2002 Conference Proceedings

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Katya Hill
Edinboro University of Pennsylvania
AAC Institute
102 Compton Hall
Edinboro University of Pennsylvania
Edinboro, PA 16444-0001
Tel: 814-732-2431
Fax: 814-732-1580
Email: khill@edinboro.edu

Barry Romich
Prentke Romich Company
University of Pittsburgh
1022 Heyl Road
Wooster, OH 44691-9786
Tel: 330-262-1984 ext. 211
Fax: 330-263-4829
Email: bromich@aol.com

Snoopi J. Botten
2100 Bloomington Avenue South, Apt. 111
Minneapolis, MN 55404
Tel: 612-872-7233
Email: dectalk@aol.com


This paper discusses AAC evidence-based practice and the privacy protections of consumers regarding the collecting of evidence to support clinical decisions. A brief overview to evidence-based practice and the current tools and methods of language sampling and language activity monitoring are presented. Procedural safeguards for privacy protections and informed decision-making by consumers are offered.

Evidence-Based Practice

The pursuit of any profession yields the most effective results when practice is based on evidence. Evidence to support practice comes from a number of sources. One category is the general knowledge that forms the foundation for the profession. In hierarchical order this might include 1) research based on the actual subject population, 2) research in which the subjects are able-bodied individuals posing as disabled, 3) research not relating to the population being served, and 4) assumptions based on consensus by the field. Research other than that based on the subject population carries the risk of leading to inaccurate or misleading results. The personal knowledge, skill, and experience of the individual service provider supplements the above general knowledge.

The remaining element of information to support evidence-based practice is that which is specific to the individual being served. Again in hierarchical order, the most useful evidence is 1) that based on actual quantitative logged or recorded data on the performance of the individual, 2) surveys or other measurement instruments of a subjective nature, and 3) qualitative descriptive evidence such as may be reported anecdotally.

For people with severe speech disability, the field of augmentative and alternative communication (AAC) offers various options. Among them is the use of assistive technology that includes synthetic and/or digitized speech output. Generally, these services are provided by a speech-language pathologist (SLP) or a team led by an SLP. Like other professionals, speech-language pathologists are rapidly embracing this notion of evidence-based practice, with significant encouragement from their professional organization, the American Speech-Language-Hearing Association (ASHA). ASHA president Jeri Logemann recently stated, "Our professions' futures depend on the effectiveness of our treatments, not on our impressions of their effectiveness."

Language Monitoring

Traditional methods of obtaining language samples have included direct transcription or audio or video recording followed by transcription. Transcripts are then edited and processed using various language analysis programs. Speech-language pathologists have used these methods for years, although not as a routine practice. Only 10% of SLPs report that they use language sampling and observations as part of their standard language assessment battery (Beck, 1996).

Some degree of language activity monitoring has been employed over the years. The Liberator AAC system has an area of memory that maintains the information that left the display, either through clearing the display or scrolling. SLPs continue to use this feature to understand how the system is being used. Also, communication using the Liberator can be accumulated in an area of memory known as a notebook. However, no time or error information is available.

Automated Language Activity Monitoring (LAM)

Until recently, clinical AAC practice was pursued largely as an art rather than as a science. Quantitative data simply was not being collected to allow otherwise. The traditional methods mentioned above were almost never used because of the huge time investment and the long delays before obtaining useful information. Still, language sampling in the natural setting is considered one of the best indicator of an augmented communicator's performance on an AAC system. With the recent development of automated language activity monitoring (LAM) and associated analysis tools, AAC performance measurement has become a clinical reality (Hill & Romich, 1999).

LAM is the recording of the content (one or more letters or words) and time of day of language events. Here is an example from a loud party. The time stamp in a 24 hour format with a resolution of one second is followed by the content between quotes.

20:37:00 "I need "
20:37:05 "*[VOLUME UP]*"
20:37:06 "*[VOLUME UP]*"
20:37:07 "*[VOLUME UP]*"
20:37:14 "something "
20:37:16 "to drink "
20:37:19 "i"
20:37:20 "m"
20:37:24 "m"
20:37:28 "ediately "

Language samples can be collected in the clinical setting or in the natural environment. Each has advantages. Clinical setting collection can be much better controlled and thus can yield data that can be compared to norms and/or previously collected data. Clinical setting procedures are based on picture description, interview, conversation, or clinician choice. Natural environment collection can yield information that may be more indicative of actual daily use of the AAC system.

The LAM data is manually processed or fed into various analysis programs to produce a list of summary measures that can be used to characterize the communication performance of people who rely on AAC. Performance measurement has many values. The analyzed data can be used in the comparison of candidate systems in the assessment process. Data can guide the therapy process. Data can be used to measure outcomes. Data can be used to support single subject and other research studies. SLPs who have used LAM attest to the value that it brings to the clinical process.

Consumer Rights and Privacy

For people who rely on AAC, personal achievement in life is a function of communication effectiveness. These people have the right to the most effective communication possible. Only through quantitative performance measurement can this be achieved and/or confirmed. They have the right to choose AAC service providers who use scientific methods. They have the right to know their communication performance and how it compares to that of others with similar profiles. With this information they can judge the quality and effectiveness of the services they are receiving.

For people who rely on AAC, as with the general population, privacy can be a concern. The very essence of communication is the conveyance of information, some of which may be personal and intended for a specific other party. The use of many modes of communication includes the risk of the message becoming known to others. This is certainly true of conventional, cordless, and wireless telephones, email, and others. Some AAC systems have had features that retain the content of recent conversation. Even the vocabulary in an AAC system, which typically can be learned by anyone, may be considered a matter of privacy.

Therefore, individuals have the right to choose when and where language activity monitoring will occur and who will learn of the content.

Privacy Safeguards

A number of things can be done to minimize concerns for privacy violation. Perhaps the most important is for consumers to know the ethical responsibility of the AAC service provider on this point. For example, the ASHA Code of Ethics includes treatment of the confidential nature of communication and appropriate treatment thereof. Consumers who do not trust the service provider on this point should find a different one who is trusted. (An AAC service provider who does not collect and analyze language samples may not be trusted to achieve the best results in therapy.) Consumers should complete a consent form prior to language sample collection.

If language activity monitoring is to occur in the natural environment, as opposed to the clinical setting, the consumer should be instructed how to turn it off and on. Depending on the system, this could be a single keystroke on the AAC system or a function accessed in a menu or an icon sequence. High performance systems provide for macros which can combine commands with other functions. Therefore a person who never wants natural environment recording to occur could have the data logging turn off with some commonly used other function such as CEAR DISPLAY. When monitoring is turned on, an indication of this would be desirable.

If a person has consented to natural environment logging and forgets to turn the system off, recording some private information, the removal of this information from the logfile can be based on a search for either content or time of day.

AAC systems can have password protection that precludes any unauthorized access to the system or parts of it. Some AAC systems support encryption (Lesher, Moulton, Rinkus, & Higginbotham, 2000). Communication partners may want to know if communication is being logged. A visible notice of the possibility of communication logging can address this concern.


For most people who rely on AAC, their right to the most effective communication possible can only be achieved through language sample collection and analysis. Through the use of appropriate safeguards, privacy concerns can be minimized.


Beck, A.R. (1996). Language assessment methods for three age groups of children. Journal of Children's Communication Development, 17 (2), 51-66.

Hill, K., & Romich, B. (1999). A proposed standard for AAC and writing system data logging for clinical intervention, outcomes measurement, and research. In Proceedings of the RESNA '99 Annual Conference. Arlington, VA: RESNA Press.

Lesher, G.W., Moulton, B.J., Rinkus, G.J., & Higginbotham, D.J. (2000). A universal logging format for augmentative communication. CSUN 2000, California State University, Northridge.

Logemann, J.A. (2000). President's Column: What is evidence based practice and why should we care? ASHA Leader, 5(5), 3.

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