A location-based prompting system to transition autonomously through vocational tasks for individuals with cognitive impairments
Highlights
► For individuals to manage vocational tasks across multiple workstations in a workplace independently, a location-based handheld system was employed with success. ► Single subject research design was used with two adults who were diagnosed with cognitive disability. ► Data showed that the participants improve vocational performance during the intervention phases.
Introduction
Job coaches at rehabilitation institutes serve as social workers and employment service providers. They work with individuals with cognitive impairments to support them in learning new job skills and maintaining paid employment (Bond et al., 1997, Bond and Liberman, 1992, Goodwin, 1997). They may work for weeks helping a trainee learn how to improve work quality. Even so, the individual may still require assistance of one form or the other. While at the work, trainees often need to be reminded by job coaches from the supporting group in order to keep things in control. Without proper intervention, paid job offers for many individuals with cognitive impairments have been declined because they failed to meet pre-practice task performance standards. For example, they may occasionally forget the procedures to make photocopies in an office setting or misplace salads when preparing food in kitchens.
Strategies incorporating the use of various technologies for the cognitively impaired have been developed for skill training of activities of daily living (ADL) across numerous settings (Cannella-Malone et al., 2006, Mechling and Ortega-Hurndon, 2007, Van Laarhoven and Van Laarhoven-Myers, 2006). Recently, supported employment programs targeted for people transitioning from institutional to community care have created more demand of cognitive aids to increase their workplace independence (Chang et al., 2010a, Chang et al., 2011). Automatic prompting would constitute a viable approach if mild stimuli delivered through an inconspicuous device could lead the subject to complete responses without staff intervention. Such a possibility would significantly improve the subject's achievement, occupational perspectives, and level of autonomy. With proper prompts the individuals may increase their effectiveness and efficiency in skill acquisition and task performance. Moreover, it would be easily viable in terms of time and cost.
Prompting systems provide antecedent cue regulation procedures that facilitate a shift in stimulus control from an individual to the system itself allowing the user more autonomous functioning. For example, picture prompts facilitate user performance by sequentially introducing visual depictions of task steps. Auditory prompts are recorded audio cues that facilitate user performance in completing targeted tasks and are typically delivered via portable devices (Carmien et al., 2005, Cihak et al., 2007, Cihak et al., 2008, Sohlberg et al., 2007). In laboratory settings (Liu et al., 2007), field trials (Carmien et al., 2005) and community-based experiments (Gentry, Wallace, Kvarfordt, & Lynch, 2008), PDAs have been used as cognitive aids for the participating individuals with cognitive impairments.
One of the key research issues in task prompting is the timing of the prompts. Researchers are faced with challenges of when, where, and how the prompts are delivered to the users. The state of the art includes “Wizard of Oz” approaches (Liu et al., 2007, Sohlberg et al., 2007), user self-conscience (Cihak et al., 2008), or constant time delay (CTD) (Cannella-Malone et al., 2006, Gentry et al., 2008) in order to trigger the prompts for planned task steps. The “Wizard of Oz” approach involving humans to operate electronic equipment is a practice followed by some instructors when interventions are implemented (Liu et al., 2007, Sohlberg et al., 2007). It is effective but labor intensive and costly. Reminder alarms or constant time delay have proved to be useful in situations such as taking medication or fixing coffee. However, for tasks that take an indefinite amount of time, setting the timers will not be quite helpful if possible at all (Cannella-Malone et al., 2006, Gentry et al., 2008). Self-operated prompting systems require extensive training so that individuals acquire skills to identify when to invoke the prompts just in time (Cihak et al., 2008, Davies et al., 2002). For example, a handheld prompting system (Cihak et al., 2008) with a hardware button to move forward to the next step was employed to transition independently through vocational tasks for individuals with intellectual disabilities. In this case, if a student forgot to press the button after finishing an assigned task, breaks in performance occurred. In addition, Taber-Doughty (2005) reported that students in some cases didn’t like having to continuously press the buttons to get prompts or they simply got messed up when using a self-operated prompting system.
This motivated us to develop a more intelligent prompting system that allows fewer manual steps and shorter learning curves. By bringing ambient intelligence to prompting devices, cognitive load on users can be reduced. The proposed system for task prompting, called Locompt (a portmanteau of the words “Location” and “prompt”), is based on Bluetooth technology which many commercial smart phones such as iPhone, HTC, and Google Phone embed. A Bluetooth-enabled smart phone can sniff ambient sensors of the same type and are suitable for detecting locations. Each Bluetooth sensor has its globally unique ID, called Blue ID, which is assigned by its manufacturer. For locations to be sniffed, a Bluetooth sensor can be permanently placed in each location. A smart phone with embedded Bluetooth module can identify a location by retrieving its unique Blue ID. An individual can use the handheld system to manage vocational tasks across multiple workstations in a workplace independently. Bluetooth as assistive technology has been used in several rehabilitation methods for indoor wayfinding (Chang and Wang, 2010a, Chang and Wang, 2010b) which demonstrated viable strategies that led to automatic response and enhanced adaptation in human-machine interactions. In the Locompt system, in-house developed software is used to transition autonomously through vocational tasks for individuals with cognitive impairments. It uses Bluetooth sensors as distributed cognitive support to enable autonomous task switching across locations in a workplace. Use of this technology can free a job coach from the burden of having to constantly stay with users for vocational training.
Section snippets
Participants
Individuals of disabilities and ages in various ranges were recommended by three participating job coaches and screened according to degrees of cognitive disabilities and the ability to achieve daily living tasks. With long-term observation, the job coach decided that Yvonne and Zen were more ready to participate in experiments than the other trainees were. Yvonne, age 22, was diagnosed as having brain injury and Dementia after she had a car accident six years ago. She has received very good
Results
Fig. 1 shows data for Yvonne. The baseline and intervention phases observed the percentage of correct task steps. During the first baseline phase (five sessions), the percentage of correct task steps was about 48%. During the first intervention phase (11 sessions), the percentage of correct task steps increased to about 98%. The percentage of correct task steps decreased to 49% during the second baseline (six sessions) and increased again, reaching nearly 99% during the second intervention
Discussion
This study assessed the effectiveness of the Locompt system for improving task performance using a baseline/intervention experimental design. Results indicate that for two subjects with cognitive impairments, the Locompt system in conjunction with operant conditioning strategies may facilitate autonomous functioning of vocational jobs across multiple workstations.
During the intervention phase, the percent of correct task steps was significantly greater compared to the baseline. These results
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