CoChat
Sign Up
Cited by 20Technology Adoption and User BehaviourHealth Systems, Economic Evaluations, Quality of LifeTechnology and Human Factors in Education and Health

The PMA scale: a measure of physicians' motivation to adopt medical devices

Open access
Hatz, Maximilian H.M., Sonnenschein, Tim, Blankart, Carl Rudolf·2017·Value in Health
DOI 10.1016/j.jval.2016.12.002
Open this paper in CoChat — free account

Abstract

BACKGROUND: Studies have often stated that individual-level determinants are important drivers for the adoption of medical devices. Empirical evidence supporting this claim is, however, scarce. At the individual level, physicians' adoption motivation was often considered important in the context of adoption decisions, but a clear notion of its dimensions and corresponding measurement scales is not available. OBJECTIVES: To develop and subsequently validate a scale to measure the motivation to adopt medical devices of hospital-based physicians. METHODS: The development and validation of the physician-motivation-adoption (PMA) scale were based on a literature search, internal expert meetings, a pilot study with physicians, and a three-stage online survey. The data collected in the online survey were analyzed using exploratory factor analysis (EFA), and the PMA scale was revised according to the results. Confirmatory factor analysis (CFA) was conducted to test the results from the EFA in the third stage. Reliability and validity tests and subgroup analyses were also conducted. RESULTS: Overall, 457 questionnaires were completed by medical personnel of the National Health Service England. The EFA favored a six-factor solution to appropriately describe physicians' motivation. The CFA confirmed the results from the EFA. Our tests indicated good reliability and validity of the PMA scale. CONCLUSIONS: This is the first reliable and valid scale to measure physicians' adoption motivation. Future adoption studies assessing the individual level should include the PMA scale to obtain more information about the role of physicians' motivation in the broader adoption context.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jval.2016.12.002

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Other researchers have used validated scales to more precisely characterize clinicians who are more or less likely to use digital tools.

    “Other researchers have used validated scales to more precisely characterize clinicians who are more or less likely to use digital tools.33”

    From Clinician Adoption of an Artificial Intelligence Algorithm to Detect Left Ventricular Systolic Dysfunction in Primary Care. (2022) · cites this paper as [33]

    The Conclusions describe the PMA scale as a validated measure of physicians’ motivation to adopt medical devices. The Discussion says whether scale scores indicate a higher or lower likelihood of adoption remains for future research to establish; the paper also does not validate the scale for digital tools generally. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 57 · Cited by 20

Research works printed but not linked: 43

  1. [1]1. Greenberg, D. ∙ Peterburg, Y. ∙ Vekstein, D. ... Decisions to adopt new technologies at the hospital level: insights from Israeli medical centers Int J Technol Assess Health Care. 2005; 21:219-227 PubMed Google Scholar
  2. [2]2. Greenhalgh, T. ∙ Robert, G. ∙ Macfarlane, F. ... Diffusion of innovations in service organizations: systematic review and recommendations Milbank Q. 2004; 82:581-629 Crossref Scopus (4850) PubMed Google Scholar
  3. [3]3. Robert, G. ∙ Greenhalgh, T. ∙ MacFarlane, F. ... Adopting and assimilating new non-pharmaceutical technologies into health care: a systematic review J Health Serv Res Policy. 2010; 15:243-250 Crossref Scopus (90) PubMed Google Scholar
  4. [4]4. Reyes, P.M. ∙ Li, S. ∙ Visich, J.K. Accessing antecedents and outcomes of RFID implementation in health care Int J Prod Econ. 2012; 136:137-150 Crossref Scopus (47) Google Scholar
  5. [5]5. Wernz, C. ∙ Zhang, H. ∙ Phusavat, K. International study of technology investment decisions at hospitals Ind Manage Data Syst. 2014; 114:568-582 Crossref Scopus (26) Google Scholar
  6. [6]6. Gold, H.T. ∙ Pitrelli, K. ∙ Hayes, M.K. ... Decision to adopt medical technology: case study of breast cancer radiotherapy techniques Med Decis Making. 2014; 34:1006-1015 Crossref Scopus (16) PubMed Google Scholar
  7. [7]7. Barasa, E.W. ∙ Molyneux, S. ∙ English, M. ... Setting healthcare priorities in hospitals: a review of empirical studies Health Policy Plan. 2015; 30:386-396 Crossref Scopus (42) PubMed Google Scholar
  8. [10]10. Berliner, E. Adopting medical technology Med Decis Making. 2014; 34:948-950 Crossref Scopus (2) PubMed Google Scholar
  9. [11]11. Vandecasteele, B. ∙ Geuens, M. Motivated consumer innovativeness: concept, measurement, and validation Int J Res Mark. 2010; 27:308-318 Crossref Scopus (184) Google Scholar
  10. [12]12. Goldsmith, R.E. The validity of a scale to measure global innovativeness J Appl Bus Res. 2011; 7:89-97 Crossref Google Scholar
  11. [13]13. Hoffmann, S. ∙ Soyez, K. A cognitive model to predict domain-specific consumer innovativeness J Bus Res. 2010; 63:778-785 Crossref Scopus (85) Google Scholar
  12. [14]14. Rogers, E.M. Diffusion of Innovations.Free Press, New York, NY, 2003 Google Scholar
  13. [15]15. Davis, F.D. A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results Sloan School of Management, Massachussetts Institute of Technology, Cambridge, MA, 1986 Google Scholar
  14. [16]16. Venkatesh, V. ∙ Davis, F.D. A theoretical extension of the Technology Acceptance Model: four longitudinal field studies Manage Sci. 2000; 46:186-204 Crossref Scopus (13499) Google Scholar
  15. [18]18. Fishbein, M. ∙ Ajzen, I. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research.Addison-Wesley, Reading, MA, 1975 Google Scholar
  16. [19]19. Ajzen, I. From intentions to actions: a theory of planned behavior Kuhl, J. ∙ Beckmann, J. (Editors) Action Control: From Cognition to Behavior Springer-Verlag, New York, NY, 1985 Crossref Google Scholar
  17. [20]20. Bartels, J. ∙ Reinders, M.J. Consumer innovativeness and its correlates: a propositional inventory for future research J Bus Res. 2011; 64:601-609 Crossref Scopus (193) Google Scholar
  18. [21]21. Venkatraman, M.P. The impact of innovativeness and innovation type on adoption J Retailing. 1991; 67:51-67 Google Scholar
  19. [22]22. Sheth, J.N. ∙ Newman, B.I. ∙ Gross, B.L. Why we buy what we buy—a theory of consumption values J Bus Res. 1991; 22:159-170 Crossref Scopus (2694) Google Scholar
  20. [23]23. Teplensky, J.D. ∙ Pauly, M.V. ∙ Kimberly, J.R. ... Hospital adoption of medical technology: an empirical test of alternative models Health Serv Res. 1995; 30:437-465 PubMed Google Scholar
  21. [24]24. Holden, R.J. ∙ Karsh, B.T. The Technology Acceptance Model: its past and its future in health care J Biomed Inform. 2010; 43:159-172 Full Text Full Text (PDF) Scopus (1543) PubMed Google Scholar
  22. [27]27. Schwartz, S.H. Universals in the content and structure of values: theoretical advances and empirical tests in 20 countries Zanna, M.P. (Editor) Advances in Experimental Social Psychology Academic Press, Inc., San Diego, CA, 1992 Crossref Scopus (9860) Google Scholar
  23. [28]28. Tellis, G.J. ∙ Yin, E. ∙ Bell, S.J. Global consumer innovativeness: cross-country differences and demographic commonalities J Int Mark. 2009; 17:1-22 Crossref Scopus (187) Google Scholar
  24. [29]29. Kennedy, M.T. ∙ Fiss, P.C. Institutionalization, framing, and diffusion: the logic of TQM adoption and implementation decisions among US hospitals Acad Manage J. 2009; 52:897-918 Crossref Scopus (349) Google Scholar
  25. [30]30. Poggi, A. Job satisfaction, working conditions and aspirations J Econ Psychol. 2010; 31:936-949 Crossref Scopus (48) Google Scholar
  26. [31]31. Williams, B. ∙ Brown, T. ∙ Onsman, A. Exploratory factor analysis: a five-step guide for novices J Emerg Prim Health Care. 2010; 8:1-13 Google Scholar
  27. [32]32. Kaiser, H.F. Index of factorial simplicity Psychometrika. 1974; 39:31-36 Crossref Scopus (8430) Google Scholar
  28. [33]33. Sainfort, F. The use of factor analysis techniques Med Decis Making. 2002; 22:451-452 PubMed Google Scholar
  29. [34]34. Conway, J.M. ∙ Huffcutt, A.I. A review and evaluation of exploratory factor analysis practices in organizational research Organ Res Methods. 2003; 6:147-168 Crossref Scopus (616) Google Scholar
  30. [35]35. Park, H.S. ∙ Dailey, R. ∙ Lemus, D. The use of exploratory factor analysis and principal components analysis in communication research Hum Commun Res. 2002; 28:562-577 Crossref Google Scholar
  31. [36]36. O’Leary-Kelly, S.W. ∙ Vokurka, R.J. The empirical assessment of construct validity J Oper Manage. 1998; 16:387-405 Crossref Google Scholar
  32. [39]39. Fabrigar, L.R. ∙ Wegener, D.T. ∙ MacCallum, R.C. ... Evaluating the use of exploratory factor analysis in psychological research Psychol Methods. 1999; 4:272-299 Crossref Scopus (5918) Google Scholar
  33. [40]40. Tavakol, M. ∙ Dennick, R. Making sense of Cronbach’s alpha. Int J Med Educ. 2011; 2:53-55 Crossref Scopus (7348) Google Scholar
  34. [42]42. Huysamen, G.K. Coefficient alpha: unnecessarily ambiguous; unduly ubiquitous SA J Ind Pyschol. 2006; 32:34-40 Google Scholar
  35. [45]45. Schmitt, T.A. Current methodological considerations in exploratory and confirmatory factor analysis J Psychoeduc Assess. 2011; 29:304-321 Crossref Scopus (675) Google Scholar
  36. [46]46. Hu, L.T. ∙ Bentler, P.M. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives Struct Equ Modeling. 1999; 6:1-55 Crossref Scopus (73931) Google Scholar
  37. [47]47. Werts, C.E. ∙ Linn, R.L. ∙ Joreskog, K.G. Intraclass reliability estimates—testing structural assumptions Educ Psychol Meas. 1974; 34:25-33 Crossref Google Scholar
  38. [48]48. Geldhof, G.J. ∙ Preacher, K.J. ∙ Zyphur, M.J. Reliability estimation in a multilevel confirmatory factor analysis framework Psychol Methods. 2014; 19:72-91 Crossref Scopus (1042) PubMed Google Scholar
  39. [49]49. Fornell, C. ∙ Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error J Mark Res. 1981; 18:39-50 Crossref Google Scholar
  40. [50]50. Thompson, B. ∙ Daniel, L.G. Factor analytic evidence for the construct validity of scores: a historical overview and some guidelines Educ Psychol Meas. 1996; 56:197-208 Crossref Scopus (652) Google Scholar
  41. [51]51. Streiner, D.L. Starting at the beginning: an introduction to coefficient alpha and internal consistency J Pers Assess. 2003; 80:99-103 Crossref Scopus (2270) PubMed Google Scholar
  42. [52]52. Bagozzi, R.P. ∙ Yi, Y. Specification, evaluation, and interpretation of structural equation models J Acad Mark Sci. 2012; 40:8-34 Crossref Scopus (2515) Google Scholar
  43. [54]54. Costello, A. ∙ Osborne, J. Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis Pract Assess Res Eval. 2005; 10:1-9 Google Scholar Figures (1) Article metrics Supplementary materials (1) Document (96.69 KB) Related Articles Advertisement Fig. 1 Hide CaptionDownloadSee figure in Article Toggle Thumbstrip Fig. 1 Fig. 1 Download .PPT Home Access for Developing Countries Articles and Issues Articles in Press Current Issue Good Research Practices List of Issues Supplements For Authors About Open Access Guide for Authors Researcher Academy Submit a Manuscript Journal Info About Open Access About Value in Health Contact Us Editorial Board Info for Advertisers New Content Alerts Subscribe Press 2/2017: ISPOR Releases New Task Force Recommendations for the Development of Clinician-Reported Outcome Assessments 2/2017: "Mapping Studies" In Cost-Utility Analyses: New Recommendations From ISPOR Task Force 12/2016: Making Choices on the Journey to Universal Health Care Coverage: From Advocacy to Analysis Themed Sections ISPOR ISPOR Member Access Information Mission, Vision, Strategy About ISPOR Membership Profile Videos VHRI The content on this site is intended for healthcare professionals. All content on this site: Copyright © 2026 Elsevier Inc., its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply. Privacy Policy Terms and Conditions Accessibility Help & Contact Responsible AI RELX Thanks for sharing! AddToAny More… We use cookies that are necessary to make our site work. We may also use additional cookies to analyze, improve, and personalize our content and your digital experience. You can manage your cookie preferences using theCookie settings link. For more information, see ourCookie Policy Company Logo Opt-Out Request Honored Cookie Preference Center We use cookies which are necessary to make our site work. We may also use additional cookies to analyse, improve and personalise our content and your digital experience. For more information, see our Cookie Policy and the list of Google Ad-Tech Vendors. You may choose not to allow some types of cookies. However, blocking some types may impact your experience of our site and the services we are able to offer. See the different category headings below to find out more or change your settings. You may also be able to exercise your privacy choices Cookie Settings | Your Privacy Choices as described in our Privacy Policy Manage Consent Preferences Strictly Necessary Cookies Always active These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work. Functional Cookies These cookies enable the website to provide enhanced functionality and personalisation. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly. Performance Cookies These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. Targeting Cookies These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. If you do not allow these cookies, you will experience less targeted advertising. Cookie List label Consent Leg.Interest label label label Powered by Onetrust

Authors
Hatz, M. H. M., Sonnenschein, T., & Blankart, C. R.
Affiliations
Universität Hamburg (DE)
Corresponding author
Blankart, Carl Rudolf
ORCID
Blankart, Carl Rudolf
Venue
Value in Health
Publisher
Elsevier BV
Published
2017-04
Volume
20
Issue
4
Pages
533-541
ISSN
1098-3015 (ISSN-L)
DOI
10.1016/j.jval.2016.12.002
OpenAlex
W2580215548
Cited by
20
References
57
Citations by year
2026: 2 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 6 · 2021: 3 · 2020: 4 · 2019: 1 · 2018: 1
FWCI
2.64
Type
journal article
Language
en
Open access
Licence
Locations
  • Value in Health (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Bern Open Repository and Information System (University of Bern) (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
Keywords
medical device adoption, physician motivation, scale development, scale validation, individual determinants, hospital physicians, technology adoption
MeSH terms
Adult, Aged, Attitude of Health Personnel, Choice Behavior, Cognition, England, Equipment and Supplies, Factor Analysis, Statistical, Female, Humans, Health Knowledge, Attitudes, Practice, Male, Middle Aged, Motivation, Practice Patterns, Physicians', Physician's Role, Pilot Projects, Surveys and Questionnaires, State Medicine, Reproducibility of Results, Risk Assessment, Hospitalists, Patient Safety

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review