TRAINING OLDER WORKERS FOR TECHNOLOGY-BASED EMPLOYMENT

Abstract

An increasingly aging workforce and advances in technology are changing work environments and structures. The continued employability of older adults, particularly those of lower socioeconomic status (SES), requires them to participate in training programs to ensure their competence in today’s workplace. Focus groups with 37 unemployed adults (51–76 years old) were conducted to gather information about barriers and obstacles for returning to work, training needs and formats, work experiences, and perceptions of the characteristics of an ideal job. Overall, results indicated that participants experienced age discrimination and lack of technology skills. They also expressed a desire to receive additional training on technology and a preference for classroom training.

The aging of the baby-boom cohort is coupled with changes in retirement policies, programs, and behavior and increased concerns about dwindling resources to support retirement incomes. These factors are contributing to a renewed interest in the development of strategies to promote continued employment of older adults. It is generally recognized that the extent to which older people remain productively employed will have a large impact on business/industry, government programs and the economy, and the quality of life of older adults themselves. In the year 2002 there were about 61 million people aged 55+ in the U.S. This number is expected to grow to 103 million by 2025, representing 30% of the population (U.S. General Accounting Office, 2003).

There are a number of factors influencing the extent to which the cohort of older adults will continue to work in order to have the financial incentives, the healthcare benefits, and/or the opportunity to socialize with others. For example, a recent report from AARP (2007) indicates that more than one-third (39%) of today’s 50+ workers from the G7 countries are planning to continue working in some capacity in retirement. Among the reasons for continuing working after retirement are the needs for extra money, staying mentally healthy, and being productive.

The changes of the work environment of the 21st century have created new knowledge, skill, and ability requirements for workers. For example, ongoing developments in technology are reshaping production processes, and the task content and skills requirements of jobs. Most workers use a computer, the Internet or some other form of technology at work, and this number will continue to grow as will the scope and sophistication of technology. In the future, the rapid pace of technological change and the transition to a knowledge-based economy is going to increase the demand for highly skilled and well-educated workers. This implies that workers, especially older workers who may not have been exposed to changes in technology, will continually need to engage in training and retraining activities to remain competitive in the work force.

Successful completion of training for job-related activities requires a broad range of perceptual, cognitive, and motor abilities. For example, Nair, Czaja, and Sharit (2007) examined individual differences in performing a computer-based task. The results indicated that age, crystallized intelligence, and fluid intelligence had an impact on both the initial level of performance and amount of changes in performance that resulted from practice and experience. The literature examining the influence of age on these abilities generally suggests age-related declines. With respect to cognition, many cognitive abilities—such as working memory, attentional processes, and spatial cognition—thatare important to learning show decline with age, especially under conditions of complexity or when a task represents an unfamiliar cognitive domain (Park, Lautenschlager, Hedden, Davidson, & Smith, 2002). Despite these age-related changes in abilities, the skill acquisition literature indicates that older adults are able to learn new skills, though it typically takes them longer than younger adults, and they require more practice and more environmental support (Charness & Czaja, 2005).

With respect to job training, Kubeck, Delp, Haslett, and McDaniele (1996) conducted a meta-analysis examining the relationship between age and job-related training outcomes. The results indicated that, on average, older adults demonstrate less mastery of the training material and take significantly longer to train than younger adults. In addition, they found variance in the age and training outcomes across studies, which could be due to moderating factors such as length of training, varying training measures, and training techniques. Overall, the authors concluded that there is a critical need for studies to examine training methods that are appropriate for older workers. Other studies (e.g., Beier & Ackerman, 2005; Nair, Czaja, & Sharit, 2007) have also shown that experience and attitudinal variables are important factors influencing how effectively someone can learn new information.

The availability of training opportunities for older workers can also have a significant impact on their adaptation to changes in job demands. Unfortunately, older adults are likely to suffer the effects of stereotypes about age-related performance declines (Kite & Johnson, 1988), which might result in negative perceptions among managers about the trainability of older adults (Sterns & Doverspike, 1989). A longitudinal study conducted by Maurer, Weiss, and Barbeite (2003) found that older workers received less support for learning and development activities. They also found that participation in training and development activities is influenced by individual or personal factors such as anxiety and self-efficacy and perceived benefits of participation. Individuals who believed that they were capable of improving and learning new skills are more likely to participate in training activities as are those who perceived a potential benefit from participation. In general, age was found to be negatively related to both individual and situational variables that foster participation in job development activities.

Overall, it is clear that age is not the only factor influencing involvement in training and development of programs. Rather, both individual and situational characteristics are important before training (ability/decisions to participate), during training (involvement in training activities), and to training success (training performance and subsequent transfer to work activities).

To date, there have been limited studies that examined attitudes among older adults about returning to the workforce and their preferences with respect to participation in training programs. In order to gain insight into the learning, training needs and preferences of older workers, we conducted several focus groups involving low socioeconomic status (SES) older adults who had been actively seeking paid employment. We were interested in understanding the barriers and obstacles that this group of older adults faced when returning to work, the type of training that these older adults need, and their preferences regarding training format. In addition, we also wanted to gather information regarding how these older adults perceive work and careers and characteristics of an ideal job.

The use of focus groups to collect qualitative data has grown tremendously in the social sciences (Morgan, 1997). We chose to use focus groups as this method provides an opportunity to gather rich and in-depth information in a limited period of time from the participants, represents a formal method of group interview, and allows for more open discussion on a particular topic. We also gathered survey and questionnaire data from our participants.

METHOD

Sample Characteristics

The sample included 37 community-dwelling older adults (9 male and 28 female) ranging in age from 51 years to 76 years (M = 65.24, SD = 6.95). The participants included a “younger” (51–64 years) older adults group and an “older” (65–76 years) older adults group. There was a total of 18 participants (5 male and 13 female) in the younger-old group (M = 58.94, SD = 3.56) and 19 participants (4 male and 15 female) in the older-old group (M = 71.21, SD = 2.72). There were 6 Hispanic, 2 White non-Hispanic, 17 Black non-Hispanic, and 2 multiracial participants. Among the participants, about 65% (n = 24) had high school education or less, and 35% (n = 13) had more than a high school education. Regarding annual income, 16 participants (43%) had an annual income of less than $9,999, and 13 participants had an annual income between $10,000 and $19,999 (35%); only 6 participants had an annual income between $20,000 and $49,999. Two participants did not provide their annual income. About 76% of the participants (n = 28) rated their general health as good to excellent; only 9 (24%) participants reported that their health was fair. Twenty participants (54%) reported not having any computer experience.

Participants were recruited using standard methods of advertisement (e.g., newspaper, flyers) from South Florida. All participants were English speakers, had at least a sixth-grade education, and not cognitively impaired (Short Portable Mental Status Questionnaire criterion: ≤2 errors, Pfeiffer, 1975; Wechsler Memory Scale Logical Memory subscale; age-adjusted criterion, Wechsler, 1997). Additional eligibility criteria included the following: (a) at least 50 years old; (b) have been seeking employment for 3 years or less, or have been involved in a job-training program; (c) not currently working for pay; (d) have no experience with common work-related computer applications such as text editing, spreadsheet, data analysis, and graphical application; and (e) annual household income not more than the median annual household income of the Miami-Dade County. The study was approved by the University of Miami’s Internal Review Board.

Eligible participants reported to the study site (e.g., local employment or training agency), received an explanation of the study, and read and signed the approved informed consent form. Participants also signed the authorization form for audiotaping of the focus group discussion. Each participant then completed a background and computer experience questionnaire (Czaja, Charness, Dijkstra, Fisk, Rogers, & Sharit, 2006), a technology experience questionnaire (Czaja, Charness, Fisk et al., 2006), and an employment questionnaire prior to the initiation of the focus group discussions. Participants were paid $25 for their participation upon the completion of the focus group discussion.

Measures

Background Questionnaire and Computer Experience Questionnaire

This questionnaire included questions on basic demographics (e.g., age, gender, education, income), perceived overall and general health, attitudes towards computers (adopted from Jay & Willis, 1992; Czaja, Charness, Dijkstra et al., 2006) including computer comfort, computer efficacy, and computer interest, and experience with computer technology, technical support and training.

Employment Questionnaire

This questionnaire assessed several areas of employment. Respondents described characteristics of their most recently held job and identified any computer-based technologies used during their employment. They are also asked to state reasons why they are currently not working, reasons why they want to return to work, and the characteristics of their “ideal job.” In addition, there was a section that assessed reaction to using computer-based technologies in their most recently held job. The format of the questionnaire included Yes and No questions, short answers, and Likert-type scale (e.g., three anchors of major factor, minor factor, no factor at all, or five anchors of strongly agree to strongly disagree).

Protocol for Focus Groups

Each focus group followed a standard protocol. The focus group moderator provided a brief welcome followed by a description of the set of procedures for the group discussion and ground rules for the conversation. Participants were instructed to speak one at a time and encouraged to share their own ideas and experiences with respect to seeking employment, their desires to receive additional training, and their preferred training and learning formats. The following questions guided the discussions:

1. Obstacles: What do you think are the biggest obstacles that seniors face when they are looking for paid employment?

2. Skills: What types of skills (e.g., using the Internet, e-mail) do you think are needed to be able to work in today’s workplace? What type of work-related skills do you currently have?

3. Types of training: What type of training do you think you need in order to obtain a job and be employed?

4. Training formats: Are you interested in receiving this type of training (based on the list of training provided during the group discussion), and where would you like to receive this training (e.g., classroom, workplace, home)? What type of training do you think would work best for you and why?

Data Analysis

Both qualitative and quantitative approaches were used to analyze the data. The audio recording tapes from the focus groups discussions were semi-transcribed. During the transcription process, key elements or responses from participants that provided answers to issues of the focus group discussions were extracted and summarized. A list of answers to each question was then compiled for each focus group. In addition, the notes taken during the focus group discussions were used to complement the results from the semi-transcription of the recording tapes.

The responses from the questionnaires were analyzed using SPSS Version 15.0. Analysis of variance (ANOVA) was used to examine the difference between the two age groups in their attitudes towards the computer (e.g., comfort, efficacy, interest). For categorical variables such as the participants’ perceptions about work and career, reactions to using computer-based technologies at work, and ideal job characteristics, the cross-tab results were reported and the Chi-square (χ²) test was used to examine whether differences existed between the two age groups. The alpha level (α) was set at .05 (two-sided test) for all analyses.

RESULTS

Focus Group Discussion

A total of 6 focus groups were conducted between February and October of 2007. Participants (n = 37) reported an array of obstacles they confronted while looking for a paid job including the lack of not knowing someone from inside the company, employers’ expectations about older workers’ ability to perform strenuous jobs, employers comparing older workers’ performance with younger workers, and insufficient wages. The following common obstacles emerged during the discussion: age discrimination, lack of computer-related skills, language barriers, health conditions, and lack of transportation to/from work. All participants (n = 37) identified both age and the lack of needed technology-related skills (e.g., computer, fax, and copy machines) as the biggest obstacles that they face while looking for a paid job. The second major obstacle reported by participants was language (n = 15). The language barrier issue was observed among English speakers who lacked the Spanish language skill and those who are not fluent English speakers. Another important obstacle was the lack of transportation or the distance between job locations and home (n = 10). The lack of education or qualified skills was also identified as an obstacle to finding a paid job (n = 7). Finally, several participants (n = 4) noted that their health was also an obstacle to finding a paid job (Table 1).

Table 1.

Sample quotes from focus group discussions

Topic/Quotes
Obstacles to finding a job
Most time most of us do not drive.
Sometimes the job that I find is too far from home.
I can’t take so many buses to get to the job.
If you do not have a high school education, they might not want you.
When I have to fill out the job application and my education is poor, I don’t know what to put.
You have to be in good health to find a job.
Some of us have illness … if you are working on a job, you got to take time off to go to the doctor, they are not going to need you afterwards.
I had a lot of problems with my weight to find a job.
Work-related skills they currently have
We can communicate, we have experience.
We have interpersonal experiences … due to our age.
We can be on-time.
Desire to receive additional computer training
Once you learn to use the computer, it would be easier to pick up the different computer systems from different companies.
I really need to learn to use computer … I would like to open my own childcare facility …and I need to look for things in the computer.
Training format
Classroom
Classroom is good … you get assignments; teacher gives assignment to do at home.
We are learning from each other.
More comprehensive structure rather than informal one-on-one.
You can discuss and get to the answer that you need.
You get the quality time with the person, you can learn at your own pace.

When asked about work-related skills they currently have, participants reported having good interpersonal and communication skills (n = 4); training in certain office clerical jobs (n = 7) such as filing, typing, and answering telephone calls; and being responsible and on-time workers (n = 8). Given the low education level of participants, most of them had a blue collar job (e.g., truck driver, carpenter) that did not require use of computer-based technology (Table 1).

All participants expressed a great deal of interest in receiving training in the overall use of computers (n = 32). They also indicated the desire to become more proficient in using computer software tools such as Microsoft Word and Excel and more familiar with the Internet and the use of e-mail. They perceived that with additional training, they would be able to get a paid job. In addition, some participants (n = 9) expressed interest in learning a new language and improving their language skills in order to facilitate their job searching.

With respect to training format, more than 50% of the participants (n = 27) indicated that they preferred a classroom training format with hands-on activities. They stated that this method allowed for sharing of experiences among classmates, and accessibility to immediate feedback from the instructor regarding the training material. A second method of training preferred by the participants is one-on-one training with hands-on activities (See Table 1). This particular method was preferred by those who wanted to learn at their own pace and to receive more personal attention from the instructor.

Computer Attitude Questionnaire

All participants completed the computer attitude questionnaire. Overall, the results indicated that there was no significant difference between the younger-old (51–64 years) and older-old (65–76 years) participants in their feelings of computer comfort, computer efficacy, and interest in using the computer. In addition, the results indicated that there was no significant different between those who had (n = 17) and those who did not have computer experience (n = 20) in their attitudes towards computers. Among those participants who had computer experience (n = 17), only about 60% felt they had received adequate training; however, they felt that the training was beneficial (100%) and that they enjoyed exploring new computer applications or software (65%). The majority (88%) reported that they had not received sufficient training on the computer and that they had insufficient time at work to learn to use computer software (71%).

Employment Questionnaire

All participants (n = 37) completed the employment questionnaire. As shown in Table 2, the major reasons reported by participants as to why they are not currently working: the job market is tight (73%), age/too old (68%), and lack of skills (54%). These results are consistent with the reasons generated during the focus group discussion. A further analysis compared the different responses between the age groups and revealed that there was no age group difference in the reasons given for not currently working. When participants were asked whether they would like to return to work, about 80% of the participants indicated they would like to return to work part-time. There was no difference between the age groups in the type of work that participants would like to return to. The biggest reason as to why the participants felt a lack of confidence in finding a job was because of their age (95%), followed by limited opportunities (51%), tight labor market/economy (49%), limited skills (49%), and lack of education (38%).

Table 2.

Reasons not currently working (n = 37)

	Younger-Old n (%)	Older-Old n (%)	All n (%)
It’s hard to find a job=The job market is tight	12 (66.7)	15 (78.9)	27 (73.0)
Age=Too old	10 (55.6)	15 (78.9)	25 (67.6)
I don’t have the skills to do anything else	11 (61.1)	9 (47.4)	20 (54.1)
I was laid off	8 (44.4)	7 (36.8)	15 (40.5)
Family responsibilities (e.g., caring for children=parents)	6 (33.3)	4 (21.1)	10 (27.0)
I did not like the commute=how far I had to travel	3 (16.7)	7 (36.8)	10 (27.0)
There was no longer a need for the type of work I did	6 (33.3)	4 (21.1)	10 (27.0)
I was sick=ill	5 (27.8)	3 (15.8)	8 (21.6)
My job did not pay me well	5 (27.8)	1 (5.3)	6 (16.2)
I do not need the health care benefits	2 (11.1)	3 (15.8)	5 (13.5)
My career was not going well	3 (16.7)	1 (5.3)	4 (10.8)
I did not like my work schedule	3 (16.7)	1 (5.3)	4 (10.8)
I was not comfortable with my job	2 (11.1)	2 (11.1)	4 (10.8)

When participants were asked about reasons for wanting to return to work, about 95% responded that money was a major factor. Another major factor was that work makes them feel useful (78%). Participants also felt that people have an obligation to work if they are able (64%), and returning to work would help participants save money for retirement (54%). Additional analysis indicated that there are significantly more older-old adults (26%) who do not believe people have an obligation to work if they are able to than younger-old adults (0%) (χ²(2, n = 36) = 6.954, p < .05). Also, about 42% of the older-old participants do not consider saving money for retirement as a reason for returning to work as compared to about 5% of the younger-old participants (χ²(3, n = 37) = 9.767, p < .05). No additional age group differences were found among the reasons for wanting to return to work.

Participants were also asked about their attitudes toward work and careers. Overall, the results indicated that participants had positive attitudes toward work and careers (Table 3). About 92% of the participants indicated that they would like to continue working, and more than 50% of the participants felt that there was still much to accomplish in their work life. In addition, about 68% of the participants would not mind learning new skills, 81% indicated that they were looking for their next work challenge, and 73% had confidence that they could get another job. When examining age group differences in participants’ perceptions about work and career, 32% (n = 6) of older-old participants did not perceive themselves as expert at what they do as compared to 61% (n = 11) of the younger-old participants (χ²(2, n = 37) = 6.996, p < .05). There were no significant age group difference in the other remaining perceptions about work and career.

Table 3.

Perceptions about work and career (n = 37)

	Younger-Old			Older-Old			All
	Agree n (%)	Neutral n (%)	Disagree n (%)	Agree n (%)	Neutral n (%)	Disagree n (%)	Agree n (%)	Neutral n (%)	Disagree n (%)
I would like to continue working	18 (100)	0 (0)	0 (0)	16 (84.2)	2 (10.5)	1 (5.3)	34 (91.9)	2 (5.4)	1 (2.7)
There is still a lot I plan to accomplish in my work life	16 (88.9)	2 (11.1)	0 (0)	12 (63.2)	6 (31.6)	1 (5.3)	28 (75.7)	8 (21.6)	1 (2.7)
At this stage of my work life, I should not have to learn new skills	3 (16.7)	2 (11.1)	13 (72.2)	2 (10.5)	5 (26.3)	12 (63.2)	5 (13.5)	7 (18.9)	25 (67.6)
I am an expert at what I do*	11 (61.1)	7 (38.9)	0 (0)	9 (47.4)	4 (21.1)	6 (31.6)	20 (54.1)	11 (29.7)	6 (16.2)
I am looking for the next work challenge	16 (88.9)	2 (11.1)	0 (0)	14 (73.7)	5 (26.3)	0 (0)	30 (81.1)	7 (18.9)	0 (0)
The only reason I continue to work is because I need money	14 (77.8)	2 (11.1)	2 (11.1)	12 (63.2)	6 (31.6)	1 (5.3)	26 (70.3)	8 (21.6)	3 (8.1)
I have difficulty keeping up with the new technology required to do my job	11 (61.1)	4 (22.2)	3 (16.7)	6 (31.6)	7 (36.8)	6 (31.6)	17 (46.0)	11 (29.7)	9 (24.3)

^*p <.05.

More than 50% of the participants expressed that they had used some computer-based technologies in their most recently held job (n = 24). The technologies used included copy machines (92%), fax machines (85%), cell phones (50%), voice mail/answering machine (50%), word processing software (e.g., Microsoft Word, Word Perfect) (23%), Internet (19%), and an e-mail system (15%). Overall, participants reported that the use of technology facilitated their ability to perform their job and made them more productive and able to work more efficiently (Table 4). Less than 50% of participants felt that they had received adequate training to use these new technologies.

Table 4.

Overall reaction to using computer-based technology in most recently held job (n = 24)

	Younger-old			Older-old			All
	Agree n (%)	Neutral n (%)	Disagree n (%)	Agree n (%)	Neutral n (%)	Disagree n (%)	Agree n (%)	Neutral n (%)	Disagree n (%)
I received adequate training to use new technologies	5 (33.3)	5 (33.3)	5 (33.3)	7 (53.9)	2 (15.4)	4 (30.8)	12 (42.9)	7 (25.0)	9 (32.1)
I felt comfortable using technology at work	11 (73.3)	4 (26.7)	0 (0)	8 (61.5)	3 (23.1)	2 (15.4)	19 (67.9)	7 (25.0)	2 (7.1)
Technology made my job more stressful	3 (20.0)	5 (33.3)	7 (46.7)	2 (15.4)	3 (23.1)	8 (61.5)	5 (17.9)	8 (28.6)	15 (53.6)
Technology made my job more complicated	4 (26.7)	3 (20.0)	8 (53.3)	2 (15.4)	1 (7.7)	10 (76.9)	6 (21.4)	4 (14.3)	18 (64.3)
Technology made me more productive	13 (86.7)	1 (6.7)	1 (6.7)	10 (76.9)	3 (23.1)	0 (0)	23 (82.1)	4 (14.3)	1 (3.6)
Technology helped me work efficiently	13 (86.7)	2 (13.3)	0 (0)	10 (76.9)	3 (23.1)	0 (0)	23 (82.1)	5 (17.9)	0 (0)

With respect to characteristics of an ideal job, most people indicated that an ideal job would have a flexible schedule (84%), provide on the job training (92%), and the opportunity to work part-time (95%). Other important characteristics included feeling respected by your boss (100%) and coworkers (95%), having the chance to use skills and talents (95%), and having opportunities to help others (95%) (Table 5). In addition, the results indicated that there is a significant age group difference in the need for availability of a retirement plan in an ideal job. About 95% of younger-old participants agreed that an ideal job should have a retirement plan; however, among the older-old participants, only 63% of them wanted to have a retirement plan in their ideal job while 32% were neutral about this issue (χ²(2, n = 37) = 6.840, p < .05).

Table 5.

Selected ideal job characteristics (n = 37)

	Younger-Old			Older-Old			All
	Agree n (%)	Neutral n (%)	Disagree n (%)	Agree n (%)	Neutral n (%)	Disagree n (%)	Agree n (%)	Neutral n (%)	Disagree n (%)
A flexible schedule	16 (88.9)	2 (11.1)	0 (0)	15 (79.0)	1 (5.3)	3 (15.8)	31 (83.8)	3 (8.1)	3 (8.1)
The ability to work from home	11 (61.1)	5 (27.8)	2 (11.1)	8 (42.1)	7 (36.8)	4 (21.1)	19 (51.4)	12 (32.4)	6 (16.2)
On the job training	16 (88.9)	1 (5.6)	1 (5.6)	18 (94.7)	1 (5.3)	0 (0)	34 (91.9)	2 (5.4)	1 (2.7)
Opportunity for part-time work	18 (100)	0 (0)	0 (0)	17 (89.5)	2 (10.5)	0 (0)	35 (94.6)	2 (5.4)	0 (0)
A retirement plan	17 (94.4)	0 (0)	1 (5.6)	12 (63.2)	6 (31.6)	1 (5.3)	29 (78.4)	6 (16.2)	2 (5.4)
You feel respected by your boss	18 (100)	0 (0)	0 (0)	19 (100)	0 (0)	0 (0)	37 (100)	0 (0)	0 (0)
You feel respected by your coworkers	17 (94.4)	0 (0)	1 (5.6)	18 (94.7)	1 (5.3)	0 (0)	35 (94.6)	1 (2.7)	1 (2.7)
Work allows you to help others	17 (94.4)	1 (5.6)	0 (0)	18 (94.7)	1 (5.3)	0 (0)	35 (94.6)	2 (5.4)	0 (0)
Healthcare benefits or insurance	15 (83.3)	1 (5.6)	2 (11.1)	14 (73.7)	5 (26.3)	0 (0)	29 (78.4)	6 (16.2)	2 (5.4)
The opportunity to learn something new	17 (94.4)	0 (0)	1 (5.6)	17 (89.5)	2 (10.5)	0 (0)	34 (91.9)	2 (5.4)	1 (2.7)
Chance to use your skills and talents	18 (100)	0 (0)	0 (0)	17 (89.5)	2 (10.5)	0 (0)	35 (94.6)	2 (5.4)	0 (0)

DISCUSSION AND CONCLUSIONS

At the same time that the workforce is aging, there are tremendous changes taking place in work environments and organizational structures. For example, the introduction of computers and other forms of technology into working life has dramatically changed the nature of many jobs and work situations for many workers. The continued reliance on computer-based technologies in the workplace will increase the demand for knowledge, and skilled workers. To adapt to the changing workplace, all workers—including older workers—will need to participate in worker training programs. This is particularly true for lower SES older adults who are less likely to have the skills needed in today’s workplace.

The purpose of the current study was to gather information about the employment challenges faced by lower SES older people wishing to return to work and their training needs and preferences. The overall goal of the study was to gather information to help guide the development of programs to prepare older people to return to work and remain as productive members of the workforce.

Overall, the participants indicated that they faced age discrimination in the workplace and that their age was a major impediment to continued employment. This result coincides with a recent report published by AARP (2007) that indicated that age discrimination is a serious concern and the single largest barrier confronted by people 50+ years of age who wish to remain employed. Other important obstacles reported by our participants with respect to finding a job included the lack of skills to compete in today’s workforce and a tight job market. Most participants’ indicated that they had insufficient technology skills. The implications of these findings with respect to training are two-fold. The first is that managers need training about aging to understand the value of the older worker to the organization. Managers also need to engage older workers and provide them with adequate job training and opportunities. The second implication is that older people need access to technology training programs that are designed to consider the learning limitations and preferred formats of older adults.

On a positive note, the participants demonstrated enthusiasm about learning computer-based technologies and computer skills and about returning to work. In terms of learning preferences, most participants indicated a preference for group formats where there are opportunities to learn and share experiences with others. They also stressed the importance of engaging in hands-on learning activities. This finding supports those of others (Callahan, Kiker, & Cross, 2003; Mitzer et al., 2008) that indicated that an active learning process is optimal for older learners. Our participants also indicated that access to feedback was important. This finding confirms results from a study by Sharit et al. (2004) that examined the abilities of people to learn and perform an e-mail-based customer service task. In that study, although the participants were able to learn to perform the task and performance improved with experience, most people indicated a need for more feedback regarding correctness of their responses. These results have implications for the design of training programs.

In addition, participants expressed their desire to return to a part-time job. They characterized an ideal job as having the opportunity to work part-time on a flexible schedule, and being able to obtain job training. As noted by AARP (2007), older workers need a flexible work schedule as they have different needs and expectations with regard to work and giving back to the community. They may also be confronted by other demands such as caregiver for a sick or disabled relative (Schulz & Martire, in press). These job-related attributes not only engage older adults to remain at work, but also to prepare those who need additional training to perform activities in a technologically-based job environment.

This study has several limitations and drawbacks. The study was conducted only in the greater Miami area. There, a large proportion of residents are bilingual including those who speak Spanish (Central and South Americans) and Creo (Haitian); therefore, conclusions regarding employment barriers such as language cannot be generalized to other areas. Also, the lack of computer skills training reported by the participants of the focus groups might be attributable to the lack of availability or lack of access to training programs because of participants’ low socioeconomic situation. Finally, this study only captures attitudes from the older workers’ perspective. Thus, future studies will also be needed to assess managers’ perspectives about hiring of older workers.