Development and Evaluation of Home-Based Speed-of-Processing Training for Older Adults

Article Outline

• Abstract
• Methods
  • Experiment 1
  • Participants
  • Measures
  • Procedures
    • Computer simulation of videotape training
    • Training
  • Statistical Analysis
  • Experiment 2
  • Participants
  • Measures
    • UFOV test
    • Road sign test
    • Trail Making Test
    • Benton Visual Retention Test
  • Procedures
  • Training
    • Laboratory-based speed-of-processing training
    • Home-based speed-of-processing training
    • Internet training
  • Statistical Analysis
• Results
  • Experiment 1
  • Primary Analyses
    • Estimation of optimal intertrial interval
    • Acceptability of the proposed videotape-training method
  • Experiment 2
    • Evaluation of home-based training
• Discussion
• Conclusions
• Acknowledgment
• References
• Copyright

Abstract 

Wadley VG, Benz RL, Ball KK, Roenker DL, Edwards JD, Vance DE. Development and evaluation of home-based speed-of-processing training for older adults.

Objectives

To develop technical parameters for a videotape-based speed-of-processing training protocol, to evaluate the feasibility of self-administration (experiment 1), and to evaluate the protocol’s effectiveness (experiment 2).

Design

A feasibility study (experiment 1) and a pre-post, 4-arm, nonrandomized controlled trial (experiment 2).

Setting

University research center.

Participants

A population-based sample (37 men, 47 women; age range, 65−94y) (experiment 1). A population-based sample (age ≥65y) with no prior exposure to the Useful Field of View assessment or speed-of-processing training, no dementia or life-limiting illness, a Mini-Mental State Examination score of greater than 24, corrected far visual acuity of greater than or equal to 20/40, contrast sensitivity of greater than or equal to 1.50 log₁₀, and deficient processing speed (experiment 2). For experiment 2, 8 of 189 eligible people declined to participate. The final sample for this experiment included 100 men and 81 women (age range, 65−91y).

Interventions

Eight to ten 1-hour cognitive training sessions.

Main Outcome Measure

Posttraining gains in processing speed.

Results

Self-administration was feasible. Subjects who underwent home-based training improved their processing speed significantly more than either control group (F_3,146=16.16, P<.001). Their gains were 74% as great as the gains of those who underwent trainer-facilitated speed-of-processing training.

Conclusions

People can improve their processing speed at home using readily available technology. Future research should explore the relation of these improvements to driving performance.

Key Words:  Elderly , Information processing, human , Rehabilitation , Training programs

OLDER ADULTS WITH processing-speed impairments are at significantly higher risk for poor driving performance and at-fault motor vehicle crashes than those without these impairments.¹, ² Information-processing speed can be improved with a standardized protocol of trainer-facilitated speed-of-processing training.³, ⁴ The protocol improved the processing speed of 87% of 712 community-dwelling older adults assigned to this training arm in a multisite randomized controlled trial (Advanced Cognitive Training for Independent and Vital Elderly [ACTIVE])⁵; the improvements remained evident 2 years later. With the same training protocol, gains in processing speed have resulted in improved speed and accuracy in the performance of instrumental activities of daily living⁶, ⁷ and in fewer dangerous maneuvers while driving.⁸ Thus, speed-of-processing training can produce gains that have the potential to improve functional performance in older adults. The aim of the present investigation was to modify the training for self-administration. If effective in enhancing the cognitive skills needed to function independently in everyday life, a home-based program might offer a more acceptable and accessible training method for older adults who are at risk for functional declines.

The overall goal of this research was to design (experiment 1) and test (experiment 2) a self-administered, video cassette recorder (VCR)−based training format that would be less costly and more widely available to older adults than laboratory- or clinic-based speed-of-processing training. Each hour of laboratory-based computer training guided by a bachelor’s level trainer in a university research setting costs a minimum of $15 an hour for 10 hours. Each hour guided by an occupational therapist or driving rehabilitation specialist in a clinical setting is estimated at $100 per hour for 10 hours. Thus, the cost of guided training ranges from $150 to $1000, plus the cost of the training software, a touch-screen monitor, and a computer if needed. The cost of self-administered, home-based training would be $50, incurred in the purchase of the videotape series and scoring manual, plus the cost of a VCR if needed.

This article describes the design and effectiveness of this self-administered, videotape-based modification of the trainer-administered, computer-based speed-of-processing training protocol. Experiment 1 evaluated feasibility and developed parameters for modifications that would permit older adults to improve their processing-speed abilities at home. Experiment 2 evaluated the effectiveness of the training program developed through experiment 1 compared with that of the original training protocol. The primary outcome examined in experiment 2 was change in processing-speed abilities; posttraining changes in driving simulator performance will be the focus of a separate study.

Back to Article Outline

Methods 

Experiment 1 

The standard speed-of-processing training protocol requires a personal computer with touch-screen technology and a certified trainer to administer and customize the training to each person’s evolving skill level. Experiment 1 developed a computer simulation of self-administered training, incorporating modifications that would be needed for transferring the protocol to videotape and VCR technology in experiment 2.

To facilitate the transition to videotapes, the simulation contained instructional screens, sample training trials, and the capacity to time participants’ intertrial response recording and evaluation intervals. This simulation enabled evaluation of the fundamental feasibility of self-administration and specification of parameters needed to develop the videotape protocol.

Participants 

Adults aged 65 years and older residing in the Birmingham, AL, metropolitan area were recruited from a zip code−stratified sample of people whose names and addresses only were purchased from Equifax, a credit agency. Letters describing the study were mailed to potential participants, along with prestamped reply postcards. Study personnel telephoned people who returned the reply postcards indicating interest. Thus, although the population of potential recruits was stratified by zip code as a proxy for other important demographic variables, the actual study sample was composed of respondents who did not necessarily represent the pool of potential recruits. These people were asked demographic and eligibility information (≥65y, living independently of formal care, able to read the newspaper and travel to the research center, no diagnosis of dementia or history of stroke within the past year, judged by the interviewer as able to communicate adequately). Those who were eligible and willing to participate were asked about spouses, friends, or relatives who might also wish to participate. A total of 84 people (37 men, 47 women) aged 65 to 94 (mean, 73y) agreed to participate. Eighty-two were white, 1 was black, and 1 was Lebanese. Education ranged from grade 5 to postgraduate, with a mean of 14.8 years.

Measures 

Visual acuity was assessed binocularly with participants’ corrective lenses, if any, by a standard method with an Early Treatment Diabetic Retinopathy Study eye chart. Mental status was screened with the Mini-Mental State Examination (MMSE)⁹; literacy was screened with a timed vocabulary measure containing 18 multiple-choice questions assessing knowledge of word meanings¹⁰, ¹¹; psychomotor speed was screened with the Wechsler Adult Intelligence Scale−Revised digit-symbol substitution test.¹² After completing these assessments, participants underwent a speed-of-processing training session using the computer simulation of videotape training, described below. Finally, participants completed the Technology and Computer Questionnaire,¹³ which assesses accessibility to and familiarity with forms of technology including VCRs and computers; the Life Space Mobility Questionnaire¹⁴; a self-reported health rating; and several questions about the training experience.

Procedures 

Eligible people came to the research center for a single 2-hour visit. At this visit, written informed consent was obtained in accord with the procedures and ethical standards of the institutional review board of the university. The study protocol then proceeded as outlined in the Measures section.

A computer simulation of speed-of-processing training that was compatible with translation to videotape was developed by university media technicians. Like the standard speed-of-processing training protocol,⁵, ¹⁵, ¹⁶ this investigational protocol included training with tasks requiring processing speed (task 1), divided attention (task 2), and selective attention (task 3). Following instructions on the monitor, participants completed 4 practice trials presented at a fixed duration of 667ms for each of the 3 tasks. After each trial, participants practiced recording their responses in pencil on a form developed for this purpose. In both the practice trials and training tasks, stimuli were presented as white targets (2×1.5cm) on a 43.2-cm (17-in) computer monitor viewed from a distance of approximately 60cm. For task 1 trials, each participant was required to identify a central target (car or truck) inside a fixation box. For task 2 trials, a peripheral target (car) was added to the display; each participant was required to identify the central target and locate the peripheral target at 1 of 8 radial locations (0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°) at a distance of 11cm from the fixation box. For task 3 trials, the peripheral target was embedded in distractor stimuli (triangles) of the same size and luminance as the peripheral target.

The investigational protocol incorporated 3 fixed display durations (500, 300, 100ms) presented in 3 blocks of 10 trials for each of the 3 tasks, for a total of 90 trials. Within each block of 10 trials, task displays were presented at increasingly brief durations (4 trials at 500ms, 2 at 300ms, 4 at 100ms). These durations encompass endpoint values at which many people find the task very easy (500ms) or very difficult (100ms). Because our purpose was to capture the intervals necessary for recording responses and evaluating response accuracy, we wanted to ensure adequate sampling of these 2 situations. The 2 trials at 300ms merely served as a transitional mechanism to minimize the perception of abrupt changes in display duration. The dependent variable of primary interest was the length of the intertrial intervals needed for participants to record and evaluate their responses. Optimal intervals could then be used in the home-based training program, obviating a need for use of the VCR’s pause feature.

Each participant trainee viewed the computer simulation of videotape training either with or without another study participant present. We originally believed that the home-based training program might prove challenging for some people, such that they would enlist the help of another person at home if one were available. However, the presence of another person did not meaningfully affect trainees’ use of the home-based training simulation; therefore, this portion of the feasibility study will not be further described.

Participants recorded their responses to each trial on a preprinted form and then pressed a key on the keyboard to time-stamp the response recording interval. They then evaluated the accuracy of their responses by pressing a key that caused the correct response to appear on the computer screen. Finally, they pressed the keyboard again to signal the end of the accuracy-evaluation interval and the beginning of the next trial. Thus, for each trial the software recorded the length of time it took each participant to record the response and the time required to evaluate its accuracy. For each participant, 12 response intervals were obtained. These intervals consisted of each required response (recording the response, evaluating its accuracy) across the 3 task types (processing speed, divided attention, selective attention) at each of the 3 display durations (500, 300, 100ms). A trained observer was also present; this observer independently recorded participants’ responses to later verify participants’ recording accuracy.

Statistical Analysis 

The goals of analyses conducted using SPSS^a for Windows were (1) to determine the optimal intertrial interval for response recording and accuracy evaluation for each of the 3 training tasks by display duration and (2) to evaluate the acceptability of the proposed videotape-training method. Optimal intertrial intervals for response recording and response evaluation were determined via frequency distributions generated for each of the 3 training tasks (processing speed, divided and selective attention) and display durations (500, 300, 100ms). Student t tests were used to evaluate differences in response recording and accuracy evaluation intervals by display duration and task type, and multivariate analysis of covariance (MANCOVA) was used to assess differences in interval durations by education level, age, self-rated health, and technology experience. Questionnaire data evaluated ease and acceptability of the proposed videotape-training method. Frequencies were examined, and nonparametric chi-square analyses were used to determine whether acceptability varied as a function of education level. Logistic and linear regression models were used to determine whether acceptability and ease of use, respectively, varied by education, age, self-rated health, technology experience, or MMSE score.

Experiment 2 

Experiment 2 explored whether self-administered, home-based speed-of-processing training could produce gains in processing speed comparable to or approaching the level of gains associated with guided, laboratory-based training. Technical parameters and qualitative data gathered from experiment 1 were used by the media group to produce a series of 8 videotapes, each containing multiple training trials with increasingly complex task demands, and a self-scoring, home-use manual. The format consisted of 2 training blocks per tape, with 2 training blocks devoted to task 1 (processing speed) (tape 1), 6 training blocks devoted to task 2 (divided attention) (tapes 2–4), and 8 training blocks devoted to task 3 (selective attention) (tapes 5–8). These materials were successfully piloted among a sample of 10 older adults who had participated in prior studies at the research center.

Participants 

Recruitment procedures were identical to those used in experiment 1. Additional eligibility criteria included no prior exposure to the Useful Field of View (UFOV) assessment or to speed-of-processing training. Those who passed telephone screening were scheduled for an in-person screening of mental status, vision, processing speed, and driving simulator performance. (Participants’ baseline and posttraining driving simulator performance will be the topic of a separate study.) This screening process yielded 189 people with intact mental status (MMSE score ≥25), intact vision (corrected far visual acuity ≥20/40, contrast sensitivity ≥1.50 log₁₀), and deficient processing speed (UFOV subtests 3 and 4 combined score ≥800ms). All of these people were invited to participate in the study. Eight people declined to participate because of illness or lack of time. The resulting sample of 181 participants (100 men, 81 women) aged 65 to 94 years (mean, 75y) included 147 white and 34 black participants with education ranging from grade 8 to postgraduate, with a mean of 14 years of education.

Measures 

In addition to far visual acuity, the MMSE, and digit symbol substitution, all of which were administered according to protocols described in experiment 1, contrast sensitivity was measured binocularly (with participants’ corrective lenses, if applicable) using the Pelli-Robson Contrast Sensitivity chart.¹⁷ Cognitive function (processing speed, attention, reaction time, executive function, visual memory) also was evaluated with the following measures.

The UFOV test¹⁸, ¹⁹, ²⁰ measures the briefest duration at which one can process multiple stimuli in the visual field. It assesses information processing speed, selective attention, and divided attention through 4 increasingly complex subtests presented on a computer. The UFOV test has good reliability and validity,²¹ and UFOV performance is a unique predictor of mobility outcomes for events such as motor vehicle crashes among older adults.² Four scores, which may be summed to form a single composite score, are derived. Each score represents the briefest display duration (in milliseconds) at which each participant achieved accuracy on 75% of trials.

The road sign test⁵, ⁶, ⁸, ²² is a computer-administered measure of reaction time and everyday speed. On a computer screen, participants view a series of changing road signs and respond by either moving or clicking the mouse, depending on the nature of the stimuli. Before the test trials, all participants practice clicking and moving the mouse until proficiency is demonstrated. The 24 test trials are composed of 12 trials each of 3-stimuli and 6-stimuli conditions. The average reaction time is calculated for all participants for both 3- and 6-stimuli conditions.

The Trail Making Test Part B (TMT-B)²³ has been described as a test of mental set flexibility,²⁴, ²⁵ an aspect of executive function. Participants draw a line connecting 25 circles containing either a number or a letter in alternating sequence as quickly as possible (eg, 1 – A – 2 – B). The time in seconds required to complete the task is recorded.

The Benton Visual Retention Test (BVRT) (Form C, Administration A)²⁶ evaluates visual memory.²⁷ Participants are shown a series of 10 geometric designs, are given 10 seconds to view each, and then draw each design from memory immediately after the design has been removed from sight. Scores reflect the number of designs correctly drawn.

Procedures 

Potential participants were asked to attend a 90-minute screening visit to determine eligibility for the project. Written informed consent was administered in accord with the procedures and ethical standards of the institutional review board of the university. The stated purpose of the study was “to test a video training program that would permit older individuals to practice their visual attention and processing speed abilities at home…compared to a computer based training program that in prior research has produced improved attention and mental processing speed…. These skills are related to good driving.” Participants were informed that “you may not personally benefit from your participation… however, your participation may provide valuable knowledge about cognitive training of skills thought to be critical to mobility and independence.” At the screening visit, participants’ vision, mental status, UFOV performance, and driving-simulator performance were assessed. People who met eligibility thresholds were asked to return for a 1-hour baseline visit during which assessments of cognitive function were completed in a fixed order. Participants then were assigned to 1 of 4 training conditions: standard laboratory-based speed-of-processing training (n=42), Internet training (a social- and computer-contact control condition) (n=42), home-based speed-of-processing training (n=65), or a no-contact control condition (n=32). Pending completion of videotape production, the first 2 conditions were assigned according to an alternating schedule before the remaining 2 conditions, which were subsequently assigned according to a schedule of 2 to home-based training for every 1 no-contact control (because home-based training was the condition of greatest experimental interest). Home-based training was self-administered by videotape in each participant’s home. Those assigned to the laboratory-based, Internet, and home-based training conditions were asked to complete ten 1-hour training sessions over the course of 5 weeks. On completion of this 5-week interval (ie, at the end of training or an equivalent time period), all participants including no-contact controls were asked to return for posttest visits, at which the baseline cognitive measures were readministered. An experimenter-generated questionnaire evaluating the home-based training program was administered only to those who participated in this condition.

Training 

Laboratory-based speed-of-processing training participants were invited to attend ten 1-hour training sessions over a 5-week period. Each session included a certified trainer with 2 to 3 participants. Sessions began with a discussion of how attention and processing-speed skills relate to everyday activities such as driving, falls, and mobility. The standardized, trainer-guided, computer-based speed-of-processing training protocol, described in detail elsewhere,⁶, ⁷, ⁸ was used in this study. Ninety-three percent of participants assigned to this arm of the study completed at least 8 of the 10 training sessions, which is the threshold used in this and prior studies to signify a full “dose” of training. The trainer decides, based on a subject’s baseline UFOV performance, the level at which to begin training. The subtests that are used to evaluate UFOV performance are the basis for the speed-of-processing training; however, training does not consist of practicing the UFOV test itself. The complexity and duration of each training task are customized by the trainer based on each participant’s performance. Once a participant achieves 75% proficiency at a specified level, the trainer increases complexity by changing the center task demand, increasing the eccentricity of the peripheral target, reducing the conspicuity (luminance) of the stimuli, or decreasing the specified display duration. Once mastery of a particular task is achieved at the briefest display duration, with the most demanding center task and with the peripheral target at the farthest eccentricity, the participant advances to a more difficult task (eg, from divided attention to selective attention). Thus, the protocol requires participants to practice on a variety of stimuli at a variety of durations.

Participants assigned to home-based training were oriented by the experimenter to pertinent training procedures and materials, including the series of 8 videotapes, each containing multiple training trials; the manual containing written instructions (including how to minimize glare on the television screen, the importance of choosing viewing times when distractions could be avoided, the order in which to proceed through the tapes); multiple scoring sheets; and diary pages on which to record the date of each session and any problems encountered during that session. As in the laboratory-training arm of the study, participants in the home-based training arm were asked to complete and to document their completion of two 1-hour training sessions per week over a 5-week period.

The series of home-based training videotapes is introduced and guided by a narrator. The narrator clearly explains the demands of each task and the scoring methods. The video practice and training trials include the same range of display durations and near versus far peripheral targets that are used in the laboratory-based training protocol, with corresponding increases in levels of difficulty across sessions. Thus, the content of the 10 home-based sessions mimics the 10 training sessions used in the laboratory protocol. The home-based, videotape-training protocol also incorporates some aspects of customized speed of processing training, using the narrator’s instructions and displayed feedback mechanisms that were piloted successfully in experiment 1. However, with the home-based protocol, all participants begin at the same level and proceed through the training tasks in a fixed sequence.

Participants view each trial on the tape and are given an interval during which to record their responses on the scoring form before receiving feedback about the correct response. On receiving the feedback via visual display with voiceover narration, participants are given another interval of 6.5 to 16.5 seconds in duration, as determined in experiment 1, during which to indicate on the scoring form the correctness of their responses.

The narrator provides cues for stopping the tape after each block of trials to calculate mastery. As in the laboratory protocol, mastery is defined as accuracy on 75% of trials within a given block (explained as 12/16 correct responses). If a participant has failed to master a block of trials on the first attempt, he/she is instructed to rewind the tape to a clearly marked flag (eg, block 3) to repeat that block until mastery is achieved before moving on to the next block. If the participant fails to achieve mastery of a block after 3 attempts, he/she is instructed to repeat the preceding block of training trials (eg, block 2) before moving ahead. In this way, a level of customized training is achieved.

On returning for the posttraining study visit, each participant randomized to home-based training returned the videotapes and scoring manual. The session diaries and scoring records contained within the manual were then inspected to assess compliance with the training protocol (number of sessions completed, validity of scoring responses and mastery calculations). Eighty percent of subjects assigned to home-based training completed at least 8 of 10 sessions, had valid responses, and correctly calculated mastery of training tasks.

Internet training⁷ was designed as a social- and computer-contact control group. This training includes introductions to computer hardware, the mouse, how to acquire and use an e-mail account, and how to find and use web pages. Like laboratory-based speed-of-processing training, Internet training took place at the research laboratory and involved ten 1-hour training sessions over 5 weeks with a certified Internet trainer and 2 to 3 participants. Sessions began with discussion of the relevance of the Internet and proceeded to individual practice exercises guided by the trainer. All participants in this condition completed at least 8 of 10 training sessions.

Statistical Analysis 

The primary goals of analyses conducted using SPSS^a were to determine via MANOVA the cognitive impact of the home-based speed-of-processing training relative to the standard, laboratory-based training and to compare the processing-speed gains made with each speed-training protocol to gains, or lack of gain, in the social-contact and no-contact control groups.

Back to Article Outline

Results 

Experiment 1 

All participants had corrected binocular distance acuity of 20/50 or better; participants’ characteristics with respect to cognitive function, mobility, technology experience, and self-rated health are summarized in table 1.

Table 1. Characteristics of Experiment 1 Sample

Measure	Mean ± SD	Raw Score at 50th Percentile for Age 73 Years
MMSE (no. correct of 30)⁎	27.58±2.03	27–28(highschool–college)
Vocabulary (no. correct of 18)	13.67±3.75	NA(literacyscreen)
Digit symbol (no. correct in 90s)	43.35±11.27	49−53
Life space (no. endorsed of 15)	13.42±1.51	NA
Self-rated health (1–5)†	2.23±0.89	NA
Technology exposure (no. of 38)	17.75±4.56	NA
Selected technology items‡ (% yes)
Own VCR	74	NA
Use VCR	79	NA
Own personal computer	43	NA
Use personal computer	42	NA

Abbreviations: NA, not available; SD, standard deviation.

Primary Analyses 

Intertrial recording interval data were analyzed by task (1, 2, 3) and display duration (500, 300, 100ms). Optimal recording intervals for the videotape-training protocol were determined by calculating the duration of the intertrial intervals that permitted 95% of participants to record and evaluate their responses. Display duration did not affect either of the 2 response intervals; subsequent analyses were collapsed across this variable. Significantly shorter intervals for response recording were needed for task 1 (requiring 1 response) than for tasks 2 and 3 (requiring 2 responses) (t=14.48 and t=6.87, respectively; all P<.001). Likewise, accuracy evaluation intervals were shorter for task 1 than the other tasks (t=15.06 and t=16.5, all P<.001). MANCOVA showed no differences in interval durations by education level, age, self-rated health, and technology experience (Wilks λ=.956, F_6,72=.555; P=not significant [NS]). Response-recording and accuracy-evaluation intervals necessary to accommodate 95% of participants are presented in table 2.

Table 2. Intertrial Interval Durations at 95th Percentile, by Response Required and Task Type

No acceptability data were collected from the first 5 study participants. Acceptability of the proposed training did not vary by education level (χ₁² test=.182, P=NS), nor by age, self-rated health, global technology experience, or MMSE score (omnibus χ₄² test=2.35, P=NS). Neither did ease of use vary by these factors (ρ=.326, F_5,73=1.83, P=NS). Ease and acceptability were high overall. On a scale ranging from very easy to very difficult, 83% of participants with 12 or fewer years of education (n=15) and 86% with more than 12 years (n=64) found using the self-administered training protocol “easy” or “very easy,” whereas 11% of the lower- and 9% of the higher-education groups, respectively, found it “somewhat difficult” to use. No participant found the protocol “difficult” or “very difficult.” Collapsed across education, 95% of participants reported that they would take a computer-based evaluation either within or outside the home if it would determine their level of safety for driving; 100% indicated that they would undergo testing for a potential automobile insurance discount; 87% said they would undergo training if they failed the original evaluation; and 92% said they would self-administer the training at home if such a program were available.

Experiment 2 

Of the 181 study participants, 17 (9%) did not return for posttraining assessments and were excluded from statistical analyses. These subjects did not differ from those who completed the posttraining assessment in age, education, race, sex, or baseline processing speed; neither did they differ by study arm. The analytic sample of 164 subjects included all people with pretraining and posttraining data, irrespective of the number of training sessions they had completed. MANOVA showed no baseline differences between the 4 study arms in mean age, education, vision, or cognitive function as indicated by scores on the MMSE, BVRT, TMT-B, road sign test, and UFOV (Wilks λ=.923, F_24,424=.50, P=.98).

To determine the impact of training type on cognitive performance, a MANOVA was conducted on participants’ pre-post difference scores on the cognitive measures. Results of the overall model showed a significant effect of training type (F_12,350=3.82, P<.001). Inspection of univariate effects showed that the overall effect was due to pre-post differences in UFOV performance by training type (F_3,160=16.16, P<.001). Post hoc comparison using the Tukey honestly significant difference procedure showed that the magnitude of home-based and laboratory-based UFOV gains did not differ significantly. Home-based training improved UFOV performance significantly more than either the no-contact (P<.005) or social-contact (Internet) control (P<.001) groups, as did laboratory-based speed-of-processing training. The training gains of the home-based group (effect size in standard deviation [SD] units, 1.74) were 74% as great as those of the standard, laboratory-based training group (effect size in SD units, 2.35) (fig 1).

• 
  • View Large Image
  • Download to PowerPoint

• Fig 1. 

  Mean processing-speed improvement by training group.

Seventy-seven percent of subjects assigned to home-based training liked the program as indicated by a 6 or higher on a Likert-type scale (0, very much disliked; 5, neutral; 10, very much liked). Thirty-six percent found self-administration difficult, responding with a 5 or higher (0, not at all difficult; 5, somewhat difficult; 10, very difficult). Seventy percent of respondents reported needing no adjustments to their home environment to accommodate training. The nature of reported problems and suggestions varied, including complaints that the self-assessment and recording intervals were either too brief or too long, complaints that the protocol was too repetitive, isolated VCR and television problems, and a request for additional instruction and practice.

Back to Article Outline

Discussion 

The primary finding of this research is that older adults can significantly improve their processing speed at home using inexpensive and readily available VCR technology. Experiment 1 showed the feasibility of self-administered speed-of-processing training, and experiment 2 showed the effectiveness of this training as conducted in the home. The processing-speed gains made by adults who self-administered a home adaptation of the laboratory-based speed-of-processing training protocol were about 75% as great as those associated with laboratory-based training, and the gains of the 2 groups did not differ statistically. Furthermore, the processing-speed gains made by subjects assigned to home-based training were significantly greater than those associated with test-retest practice effects alone (as represented by the no-contact control group) or with practice plus social contact, computer contact, intellectual stimulation, and task mastery (as represented by the Internet-training group).

Self-administered, home-based speed-of-processing training did not provide the same degree of structure that trainer-facilitated, laboratory-based training provided. It is therefore not surprising that the percentage of subjects who successfully completed a full dose of home-based training (81% completed ≥8/10 sessions) was somewhat lower than the percentage who completed the full complement of laboratory-based training (93% completed ≥8/10 sessions). Even so, our analyses included all subjects with both pretraining and posttraining data, irrespective of the number of training sessions they completed. Thus, the analyses are based on a modified intention-to-treat model that takes into account the degree of noncompliance likely to occur in real-world home training applications.

Although subjects’ processing speed improved, as indicated by posttraining UFOV gains, there was no improvement relative to control groups on the other cognitive measures, including measures of visual memory, executive function, reaction time, and psychomotor speed. Thus, processing-speed gains were limited to performance on a computer-administered measure that taps the processing-speed construct assessed in a modality similar to that used in the laboratory-training paradigm. Nevertheless, these posttraining gains occurred not only with computer-based speed-of-processing training but also with VCR-based training, and both groups made gains significantly greater than those of the computer-based Internet-training control group.

One reason that the UFOV assessment might be most sensitive to improvements after training is that it involves multiple task demands that have been shown to tap not only information processing speed but also visual sensory function, the ability to divide attention, and susceptibility to distraction.²⁰ Posttraining improvements in performance on this multidimensional measure therefore might be due to improvements on 1 or more of these indices. The design of these studies does not permit isolation of the nature of subjects’ improvements among these interrelated visual/cognitive constructs.

The significance of improvement in UFOV scores, irrespective of training method, lies in the previously described relation of UFOV performance to crash risk² and of posttraining UFOV gains to enhanced driving safety and successful performance of everyday tasks.⁶, ⁸ Prior research has shown that laboratory-based training produces improvements in processing speed that are durable for at least 2 years and that booster training sessions result in even more robust gains.⁵ More research is needed to determine whether processing-speed improvements after home-based speed-of-processing training are equally durable. However, the fact that a home-based training program, once acquired by an older adult, would remain at his/her disposal, suggests the potential for self-administered booster sessions that would likely maintain training gains. The durability of home-based training gains and the impact of booster sessions should be directly assessed.

Several other areas of future research are indicated by these results. Based on feedback from participants in experiment 2, work should be done to increase the ease of administering the home-based program and the novelty of the component tasks to enhance task engagement. Such improvements would increase the probability that people would comply with the full program, perhaps enhancing the magnitude of their training gains to the level achieved with facilitated, computer-based training. At the same time, alternative modalities for the home-based program should be developed to make the application as widely available as possible. Indeed, in just the past year, VCRs are rapidly becoming replaced with digital video disk technology, and computer use and ownership are rapidly increasing in all segments of the population. Further research is also necessary to determine how different degrees of training customization affect processing-speed gains. Finally, the role of home-based training in improving driving performance, reducing crash risk, and enhancing everyday functioning should be explicitly evaluated.

Back to Article Outline

Conclusions 

This research also suggests directions for public policy regarding older drivers. Acceptability data from experiment 1 suggest that seniors’ concerns about their driving-related skills provide intrinsic motivation for undergoing cognitive testing. The data also show that discounted car insurance premiums would be a strong incentive for completing rehabilitation programs such as the present program of home-based training. Therefore, when combined with appropriate incentives, such programs have the potential to become an accepted and viable component of multifaceted approaches to safe mobility for older adults.

Supplier

Back to Article Outline

Acknowledgment 

The UFOV assessment and speed-of-processing training programs are products of Visual Awareness Inc.

Back to Article Outline

References 

1. Ball K , Owsley C . Identifying correlates of accident involvement for the older driver . Hum Factors . 1991;33:583–595
   • View In Article
   • MEDLINE
2. Owsley C , Ball K , McGwin G , et al.   Visual processing impairment and risk of motor vehicle crash among older adults . JAMA . 1998;279:1083–1088
   • View In Article
   • MEDLINE
   • CrossRef
3. Ball K , Beard B , Roenker D , Miller R , Ball D . Visual search (age and practice) . [abstract] Invest Ophthal Vis Sci Suppl . 1988;29:448
   • View In Article
4. Ball K , Owsley C . Increasing mobility and reducing accidents of older drivers . In:  Schaie KW ,  Pietrucha M editor. Mobility and transportation in the elderly . New York: Springer; 2000;p. 213–250
   • View In Article
5. Ball K , Berch DB , Helmers KF , et al.   Effects of cognitive training interventions with older adults (a randomized controlled trial) . JAMA . 2002;288:2271–2281
   • View In Article
   • MEDLINE
   • CrossRef
6. Edwards JD , Wadley VG , Myers RS , Roenker DL , Cissell GM , Ball KK . Transfer of a speed of processing intervention to near and far cognitive functions . Gerontology . 2002;48:329–340
   • View In Article
   • MEDLINE
   • CrossRef
7. Edwards JD , Wadley VG , Vance DE , Roenker DL , Ball KK . The impact of speed of processing training on cognitive and everyday performance . Aging Ment Health . 2005;9:1–10
   • View In Article
   • MEDLINE
   • CrossRef
8. Roenker DL , Cissell GM , Ball KK , Wadley VG , Edwards JD . Speed-of-processing and driving simulator training result in improved driving performance . Hum Factors . 2003;45:218–233
   • View In Article
   • MEDLINE
   • CrossRef
9. Folstein MF , Folstein SE , McHugh PR . “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician . J Psychiatr Res . 1975;12:189–198
   • View In Article
   • Full-Text PDF (635 KB)
   • CrossRef
10. Ekstrom RB , French JW , Harman H , Derman D . In: Kit of factor referenced cognitive tests . Revised ed.. Princeton: Educational Testing Serv; 1976;
    • View In Article
11. Jobe JB , Ball K , Marsiske M , Rebok GW , Helmers KF , Kleinman K . ACTIVE (a cognitive intervention trial to promote independence in older adults) . Control Clin Trials . 2001;22:453–479
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (172 KB)
    • CrossRef
12. Wechsler D . WAIS-R manual . New York: Psychological Corp; 1981;
    • View In Article
13. Czaja SJ , Sharit J . Age differences in attitudes toward computers . J Gerontol B Psychol Sci Soc Sci . 1998;53:P329–P340
    • View In Article
    • MEDLINE
14. Stalvey BT , Owsley C , Sloane ME , Ball K . The Life Space Questionnaire (a measure of the extent of mobility of older adults) . J Appl Gerontol . 1999;18:460–478
    • View In Article
    • CrossRef
15. Ball KK , Beard BL , Roenker DL , Miller RL , Griggs DS . Age and visual search (expanding the useful field of view) . J Opt Soc Am A . 1988;5:2210–2219
    • View In Article
    • MEDLINE
16. Ball LJ , Bisher GB , Birge SJ . A simple test of central processing speed (an extension of the Short Blessed Test) . J Am Geriatr Soc . 1999;47:1359–1363
    • View In Article
    • MEDLINE
17. Pelli DG , Robson JG , Wilkins AJ . The design of a new letter chart for measuring contrast sensitivity . Clin Vision Sci . 1988;2:187–199
    • View In Article
18. Ball K , Owsley C . The useful field of view test (a new technique for evaluating age-related declines in visual function) . J Am Optom Assoc . 1993;64:71–79
    • View In Article
    • MEDLINE
19. Ball K , Owsley C , Sloane ME , Roenker DL , Bruni JR . Visual attention problems as a predictor of vehicle crashes in older drivers . Invest Ophthalmol Vis Sci . 1993;34:3110–3123
    • View In Article
    • MEDLINE
20. Ball K , Roenker D , Bruni J , Jackson L , Dahl RM . Age and visual search (bases for shrinkage of the Useful Field of View) . [abstract] Invest Ophthalmol Vis Sci Suppl . 1990;31:1748
    • View In Article
21. Edwards JD , Vance DE , Wadley VG , Cissell GM , Roenker DL , Ball KK . Reliability and validity of useful field of view test scores as administered by personal computer . J Clin Exp Neuropsychol . 2005;27:529–543
    • View In Article
    • MEDLINE
    • CrossRef
22. Ball K , Owsley C . Increasing mobility and reducing accidents of older drivers . In:  Schaie KW ,  Pietrucha M editor. Mobility and transportation in the elderly . New York: Springer; 2000;p. 213–251
    • View In Article
23. Spreen O , Strauss E . A compendium of neuropsychological tests (administration, norms, and commentary) . New York: Oxford Univ Pr; 1991;
    • View In Article
24. Reitan RM . Trail Making Test (manual for administration, scoring and interpretation) . Indianapolis: Dept of Neurology, Indiana Univ Med Ctr; 1958;
    • View In Article
25. Stern RA , Prohaska ML . Neuropsychological evaluation of executive functioning . Rev Psychiatry . 1996;15:243–266
    • View In Article
26. Sivan AB . In: Benton Visual Retention Test . 5th ed.. San Antonio: Psychological Corp; 1992;
    • View In Article
27. Spreen O , Strauss E . In: A compendium of neuropsychological tests (administration, norms, and commentary) . 2nd ed.. New York: Oxford Univ Pr; 1998;
    • View In Article

• a Version 11.5; SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606.