021，11月)．促進健康體能的方法https://www.hpa.gov.tw/Pages/Det
ail.aspx?nodeid=571&pid=882
國民健康署(2019，9月)．運動不足已成全球第四大致死因素。https://www.hpa.gov.
tw/Pages/Detail.aspx?nodeid=1132&pid=2473
教育部體育署(2022)．心肺耐力。https://www.fitness.org.tw/direct02.php
教育部體育署(2022)．體適能常模心肺耐力。https://www.fitness.org.tw/model07.
php
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and
Human Decision Processes,50, 179–211.
Bandura, A.(1995)．社會學習理論(周曉虹譯)．桂冠。
Bandura, A. (1977). Social learning theory. Englewood Cliffs. Prentice-Hall.
Choi, J., Lee, M., Lee, J. K., Kang, D., & Choi, J. Y. (2017). Correlates associated
with participation in physical activity among adults: a systematic review of
reviews and update. BMC public health, 17(1), 356.
https://doi.org/10.1186/s12889-017-4255-2
DeVitis, Celia; Beddoes, Zack; Sazama, Debra; Hepler, Teresa.(2020). The
Influence of Posting Physical Activity Posts to Social Networking Sites on
Young Adults' Physical Activity Engagement and Motivational Profiles.
Physical Educator,77(3),595-614.https://doi.org/10.18666/TPE-2020-V77-I3-
9630
Deci, E. L., & Ryan, R. M. (2012). Self-determination theory. In P. A. M. Van Lange,
A. W. Kruglanski, & E. T. Higgins (Eds.), Handbook of theories of social
psychology (pp. 416–436). Sage Publications Ltd.
https://doi.org/10.4135/9781446249215.n21
Das, B. M., Petruzzello, S. J., & Ryan, K. E. (2014). Development of a logic model for
a physical activity-based employee wellness program for mass transit
workers. Preventing chronic disease, 11,E123.
https://doi.org/10.5888/pcd11.140124
Guthold, R., Stevens, G. A., Riley, L. M., & Bull, F. C. (2018). Worldwide trends in
insufficient physical activity from 2001 to 2016: a pooled analysis of 358
population-based surveys with 1·9 million participants. The Lancet. Global
health, 6(10), e1077–e1086. https://doi.org/10.1016/S2214-109X(18)30357-7
Huhman, M., Heitzler, C., & Wong, F. (2004). The VERB™ campaign logic model:
A tool for planning and evaluation. Preventing chronic disease, 1(3).
Horacek, T. M., Dede Yildirim, E., Kattelmann, K., Brown, O., Byrd-Bredbenner, C.,
Colby, S., ... & White, A. (2018). Path analysis of campus walkability/bikeability
and college students’ physical activity attitudes, behaviors, and body mass
index. American Journal of Health Promotion, 32(3), 578-586.
West, J. F.(2014).Public health program planning logic model for community
engaged Type 2 diabetes management and prevention.Evaluation and
Program Planning,42,43-49.https://doi.org/10.1016/j.evalprogplan.2013.09.
001
Lamit, Hasanuddin & Shafaghat, Arezou & Abd Majid, Muhd.Zaimi & Keyvanfar,
Ali & Ahmad, Mohd & Ahmad, Bin & Malik, Tahir & Mohamad zin, Rosli &
Yadollahi, Mohammadreza. (2013). Application of the Path Walkability Index
(Pawdex) Model: A Case Study of Retail Walking Pattern Recognition in
Taman University Skudai, Johor, Malaysia. Advanced Science Letters. 19.
3021-3024. https://doi.org/10.1166/asl.2013.5067.
Ken-Opurum, J., Darbishire, L., Miller, D. K., & Savaiano, D. (2020). Assessing
Rural Health Coalitions Using the Public Health Logic Model: A Systematic
Review. American journal of preventive medicine, 58(6), 864–878.
https://doi.org/10.1016/j.amepre.2020.01.015
McAlister, A. L., Perry, C. L., & Parcel, G. S. (2008). How individuals, environments,
and health behaviors interact: Social cognitive theory. In Health behavior
and health education: Theory, research, and practice, 4th ed. (pp. 169-188).
Jossey-Bass.
Moudon, Anne & Lee, Chanam. (2003). Walking and Bicycling: An Evaluation of
Environmental Audit Instruments. American journal of health promotion :
AJHP. 18. 21-37. https://doi.org/10.4278/0890-1171-18.1.21.
Mandic, D., Bjegovic-Mikanovic, V., Vukovic, D., Djikanovic, B., Stamenkovic, Z., &
Lalic, N. (2020). Successful promotion of physical activity among students of
medicine through motivational interview and Web-based intervention.
PeerJ, 8.https://doi.org/10.7717/peerj.9495
Mo, D., Xiang, M., Luo, M., Dong, Y., Fang, Y., Zhang, S., Zhang, Z., & Liang, H.
(2019). Using Gamification and Social Incentives to Increase Physical Activity
and Related Social Cognition among Undergraduate Students in Shanghai,
China. International journal of environmental research and public health,
16(5), 858. https://doi.org/10.3390/ijerph16050858
Marta Miragall, Alejandro Dominguez-Rodriguez, Jessica Navarro, Ausias Cebolla
& Rosa M. Banos (2018) Increasing physical activity through an Internet-
based motivational intervention supported by pedometers in a sample of
sedentary students: A randomised controlled trial, Psychology & Health, 33:4,
465-482. https://doi.org/10.1080/08870446.2017.1368511
Magoc, Dejan & Tomaka, Joe & Bridges-Arzaga, Amber. (2011). Using the Web to
Increase Physical Activity in College Students.American journal of health
behavior.35(2):142-54.https://doi.org/35. 142-54. 10.5993/AJHB.35.2.2.
Medrano-Urena, M., Ortega-Ruiz, R., & Benítez-Sillero, J. D. (2020). Physical
Fitness, Exercise Self-Efficacy, and Quality of Life in Adulthood: A Systematic
Review. International journal of environmental research and public health,
17(17), 6343. https://doi.org/10.3390/ijerph17176343
Nelson, M. C., Story, M., Larson, N. I., Neumark-Sztainer, D., & Lytle, L. A. (2008).
Emerging adulthood and college-aged youth: an overlooked age for
weight-related behavior change. Obesity (Silver Spring, Md.), 16(10), 2205–
2211. https://doi.org/10.1038/oby.2008.365
Ornes, L.L., & Ransdell, L. (2007). Web-Based Physical Activity Intervention for
College-Aged Women. The international electronic journal of health
education, 10, 126-137.https://doi.org/10.5993/ajhb.34.1.8.
Piercy KL, Troiano RP, Ballard RM, et al.(2018).The Physical Activity Guidelines for
Americans. JAMA.,320(19),2020–2028. https://doi.org/ 10.1001/jama.2018.
14854
Pope, Z. C., Barr-Anderson, D. J., Lewis, B. A., Pereira, M. A., & Gao, Z. (2019). Use
of Wearable Technology and Social Media to Improve Physical Activity and
Dietary Behaviors among College Students: A 12-Week Randomized Pilot
Study. International journal of environmental research and public health,
16(19), 3579. https://doi.org/10.3390/ijerph16193579
Pope, Zachary & Gao, Zan. (2020). Feasibility of smartphone application- and
social media-based intervention on college students’ health outcomes: A
pilot randomized trial. Journal of American College Health. 1-10.
https://doi.org/10.1080/07448481.2020.1726925.
Pender NJ. Heath Promotion Model Manual. Michigan, United State: University of
ichigan;2011.https://deepblue.lib.umich.edu/bitstream/handle/2027.42/853
50/HEALTH_PROMOTION_MANUAL_Rev_5-2011.pdf.
Prochaska, J. O., & DiClemente, C. C. (1983). Stages and processes of self-
change of smoking: Toward an integrative model of change. Journal of
Consulting and Clinical Psychology, 51(3), 390–395.
https://doi.org/10.1037/0022-006X.51.3.390
Sabooteh, S., Feizi, A., Shekarchizadeh, P. et al. Designing and evaluation of E-
health educational intervention on students’ physical activity: an
application of Pender’s health promotion model. BMC Public Health 21, 657
(2021). https://doi.org/10.1186/s12889-021-10641-y
Sriramatr, S., Berry, T. R., & Spence, J. C. (2014). An Internet-based intervention
for promoting and maintaining physical activity: a randomized controlled
trial. American journal of health behavior, 38(3), 430–439.
https://doi.org/10.5993/ajhb.38.3.12
Taylor, W. C., Das, B. M., Paxton, R. J., Shegog, R., Suminski, R. R., Johnson, S. R.,
Akintola, O. A., Hammad, A., & Guidry, M. K. (2020). Development and
implementation of a logic model: Occupational stress, physical activity, and
sedentary behavior in the workplace. Work (Reading, Mass.), 67(1), 203–213.
https://doi.org/10.3233/WOR-203266
World Health Organization.(2020, December 26). Physical activity. https://www.
who.int/news-room/fact-sheets/detail/physical-activity
Walsh, J. C., Corbett, T., Hogan, M., Duggan, J., & McNamara, A. (2016). An
mHealth Intervention Using a Smartphone App to Increase Walking Behavior
in Young Adults: A Pilot Study. JMIR mHealth and uHealth, 4(3), e109.
https://doi.org/10.2196/mhealth.5227
W.K. Kellogg Foundation(2004).Logic Model Development Guide.https://www.w
kkf.org/resource-directory/resources/2004/01/logic-model-development-
guide
Wadsworth, D. D., & Hallam, J. S. (2010). Effect of a web site intervention on
physical activity of college females. American journal of health behavior,
34(1), 60–69. https://doi.org/10.5993/ajhb.34.1.8
Zapata-Diomedi, B., & Veerman, J. L. (2016). The association between built
environment features and physical activity in the Australian context: a
synthesis of the literature. BMC public health, 16, 484.
https://doi.org/10.1186/s12889-016-3154-2