Health Care Practitioners’ Determinants of Telerehabilitation Acceptance

Authors

  • Abdullah A. Almojaibel Imam Abdulrhman Bin Faisal University (IAU) https://orcid.org/0000-0002-2122-7699
  • Niki Munk School of Health and Human Services, Indiana University
  • Lynda T. Goodfellow Lewis College of Nursing and Health Professions Georgia State University
  • Thomas F. Fisher Dwyer College of Health Sciences IU South Bend
  • Kristine K. Miller Indiana University School of Health and Human Services
  • Amber R. Comer School of Health and Human Services Indiana University
  • Tamilyn Bakas University of Cincinnati College of Nursing
  • Michael D. Justiss School of Applied Health Sciences Brooks Rehabilitation College of Healthcare Sciences Jacksonville University

DOI:

https://doi.org/10.5195/ijt.2020.6308

Keywords:

Health care practitioners, Pulmonary rehabilitation, Respiratory care, Technology acceptance model, Telehealth, Telerehabilitation

Abstract

Background: Pulmonary rehabilitation is a multidisciplinary patient-tailored intervention that aims to improve the physical and psychological condition of people with chronic respiratory diseases. Providing pulmonary rehabilitation (PR) services to the growing population of patients is challenging due to shortages in health care practitioners and pulmonary rehabilitation programs. Telerehabilitation has the potential to address this shortage in practitioners and PR programs as well as improve patients’ participation and adherence. This study’s purpose was to identify and evaluate the influences of intention of health care practitioners to use telerehabilitation. Methods: Data were collected through a self-administered Internet-based survey. Results: Surveys were completed by 222 health care practitioners working in pulmonary rehabilitation with 79% having a positive intention to use telerehabilitation. Specifically, perceived usefulness was a significant individual predictor of positive intentions to use telerehabilitation. Conclusion: Perceived usefulness may be an important factor associated with health care providers’ intent to use telerehabilitation for pulmonary rehabilitation.

  

Author Biographies

Abdullah A. Almojaibel, Imam Abdulrhman Bin Faisal University (IAU)

Assistant Prof- Respiratory Care Department 
Imam Abdulrahman Bin Faisal University, KSA
College of Applied Medical Sciences 
President of Saudi Society for Respiratory Care

Niki Munk, School of Health and Human Services, Indiana University

Niki Munk, Ph.D., LMT

Assistant Professor – Department of Health Sciences

School of Health and Human Services

Indiana University

School of Health and Rehabilitation Sciences

Lynda T. Goodfellow, Lewis College of Nursing and Health Professions Georgia State University

Lynda T. Goodfellow, Ed.D., RRT, AE-C, FAARC

Professor and Senior Associate Academic Dean

Lewis College of Nursing and Health Professions

Georgia State University

Thomas F. Fisher, Dwyer College of Health Sciences IU South Bend

Thomas F. Fisher, Ph.D., OT, CCM, FAOTA

Dean & Professor

Dwyer College of Health Sciences

IU South Bend

Kristine K. Miller, Indiana University School of Health and Human Services

Kristine K. Miller, PT, PhD

Associate Professor

Indiana University

School of Health and Human Services

Physical Therapy Program

Amber R. Comer, School of Health and Human Services Indiana University

Amber R. Comer, JD, PhD

Assistant Professor

School of Health and Human Services

Indiana University

 

Tamilyn Bakas, University of Cincinnati College of Nursing

Tamilyn Bakas, Ph.D., RN, FAHA, FAAN

Professor and Jane E. Procter Endowed Chair

University of Cincinnati College of Nursing

Michael D. Justiss, School of Applied Health Sciences Brooks Rehabilitation College of Healthcare Sciences Jacksonville University

Michael D. Justiss, Ph.D., OTR

Associate Professor and Chair

Department of Occupational Therapy

Doctor of Occupational Therapy (OTD) Program

School of Applied Health Sciences

Brooks Rehabilitation College of Healthcare Sciences

Jacksonville University

References

Almojaibel A. A. (2016). Delivering pulmonary rehabilitation for patients with chronic obstructive pulmonary disease at home using telehealth: A review of the literature. Saudi Journal of Medicine & Medical Sciences, 4(3), 164–171. https://doi.org/10.4103/1658-631X.188247

Almojaibel, A. A., Munk, N., Goodfellow, L. T., Fisher, T. F., Miller, K. K., Comer, A. R., Bakas, T., & Justiss, M. D. (2019). Development and validation of the tele-pulmonary rehabilitation acceptance scale. Respiratory Care, 64(9), 1057–1064. https://doi.org/10.4187/respcare.06432

Asaro, P. V., Williams, J., & Banet, G. A. (2004). Measuring the effect of a computerized nursing documentation system with objective measures and reported perceptions. Annals of Emergency Medicine, 4(44), S131-S132. https://doi.org/10.1016/j.annemergmed.2004.07.420

Brewster, L., Mountain, G., Wessels, B., Kelly, C., & Hawley, M. (2014). Factors affecting front line staff acceptance of telehealth technologies: A mixed-method systematic review. Journal of Advanced Nursing, 70(1), 21–33. https://doi.org/10.1111/jan.12196

Chen, J., Jin, W., Zhang, X. X., Xu, W., Liu, X. N., & Ren, C. C. (2015). Telerehabilitation approaches for stroke patients: Systematic review and meta-analysis of randomized controlled trials. Journal of Stroke and Cerebrovascular Diseases, 24(12), 2660–2668. https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.09.014

Doarn, C. R., Pruitt, S., Jacobs, J., Harris, Y., Bott, D. M., Riley, W., Lamer, C., & Oliver, A. L. (2014). Federal efforts to define and advance telehealth--a work in progress. Telemedicine Journal and e-Health, 20(5), 409–418. https://doi.org/10.1089/tmj.2013.0336

Ferketich S. (1991). Focus on psychometrics. Aspects of item analysis. Research in Nursing & Health, 14(2), 165–168. https://doi.org/10.1002/nur.4770140211

Gagnon, M. P., Orruño, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. (2012). Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemedicine Journal and e-Health, 18(1), 54–59. https://doi.org/10.1089/tmj.2011.0066

Garvey, C., Bayles, M. P., Hamm, L. F., Hill, K., Holland, A., Limberg, T. M., & Spruit, M. A. (2016). Pulmonary rehabilitation exercise prescription in chronic obstructive pulmonary disease: review of selected guidelines: An official statement from the american association of cardiovascular and pulmonary rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention, 36(2), 75–83. https://doi.org/10.1097/HCR.0000000000000171

Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O'Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., Duda, S. N., & REDCap Consortium (2019). The REDCap consortium: Building an international community of software platform partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/10.1016/j.jbi.2019.103208

Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. https://doi.org/10.1080/07421222.1999.11518247

Huis in 't Veld, R. M., Kosterink, S. M., Barbe, T., Lindegård, A., Marecek, T., & Vollenbroek-Hutten, M. M. (2010). Relation between patient satisfaction, compliance and the clinical benefit of a teletreatment application for chronic pain. Journal of Telemedicine and Telecare, 16(6), 322–328. https://doi.org/10.1258/jtt.2010.006006

Keating, A., Lee, A., & Holland, A. E. (2011). What prevents people with chronic obstructive pulmonary disease from attending pulmonary rehabilitation? A systematic review. Chronic Respiratory Disease, 8(2), 89–99. https://doi.org/10.1177/1479972310393756

Ko, F. W., Cheung, N. K., Rainer, T. H., Lum, C., Wong, I., & Hui, D. S. (2017). Comprehensive care programme for patients with chronic obstructive pulmonary disease: A randomised controlled trial. Thorax, 72(2), 122–128. https://doi.org/10.1136/thoraxjnl-2016-208396

Kowitlawakul Y. (2011). The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU). Computers, Informatics, Nursing, 29(7), 411–418. https://doi.org/10.1097/NCN.0b013e3181f9dd4a

Liu, L., Miguel Cruz, A., Rios Rincon, A., Buttar, V., Ranson, Q., & Goertzen, D. (2015). What factors determine therapists' acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disability and Rehabilitation, 37(5), 447–455. https://doi.org/10.3109/09638288.2014.923529

Liu, X. L., Tan, J. Y., Wang, T., Zhang, Q., Zhang, M., Yao, L. Q., & Chen, J. X. (2014). Effectiveness of home-based pulmonary rehabilitation for patients with chronic obstructive pulmonary disease: A meta-analysis of randomized controlled trials. Rehabilitation Nursing, 39(1), 36–59. https://doi.org/10.1002/rnj.112

Rho, M. J., Choi, I. Y., & Lee, J. (2014). Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International Journal of Medical Informatics, 83(8), 559–571. https://doi.org/10.1016/j.ijmedinf.2014.05.005

Ries, A. L., Bauldoff, G. S., Carlin, B. W., Casaburi, R., Emery, C. F., Mahler, D. A., Make, B., Rochester, C. L., Zuwallack, R., & Herrerias, C. (2007). Pulmonary Rehabilitation: Joint ACCP/AACVPR Evidence-Based Clinical Practice Guidelines. Chest, 131(5 Suppl), 4S–42S. https://doi.org/10.1378/chest.06-2418

Spruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., Gosselink, R., … ATS/ERS Task Force on Pulmonary Rehabilitation (2013). An official American Thoracic Society/European Respiratory Society statement: Key concepts and advances in pulmonary rehabilitation. American Journal of Respiratory and Critical Care Medicine, 188(8), e13–e64. https://doi.org/10.1164/rccm.201309-1634ST

Tang, J., Mandrusiak, A., & Russell, T. (2012). The feasibility and validity of a remote pulse oximetry system for pulmonary rehabilitation: A pilot study. International Journal of Telemedicine and Applications, 2012, 798791. https://doi.org/10.1155/2012/798791

Wade, V. A., Eliott, J. A., & Hiller, J. E. (2014). Clinician acceptance is the key factor for sustainable telehealth services. Qualitative Health Research, 24(5), 682–694. https://doi.org/10.1177/1049732314528809

Zailani, S., Gilani, M. S., Nikbin, D., & Iranmanesh, M. (2014). Determinants of telemedicine acceptance in selected public hospitals in Malaysia: Clinical perspective. Journal of Medical Systems, 38(9), 111. https://doi.org/10.1007/s10916-014-0111-4

Almojaibel A. A. (2016). Delivering pulmonary rehabilitation for patients with chronic obstructive pulmonary disease at home using telehealth: A review of the literature. Saudi Journal of Medicine & Medical Sciences, 4(3), 164–171. https://doi.org/10.4103/1658-631X.188247

Almojaibel, A. A., Munk, N., Goodfellow, L. T., Fisher, T. F., Miller, K. K., Comer, A. R., Bakas, T., & Justiss, M. D. (2019). Development and validation of the tele-pulmonary rehabilitation acceptance scale. Respiratory Care, 64(9), 1057–1064. https://doi.org/10.4187/respcare.06432

Asaro, P. V., Williams, J., & Banet, G. A. (2004). Measuring the effect of a computerized nursing documentation system with objective measures and reported perceptions. Annals of Emergency Medicine, 4(44), S131-S132. https://doi.org/10.1016/j.annemergmed.2004.07.420

Brewster, L., Mountain, G., Wessels, B., Kelly, C., & Hawley, M. (2014). Factors affecting front line staff acceptance of telehealth technologies: A mixed-method systematic review. Journal of Advanced Nursing, 70(1), 21–33. https://doi.org/10.1111/jan.12196

Chen, J., Jin, W., Zhang, X. X., Xu, W., Liu, X. N., & Ren, C. C. (2015). Telerehabilitation approaches for stroke patients: Systematic review and meta-analysis of randomized controlled trials. Journal of Stroke and Cerebrovascular Diseases, 24(12), 2660–2668. https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.09.014

Doarn, C. R., Pruitt, S., Jacobs, J., Harris, Y., Bott, D. M., Riley, W., Lamer, C., & Oliver, A. L. (2014). Federal efforts to define and advance telehealth--a work in progress. Telemedicine Journal and e-Health, 20(5), 409–418. https://doi.org/10.1089/tmj.2013.0336

Ferketich S. (1991). Focus on psychometrics. Aspects of item analysis. Research in Nursing & Health, 14(2), 165–168. https://doi.org/10.1002/nur.4770140211

Gagnon, M. P., Orruño, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. (2012). Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemedicine Journal and e-Health, 18(1), 54–59. https://doi.org/10.1089/tmj.2011.0066

Garvey, C., Bayles, M. P., Hamm, L. F., Hill, K., Holland, A., Limberg, T. M., & Spruit, M. A. (2016). Pulmonary rehabilitation exercise prescription in chronic obstructive pulmonary disease: review of selected guidelines: An official statement from the american association of cardiovascular and pulmonary rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention, 36(2), 75–83. https://doi.org/10.1097/HCR.0000000000000171

Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O'Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., Duda, S. N., & REDCap Consortium (2019). The REDCap consortium: Building an international community of software platform partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/10.1016/j.jbi.2019.103208

Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. https://doi.org/10.1080/07421222.1999.11518247

Huis in 't Veld, R. M., Kosterink, S. M., Barbe, T., Lindegård, A., Marecek, T., & Vollenbroek-Hutten, M. M. (2010). Relation between patient satisfaction, compliance and the clinical benefit of a teletreatment application for chronic pain. Journal of Telemedicine and Telecare, 16(6), 322–328. https://doi.org/10.1258/jtt.2010.006006

Keating, A., Lee, A., & Holland, A. E. (2011). What prevents people with chronic obstructive pulmonary disease from attending pulmonary rehabilitation? A systematic review. Chronic Respiratory Disease, 8(2), 89–99. https://doi.org/10.1177/1479972310393756

Ko, F. W., Cheung, N. K., Rainer, T. H., Lum, C., Wong, I., & Hui, D. S. (2017). Comprehensive care programme for patients with chronic obstructive pulmonary disease: A randomised controlled trial. Thorax, 72(2), 122–128. https://doi.org/10.1136/thoraxjnl-2016-208396

Kowitlawakul Y. (2011). The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU). Computers, Informatics, Nursing, 29(7), 411–418. https://doi.org/10.1097/NCN.0b013e3181f9dd4a

Liu, L., Miguel Cruz, A., Rios Rincon, A., Buttar, V., Ranson, Q., & Goertzen, D. (2015). What factors determine therapists' acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disability and Rehabilitation, 37(5), 447–455. https://doi.org/10.3109/09638288.2014.923529

Liu, X. L., Tan, J. Y., Wang, T., Zhang, Q., Zhang, M., Yao, L. Q., & Chen, J. X. (2014). Effectiveness of home-based pulmonary rehabilitation for patients with chronic obstructive pulmonary disease: A meta-analysis of randomized controlled trials. Rehabilitation Nursing, 39(1), 36–59. https://doi.org/10.1002/rnj.112

Rho, M. J., Choi, I. Y., & Lee, J. (2014). Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International Journal of Medical Informatics, 83(8), 559–571. https://doi.org/10.1016/j.ijmedinf.2014.05.005

Ries, A. L., Bauldoff, G. S., Carlin, B. W., Casaburi, R., Emery, C. F., Mahler, D. A., Make, B., Rochester, C. L., Zuwallack, R., & Herrerias, C. (2007). Pulmonary Rehabilitation: Joint ACCP/AACVPR Evidence-Based Clinical Practice Guidelines. Chest, 131(5 Suppl), 4S–42S. https://doi.org/10.1378/chest.06-2418

Spruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., Gosselink, R., … ATS/ERS Task Force on Pulmonary Rehabilitation (2013). An official American Thoracic Society/European Respiratory Society statement: Key concepts and advances in pulmonary rehabilitation. American Journal of Respiratory and Critical Care Medicine, 188(8), e13–e64. https://doi.org/10.1164/rccm.201309-1634ST

Tang, J., Mandrusiak, A., & Russell, T. (2012). The feasibility and validity of a remote pulse oximetry system for pulmonary rehabilitation: A pilot study. International Journal of Telemedicine and Applications, 2012, 798791. https://doi.org/10.1155/2012/798791

Wade, V. A., Eliott, J. A., & Hiller, J. E. (2014). Clinician acceptance is the key factor for sustainable telehealth services. Qualitative Health Research, 24(5), 682–694. https://doi.org/10.1177/1049732314528809

Zailani, S., Gilani, M. S., Nikbin, D., & Iranmanesh, M. (2014). Determinants of telemedicine acceptance in selected public hospitals in Malaysia: Clinical perspective. Journal of Medical Systems, 38(9), 111. https://doi.org/10.1007/s10916-014-0111-4

patients with chronic obstructive pulmonary disease at home using telehealth: A review of the literature. Saudi Journal of Medicine & Medical Sciences, 4(3), 164–171. https://doi.org/10.4103/1658-631X.188247

Almojaibel, A. A., Munk, N., Goodfellow, L. T., Fisher, T. F., Miller, K. K., Comer, A. R., Bakas, T., & Justiss, M. D. (2019). Development and validation of the tele-pulmonary rehabilitation acceptance scale. Respiratory Care, 64(9), 1057–1064. https://doi.org/10.4187/respcare.06432

Asaro, P. V., Williams, J., & Banet, G. A. (2004). Measuring the effect of a computerized nursing documentation system with objective measures and reported perceptions. Annals of Emergency Medicine, 4(44), S131-S132. https://doi.org/10.1016/j.annemergmed.2004.07.420

Brewster, L., Mountain, G., Wessels, B., Kelly, C., & Hawley, M. (2014). Factors affecting front line staff acceptance of telehealth technologies: A mixed-method systematic review. Journal of Advanced Nursing, 70(1), 21–33. https://doi.org/10.1111/jan.12196

Chen, J., Jin, W., Zhang, X. X., Xu, W., Liu, X. N., & Ren, C. C. (2015). Telerehabilitation approaches for stroke patients: Systematic review and meta-analysis of randomized controlled trials. Journal of Stroke and Cerebrovascular Diseases, 24(12), 2660–2668. https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.09.014

Doarn, C. R., Pruitt, S., Jacobs, J., Harris, Y., Bott, D. M., Riley, W., Lamer, C., & Oliver, A. L. (2014). Federal efforts to define and advance telehealth--a work in progress. Telemedicine Journal and e-Health, 20(5), 409–418. https://doi.org/10.1089/tmj.2013.0336

Ferketich S. (1991). Focus on psychometrics. Aspects of item analysis. Research in Nursing & Health, 14(2), 165–168. https://doi.org/10.1002/nur.4770140211

Gagnon, M. P., Orruño, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. (2012). Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemedicine Journal and e-Health, 18(1), 54–59. https://doi.org/10.1089/tmj.2011.0066

Garvey, C., Bayles, M. P., Hamm, L. F., Hill, K., Holland, A., Limberg, T. M., & Spruit, M. A. (2016). Pulmonary rehabilitation exercise prescription in chronic obstructive pulmonary disease: review of selected guidelines: An official statement from the american association of cardiovascular and pulmonary rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention, 36(2), 75–83. https://doi.org/10.1097/HCR.0000000000000171

Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O'Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., Duda, S. N., & REDCap Consortium (2019). The REDCap consortium: Building an international community of software platform partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/10.1016/j.jbi.2019.103208

Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. https://doi.org/10.1080/07421222.1999.11518247

Huis in 't Veld, R. M., Kosterink, S. M., Barbe, T., Lindegård, A., Marecek, T., & Vollenbroek-Hutten, M. M. (2010). Relation between patient satisfaction, compliance and the clinical benefit of a teletreatment application for chronic pain. Journal of Telemedicine and Telecare, 16(6), 322–328. https://doi.org/10.1258/jtt.2010.006006

Keating, A., Lee, A., & Holland, A. E. (2011). What prevents people with chronic obstructive pulmonary disease from attending pulmonary rehabilitation? A systematic review. Chronic Respiratory Disease, 8(2), 89–99. https://doi.org/10.1177/1479972310393756

Ko, F. W., Cheung, N. K., Rainer, T. H., Lum, C., Wong, I., & Hui, D. S. (2017). Comprehensive care programme for patients with chronic obstructive pulmonary disease: A randomised controlled trial. Thorax, 72(2), 122–128. https://doi.org/10.1136/thoraxjnl-2016-208396

Kowitlawakul Y. (2011). The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU). Computers, Informatics, Nursing, 29(7), 411–418. https://doi.org/10.1097/NCN.0b013e3181f9dd4a

Liu, L., Miguel Cruz, A., Rios Rincon, A., Buttar, V., Ranson, Q., & Goertzen, D. (2015). What factors determine therapists' acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disability and Rehabilitation, 37(5), 447–455. https://doi.org/10.3109/09638288.2014.923529

Liu, X. L., Tan, J. Y., Wang, T., Zhang, Q., Zhang, M., Yao, L. Q., & Chen, J. X. (2014). Effectiveness of home-based pulmonary rehabilitation for patients with chronic obstructive pulmonary disease: A meta-analysis of randomized controlled trials. Rehabilitation Nursing, 39(1), 36–59. https://doi.org/10.1002/rnj.112

Rho, M. J., Choi, I. Y., & Lee, J. (2014). Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International Journal of Medical Informatics, 83(8), 559–571. https://doi.org/10.1016/j.ijmedinf.2014.05.005

Ries, A. L., Bauldoff, G. S., Carlin, B. W., Casaburi, R., Emery, C. F., Mahler, D. A., Make, B., Rochester, C. L., Zuwallack, R., & Herrerias, C. (2007). Pulmonary Rehabilitation: Joint ACCP/AACVPR Evidence-Based Clinical Practice Guidelines. Chest, 131(5 Suppl), 4S–42S. https://doi.org/10.1378/chest.06-2418

Spruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., Gosselink, R., … ATS/ERS Task Force on Pulmonary Rehabilitation (2013). An official American Thoracic Society/European Respiratory Society statement: Key concepts and advances in pulmonary rehabilitation. American Journal of Respiratory and Critical Care Medicine, 188(8), e13–e64. https://doi.org/10.1164/rccm.201309-1634ST

Tang, J., Mandrusiak, A., & Russell, T. (2012). The feasibility and validity of a remote pulse oximetry system for pulmonary rehabilitation: A pilot study. International Journal of Telemedicine and Applications, 2012, 798791. https://doi.org/10.1155/2012/798791

Wade, V. A., Eliott, J. A., & Hiller, J. E. (2014). Clinician acceptance is the key factor for sustainable telehealth services. Qualitative Health Research, 24(5), 682–694. https://doi.org/10.1177/1049732314528809

Zailani, S., Gilani, M. S., Nikbin, D., & Iranmanesh, M. (2014). Determinants of telemedicine acceptance in selected public hospitals in Malaysia: Clinical perspective. Journal of Medical Systems, 38(9), 111. https://doi.org/10.1007/s10916-014-0111-4

patients with chronic obstructive pulmonary disease at home using telehealth: A review of the literature. Saudi Journal of Medicine & Medical Sciences, 4(3), 164–171. https://doi.org/10.4103/1658-631X.188247

Almojaibel, A. A., Munk, N., Goodfellow, L. T., Fisher, T. F., Miller, K. K., Comer, A. R., Bakas, T., & Justiss, M. D. (2019). Development and validation of the tele-pulmonary rehabilitation acceptance scale. Respiratory Care, 64(9), 1057–1064. https://doi.org/10.4187/respcare.06432

Asaro, P. V., Williams, J., & Banet, G. A. (2004). Measuring the effect of a computerized nursing documentation system with objective measures and reported perceptions. Annals of Emergency Medicine, 4(44), S131-S132. https://doi.org/10.1016/j.annemergmed.2004.07.420

Brewster, L., Mountain, G., Wessels, B., Kelly, C., & Hawley, M. (2014). Factors affecting front line staff acceptance of telehealth technologies: A mixed-method systematic review. Journal of Advanced Nursing, 70(1), 21–33. https://doi.org/10.1111/jan.12196

Chen, J., Jin, W., Zhang, X. X., Xu, W., Liu, X. N., & Ren, C. C. (2015). Telerehabilitation approaches for stroke patients: Systematic review and meta-analysis of randomized controlled trials. Journal of Stroke and Cerebrovascular Diseases, 24(12), 2660–2668. https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.09.014

Doarn, C. R., Pruitt, S., Jacobs, J., Harris, Y., Bott, D. M., Riley, W., Lamer, C., & Oliver, A. L. (2014). Federal efforts to define and advance telehealth--a work in progress. Telemedicine Journal and e-Health, 20(5), 409–418. https://doi.org/10.1089/tmj.2013.0336

Ferketich S. (1991). Focus on psychometrics. Aspects of item analysis. Research in Nursing & Health, 14(2), 165–168. https://doi.org/10.1002/nur.4770140211

Gagnon, M. P., Orruño, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. (2012). Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemedicine Journal and e-Health, 18(1), 54–59. https://doi.org/10.1089/tmj.2011.0066

Garvey, C., Bayles, M. P., Hamm, L. F., Hill, K., Holland, A., Limberg, T. M., & Spruit, M. A. (2016). Pulmonary rehabilitation exercise prescription in chronic obstructive pulmonary disease: review of selected guidelines: An official statement from the american association of cardiovascular and pulmonary rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention, 36(2), 75–83. https://doi.org/10.1097/HCR.0000000000000171

Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O'Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., Duda, S. N., & REDCap Consortium (2019). The REDCap consortium: Building an international community of software platform partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/10.1016/j.jbi.2019.103208

Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. https://doi.org/10.1080/07421222.1999.11518247

Huis in 't Veld, R. M., Kosterink, S. M., Barbe, T., Lindegård, A., Marecek, T., & Vollenbroek-Hutten, M. M. (2010). Relation between patient satisfaction, compliance and the clinical benefit of a teletreatment application for chronic pain. Journal of Telemedicine and Telecare, 16(6), 322–328. https://doi.org/10.1258/jtt.2010.006006

Keating, A., Lee, A., & Holland, A. E. (2011). What prevents people with chronic obstructive pulmonary disease from attending pulmonary rehabilitation? A systematic review. Chronic Respiratory Disease, 8(2), 89–99. https://doi.org/10.1177/1479972310393756

Ko, F. W., Cheung, N. K., Rainer, T. H., Lum, C., Wong, I., & Hui, D. S. (2017). Comprehensive care programme for patients with chronic obstructive pulmonary disease: A randomised controlled trial. Thorax, 72(2), 122–128. https://doi.org/10.1136/thoraxjnl-2016-208396

Kowitlawakul Y. (2011). The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU). Computers, Informatics, Nursing, 29(7), 411–418. https://doi.org/10.1097/NCN.0b013e3181f9dd4a

Liu, L., Miguel Cruz, A., Rios Rincon, A., Buttar, V., Ranson, Q., & Goertzen, D. (2015). What factors determine therapists' acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disability and Rehabilitation, 37(5), 447–455. https://doi.org/10.3109/09638288.2014.923529

Liu, X. L., Tan, J. Y., Wang, T., Zhang, Q., Zhang, M., Yao, L. Q., & Chen, J. X. (2014). Effectiveness of home-based pulmonary rehabilitation for patients with chronic obstructive pulmonary disease: A meta-analysis of randomized controlled trials. Rehabilitation Nursing, 39(1), 36–59. https://doi.org/10.1002/rnj.112

Rho, M. J., Choi, I. Y., & Lee, J. (2014). Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International Journal of Medical Informatics, 83(8), 559–571. https://doi.org/10.1016/j.ijmedinf.2014.05.005

Ries, A. L., Bauldoff, G. S., Carlin, B. W., Casaburi, R., Emery, C. F., Mahler, D. A., Make, B., Rochester, C. L., Zuwallack, R., & Herrerias, C. (2007). Pulmonary Rehabilitation: Joint ACCP/AACVPR Evidence-Based Clinical Practice Guidelines. Chest, 131(5 Suppl), 4S–42S. https://doi.org/10.1378/chest.06-2418

Spruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., Gosselink, R., … ATS/ERS Task Force on Pulmonary Rehabilitation (2013). An official American Thoracic Society/European Respiratory Society statement: Key concepts and advances in pulmonary rehabilitation. American Journal of Respiratory and Critical Care Medicine, 188(8), e13–e64. https://doi.org/10.1164/rccm.201309-1634ST

Tang, J., Mandrusiak, A., & Russell, T. (2012). The feasibility and validity of a remote pulse oximetry system for pulmonary rehabilitation: A pilot study. International Journal of Telemedicine and Applications, 2012, 798791. https://doi.org/10.1155/2012/798791

Wade, V. A., Eliott, J. A., & Hiller, J. E. (2014). Clinician acceptance is the key factor for sustainable telehealth services. Qualitative Health Research, 24(5), 682–694. https://doi.org/10.1177/1049732314528809

Zailani, S., Gilani, M. S., Nikbin, D., & Iranmanesh, M. (2014). Determinants of telemedicine acceptance in selected public hospitals in Malaysia: Clinical perspective. Journal of Medical Systems, 38(9), 111. https://doi.org/10.1007/s10916-014-0111-4

patients with chronic obstructive pulmonary disease at home using telehealth: A review of the literature. Saudi Journal of Medicine & Medical Sciences, 4(3), 164–171. https://doi.org/10.4103/1658-631X.188247

Almojaibel, A. A., Munk, N., Goodfellow, L. T., Fisher, T. F., Miller, K. K., Comer, A. R., Bakas, T., & Justiss, M. D. (2019). Development and validation of the tele-pulmonary rehabilitation acceptance scale. Respiratory Care, 64(9), 1057–1064. https://doi.org/10.4187/respcare.06432

Asaro, P. V., Williams, J., & Banet, G. A. (2004). Measuring the effect of a computerized nursing documentation system with objective measures and reported perceptions. Annals of Emergency Medicine, 4(44), S131-S132. https://doi.org/10.1016/j.annemergmed.2004.07.420

Brewster, L., Mountain, G., Wessels, B., Kelly, C., & Hawley, M. (2014). Factors affecting front line staff acceptance of telehealth technologies: A mixed-method systematic review. Journal of Advanced Nursing, 70(1), 21–33. https://doi.org/10.1111/jan.12196

Chen, J., Jin, W., Zhang, X. X., Xu, W., Liu, X. N., & Ren, C. C. (2015). Telerehabilitation approaches for stroke patients: Systematic review and meta-analysis of randomized controlled trials. Journal of Stroke and Cerebrovascular Diseases, 24(12), 2660–2668. https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.09.014

Doarn, C. R., Pruitt, S., Jacobs, J., Harris, Y., Bott, D. M., Riley, W., Lamer, C., & Oliver, A. L. (2014). Federal efforts to define and advance telehealth--a work in progress. Telemedicine Journal and e-Health, 20(5), 409–418. https://doi.org/10.1089/tmj.2013.0336

Ferketich S. (1991). Focus on psychometrics. Aspects of item analysis. Research in Nursing & Health, 14(2), 165–168. https://doi.org/10.1002/nur.4770140211

Gagnon, M. P., Orruño, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. (2012). Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemedicine Journal and e-Health, 18(1), 54–59. https://doi.org/10.1089/tmj.2011.0066

Garvey, C., Bayles, M. P., Hamm, L. F., Hill, K., Holland, A., Limberg, T. M., & Spruit, M. A. (2016). Pulmonary rehabilitation exercise prescription in chronic obstructive pulmonary disease: review of selected guidelines: An official statement from the american association of cardiovascular and pulmonary rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention, 36(2), 75–83. https://doi.org/10.1097/HCR.0000000000000171

Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O'Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., Duda, S. N., & REDCap Consortium (2019). The REDCap consortium: Building an international community of software platform partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/10.1016/j.jbi.2019.103208

Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. https://doi.org/10.1080/07421222.1999.11518247

Huis in 't Veld, R. M., Kosterink, S. M., Barbe, T., Lindegård, A., Marecek, T., & Vollenbroek-Hutten, M. M. (2010). Relation between patient satisfaction, compliance and the clinical benefit of a teletreatment application for chronic pain. Journal of Telemedicine and Telecare, 16(6), 322–328. https://doi.org/10.1258/jtt.2010.006006

Keating, A., Lee, A., & Holland, A. E. (2011). What prevents people with chronic obstructive pulmonary disease from attending pulmonary rehabilitation? A systematic review. Chronic Respiratory Disease, 8(2), 89–99. https://doi.org/10.1177/1479972310393756

Ko, F. W., Cheung, N. K., Rainer, T. H., Lum, C., Wong, I., & Hui, D. S. (2017). Comprehensive care programme for patients with chronic obstructive pulmonary disease: A randomised controlled trial. Thorax, 72(2), 122–128. https://doi.org/10.1136/thoraxjnl-2016-208396

Kowitlawakul Y. (2011). The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU). Computers, Informatics, Nursing, 29(7), 411–418. https://doi.org/10.1097/NCN.0b013e3181f9dd4a

Liu, L., Miguel Cruz, A., Rios Rincon, A., Buttar, V., Ranson, Q., & Goertzen, D. (2015). What factors determine therapists' acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disability and Rehabilitation, 37(5), 447–455. https://doi.org/10.3109/09638288.2014.923529

Liu, X. L., Tan, J. Y., Wang, T., Zhang, Q., Zhang, M., Yao, L. Q., & Chen, J. X. (2014). Effectiveness of home-based pulmonary rehabilitation for patients with chronic obstructive pulmonary disease: A meta-analysis of randomized controlled trials. Rehabilitation Nursing, 39(1), 36–59. https://doi.org/10.1002/rnj.112

Rho, M. J., Choi, I. Y., & Lee, J. (2014). Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International Journal of Medical Informatics, 83(8), 559–571. https://doi.org/10.1016/j.ijmedinf.2014.05.005

Ries, A. L., Bauldoff, G. S., Carlin, B. W., Casaburi, R., Emery, C. F., Mahler, D. A., Make, B., Rochester, C. L., Zuwallack, R., & Herrerias, C. (2007). Pulmonary Rehabilitation: Joint ACCP/AACVPR Evidence-Based Clinical Practice Guidelines. Chest, 131(5 Suppl), 4S–42S. https://doi.org/10.1378/chest.06-2418

Spruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., Gosselink, R., … ATS/ERS Task Force on Pulmonary Rehabilitation (2013). An official American Thoracic Society/European Respiratory Society statement: Key concepts and advances in pulmonary rehabilitation. American Journal of Respiratory and Critical Care Medicine, 188(8), e13–e64. https://doi.org/10.1164/rccm.201309-1634ST

Tang, J., Mandrusiak, A., & Russell, T. (2012). The feasibility and validity of a remote pulse oximetry system for pulmonary rehabilitation: A pilot study. International Journal of Telemedicine and Applications, 2012, 798791. https://doi.org/10.1155/2012/798791

Wade, V. A., Eliott, J. A., & Hiller, J. E. (2014). Clinician acceptance is the key factor for sustainable telehealth services. Qualitative Health Research, 24(5), 682–694. https://doi.org/10.1177/1049732314528809

Zailani, S., Gilani, M. S., Nikbin, D., & Iranmanesh, M. (2014). Determinants of telemedicine acceptance in selected public hospitals in Malaysia: Clinical perspective. Journal of Medical Systems, 38(9), 111. https://doi.org/10.1007/s10916-014-0111-4

Almojaibel A. A. (2016). Delivering pulmonary rehabilitation for patients with chronic obstructive pulmonary disease at home using telehealth: A review of the literature. Saudi Journal of Medicine & Medical Sciences, 4(3), 164–171. https://doi.org/10.4103/1658-631X.188247

Almojaibel, A. A., Munk, N., Goodfellow, L. T., Fisher, T. F., Miller, K. K., Comer, A. R., Bakas, T., & Justiss, M. D. (2019). Development and validation of the tele-pulmonary rehabilitation acceptance scale. Respiratory Care, 64(9), 1057–1064. https://doi.org/10.4187/respcare.06432

Asaro, P. V., Williams, J., & Banet, G. A. (2004). Measuring the effect of a computerized nursing documentation system with objective measures and reported perceptions. Annals of Emergency Medicine, 4(44), S131-S132. https://doi.org/10.1016/j.annemergmed.2004.07.420

Brewster, L., Mountain, G., Wessels, B., Kelly, C., & Hawley, M. (2014). Factors affecting front line staff acceptance of telehealth technologies: A mixed-method systematic review. Journal of Advanced Nursing, 70(1), 21–33. https://doi.org/10.1111/jan.12196

Chen, J., Jin, W., Zhang, X. X., Xu, W., Liu, X. N., & Ren, C. C. (2015). Telerehabilitation approaches for stroke patients: Systematic review and meta-analysis of randomized controlled trials. Journal of Stroke and Cerebrovascular Diseases, 24(12), 2660–2668. https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.09.014

Doarn, C. R., Pruitt, S., Jacobs, J., Harris, Y., Bott, D. M., Riley, W., Lamer, C., & Oliver, A. L. (2014). Federal efforts to define and advance telehealth--a work in progress. Telemedicine Journal and e-Health, 20(5), 409–418. https://doi.org/10.1089/tmj.2013.0336

Ferketich S. (1991). Focus on psychometrics. Aspects of item analysis. Research in Nursing & Health, 14(2), 165–168. https://doi.org/10.1002/nur.4770140211

Gagnon, M. P., Orruño, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. (2012). Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemedicine Journal and e-Health, 18(1), 54–59. https://doi.org/10.1089/tmj.2011.0066

Garvey, C., Bayles, M. P., Hamm, L. F., Hill, K., Holland, A., Limberg, T. M., & Spruit, M. A. (2016). Pulmonary rehabilitation exercise prescription in chronic obstructive pulmonary disease: Review of selected guidelines: An official statement from the american association of cardiovascular and pulmonary rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention, 36(2), 75–83. https://doi.org/10.1097/HCR.0000000000000171

Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O'Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., Duda, S. N., & REDCap Consortium (2019). The REDCap consortium: Building an international community of software platform partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/10.1016/j.jbi.2019.103208

Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. https://doi.org/10.1080/07421222.1999.11518247

Huis in 't Veld, R. M., Kosterink, S. M., Barbe, T., Lindegård, A., Marecek, T., & Vollenbroek-Hutten, M. M. (2010). Relation between patient satisfaction, compliance and the clinical benefit of a teletreatment application for chronic pain. Journal of Telemedicine and Telecare, 16(6), 322–328. https://doi.org/10.1258/jtt.2010.006006

Keating, A., Lee, A., & Holland, A. E. (2011). What prevents people with chronic obstructive pulmonary disease from attending pulmonary rehabilitation? A systematic review. Chronic Respiratory Disease, 8(2), 89–99. https://doi.org/10.1177/1479972310393756

Ko, F. W., Cheung, N. K., Rainer, T. H., Lum, C., Wong, I., & Hui, D. S. (2017). Comprehensive care programme for patients with chronic obstructive pulmonary disease: A randomised controlled trial. Thorax, 72(2), 122–128. https://doi.org/10.1136/thoraxjnl-2016-208396

Kowitlawakul Y. (2011). The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU). Computers, Informatics, Nursing, 29(7), 411–418. https://doi.org/10.1097/NCN.0b013e3181f9dd4a

Liu, L., Miguel Cruz, A., Rios Rincon, A., Buttar, V., Ranson, Q., & Goertzen, D. (2015). What factors determine therapists' acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disability and Rehabilitation, 37(5), 447–455. https://doi.org/10.3109/09638288.2014.923529

Liu, X. L., Tan, J. Y., Wang, T., Zhang, Q., Zhang, M., Yao, L. Q., & Chen, J. X. (2014). Effectiveness of home-based pulmonary rehabilitation for patients with chronic obstructive pulmonary disease: A meta-analysis of randomized controlled trials. Rehabilitation Nursing, 39(1), 36–59. https://doi.org/10.1002/rnj.112

Rho, M. J., Choi, I. Y., & Lee, J. (2014). Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International Journal of Medical Informatics, 83(8), 559–571. https://doi.org/10.1016/j.ijmedinf.2014.05.005

Ries, A. L., Bauldoff, G. S., Carlin, B. W., Casaburi, R., Emery, C. F., Mahler, D. A., Make, B., Rochester, C. L., Zuwallack, R., & Herrerias, C. (2007). Pulmonary Rehabilitation: Joint ACCP/AACVPR Evidence-Based Clinical Practice Guidelines. Chest, 131(5 Suppl), 4S–42S. https://doi.org/10.1378/chest.06-2418

Spruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., Gosselink, R., … ATS/ERS Task Force on Pulmonary Rehabilitation (2013). An official American Thoracic Society/European Respiratory Society statement: Key concepts and advances in pulmonary rehabilitation. American Journal of Respiratory and Critical Care Medicine, 188(8), e13–e64. https://doi.org/10.1164/rccm.201309-1634ST

Tang, J., Mandrusiak, A., & Russell, T. (2012). The feasibility and validity of a remote pulse oximetry system for pulmonary rehabilitation: A pilot study. International Journal of Telemedicine and Applications, 2012, 798791. https://doi.org/10.1155/2012/798791

Wade, V. A., Eliott, J. A., & Hiller, J. E. (2014). Clinician acceptance is the key factor for sustainable telehealth services. Qualitative Health Research, 24(5), 682–694. https://doi.org/10.1177/1049732314528809

Zailani, S., Gilani, M. S., Nikbin, D., & Iranmanesh, M. (2014). Determinants of telemedicine acceptance in selected public hospitals in Malaysia: Clinical perspective. Journal of Medical Systems, 38(9), 111. https://doi.org/10.1007/s10916-014-0111-4

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2020-06-30

How to Cite

Almojaibel, A. A., Munk, N., Goodfellow, L. T., Fisher, T. F., Miller, K. K., Comer, A. R., Bakas, T., & Justiss, M. D. (2020). Health Care Practitioners’ Determinants of Telerehabilitation Acceptance. International Journal of Telerehabilitation, 12(1), 43–50. https://doi.org/10.5195/ijt.2020.6308

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Vol. 12 No. 1 (2020)

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Research

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