Analyzing Older Adults’ Perceived Values of Using Smart Bracelets by Means–End Chain
Abstract
:1. Introduction
2. Literature Review
2.1. Demand for Mobile Health Devices in an Aging Society
2.2. Mobile Health Devices
2.3. Value
2.4. Means–End Chains (MECs)
3. Research Methods
3.1. Data Collection
3.2. Data Analysis
- Intercoder agreement:
- 2.
- Compound reliability:
4. Research Results
4.1. Description of the Interview Sample
4.2. Reliability of Interview Data and Intercoder Agreement
4.2.1. Coding Results
4.2.2. Reliability and Intercoder Agreement
4.2.3. Definitions of Attributes, Consequences, and Values
4.2.4. Implication Matrix
4.2.5. Creating the Hierarchical Value Map
4.3. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Chen, C.Y. Probing the Technology Acceptance for Older Adults: A Case Study on Southern Part of Taiwan. J. Kun Shan Univ. 2015, 10, 132–144. [Google Scholar]
- Lin, C.S.; Jeng, M.Y.; Yeh, T.M. The elderly perceived meanings and values of virtual reality leisure activities: A means-end chain approach. Int. J. Environ. Res. Public Health 2018, 15, 663. [Google Scholar] [CrossRef] [Green Version]
- Wang, B.J.; Wu, W.Z.; Sun, C. A Study on the Acceptance of Care Robots by the Elderly via Unified Theory of Acceptance and Use of Technology. J. Gerontechnol. Serv. Manag. 2017, 5, 109–120. [Google Scholar] [CrossRef]
- United Nations Department of Economic and Social Affairs. World Population Prospects 2019: Release Note; Population Division, United Nations Department of Economic and Social Affairs: New York, NY, USA, 2019. [Google Scholar]
- Ho, H.H.; Wang, L.T.; Chang, S.H. Use of a technology acceptance model to explore the smart phone exercise application needs of middle-aged and older adults. J. Gerontechnol. Serv. Manag. 2020, 8, 137–147. [Google Scholar] [CrossRef]
- Jeng, M.Y.; Pai, F.Y.; Yeh, T.M. The virtual reality leisure activities experience on elderly people. Appl. Res. Qual. Life 2017, 12, 49–65. [Google Scholar] [CrossRef]
- Helbostad, J.L.; Vereijken, B.; Becker, C.; Todd, C.; Taraldsen, K.; Pijnappels, M.; Aminian, K.; Mellone, S. Mobile health applications to promote active and healthy ageing. Sensors 2017, 17, 622. [Google Scholar] [CrossRef] [PubMed]
- Fang, Y.M.; Chang, C.C. Users’ psychological perception and perceived readability of wearable devices for elderly people. J. Behav. Inf. Technol. 2016, 35, 225–232. [Google Scholar] [CrossRef]
- Hsu, C.J.; Lin, C.C. Evaluation of the Effects of Situational Somatosensory Games on Balance in the Older Adults. J. Gerontechnol. Serv. Manag. 2020, 8, 193–206. [Google Scholar] [CrossRef]
- Hallal, P.C.; Andersen, L.B.; Bull, F.C. Global physical activity levels: Surveillance progress. Lancet 2012, 380, 247–257. [Google Scholar] [CrossRef]
- Olesen, K.R.; Rod, N.H.; Madsen, I.E.H.; Bonde, J.P.; Rugulies, R. Does retirement reduce the risk of mental disorders? A national registry-linkage study of treatment for mental disorders before and after retirement of Danish residents. Occup. Environ. Med. 2015, 72, 366–372. [Google Scholar] [CrossRef] [Green Version]
- Boulos, M.N.K.; Wheeler, S.; Tavares, C.; Jones, R. How smartphones are changing the face of mobile and participatory healthcare: An overview, with example from eCAALYX. Biomed. Eng. Online 2011, 10, 24. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lai, H.J. Factors Affecting Older Adult Learners’ Usage of Digital Game-Based Learning. J. Gerontechnol. Serv. Manag. 2020, 8, 58–71. [Google Scholar] [CrossRef]
- Wang, Z.H.; Yang, Z.H.; Dong, T. A review of wearable technologies for elderly care that can accurately track indoor position, recognize physical activities and monitor vital signs in real time. Sensors 2017, 17, 341. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kekade, S.; Hseieh, C.H.; Islam, M.M.; Atique, S.; Khalfan, M.K.; Li, Y.C.; Abdul, S.S. The usefulness and actual use of wearable devices among the elderly population. Comput. Methods Progr. Biomed. 2018, 153, 137–159. [Google Scholar] [CrossRef]
- Spagnolli, A.; Guardigli, E.; Orso, V.; Varotto, A.; Gamberini, L. Measuring user acceptance of wearable symbiotic devices: Validation study across application scenarios. In Proceedings of the International Workshop on Symbiotic Interaction, Helsinki, Finland, 30–31 October 2014. [Google Scholar]
- Chuang, H.F. Factors influencing behavioral intention of wearable symbiotic devices—Case study of the mi band. Soochow J. Econ. Bus. 2016, 93, 1–24. [Google Scholar]
- Chiu, C.J.; Hu, Y.H.; Lin, D.C.; Chang, F.Y.; Chang, C.S.; Lai, C.F. The attitudes, impact, and learning needs of older adults using apps on touchscreen mobile devices: Results from a pilot study. Comput. Hum. Behav. 2016, 63, 189–197. [Google Scholar] [CrossRef]
- Levine, D.M.; Lipsitz, S.R.; Linder, J.A. Trends in seniors’ use of digital health technology in the United States, 2011–2014. J. Am. Med. Assoc. 2016, 316, 538–540. [Google Scholar] [CrossRef] [Green Version]
- Nie, N.H.; Hillygus, D.S. The impact of internet use on sociability: Time-diary findings. IT Soc. 2002, 1, 1–20. [Google Scholar]
- Nyman, A.; Isaksson, G. Togetherness in another way: Internet as a tool for togetherness in everyday occupations among older adults. Scand. J. Occup. Ther. 2015, 5, 387–393. [Google Scholar] [CrossRef]
- Shieh, M.D.; Hsiao, H.C.; Lin, Y.H.; Lin, J.Y. A study of the elderly people’s perception of wearable device forms. J. Interdiscip. Math. 2017, 20, 789–804. [Google Scholar] [CrossRef]
- Smith, A. Older Adults and Technology Use; Pew Research Center: Washington, DC, USA, 2014. [Google Scholar]
- Green, M.; Rossall, P. Digital Inclusion Evidence Report; Age UK: London, UK, 2013. [Google Scholar]
- Hofstede, F.T.; Audenaert, A.; Steenkamp, J.E.M.; Wedel, M. An investigation in to the association pattern technique as a quantitative approach to means-end chains. Int. J. Res. Mark. 1998, 15, 37–50. [Google Scholar] [CrossRef]
- Bruijink, A.W.; Viser, B.J.; Marshall, L. Medical apps for smartphones: Lack of evidence undermines quality and safety. Evid. Based Med. 2015, 18, 90–92. [Google Scholar] [CrossRef] [PubMed]
- Quinn, C.C.; Shardell, M.D.; Terrin, M.L.; Barr, E.A.; Ballew, S.H.; Gruber-Baldini, A.L. Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care 2011, 34, 1934–1942. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bexelius, C.; Lof, M.; Sandin, S.; Lagerros, Y.T.; Forsum, E.; Litton, J.E. Measures of physical activity using cell phones: Validation using criterion methods. J. Med. Internet Res. 2010, 12, e2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Carrasco, M.P.; Salvador, C.H.; Sagredo, P.G.; Márquez-Montes, J.; González de Mingo, M.A.; Fragua, J.A.; Rodríguez, M.C.; García-Olmos, L.M.; García-López, F.; Carrero, A.M. Impact of patient-general practitioner short-messages-based interaction on the control of hypertension in a follow-up service for low-to-medium risk hypertensive patients: A randomized controlled trial. IEEE Trans. Inf. Technol. Biomed. 2008, 12, 780–791. [Google Scholar] [CrossRef] [PubMed]
- Burke, L.E.; Conroy, M.B.; Sereika, S.M.; Elci, O.U.; Styn, M.A.; Acharya, S.D.; Sevick, M.A.; Ewing, L.J.; Glanz, K. The effect of electronic self-monitoring on weight loss and dietary intake: A randomized behavioral weight loss trial. Obesity 2011, 19, 338–344. [Google Scholar] [CrossRef] [PubMed]
- Schoeppe, S.; Alley, S.; Van Lippevelde, W.; Bray, N.A.; Williams, S.L.; Duncan, M.J.; Vandelanotte, C. Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: A systematic review. Int. J. Behav. Nutr. Phys. Act. 2016, 13, 127. [Google Scholar] [CrossRef] [Green Version]
- King, A.C.; Hekler, E.B.; Grieco, L.A.; Winter, S.J.; Sheats, J.L.; Buman, M.P.; Banerjee, B.; Robinsom, T.N.; Cirimele, J. Effects of three motivationally targeted mobile device applications on initial physical activity and sedentary behavior change in midlife and older adults: A randomized trial. PLoS ONE 2016, 11, e0160113. [Google Scholar] [CrossRef]
- Woodall, T. Conceptualizing value for the customer: An attributional structural and dispositional analysis. Acad. Mark. Sci. Rev. Vanc. 2003, 27, 1–23. [Google Scholar]
- Nasution, H.N.; Mavondo, F.T. Customer value in the hotel industry: What managers believe they deliver and what customer experience. Int. J. Hosp. Manag. 2008, 27, 204–213. [Google Scholar] [CrossRef]
- Gallarza, M.G.; Saura, I.G. Value dimension, perceived value, satisfaction and loyalty: An investigation of university students. Travel Behav. Tour. Manag. 2006, 27, 437–452. [Google Scholar] [CrossRef]
- Gutman, J. Means-end chains as goal hierarchies. Psychol. Mark. 1997, 14, 545–560. [Google Scholar] [CrossRef]
- Tey, Y.S.; Arsil, P.; Brindal, M.; Teoh, C.T.; Lim, H.W. Motivations underlying consumers’ preference for farmers’ markets in klang valley: A means-end chain approach. Sustainability 2017, 9, 1958. [Google Scholar] [CrossRef] [Green Version]
- Lin, C.F.; Fu, C.S.; Chen, Y.T. Exploring customer perceptions toward different service volumes: An integration of means–end chain and balance theories. Food Qual. Prefer. 2019, 73, 86–96. [Google Scholar] [CrossRef]
- Lin, C.F.; Fu, C.S. Cognitive implications of experiencing religious tourism: An integrated approach of means–end chain and social network theories. Int. J. Tour. Res. 2020, 22, 71–75. [Google Scholar] [CrossRef]
- Reynolds, T.J.; Dethloff, C.; Westberg, S.J. Advancements in Laddering, Understanding Consumer Decision Making: The Means-End Approach to Marketing and Advertising Strategy; Lawrence Erlbaum Associates: New York, NY, USA, 2001. [Google Scholar]
- Peter, A.P.; Olson, J.C. Consumer Behavior and Marketing Strategy; Mcgraw-Hill/Irwin: Chicago, IL, USA, 1999. [Google Scholar]
- Arsil, P.; Li, E.; Bruwer, J. Using means-end chain analysis to reveal consumers’ motivation for buying local foods: An exploratory study. Gadjah Mada Int. J. Bus. 2016, 18, 285–300. [Google Scholar] [CrossRef] [Green Version]
- Reynolds, T.J.; Gutman, J. Laddering theory, method, analysis and interpretation. J. Advert. Res. 1988, 28, 11–31. [Google Scholar] [CrossRef]
- Hinkle, D. The Change of Personal Constructs from the Viewpoint of Theory of Construct Implications. Ph.D. Thesis, Ohio State University, Athens, OH, USA, 1965. Unpublished. [Google Scholar]
- Grunert, K.G.; Grunert, S.C. Measuring subjective meaning structures by the laddering method. Theoretical considerations and methodological problems. Int. J. Res. Mark. 1995, 12, 209–225. [Google Scholar] [CrossRef]
- Costa, A.I.A.; Dekker, M.; Jongen, W.M.F. An overview of means-end theory: Potential application in consumer-oriented food product design. Trends Food Sci. Technol. 2004, 15, 403–415. [Google Scholar] [CrossRef]
- Vriens, M.; Hofstede, F.T. Linking attributes, benefits, and consumer values. Mark. Res. 2000, 12, 4–10. [Google Scholar]
- Russell, C.G.; Flight, I.; Leppard, P.; Van Lawick, V.P.; Syrette, J.A.; Cox, D.N. A comparison of paper-and-pencil and computerized methods of hard laddering. Food Qual. Prefer. 2004, 15, 279–291. [Google Scholar] [CrossRef]
- Pieters, R.; Baumgartner, H.; Allen, D. A means-end chain approach to consumer goal structures. Int. J. Res. Mark. 1995, 12, 227–244. [Google Scholar] [CrossRef] [Green Version]
- Ho, C.I.; Chen, H.M.; Hung, S.C. Understanding the factors influencing family travel product purchasing: Using the means-end approach. Mark. Rev. 2013, 10, 323–344. [Google Scholar]
- Berelson, B. Content Analysis in Communication Research; Free Press: Glencoe, IL, USA, 1952. [Google Scholar]
- Budd, R.W.; Thorp, R.K.; Donohew, L. Content Analysis of Communications; Macmillan: New York, NY, USA, 1967. [Google Scholar]
- Kassarjian, H.H. Content analysis in consumer research. J. Consum. Res. 1977, 4, 8–18. [Google Scholar] [CrossRef]
- Fotopoulos, C.; Krystallis, A.; Ness, C. Wine produced by organic grapes in Greece: Using means-end chains analysis to reveal organic buyers’ purchasing motives in comparison to the non-buyers. Food Qual. Prefer. 2003, 14, 549–566. [Google Scholar] [CrossRef]
- Holzinger, A.; Searle, G.; Nischelwitzer, A. On some aspects of improving mobile applications for the elderly. In Universal Access in HCI, Part I; Stephanidis, C., Ed.; Springer: Berlin/Heidelberg, Germany, 2007; pp. 923–932. [Google Scholar] [CrossRef]
- Hawley-Hague, H.; Boulton, E.; Hall, A.; Pfeiffer, K.; Todd, C. Older adults’ perceptions of technologies aimed at falls prevention, detection or monitoring: A systematic review. Int. J. Med. Inform. 2014, 83, 416–426. [Google Scholar] [CrossRef]
- King, A.C.; Hekler, E.B.; Grieco, L.A.; Winter, S.J.; Sheats, J.L.; Buman, M.P.; Banerjee, B.; Robinson, T.N.; Cirimele, J. Harnessing Different Motivational Frames via Mobile Phones to Promote Daily Physical Activity and Reduce Sedentary Behavior in Aging Adults. PLoS ONE 2013, 8, e62613. [Google Scholar] [CrossRef] [Green Version]
- Yardley, L.; Kirby, S.; Ben-Shlomo, Y.; Gilbert, R.; Whitehead, S.; Todd, C. How likely are older people to take up different falls prevention activities? Prev. Med. 2008, 47, 554–558. [Google Scholar] [CrossRef]
- Davos, P.; Jou, A.M.; De Waele, G.; Petrovic, M. Design for personallized mobile health applications for enhanced older people participation. Eur. Geriatr. Med. 2015, 6, 593–597. [Google Scholar] [CrossRef]
- Routasalo, P.E.; Savikko, N.; Tilvis, R.S.; Strandberg, T.E.; Pitkälä, K.H. Social contacts and their relationship to loneliness among aged people—A population-based study. Gerontology 2006, 52, 181–187. [Google Scholar] [CrossRef]
- Arthanat, S.; Vroman, K.G.; Lysack, C. Home-based individualized information communication technology training program for older adults: A demonstration of effectiveness and value. Disabil. Rehabil. Assist. Technol. 2016, 11, 316–324. [Google Scholar] [CrossRef] [PubMed]
- Mehra, S.; Visser, S.; Dadema, T.; Helder, J.D.; Engellert, R.H.; Weijs, P.J.; Krise, B.J. Translating behavior change principles into a blended exercise intervention for older adults: Design study. JMIR Res. Protoc. 2018, 7, e117. [Google Scholar] [CrossRef] [PubMed]
Type | Item | Number of People | Percentage |
---|---|---|---|
Sex | Male | 24 | 60% |
Female | 16 | 40% | |
Age | 60–65 | 6 | 15% |
66–70 | 24 | 60% | |
71–75 | 6 | 15% | |
Over 76 | 4 | 10% | |
Level of education | Elementary school | 2 | 5% |
Junior high school | 6 | 15% | |
Senior high school and vocational | 16 | 40% | |
Junior college or above | 16 | 40% | |
Occupation | Military and government personnel | 8 | 20% |
Service industry | 4 | 10% | |
Manufacturing industry | 10 | 25% | |
Retirees | 18 | 45% | |
Monthly disposable income | NT$20,000 or less | 6 | 15% |
NT$20,001–NT$40,000 | 14 | 35% | |
NT$40,001–NT$60,000 | 14 | 35% | |
More than NT$60,001 | 6 | 15% | |
Housing situation | Living with spouse | 12 | 30% |
Living with family members | 24 | 60% | |
Living alone | 2 | 5% | |
Other | 2 | 5% |
Name of Factor | Definition of Factor | Content |
---|---|---|
1. Real-time information feedback | Real-time display of data | Steps, sleep quality, heartbeat, heart rate, calories burned |
2. Safe use | Device is not harmful to the body | Radiation, battery, usage method |
3. Comfortable wear | Device does not cause feelings of constraint when worn | Made from soft materials, small size |
4. Clear screen | The bracelet screen is clear | Color, symbols, font size |
5. Correct data | Monitoring data accuracy | Heartbeat, calories burned, sleep quality |
6. Cheap price | Long-term use represents excellent value | Low failure rate, many functions |
7. Learning about smart products | Understanding the significance of smart products in health education | Experience of different functions |
8. Understanding technology applications | Understanding the impact of technology on health | Health, food, travel, housing, and recreation |
9. Increased health awareness | Understanding physical conditions and how to prevent decline | Exercise motivation, health monitoring |
10. Relaxation | Eliminating fatigue, causing a relaxed feeling | Physical and mental relaxation |
11. Satisfying curiosity | Being driven to explore new technologies | Curiosity, stimulation of creativity |
12. Healthier bodies | Having balance in mind and body, living longer | In good spirits, in good health |
13. Improved quality of life | Living comfortably, having fun, achieving goals | Happy, joyful, satisfied |
14. A sense of social belonging | Fitting into society, being respected | Harmonious society, caring society |
15. Better relationships with others | Having a better understanding of other people, living in harmony with other people | Interaction, communication |
Factors | Attributes | Consequences | Values | |||||||
---|---|---|---|---|---|---|---|---|---|---|
a | b | c | a | b | c | a | b | c | ||
Attributes | A1. Real-time information feedback | O | O | O | ||||||
A2. Safe use | O | O | O | |||||||
A3. Comfortable wear | × | O | O | |||||||
A4. Clear screen | O | O | O | |||||||
A5. Correct data | O | O | × | |||||||
A6. Cheap price | O | O | O | |||||||
Consequences | C1. Learning about smart products | O | O | O | ||||||
C2. Understanding technology applications | O | O | O | |||||||
C3. Increased health awareness | × | O | O | |||||||
C4. Relaxation | O | O | O | |||||||
C5. Satisfying curiosity | O | O | O | |||||||
Values | V1. Healthier bodies | O | O | O | ||||||
V2. Improved quality of life | × | O | O | |||||||
V3. A sense of social belonging | O | O | O | |||||||
V4. Better relationships with others | O | O | O |
Coder | a:b | b:c | c:a |
---|---|---|---|
Intercoder agreement | 0.89 | 0.96 | 0.85 |
Average level of agreement | 0.90 | ||
Overall reliability | 0.96 |
Attributes (Number of Times Mentioned) | Consequences (Number of Times Mentioned) | Values (Number of Times Mentioned) | |||
---|---|---|---|---|---|
Specific attributes | A1. Real-time information feedback (8) A2. Safe use (6) A5. Correct data (8) | Functional consequences | C1. Learning about smart products (4) C2. Understanding technology products (14) C3. Increased health awareness (10) | Functional values | V2. Improved quality of life (14) V3. A sense of social belonging (16) |
Abstract attributes | A3. Comfortable wear (12) A4. Clear screen (4) A6. Cheap price (2) | Psychological consequences | C4. Relaxation (24) C5. Satisfying curiosity (10) | Terminal values | V1. Healthier bodies (20) V4. Better relationships with others (2) |
Factor | C1 | C2 | C3 | C4 | C5 | V1 | V2 | V3 | V4 | Total |
---|---|---|---|---|---|---|---|---|---|---|
A1 | 0;0 | 4;0 | 4;0 | 0;6 | 0;0 | 0;6 | 0;0 | 0;4 | 0;2 | 8;18 |
A2 | 0;0 | 6;2 | 0;0 | 0;6 | 0;0 | 0;4 | 0;4 | 0;4 | 0;0 | 6;20 |
A3 | 4;0 | 4;0 | 8;0 | 0;16 | 0;0 | 0;4 | 0;12 | 0;2 | 0;2 | 16;36 |
A4 | 0;0 | 0;0 | 0;0 | 0;0 | 4;0 | 0;2 | 0;0 | 0;2 | 0;0 | 4;4 |
A5 | 0;0 | 0;0 | 0;0 | 0;0 | 8;0 | 0;4 | 0;0 | 0;4 | 0;4 | 8;12 |
A6 | 2;0 | 0;2 | 0;0 | 0;0 | 2;0 | 0;0 | 0;0 | 0;2 | 0;2 | 4;6 |
C1 | 0;0 | 0;0 | 0;0 | 4;0 | 0;0 | 0;0 | 0;4 | 0;0 | 0;4 | 4;8 |
C2 | 0;0 | 0;0 | 0;0 | 14;0 | 0;0 | 0;6 | 0;8 | 0;8 | 0;0 | 14;22 |
C3 | 0;0 | 0;0 | 0;0 | 6;0 | 0;0 | 4;2 | 0;4 | 0;2 | 0;2 | 10;10 |
C4 | 0;0 | 0;2 | 0;0 | 0;0 | 0;2 | 0;10 | 12;2 | 10;0 | 2;0 | 24;16 |
C5 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 6;0 | 0;0 | 6;0 | 0;2 | 12;2 |
V1 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;2 | 0;0 | 0;2 | 0;4 |
V2 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 |
V3 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 10;0 | 0;0 | 0;0 | 0;0 | 10;0 |
V4 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 | 0;0 |
Total | 6;0 | 14;6 | 12;0 | 24;28 | 14;2 | 20;38 | 12;36 | 16;28 | 2;20 | 120;158 |
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Jeng, M.-Y.; Yeh, T.-M.; Pai, F.-Y. Analyzing Older Adults’ Perceived Values of Using Smart Bracelets by Means–End Chain. Healthcare 2020, 8, 494. https://doi.org/10.3390/healthcare8040494
Jeng M-Y, Yeh T-M, Pai F-Y. Analyzing Older Adults’ Perceived Values of Using Smart Bracelets by Means–End Chain. Healthcare. 2020; 8(4):494. https://doi.org/10.3390/healthcare8040494
Chicago/Turabian StyleJeng, Mei-Yuan, Tsu-Ming Yeh, and Fan-Yun Pai. 2020. "Analyzing Older Adults’ Perceived Values of Using Smart Bracelets by Means–End Chain" Healthcare 8, no. 4: 494. https://doi.org/10.3390/healthcare8040494