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Journal articles on the topic 'Interactive voice response (IVR)'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Pradani, Winangsari. "Struktur Pesan pada Interactive Voice Response (IVR)." JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI 1, no. 1 (April 4, 2011): 13. http://dx.doi.org/10.36722/sst.v1i1.13.

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Interactive Voice Response (IVR) is an automated telephony system that interacts with callers, gathers information and routes calls to the appropriate recipient. An IVR system (IVRS) accepts a combination of voice telephone input and touch-tone keypad selection and provides appropriate responses in the form of voice, fax, callback, e-mail and perhaps other media. In recent years, many enterprises use IVR as their customer service media. Some problems arise as user problems, that is user have to remembering the too many choices; user does’nt achieve what they want (did not find the right choices); and the worst is tiring finding choices yet they have not find the human operator. This paper will observe the effect of message structuring for IVR customer satisfication. Human information processing (especially audio-based information) theory as well as menu organizing theory will be used as analysis fundamentals. Questionnaire will be distributed to IVR users to grab the real user experience<strong>.</strong>

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Abanoz, Hüseyin, and Özgür Erbaş. "Mass-IVR — A High Performance Outbound Interactive Voice Response Management System." International Journal of Computer Theory and Engineering 8, no. 4 (August 2016): 295–98. http://dx.doi.org/10.7763/ijcte.2016.v8.1061.

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Kopylov, Andrei, Oleg Seredin, Andrei Filin, and Boris Tyshkevich. "Detection of interactive voice response (IVR) in phone call records." International Journal of Speech Technology 23, no. 4 (November 17, 2020): 907–15. http://dx.doi.org/10.1007/s10772-020-09754-3.

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Khudyakov, Polyna, Paul D. Feigin, and Avishai Mandelbaum. "Designing a call center with an IVR (Interactive Voice Response)." Queueing Systems 66, no. 3 (October 14, 2010): 215–37. http://dx.doi.org/10.1007/s11134-010-9193-y.

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Shaw, William S., and Santosh K. Verma. "Data Equivalency of an Interactive Voice Response System for Home Assessment of Back Pain and Function." Pain Research and Management 12, no. 1 (2007): 23–30. http://dx.doi.org/10.1155/2007/185863.

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BACKGROUND: Interactive voice response (IVR) systems that collect survey data using automated, push-button telephone responses may be useful to monitor patients’ pain and function at home; however, its equivalency to other data collection methods has not been studied.OBJECTIVES: To study the data equivalency of IVR measurement of pain and function to live telephone interviewing.METHODS: In a prospective cohort study, 547 working adults (66% male) with acute back pain were recruited at an initial outpatient visit and completed telephone assessments one month later to track outcomes of pain, function, treatment helpfulness and return to work. An IVR system was introduced partway through the study (after the first 227 participants) to reduce the staff time necessary to contact participants by telephone during nonworking hours.RESULTS: Of 368 participants who were subsequently recruited and offered the IVR option, 131 (36%) used IVR, 189 (51%) were contacted by a telephone interviewer after no IVR attempt was made within five days, and 48 (13%) were lost to follow-up. Those with lower income were more likely to use IVR. Analysis of outcome measures showed that IVR respondents reported comparatively lower levels of function and less effective treatment, but not after controlling for differences due to the delay in reaching non-IVR users by telephone (mean: 35.4 versus 29.2 days).CONCLUSIONS: The results provided no evidence of information or selection bias associated with IVR use; however, IVR must be supplemented with other data collection options to maintain high response rates.

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Mundt, James C., Peter J. Snyder, Michael S. Cannizzaro, Kara Chappie, and Dayna S. Geralts. "Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology." Journal of Neurolinguistics 20, no. 1 (January 2007): 50–64. http://dx.doi.org/10.1016/j.jneuroling.2006.04.001.

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Mittal, Akhil. "Manual Testing and Quality Monitoring of Interactive Voice Response (IVR) applications." International Journal of Computer Applications 4, no. 6 (July 10, 2010): 30–36. http://dx.doi.org/10.5120/830-1124.

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Kepple, Nancy J., Bridget Freisthler, and Michelle Johnson-Motoyama. "Bias in child maltreatment self-reports using interactive voice response (IVR)." Child Abuse & Neglect 38, no. 10 (October 2014): 1694–705. http://dx.doi.org/10.1016/j.chiabu.2014.04.001.

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Gardner-Bonneau, Daryle, Cristina Delogu, Chuck Green, Lydia Volaitis, Martha Lindeman, and Lila Laux. "Interactive Voice Response (IVR) Systems as Automatic Speech Recognition (ASR) Comes of Age." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 4 (October 1998): 444–47. http://dx.doi.org/10.1177/154193129804200409.

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While interactive voice response (IVR) systems were rapidly making their way into the workplace, speech scientists were working hard to improve the performance of automatic speech recognition (ASR) systems to foster their acceptance among potential customers. In the last five years, great strides have been made in this regard, and the commercial use ASR is on the rise. The purpose of this panel is to explore the impact that ASR is (or is not) having on the design of IVR systems that were envisioned originally to operate solely via touch-tone input.

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Forrester, Mathias B., John F. Villanacci, and Norma Valle. "Use of Interactive Voice Response Technology by Poison Centers during the H1N1 Outbreak." Prehospital and Disaster Medicine 25, no. 5 (October 2010): 415–18. http://dx.doi.org/10.1017/s1049023x00008475.

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AbstractIntroduction:Interactive voice response (IVR) technology may facilitate poison centers to handle increased call volumes that may occur during public health emergencies. On 28 April 2009, the Texas Poison Center Network (TPCN) added a H1N1 message in English and Spanish to its IVR system. This study tested whether IVR technology could be used to assist Texas poison centers during the H1N1 outbreak.Methods:The distribution of callers who accessed the H1N1 message during 29 April–31 May 2009 was determined with respect to message language, subsequent caller action, and date of the call.Results:The H1N1 message was accessed by 1,142 callers, of whom, 92.9% listened to the message in English, and 7.1% listened to the message in Spanish. After listening to the message, 33.3% hung up while 66.7% spoke to a poison center agent. The number of callers who accessed the message was highest on 29 April 2009 and then declined.Conclusions:Interactive voice response technology can be used to assist poison centers to provide information and handle calls from the public during a public health emergency.

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Stritzke, Werner G. K., Justine Dandy, Kevin Durkin, and Stephen Houghton. "Use of interactive voice response (IVR) technology in health research with children." Behavior Research Methods 37, no. 1 (February 2005): 119–26. http://dx.doi.org/10.3758/bf03206405.

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Gardner-Bonneau, Daryle Jean. "Human Factors Problems in Interactive Voice Response (IVR) Applications: Do we Need a Guideline/Standard?" Proceedings of the Human Factors Society Annual Meeting 36, no. 3 (October 1992): 222–26. http://dx.doi.org/10.1518/107118192786751899.

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The purpose of this paper is to present a case for the development of a user interface design guideline or standard for interactive voice response applications, to be widely disseminated throughout business and industry. A number of sample problems are cited, based on the author's consulting experience in this area, which serve to demonstrate that many of the problems encountered in IVR application development, particularly in scripting/dialogue design and use of automated speech recognition as a front-end, are not only solvable, but easily avoidable, given the current human factors knowledge base. The paper also discusses the Specification Document developed by the Voice Messaging User Interface Forum (1990, April), and the reasons why it cannot be applied, as written, to the user interface design of more complex IVR applications. Finally, the author proposes an approach to developing the proposed guideline/standard.

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Motta, Isabela, Jorge Lopes, and Manuela Quaresma. "Interactive Voice Response systems for informing citizens about the COVID-19 pandemic: A study on Brazil's Disque Saúde." Strategic Design Research Journal 13, no. 3 (December 23, 2020): 552–63. http://dx.doi.org/10.4013/sdrj.2020.133.20.

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In order to slow down the spread of the coronavirus SARS-CoV-2, it is vital to adopt measures to inform citizens about preventive actions. Such an operation requires a wide-ranged system that comprises a variety of interfaces as channels between citizens and healthcare authority’s information services. Amongst such interfaces, the Interactive Voice Response (IVR) systems can present benefits for informing citizens about the pandemic. Although the literature shows that IVR systems have been used for healthcare, the extent of the COVID-19 pandemic demands new examinations on the role of IVR systems on a multiplatform system for delivering information. This paper aimed to identify gaps and opportunities for the use of IVR systems to inform citizens about the COVID-19 pandemic. A case study was conducted by mapping the Brazilian Ministry of Healthcare’s channels of information about the coronavirus and analyzing the Disque Saúde IVR system – a phone-based ombudsman channel - based on literature recommendations. The results showed that while IVR systems have great potential for accessibility, it is essential that all types of information are available and continuously updated for citizens. Furthermore, the vast and mutable availability of information in a pandemic scenario may be a challenge for the usability of such systems.

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Ainsworth, Matthew. "Effects of Interactive Voice Response (IVR) Counseling on Physical Activity Benefits and Barriers." Health Behavior and Policy Review 7, no. 5 (October 2020): 407–15. http://dx.doi.org/10.14485/hbpr.7.5.3.

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Perrine, M. W., J. C. Mundt, J. S. Searles, and L. S. Lester. "Validation of daily self-reported alcohol consumption using interactive voice response (IVR) technology." Journal of Studies on Alcohol 56, no. 5 (September 1995): 487–90. http://dx.doi.org/10.15288/jsa.1995.56.487.

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., Tubonimi Jenewari. "INTERACTIVE VOICE RESPONSE (IVR) ELECTRONIC CONTROL UNIT (ECU) FOR UNMANNED GROUND VEHICLE (UGV)." International Journal of Research in Engineering and Technology 04, no. 11 (November 25, 2015): 199–201. http://dx.doi.org/10.15623/ijret.2015.0411034.

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Perera, Kasun, Nuwan Waidyanatha, Tharaka Wilfred, Manoj Silva, Brenda Burrell, and Tichafara Sigauke. "Complexity and Usability of Voice-Enabled Alerting and Situational Reporting Decoupled Systems." International Journal of Information Systems for Crisis Response and Management 4, no. 4 (October 2012): 38–58. http://dx.doi.org/10.4018/jiscrm.2012100103.

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Telephone calls are the predominant telecommunication mode in Sri Lanka (Zainudeen et al). Leveraging low cost voice-based applications for disaster communication would be acceptable and sustainable. The findings in this paper are from an experiment concerning interactive voice for connecting community-based emergency field operatives with their central emergency coordination hub. Challenge was in interchanging the Freedom Fone (FF) Interactive Voice Response (IVR) generated, Sinhala and Tamil language speech data with the text-based ’Sahana’ disaster management system for analysis and decision support. Human interactions with the two decoupled software systems to accomplish the sequence of tasks, point to instabilities. Emergency Data Exchange Language (EDXL), a XML-based, interoperable content standard was adopted for mediation between the two disparate systems. Low quality voice data resulting in incomplete information was a barrier to automating transformations between the FF IVR and Sahana. Replacing these processes with human procedures significantly degrades the reliability. This paper discusses the complexities, usability and utility shortcomings discovered through controlled-exercises, in Sri Lanka.

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Kerta, Johan Muliadi, Wike Apryanto Jufri, Alexander Aryo Nugroho, and Andreas Kurniawan. "Analisis dan Perancangan Sistem Interactive Voice Response (IVR) Berbasis Openvxi Menggunakan Asterisk Pada Hotel Sahid Jaya." ComTech: Computer, Mathematics and Engineering Applications 1, no. 2 (December 1, 2010): 723. http://dx.doi.org/10.21512/comtech.v1i2.2573.

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The purpose of this study is to provide a deep understanding of technology of IVR (Interactive Voice Recognition) in OpenVXI based network using Asterisk, that help Sahid Jaya hotel to streamline communication with the guests, improving service and employee effectiveness. The methodology used is analysis which is through surveys, observation and interviews with the company and the design method by designing system from the existing needs analysis. The results obtained from this research is Communication System based in IVR OpenVXI can be applied to existing VoIP network, without disrupting the existing network. Some existing services can be supported with this system usage. Conclusions can be drawn is the use of IVR in the network using VoIP technology is the best solution to overcome the problems and needs of the hospitality which one of these is limited information guest cna get that can provided by non-operators and for support service improvement.

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Mocanu, Bogdan-Costel, Ion-Dorinel Filip, Remus-Dan Ungureanu, Catalin Negru, Mihai Dascalu, Stefan-Adrian Toma, Titus-Constantin Balan, Ion Bica, and Florin Pop. "ODIN IVR-Interactive Solution for Emergency Calls Handling." Applied Sciences 12, no. 21 (October 26, 2022): 10844. http://dx.doi.org/10.3390/app122110844.

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Human interaction in natural language with computer systems has been a prime focus of research, and the field of conversational agents (including chatbots and Interactive Voice Response (IVR) systems) has evolved significantly since 2009, with a major boost in 2016, especially for industrial solutions. Emergency systems are crucial elements of today’s societies that can benefit from the advantages of intelligent human–computer interaction systems. In this paper, we present two solutions for human-to-computer emergency systems with critical deadlines that use a multi-layer FreeSwitch IVR solution and the Botpress chatbot platform. We are the pioneers in Romania who designed and implemented such a solution, which was evaluated in terms of performance and resource management concerning Quality of Service (QoS). Additionally, we assessed our Proof of Concept (PoC) with real data as part of the system for real-time Romanian transcription of speech and recognition of emotional states within emergency calls. Based on our feasibility research, we concluded that the telephony IVR best fits the requirements and specifications of the national 112 system, with the presented PoC ready to be integrated into the Romanian emergency system.

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Hamidi, Mohamed, Hassan Satori, Ouissam Zealouk, and Naouar Laaidi. "Estimation of ASR Parameterization for Interactive System." International Journal of Natural Computing Research 10, no. 1 (January 2021): 28–40. http://dx.doi.org/10.4018/ijncr.2021010103.

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In this study, the authors explore the integration of speaker-independent automatic Amazigh speech recognition technology into interactive applications to extract data remotely from a distance database. Based on the combined interactive voice response (IVR) and automatic speech recognition (ASR) technologies, the authors built an interactive speech system to allow users to interact with the interactive system through voice commands. The hidden Markov models (HMMs), Gaussian mixture models (GMMs), and Mel frequency spectral coefficients (MFCCs) are used to develop a speech system based on the ten first Amazigh digits and six Amazigh words. The best-obtained performance is 89.64% by using 3 HMMs and 16 GMMs.

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Mundt, James C., M. W. Perrine, John S. Searles, and Dan Walter. "An application of interactive voice response (ivr) technology to longitudinal studies of daily behavior." Behavior Research Methods, Instruments, & Computers 27, no. 3 (September 1995): 351–57. http://dx.doi.org/10.3758/bf03200429.

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Mukhopadhyay, Prabir, and Sajan S. "Ergonomic design intervention at an Interactive Voice Response (IVR) system in a developing country." Information Design Journal 20, no. 2 (December 31, 2013): 148–60. http://dx.doi.org/10.1075/idj.20.2.05muk.

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Toll, Benjamin A., Ned L. Cooney, Sherry A. McKee, and Stephanie S. O'Malley. "Correspondence between Interactive Voice Response (IVR) and Timeline Followback (TLFB) reports of drinking behavior." Addictive Behaviors 31, no. 4 (April 2006): 726–31. http://dx.doi.org/10.1016/j.addbeh.2005.05.044.

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Andersson, Claes. "Comparison of WEB and Interactive Voice Response (IVR) Methods for Delivering Brief Alcohol Interventions to Hazardous-Drinking University Students: A Randomized Controlled Trial." European Addiction Research 21, no. 5 (2015): 240–52. http://dx.doi.org/10.1159/000381017.

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This study evaluated automated techniques including personalized normative feedback and protective behavioral strategies, for brief interventions intended to reduce peak alcohol concentrations in university students. After completing baseline assessment, a total of 1,678 hazardous-drinking consumers were randomized to a single or a repeated Internet (WEB) or Interactive Voice Response (IVR) intervention, or to a control group (Single WEB: 323; Single IVR: 329; Repeated WEB: 318; Repeated IVR: 334; Control group: 374). At follow-up, six weeks after baseline, questionnaires were returned by 1,422 participants (Single WEB: 277; Single IVR: 286; Repeated WEB: 259; Repeated IVR: 279; Control group: 321). It was found that peak estimated BAC was reduced in the total group (b -0.14, 95% confidence interval (CI) -0.023; -0.005), in the total (b -0.17, 95% CI -0.027; -0.007) and single (b -0.021, 95% CI -0.032; -0.011) WEB group, and in the total (b -0.011, 95% CI -0.021; -0.015) and repeated (b -0.012, 95% CI -0.023; -0.000) IVR groups, compared to controls. The reduction in peak estimated BAC was greater in the single WEB group compared to the single IVR group (b -0.011, 95% CI -0.022; -0.000). This study concluded that both WEB and IVR interventions have a small but significant effect in reducing heavy episodic drinking, which may be due to the relatively large sample size. Repeated intervention may be needed if delivered by IVR.

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Piette, John D., Nicolle Marinec, Esther C. Gallegos-Cabriales, Juana Mercedes Gutierrez-Valverde, Joel Rodriguez-Saldaña, Milton Mendoz-Alevares, and Maria J. Silveira. "Spanish-speaking patients’ engagement in interactive voice response (IVR) support calls for chronic disease self-management: data from three countries." Journal of Telemedicine and Telecare 19, no. 2 (February 2013): 89–94. http://dx.doi.org/10.1177/1357633x13476234.

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We measured Spanish-speaking patients’ engagement in Interactive Voice Response (IVR) calls using data from self-management support studies in Honduras, Mexico and the US. A total of 268 patients with diabetes or hypertension participated in 6-12 weeks of weekly IVR follow-up. Participants had an average of 6.1 years of education, and 73% of them were women. After 2443 person-weeks of follow-up, patients had completed 1494 IVR assessments. The call completion rates were higher in the US (75%) than in Honduras (59%) or Mexico (61 %; P < 0.001). Patients participating with an informal caregiver were more likely to complete calls (adjusted odds ratio 1.5; P = 0.03) while patients reporting fair or poor health at enrolment were less likely (adjusted odds ratio 0.59; P = 0.02). Satisfaction rates were high, with 98% of patients reporting that the system was easy to use, and 86% reporting that the calls helped them a great deal in managing their health problems. IVR self-management support is feasible among Spanish-speaking patients with chronic disease, including those living in less-developed countries. Involving informal caregivers may increase patient engagement.

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Thirumalai, Mohanraj, Nashira Brown, Soumya Niranjan, Sh'Nese Townsend, Mary Anne Powell, Whitney Neal, Erica Schleicher, et al. "An Interactive Voice Response System to Increase Physical Activity and Prevent Cancer in the Rural Alabama Black Belt: Design and Usability Study." JMIR Human Factors 9, no. 1 (January 4, 2022): e29494. http://dx.doi.org/10.2196/29494.

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Background Increased physical activity (PA) levels are associated with reduced risk and improved survival for several cancers; however, most Americans engage in less than the recommended levels of PA. Using interactive voice response (IVR) systems to provide personalized health education and counseling may represent a high-reach, low-cost strategy for addressing physical inactivity and cancer disparities in disproportionately burdened rural regions. However, there has been a paucity of research conducted in this area to date. Objective The aim of this study is to design, develop, and test the usability of an IVR system aimed at increasing PA levels in the rural Alabama Black Belt. Methods A pilot version of the IVR system was used to assess initial feasibility and acceptability. Detailed exit interviews were conducted to elicit participant feedback, which helped inform the development of a substantially upgraded in-house IVR system. This refined IVR system was then subjected to a sequential explanatory mixed methods evaluation. Participating rural county coordinators and research staff (N=10) tested the usability of the IVR system features for 2 weeks and then completed the System Usability Scale and qualitative semistructured interviews. Results The study sample comprised mostly African American people, women, rural county coordinators, and research staff (N=10). Participants rated the IVR system with a mean score of 81 (SD 5) on the System Usability Scale, implying excellent usability. In total, 5 overarching themes emerged from the qualitative interviews: likes or dislikes of the intervention, barriers to or facilitators of PA, technical difficulties, quality of calls, and suggestions for intervention improvement. Message framing on step feedback, call completion incentives, and incremental goal-setting challenges were areas identified for improvement. The positive areas highlighted in the interviews included the personalized call schedules, flexibility to call in or receive a call, ability to make up for missed calls, narration, and PA tips. Conclusions The usability testing and feedback received from the rural county coordinators and research staff helped inform a final round of refinement to the IVR system before use in a large randomized controlled trial. This study stresses the importance of usability testing of all digital health interventions and the benefits it can offer to the intervention.

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Vogel, Adam P., Susan Block, Elaina Kefalianos, Mark Onslow, Patricia Eadie, Ben Barth, Laura Conway, James C. Mundt, and Sheena Reilly. "Feasibility of automated speech sample collection with stuttering children using interactive voice response (IVR) technology." International Journal of Speech-Language Pathology 17, no. 2 (July 14, 2014): 115–20. http://dx.doi.org/10.3109/17549507.2014.923511.

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Lindsay, Jan A., Charles G. Minard, Sonora Hudson, Charles E. Green, and Joy M. Schmitz. "Using prize-based incentives to enhance daily interactive voice response (IVR) compliance: A feasibility study." Journal of Substance Abuse Treatment 46, no. 1 (January 2014): 74–77. http://dx.doi.org/10.1016/j.jsat.2013.08.003.

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Kaminer, Yifrah, Mark D. Litt, Rebecca H. Burke, and Joseph A. Burleson. "An Interactive Voice Response (IVR) System for Adolescents with Alcohol Use Disorders: A Pilot Study." American Journal on Addictions 15, s1 (January 2006): 122–25. http://dx.doi.org/10.1080/10550490601006121.

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Lundy, J. Jason, Stephen Joel Coons, and Neil K. Aaronson. "Test–Retest Reliability of an Interactive Voice Response (IVR) Version of the EORTC QLQ-C30." Patient - Patient-Centered Outcomes Research 8, no. 2 (June 24, 2014): 165–70. http://dx.doi.org/10.1007/s40271-014-0071-2.

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Kassavou, Aikaterini, and Stephen Sutton. "Reasons for non-adherence to cardiometabolic medications, and acceptability of an interactive voice response intervention in patients with hypertension and type 2 diabetes in primary care: a qualitative study." BMJ Open 7, no. 8 (August 2017): e015597. http://dx.doi.org/10.1136/bmjopen-2016-015597.

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ObjectivesThis study explored the reasons for patients’ non-adherence to cardiometabolic medications, and tested the acceptability of the interactive voice response (IVR) as a way to address these reasons, and support patients, between primary care consultations.Design, method, participants and settingThe study included face-to-face interviews with 19 patients with hypertension and/or type 2 diabetes mellitus, selected from primary care databases, and presumed to be non-adherent. Thirteen of these patients pretested elements of the IVR intervention few months later, using a think-aloud protocol. Five practice nurses were interviewed. Data were analysed using multiperspective, and longitudinalthematic analysis.ResultsNegative beliefs about taking medications, the complexity of prescribed medication regimens, and the limited ability to cope with the underlying affective state, within challenging contexts, were mentioned as important reasons for non-adherence. Nurses reported time constraints to address each patient’s different reasons for non-adherence, and limited efficacy to support patients, between primary care consultations. Patients gave positive experiential feedback about the IVR messages as a way to support them take their medicines, and provided recommendations for intervention content and delivery mode. Specifically, they liked the voice delivering the messages and the voice recognition software. For intervention content, they preferred messages that were tailored, and included messages with ‘information about health consequences’, ‘action plans’, or simple reminders for performing the behaviour.ConclusionsPatients with hypertension and/or type 2 diabetes, and practice nurses, suggested messages tailored to each patient’s reasons for non-adherence. Participants recommended IVR as an acceptable platform to support adherence to cardiometabolic medications between primary care consultations. Future studies could usefully test the acceptability, and feasibility, of tailored IVR interventions to support medication adherence, as an adjunct to primary care.

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Falconi, Michael, Sharon Johnston, and William Hogg. "A scoping review to explore the suitability of interactive voice response to conduct automated performance measurement of the patient’s experience in primary care." Primary Health Care Research & Development 17, no. 03 (August 5, 2015): 209–25. http://dx.doi.org/10.1017/s1463423615000407.

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IntroductionPractice-based performance measurement is fundamental for improvement and accountability in primary care. Traditional performance measurement of the patient’s experience is often too costly and cumbersome for most practices.Objective/MethodsThis scoping review explores the literature on the use of interactive voice response (IVR) telephone surveys to identify lessons for its use for collecting data on patient-reported outcome measures at the primary care practice level.ResultsThe literature suggests IVR could potentially increase the capacity to reach more representative patient samples and those traditionally most difficult to engage. There is potential for long-term cost effectiveness and significant decrease of the burden on practices involved in collecting patient survey data. Challenges such as low response rates, mode effects, high initial set-up costs and maintenance fees, are also reported and require careful attention.ConclusionThis review suggests IVR may be a feasible alternative to traditional patient data collection methods, which should be further explored.

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Tsoli, Stergiani, Stephen Sutton, and Aikaterini Kassavou. "Interactive voice response interventions targeting behaviour change: a systematic literature review with meta-analysis and meta-regression." BMJ Open 8, no. 2 (February 2018): e018974. http://dx.doi.org/10.1136/bmjopen-2017-018974.

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ObjectiveA number of promising automated behaviour change interventions have been developed using advanced phone technology. This paper reviewed the effectiveness of interactive voice response (IVR)-based interventions designed to promote changes in specific health behaviours.MethodsA systematic literature review of papers published between January 1990 and September 2017 in MEDLINE, CINAHL, Embase, PsycINFO, SCOPUS and the Cochrane Central Register of Controlled Trials (CENTRAL) was conducted. From the total of 2546 papers identified, 15 randomised control trials (RCTs) met the eligibility criteria and were included in a random effects meta-analysis. Meta-regression analysis was used to explore whether behaviour change techniques (BCTs) that were used in the interventions were associated with intervention effectiveness.ResultsMeta-analysis of 15 RCTs showed that IVR-based interventions had small but significant effects on promoting medication adherence (OR=1.527, 95% CI 1.207 to 1.932, k=9, p=0.000) and physical activity (Hedges’ g=0.254, 95% CI 0.068 to 0.439, k=3, p=0.007). No effects were found for alcohol (Hedges’ g=−0.077, 95% CI −0.162 to 0.007, k=4, p=0.073) or diet (Hedges’ g=0.130, 95% CI −0.088 to 0.347, k=2, p=0.242). In the medication adherence studies, multivariable meta-regression including six BCTs explained 100% of the observed variance in effect size, but only the BCT ‘information about health consequences’ was significantly associated with effect size (β=0.690, SE=0.199, 95% CI 0.29 to 1.08, p=0.000).ConclusionIVR-based interventions appear promising in changing specific health behaviours, such as medication adherence and physical activity. However, more studies are needed to elucidate further the combination of active components of IVR interventions that make them effective and test their feasibility and effectiveness using robust designs and objective outcome measures.

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Mudliar, Preeti, and Jonathan Donner. "Experiencing interactive voice response (IVR) as a participatory medium: The case of CGNet Swara in India." Mobile Media & Communication 3, no. 3 (March 10, 2015): 366–82. http://dx.doi.org/10.1177/2050157915571591.

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Mundt, James C., Heidi K. Moore, and John H. Greist. "A Novel Interactive Voice Response (IVR) System for Dementia Screening, Education, and Referral: One-Year Summary." Alzheimer Disease & Associated Disorders 19, no. 3 (July 2005): 143–47. http://dx.doi.org/10.1097/01.wad.0000174992.68332.0d.

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Lundy, JJ, SJ Coons, and NK Aaronson. "PCN87 TEST-RETEST RELIABILITY OF AN INTERACTIVE VOICE RESPONSE (IVR) VERSION OF THE EORTC QLQ-C30." Value in Health 12, no. 3 (May 2009): A52—A53. http://dx.doi.org/10.1016/s1098-3015(10)73324-6.

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Twyman, K., S. Goge, A. Arnaout, S. Struthers, H. Sherrard, and B. Quinlan. "USE OF INTERACTIVE VOICE RESPONSE TECHNOLOGY (IVR) TO IMPROVE COMPLIANCE WITH DYSGLYCEMIA BEST PRACTICE GUIDELINES (BPGS)." Canadian Journal of Cardiology 31, no. 10 (October 2015): S327. http://dx.doi.org/10.1016/j.cjca.2015.07.689.

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Brown, Nashira I., Mary Anne Powell, Monica Baskin, Robert Oster, Wendy Demark-Wahnefried, Claudia Hardy, Maria Pisu, et al. "Design and Rationale for the Deep South Interactive Voice Response System–Supported Active Lifestyle Study: Protocol for a Randomized Controlled Trial." JMIR Research Protocols 10, no. 5 (May 25, 2021): e29245. http://dx.doi.org/10.2196/29245.

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Background The rates of physical inactivity and related cancer incidence and mortality are disproportionately high in the Deep South region in the United States, a rural, medically underserved region with a large African American population compared with the rest of the nation. Given this region’s lower rates of literacy and internet access, interactive voice response (IVR) system–automated telephone-based interventions have the potential to help overcome physical activity intervention barriers (literacy, internet access, costs, and transportation) but have yet to be extended to rural, underserved populations, such as in the Deep South. Thus, extensive formative research is being conducted to develop and beta test the Deep South IVR System–Supported Active Lifestyle intervention in preparation for dissemination in rural Alabama counties. Objective This paper aims to describe the design and rationale of an ongoing efficacy trial of the Deep South IVR System–Supported Active Lifestyle intervention. Methods A two-arm randomized controlled trial will be conducted to compare a 12-month physical activity intervention versus a wait-list control condition in 240 underactive adults from 6 rural Alabama counties. The Deep South IVR System–Supported Active Lifestyle intervention is based on the Social Cognitive Theory and includes IVR-automated physical activity–related phone counseling (daily in months 0-3, twice weekly in months 4-6, and weekly in months 7-12) and support from local rural county coordinators with the University of Alabama O’Neal Comprehensive Cancer Center Community Outreach and Engagement Office. The primary outcome is weekly minutes of moderate- to vigorous-intensity physical activity (7-day physical activity recall; accelerometry) at baseline, 6 months, 12 months, and 18 months. Rural Active Living Assessments will be conducted in each rural county to assess walkability, assess recreational amenities, and inform future environment and policy efforts. Results This study was funded in March 2019 and approved by the institutional review board of the University of Alabama at Birmingham in April 2019. As of February 2020, start-up activities (hiring and training staff and purchasing supplies) were completed. Study recruitment and assessments began in September 2020 and are ongoing. As of February 2021, a total of 43 participants have been enrolled in Dallas County, 42 in Sumter County, and 51 in Greene County. Conclusions IVR-supported phone counseling has great potential for addressing physical activity barriers (eg, culture, literacy, cost, or transportation) and reducing related rural health disparities in this region. Trial Registration ClinicalTrials.gov NCT03903874; https://clinicaltrials.gov/ct2/show/NCT03903874. International Registered Report Identifier (IRRID) DERR1-10.2196/29245

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Athikkal, Sagina, and John Jenq. "An Implementation of Voice Assistant for Hospitality." Signal & Image Processing : An International Journal 13, no. 4 (August 31, 2022): 1–11. http://dx.doi.org/10.5121/sipij.2022.13401.

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Voice user interface has gained popularity in the recent years. A chatbot is a machine with the ability to answer automatically through a conversational interface. Instead of using mouse and keyboards as input and screen as output, a chatbot with extra voice user interface feature improve the system and enhance the user experience. A chatbot is considered as one of the most exceptional and promising expressions of human computer interaction. Voice-based chatbots or artificial intelligence (AI) devices transform humancomputer bidirectional interactions that allow users to navigate an interactive voice response (IVR) system with their voice generally using natural language. In this paper, we focus on voice based chatbots for mediating interactions between hotels and guests from both the hospitality technology providers’ and guests’ perspectives. A hotel web application with voice user interface was implemented which provides voice input/output interface to enhance the user experience. Speech recognition component was used to dictate the user voice input to text. Speech synthesis API was used for text to voice conversion. A closed domain question answering (cdQA) Natural Language Processing (NLP) solution was used for processingof query and return the best answer possible.

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Kurniawan, Ashadi. "Penggunaan Teknologi IVR untuk Meningkatkan Kinerja Dosen Praktikum." Teknoin 25, no. 1 (June 24, 2019): 23–30. http://dx.doi.org/10.20885/teknoin.vol25.iss1.art3.

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Lecturers have activities besides teaching as well as conducting research, guiding students who are in the final project, and some who get structural positions. To assist with the accuracy of the teaching process, a system to automatically remind lecturers is made, where a database is connected to the Interactive Voice Response (IVR) system. The performance of this system is tested based on the timeliness and accuracy of the lecturer room extension number contacted. Based on the results of the tests performed, the system can contact the extension number of the lecturer room registered in the database. While the delay of calls from the system to the extension number of the lecturer room reaches 5 seconds on average. So that with the system being created, it can help and expedite the teaching and learning process especially for practicum courses and also improve the performance of Practicum lecturers.

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Ssemugabo, Charles, Elizeus Rutebemberwa, Dan Kajungu, George W. Pariyo, Adnan A. Hyder, and Dustin G. Gibson. "Acceptability and Use of Interactive Voice Response Mobile Phone Surveys for Noncommunicable Disease Behavioral Risk Factor Surveillance in Rural Uganda: Qualitative Study." JMIR Formative Research 3, no. 4 (December 3, 2019): e15000. http://dx.doi.org/10.2196/15000.

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Background There is need for more timely data to inform interventions that address the growing noncommunicable disease (NCD) epidemic. With a global increase in mobile phone ownership, mobile phone surveys can bridge this gap. Objective This study aimed to explore the acceptability and use of interactive voice response (IVR) surveys for surveillance of NCD behavioral risk factors in rural Uganda. Methods This qualitative study employed user group testing (UGT) with community members. The study was conducted at the Iganga-Mayuge Health and Demographic Surveillance Site (IM-HDSS) in Eastern Uganda. We conducted four UGTs which consisted of different categories of HDSS members: females living in urban areas, males living in urban areas, females living in rural areas, and males living in rural areas. Participants were individually sent an IVR survey, then were brought in for a group discussion using a semistructured guide. Data were analyzed thematically using directed content analysis. Results Participants perceived that IVR surveys may be useful in promoting confidentiality, saving costs, and raising awareness on NCD behavioral risk factors. Due to the clarity and delivery of questions in the local language, the IVR survey was perceived as easy to use. Community members suggested scheduling surveys on specific days and sending reminders as ways to improve their use for surveillance. Social issues such as domestic violence and perceptions toward unknown calls, technological factors including poor network connections and inability to use phones, and personal issues such as lack of access to phones and use of multiple networks were identified as barriers to the acceptability and use of mobile phone surveys. However, incentives were reported to motivate people to complete the survey. Conclusions Community members reflected on contextual and sociological implications of using mobile phones for surveillance of NCD behavioral risk factors. The opportunities and challenges that affect acceptability and use of IVR surveys should be considered in designing and implementing surveillance programs for NCD risk factors.

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Colladon, Andrea Fronzetti, Maurizio Naldi, and Massimiliano M. Schiraldi. "Quality Management in the Design of TLC Call Centres." International Journal of Engineering Business Management 5 (January 1, 2013): 48. http://dx.doi.org/10.5772/56921.

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Call centres rely heavily on the self-service paradigm through the use of an automated IVR (Interactive Voice Response) system. The service time delivered by the IVR is a major component of the overall QoS (Quality of Service) delivered by the call centre. We analyse the structure and service times of IVR systems through a case study of five call centres in the telecommunications sector. The service trees of the call centres under survey are reconstructed by complete exploration and analysed through a set of metrics. The present design of service trees leads to service times typically larger than those spent waiting for a human agent and to excessively long announcements, with a negative impact on the overall QoS. Imbalances in the popularity of the services offered by the IVR can be exploited to reduce remarkably the average service time, by properly matching the most popular services with the shortest service times.

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Dillman, Don A., Glenn Phelps, Robert Tortora, Karen Swift, Julie Kohrell, Jodi Berck, and Benjamin L. Messer. "Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the Internet." Social Science Research 38, no. 1 (March 2009): 1–18. http://dx.doi.org/10.1016/j.ssresearch.2008.03.007.

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Byonanebye, Dathan Mirembe, Maria S. Nabaggala, Agnes Bwanika Naggirinya, Mohammed Lamorde, Elizabeth Oseku, Rachel King, Noela Owarwo, et al. "An Interactive Voice Response Software to Improve the Quality of Life of People Living With HIV in Uganda: Randomized Controlled Trial." JMIR mHealth and uHealth 9, no. 2 (February 11, 2021): e22229. http://dx.doi.org/10.2196/22229.

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Background Following the successful scale-up of antiretroviral therapy (ART), the focus is now on ensuring good quality of life (QoL) and sustained viral suppression in people living with HIV. The access to mobile technology in the most burdened countries is increasing rapidly, and therefore, mobile health (mHealth) technologies could be leveraged to improve QoL in people living with HIV. However, data on the impact of mHealth tools on the QoL in people living with HIV are limited to the evaluation of SMS text messaging; these are infeasible in high-illiteracy settings. Objective The primary and secondary outcomes were to determine the impact of interactive voice response (IVR) technology on Medical Outcomes Study HIV QoL scores and viral suppression at 12 months, respectively. Methods Within the Call for Life study, ART-experienced and ART-naïve people living with HIV commencing ART were randomized (1:1 ratio) to the control (no IVR support) or intervention arm (daily adherence and pre-appointment reminders, health information tips, and option to report symptoms). The software evaluated was Call for Life Uganda, an IVR technology that is based on the Mobile Technology for Community Health open-source software. Eligibility criteria for participation included access to a phone, fluency in local languages, and provision of consent. The differences in differences (DIDs) were computed, adjusting for baseline HIV RNA and CD4. Results Overall, 600 participants (413 female, 68.8%) were enrolled and followed-up for 12 months. In the intervention arm of 300 participants, 298 (99.3%) opted for IVR and 2 (0.7%) chose SMS text messaging as the mode of receiving reminders and health tips. At 12 months, there was no overall difference in the QoL between the intervention and control arms (DID=0.0; P=.99) or HIV RNA (DID=0.01; P=.94). At 12 months, 124 of the 256 (48.4%) active participants had picked up at least 50% of the calls. In the active intervention participants, high users (received >75% of reminders) had overall higher QoL compared to low users (received <25% of reminders) (92.2 versus 87.8, P=.02). Similarly, high users also had higher QoL scores in the mental health domain (93.1 versus 86.8, P=.008) and better appointment keeping. Similarly, participants with moderate use (51%-75%) had better viral suppression at 12 months (80/94, 85% versus 11/19, 58%, P=.006). Conclusions Overall, there was high uptake and acceptability of the IVR tool. While we found no overall difference in the QoL and viral suppression between study arms, people living with HIV with higher usage of the tool showed greater improvements in QoL, viral suppression, and appointment keeping. With the declining resources available to HIV programs and the increasing number of people living with HIV accessing ART, IVR technology could be used to support patient care. The tool may be helpful in situations where physical consultations are infeasible, including the current COVID epidemic. Trial Registration ClinicalTrials.gov NCT02953080; https://clinicaltrials.gov/ct2/show/NCT02953080

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Clinton, Joshua D., and Steven Rogers. "Robo-Polls: Taking Cues from Traditional Sources?" PS: Political Science & Politics 46, no. 02 (March 28, 2013): 333–37. http://dx.doi.org/10.1017/s1049096513000012.

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AbstractAfter the 2012 Republican New Hampshire primary, 159 poll results were released prior to the subsequent nomination contests in the Republican presidential primary. More than two-thirds of these polls relied on interactive voice response (IVR) software to conduct the interviews. We evaluate the ability of polls to predict the vote-share for the Republican candidates Romney, Santorum, and Gingrich. We find no overall difference in the average accuracy of IVR and traditional human polls, but IVR polls conducted prior to human polls are significantly poorer predictors of election outcomes than traditional human polls even after controlling for characteristics of the states, polls, and electoral environment. These findings provide suggestive, but not conclusive, evidence that pollsters may take cues from one another given the stakes involved. If so, reported polls should not be assumed to be independent of one another and so-called poll-of-polls will be misleadingly precise.

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Lundy, JJ, and SJ Coons. "PCN82 TESTING THE MEASUREMENT EQUIVALENCE OF PAPER AND INTERACTIVE VOICE RESPONSE (IVR) VERSIONS OF THE EQ-5D." Value in Health 11, no. 6 (November 2008): A485—A486. http://dx.doi.org/10.1016/s1098-3015(10)66619-3.

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Kähr, Caroline, and Martin Steinert. "Explaining the (non) adoption and use of interactive voice response (IVR) among small and medium-sized enterprises." International Journal of Speech Technology 14, no. 1 (December 3, 2010): 11–18. http://dx.doi.org/10.1007/s10772-010-9083-z.

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Toll, Benjamin, Judith Cooney, Sherry McKee, Stephanie O'Malley, and Ned Cooney. "Correspondence of interactive voice response (IVR) reports of nicotine withdrawal, craving, and negative mood with questionnaire ratings." Nicotine & Tobacco Research 10, no. 6 (June 2008): 1057–64. http://dx.doi.org/10.1080/14622200802097498.

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Virzi, Robert A., and John S. Huitema. "Telephone-Based Menus: Evidence that Broader is Better than Deeper." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 41, no. 1 (October 1997): 315–19. http://dx.doi.org/10.1177/107118139704100171.

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Recent guidelines intended for designers of telephone menus for Interactive Voice Response (IVR) systems advocate keeping menus to four or fewer items. Additional items, the guidelines recommend, should appear on a secondary menu accessible from the first. The current study compared this deep-menu approach to a broad-menu approach wherein all the items appear on a single menu. Item selection times favored the broad-menu approach for both repeated and unique trials, casting some doubt on the validity of this particular guideline.

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Fowler, Floyd J., Philip Brenner, Anthony M. Roman, and J. Lee Hargraves. "The Effects of Nonresponse and Sampling Omissions on Estimates on Various Topics in Federal Surveys: Telephone and IVR Surveys of Address-Based Samples." Journal of Official Statistics 36, no. 3 (September 1, 2020): 631–45. http://dx.doi.org/10.2478/jos-2020-0032.

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AbstractWith declining response rates and challenges of using RDD sampling for telephone surveys, collecting data from address-based samples has become more attractive. Two approaches are doing telephone interviews at telephone numbers matched to addresses and asking those at sampled addresses to call into an Interactive Voice Response (IVR) system to answer questions. This study used in-person interviewing to evaluate the effects of nonresponse and problems matching telephone numbers when telephone and IVR were used as the initial modes of data collection. The survey questions were selected from major US federal surveys covering a variety of topics. Both nonresponse and, for telephone, inability to find matches result in important nonresponse error for nearly half the measures across all topics, even after adjustments to fit the known demographic characteristics of the residents. Producing credible estimates requires using supplemental data collection strategies to reduce error from nonresponse.

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