grant review & proposal 2015

Impact of the Aging Population and delayed retirement on Workforce Productivity

SSRM Spring, 2015 Dr. Susan Schrader

By: Nick Pappas

Impact of the Aging Population and Delayed Retirement on Workforce Productivity 2

Abstract

There are many different variables that go into delayed retirement and with the baby

boomers on rise it is important that we as a society take this problem seriously to ensure

financial, mental, and social stability for all. In order to understand the impact of delayed

retirement on workforce productivity I will need to send out a survey to 1,331 addresses. I will

use demographic information online to obtain addresses and then I will send out the first wave of

700 surveys. I am looking to receive at least 200 surveys from both a 3064 year old sample and

200 surveys from a 65+ year old sample. Measurements for the survey include education level,

age, retirement status, frailty, proactive personality, cognitive ability, and openness to

experience. I am asking for $3,300 to complete my study. Not being able to retire at age 65 puts

these men and women in a vulnerable situation. The results will help to develop new ideas for

programs to assist individuals if need be. Without this study we will not understand the full

reasoning behind delayed retirement. Also, it is important for every person to understand the

stereotypes put upon them because of age. The information will be beneficial for virtually every

institution in Sioux Falls, South Dakota.

Retirees are a rapidly growing segment of the United States and other countries. There

are many different variables that go into the idea of retirement and delayed retirement. With the

growing percentage of elderly individuals in the United States there is a growing cost of health

insurance for these elders. This is forcing them to stay employed strictly so they can pay for it.

Due to age discrimination laws set into place, these elderly men and women are not forced to

retired at age 65. Managers are being forced to cut elderly workers at a late age because they can

be a financial burden to the company because of their health issues. At the age of 65 Medicare is


available to these older people to cover their medical expenses, but many are realizing that they

cannot just live off Medicare anymore. Older citizens must stay employed for longer durations to

keep up with the economy. So, these themes above had me questioning how delayed retirement

impacts workforce productivity.

I became intrigued with this field of research while taking copious amounts of sociology

courses. I am amazed at how much interest I show in the studies of the aging population given

the background that I have. The research that is compiled for this subject is alarming and I want

to find out the facts. Not only are these elderly individuals being bombarded with medical issues

but they are also having to deal with stereotypes, financial problems, and ageism in the work

place. My goal by the end of this study is to find the reason why they are forced or not forced to

retire. My research question is, “What is the Impact of the Aging Population and delayed

retirement on Workforce Productivity in Sioux Falls, South Dakota Today?”

After a review of many pieces of literature related to my research question, some clear

themes were identified. Psychosocial working conditions on the job (Kalousova, Mendes de

Leon, 2014), stereotypes, health status, and retention of older workers are themes that have been

focused on by many social researchers.

In the United States, people aged 65 years and older are the fastest growing demographic

group. The percentage of men and women aged 65 years and older is projected to almost double

between the present day and 2050, rising from 6% to 11%, and 1 in 5 of these elderly are poor

(Hobbs, Damon, & Taeuber, 2006). This means that the rates of health insurance will raise for

the high percentage of elderly workers. Although many of these workers may work past the age

of retirement, many will be forced to work past retirement due to the lack of funds(Ghilarducci


& Turner, 2007). Older workers are not as healthy as younger workers in general. Thus, the

question of retention of these older workers must be explored. This idea follows the framework

of the rational choice theory, in that managers’ staffing decision, costs of prolonged employment

are assumed to be weighed against its benefits (Coleman, 1990).

Caban Martinez et al. (2011) wanted to understand how arthritis contributes to

managers’ staffing decisions. Arthritis in elderly workers is a common disabling condition that

would almost definitely force elderly workers to leave the workforce early. The prevalence of

arthritis is 50% for those over the age 65 (CabanMartinez et al. p. 9). Although arthritis has been

shown to contribute to many social phenomena, losing ones job is what Caban Martinez et al.

wanted to focus on. The data was obtained from interviews along with previous nationally

representative samples of the US adult population. The interviews were conducted in person to

obtain in depth answers.

Occupational and arthritis classification was determined by asking employed 18 year olds

(N=17967) what their correct working status is. These workers were then split up into four major

occupational groups, white collar, service, farm, and bluecollar workers. Arthritis status in these

workers was assessed by the response to the question, “ Have you ever been told by a doctor or

other health professional that you have some form of arthritis?” To estimate the probability of

death, age and occupational probabilities of death were calculated by using the NAtional death

index. The probability of death was then calculated for all arthritis persons aged 1888 years.

Overall, the results showed that whitecollar workers were only slightly less likely to work

beyond the age of 65 than were the other workers. For the health related quality of life the study

found that whitecollar workers with arthritis suffered considerably less overall than did other


workers. The study also found that those whom stay in the workforce with arthritis lose 6 years

of their health for every one year working. This study shows us that those of us who are faced

with financial problems may have to work through our pain to make it day by day. The downfall

to this is the number of days one loses of their life due to working with the horrific condition.

This is proof to many managers that it may not be in their best benefit to hire these elderly men

and women. The question that the researchers pondered on was then how will these workers

survive with no source of income?

Karpinska, Henkens, and Schippers (2013) examined the idea of retention and age norms.

This was a qualitative research design with two studies built in it. During the first study, those

who held a managerial position at the time of the study were identified and presented with

specific questions on stereotypes regarding older workers, age norms, and other background

characteristics. The response rate for the first study was 73.6 per cent (N=515). In total, 324

managers participated in study 1. Age norms were measured on the basis of one question: At

what age do you consider a person too old to work in your organization for 20 hours a week or

more? The answer ranged from 40 to 100. Stereotypes were then measured with two questions.

The first question asked: To what extent do the following characteristics apply to workers age 60

or older? And: To what extent do the following characteristics apply to workers aged 35 and

younger? The answer categories were (i) hardly, (ii) somewhat, (iii) strongly, and (iv) very

strongly. During this study the control variables, respondents’ gender and respondents’ age were

also collected.

The second study consisted of a vignette survey. A vignette survey is a method intended

for investigation of human decisions. A vignette is a short description of a situation or person,


generated by combining characteristics randomly manipulated by the researcher (Ganong &

Coleman, 2006). For study 2, all respondents who participated in the first round were contacted

to participate in the vignette survey. A total of 238 managers participated and the response rate

for study 2 was 82.3 per cent. In study 2, various hypothetical older workers who were eligible

for retirement were described by several characteristics. The eight different vignette

characteristics were as follows: Organizational context (organization facing structural labour

force shortages, incidental labour force shortages, no labour force shortages, need for

downsizing); knowledge and experience (difficult to replace/ not difficult to replace);

occupational flexibility (yes/ no); attitude towards retirement (looking forward to it/not looking

looking forward); health condition (healthy/frail); motivation to participate in training (high,

average, low); manageability (employee easy to manage, sometimes not easy, difficult to

manage). The study constructed 2,304 unique vignettes. Each manager was then given a random

sample of five vignettes (random selection with replacement). The instructions was as follows:

Below you can find the description of older workers who are eligible for early retirement. Please

indicate, for each profile, what is the likelyhood of you willing to retain that older worker for a

few more years in your organization for the position you supervise most often (Karpinska et al.

2013, pg.1331). Each manager then rated each vignette on an 11point scale, ranging from 1

(retaining very undesirable) to 11 (retaining very desirable).

The study shows that various factors affect older workers’ chances for retention. High

employability were those whose experience was difficult to replace and were versatile in their

tasks, healthy, willing to participate in training, and motivated to stay employed. Workers

characterized as low employability did not have experience that was difficult to replace, were not


occupationally flexible, were in frail health, were not willing to participate in training, and were

looking forward to retirement. In short, the results suggest that the employment opportunities for

high employable older workers are to a large extent dependent on labor market circumstances

and existing age norms within organizations. Older workers with low employability have few

opportunities even when there are labour market shortages and few normative barriers to their

employment (Karpinska et al. 2013, p.1331).

The study showed that age norms regarding retirement significantly affected managers’

decisions to retain older workers. Managers who held older age norms were much more likely to

support employee’s retention. Even though there was a positive result, manager support for

prolonged employment of older workers was limited, with few managers supporting the idea. It

is important to understand that retention is an aspect of aging and delayed retirement, but an even

greater aspect is health in later life. Although Karpinska and colleagues (2013) touched on health

in their research much research has gone further in depth with the aspect of health.

A well established body of literature has shown that psychosocial characteristics of our

jobs have important consequences for health while in the labor force (Truxillo, Fraccaroli &

Bertolino, 2012). A commission jointly assembled by the International Labor Office and the

World Health Organization defined psychosocial factors in the workplace as, “ interactions

among job content, work organizations and management, and other environmental and

organizational conditions, on the one hand, and employees’ competencies and needs on the

other” (1986). Some of the strongest research has suggested that poor psychosocial working

conditions may pose an especially high risk for our cardiovascular systems, as evidenced by an

elevated risk of developing coronary heart disease (Bosma, Peter, Siegrist, & Marmot, 1998).


Empirical evidence has shown that working conditions characterized by high job demands with a

low reciprocal rewards can be particularly detrimental to individual’s physical health (Van

Vegehel, De Jonge, Bosma, & Schaufeli, 2005). Scholars of working conditions have recently

teamed with gerontologists to begin conceptualizing psychosocial working conditions as an

exposure with potential late lifeeffects. For example, Wahrendorf and colleagues found that in a

sample of former French employees, those who experienced less favorable working conditions

reported worse physical and mental health after retirement (Wahrendorf et al. 2012). Kalousova

and Mendes de Leon (2014) were determined to expand on the emergent line of research by

asking two research questions. First, are poor psychosocial working conditions associated with a

greater rate of decline in physical health in later life? Second, does retirement buffer the effects

of negative working conditions on health in later life?

In order to answer the two questions, Kalousova and Mendes de Leon used two waves of

data collected by the crossnational Survey of Health, Ageing and Retirement in Europe SHARE

1 in 2004 and SHARE IV in 2010/2010. At baseline, SHARE collected data from 31,115 people

residing in one on the following twelve countries: Austria, Belgium, Denmark, France, Germany,

Greece, Italy, Netherlands, Spain, Sweden, Switzerland, and Israel. The analytical sample

excluded Israel respondents because the responses were made nearly two years later than the

other countries. Of these countries, 12,211 respondents participated in both SHARE 1 and

SHARE IV data collection waves. For the study they decided to only include the subset of the

responses that were employed, or selfemployed at baseline (N=3865). Data of participants who

provided complete information about their health status with the biomarker data necessary for


the construction of the frailty score at both waves (N=3562), those who answered questions

about their working conditions (N=3408).

The frailty measure was created based on five criteria developed by Fried and colleagues

(Fried et al., 2009). These dimensions included exhaustion, shrinking, weakness, slowness, and

low activity. Exhaustion was identified by the question: “In the last month, have you had too

little energy to do things you wanted to do?” (25% positive at SHARE 1; 27% positive at

SHARE IV). Shrinking was considered fulfilled when the respondent said they were

experiencing “a diminution in desire for food” when asked: ‘What has your appetite been like?”

(3% positive at SHARE 1; 5% positive at SHARE IV). Level of weakness was assessed by a

dynamometer during the interview to determine weakness. Each person was measured four

times, twice in each hand and the highest measurement was used. (3% positive at SHARE 1; 4%

positive at SHARE IV). Two questions were used to assess slowness. These questions were:

“Because of a health problem, do you have difficulty walking 100 meters? or “...climbing one

flight of stairs without resting?” Finally, participants were assessed for the lowactivity

dimension if they said they “engage in activities that require a low or moderate level of energy

such as gardening, cleaning the car, or going on a walk” only “one to three times” a month,”

“hardly ever,” or “never’ (10% positive at SHARE 1; 8% positive at SHARE IV). A respondent

could earn a maximum number of five points. The average score was 0.45 and 0.49 at SHARE 1

and IV. Respondents with no points on any dimension are considered nonfrail (63% at SHARE

1; SHARE IV); those with one to two points prefrail(36% at SHARE 1; 55% at SHARE IV);

and those with three to five points frail (1% at SHARE 1; 2% at SHARE IV).


The SHARE questionnaire that was used included a set of psychosocial work quality

items derived from the conceptual frameworks put forth by Karasek and Theorell (1990). These

questions were used to construct scales of effort, reward, and control and, five measures of

negative psychosocial working condition. The first three of these indicated high score on the

effort scale, low score on the reward scale and low score one the control scale. The second two

were ratio measures: effort/reward ratio and effort/control ratio. The effort scale ranged from 2 to

8, the mean of the analytical sample being 5.16. The highest quartile of the responses, 6 or more

points, were thought to be exerting the most effort 40%. The reward scale ranged from 4 to 16,

with the mean of the analytical sample 10.64. Those who reported 9 or fewer points, the lowest

quarter of the responses, were designated as receiving low reward (28%). The control scale

ranges from 3 to 12, with the mean of the analytical sample 8.69. Respondents with 8 or fewer

points, in the bottom quartile of all responses, were designated as having low control (43%). The

research found that high effort and low reward are both associated with an increase in frailty.

The data reported that men showed smaller increases in frailty in comparison to women. Those

with low level education had a greater increase in frailty compared to those with higher

education. They found that retirement does not modify the associations between change in frailty

and working conditions with one exception: low reward. The study found that high effort with

little reward predicted greater decline in health (Frailty). The study also found that a greater

effort to control ratio predicted an increase in frailty. The study suggest that adverse working

conditions might translate to more permanent or progressive damage to physical health.

It is important to understand the perceptions of these older workers vs. younger workers.

Truxillo and colleagues (2012) examined the stereotypes from both sides of the age spectrum.


The study consisted of 142 employed or recently employed adults who were recruited from

undergraduate psychology classes at an urban, western U.S. university. There were 70

participants in the “older worker” condition and 72 participants in the “younger worker”

condition.

Participants completed an online survey that would grant them an extra credit reward.

The conditions were assigned randomly to the participants using online software, in which they

were rated either and older worker or a younger worker. Older worker and younger worker were

operationalized in that “older worker” age range would represent a person who is approaching

U.S. retirement age. The “younger worker” condition was defined as any person starting his or

her career. These men and women were then sat down and asked questions based off their

condition. For example, “Here is a list used to describe people. Please indicate the extent to

which you believe that each describes a typical worker who is 24 to 34 years old (p.2617).” The

questions were framed using these seven characteristics: Conscientiousness, Extraversion,

Agreeableness, Neuroticism, Openness to Experience, Proactive Personality, and Cognitive

Ability. Conscientious people tend to be goaloriented, strong willed, and determined. People

high in extraversion are characterized as liking other people and being assertive, active,

gregarious, and talkative. The facets of agreeableness include trust, morality, altruism,

cooperation, modesty, and sympathy. The facets of neuroticism include anxiety, anger,

depression, self consciousness, immoderation, and vulnerability. The facets of openness to

experience include imagination, artistic interest, emotionality, intellectual, adventurousness, and

liberalism. Those with high proactive personality show initiative, take action, and persevere.

Cognitive ability includes fluid and crystallized intelligence. Fluid intelligence being short term


memory and the processing of new information. Crystallized intelligence being educational and

experiential components of intelligence, such as general knowledge and vocabulary.

The study found that younger workers were perceived as more open to experience, more

extraverted, more proactive, and possessing relatively higher levels of fluid intelligence. Older

workers were perceived as more conscientious, less neurotic, and possessing relatively higher

levels of crystallized intelligence. The results were mixed for agreeableness.

Curl & Havig, 2014 wanted to study how delayed retirement incentives can retain elderly

employees. A number of states have adopted the delayed retirement incentives laws. These laws

state that those whom are working past the retirement age of 65 still get to recieve retirement

benefits. Previous retirement option plans (Back DROP) required employees to enroll in a

program where they were to provide specific dates for which they will be retiring. This study

focused on four specific questions. One, “what factors predict knowledge about BackDROP

eligibility status?” Two, “what factors predict delayed retirement?” Three, “What factors predict

BackDROP selection?” Finally, “What factors predict that BackDROP is a primary motivation

for delayed retirement?”

Surveys were sent out to 462 regular state employees who retired during February,

March, and April of 2008. The first mailing was sent out the second week of September 2008

and included a $1 token incentive, as well as the survey, cover letter, and selfaddressed/stamped

envelope. The survey was mailed a second time two weeks later to those from whom we had yet

to receive a response. Knowledge of BackDROP eligibility was determined by respondents being

asked whether they were eligible for the BackDROP payment option at retirement (had delayed

retirement at least two years past eligibility) and were given response choices of yes, no, or don’t


know. Respondents were asked questions about their reason(s) for retirement. For each item,

respondents were asked to indicate whether the reason was very important, moderately

important, somewhat important, or not at all important in their decision to retire. Based on

principal component factor analysis of the entire sample, three measures were created from these

items: (1) retired because of poor health of self or family members, (2) retired to do other things

(spend more time with family, spouse/partner retired, do other things), and (3) retired because

did not like the work. For each measure, respondents were coded 1 if they indicated that the

reason was very important in their decision to retire or 0 if less important. Together, these

measures represent known predictors of retirement: poor health, spousal health, care giving

responsibilities, job dissatisfaction, and attitude about leisure and retirement.

This studied showed that if there were incentives and they did not have to write a specific

date for when they were going to retire, they would delay their retirement. The study also found

that these elderly employees may not want to work in a state that has these strict laws and move

to a state where they can delay retirement and keep the benefits. This study led to the change in

retirement laws in Missouri in 2010.

Through my research of the literature some of my questions remain unanswered but what

is known through the research is a series of methods used by each. By examining these methods

used by various researches I find myself making my own. Karpinska et al. (2013) was my

favorite research due to the way it was presented. It was very interesting the way the three

researchers constructed the surveys. It was a great perspective to come from a manager's

standpoint.


I believe that the information in congruence with what I have learned from the literature

will give me a solid background for my grant proposal. Once again, my research will be focused

on the question, “What is the Impact of the Ageing Population and Delayed Retirement on

Workforce Productivity in Sioux Falls, South Dakota Today?”

The literature that I have found that has really captured my eye was the work of

Karpinska and colleagues, 2013. To me it made sense that when workers get old they can slow

down the operation but, I did not know that managers may feel reluctant to hire these individuals

because of the age. I personally loved the methods that were used to accomplish the study. The

way that the drew evidence from the managers was astonishing. The stereotypes that are given to

these elderly workers are way more vast than I thought before. Overall, the literature was

compiled of research that I hope to one day reference to.

Methods

In order to understand the ageing population and delayed retirement on workforce

productivity I need to conduct a survey. The survey will help me get a wide range of answers

from a wide range of ages. The survey itself will be administered to not just those of retirement

age (65 years), but those who are at least age 30. The reason for choosing the minimum age of 30

was the assumption that at the age of 30 they are beginning the career that they will pursue until

retirement age. The advantage to using this method is I will be able to obtain specific

information from those of professional institutions and regular employed men and women where

those who are 3065+ years make up a great percentage. This is beneficial because the survey

will then not be distributed to those who are necessarily retired, but also those who are at the

beginning stages of their career and those who are approaching retirement. This will help me


understand the impact of delayed retirement from different perspectives. I will probe to

understand the stereotypes connected to age, why those who are eligible to retire don’t, financial

issues, and understand why manager won’t hire 65+ year old men and women in Sioux Falls,

South Dakota. The disadvantages to my method are, the cost of the mailing of surveys, and the

validity of the respondent because I am not physically facetoface giving interviews.

The sample size of my study is 350 surveys to those 65+ years of age and 350 surveys to

those who are 3064 years of age. After a demographic search I found that there are 44,564 men

and women ages 3064 years of age and 13,732 men and women who are 65+ years of age in

Sioux Falls (Sioux Falls City Data, 2009). The highest percentage of 65+ years of age residents

in Sioux Falls is in area codes: 57103, 57104, and 57105(25.5% 65+). In this neighborhood there

are 1,331 residents, thus there are approximately 340 residents who fit the profile of 65+ years of

age. I will use the demographic information to obtain addresses of these men and women and

send out the first wave of 700 surveys. The problem with this method of conducting my research

is that I am sending only 700 surveys to a neighborhood of 1,331 residents. My hopes are that the

first wave of surveys will fulfil a majority of the 3064 year old sample and a fair amount of the

65+ age sample.

I predict that the younger group will have survey answers that are stereotypical. I believe

that the younger sample will think that those who can retire should because they are weak,

cannot keep up with demands of job, have less proactive personality, and the younger group will

believe that the older group cannot and/or do not want to learn a new position. On the other side

of the spectrum, I predict that the older group will say they can keep up with the technology and

the physical demands of their jobs. Another prediction is the 65+ year old group have to maintain


their positions to fulfil health benefits and to keep up with bills. Using a survey with a specific

technique of probing, I hope to capture what is leading to delayed retirement, and unemployment

of elderly men and women. Finally, I hope to capture what the 65+ year old group felt would

have helped prepare them for retirement.

To compensate for the threat of unveiling these respondents opinions, I propose to put in

a promise of confidentiality upon received respondents surveys. The respondents names will not

be seen or asked throughout the survey, but the addresses of received respondents will be in my

possession. I believe that the participants in the survey will not need compensation for their

contributions because once the data is published it will be compelling enough itself. On the other

hand, I propose to ask the participants at the end of the surveys if they would like to receive a

full data report and finished study they must sign their name and provide an email address(if they

have one).

Measurements

Measurements for the survey include education level, age, retirement status, frailty,

proactive personality, cognitive ability, and openness to experience. Education level will be

categorized as low (preprimary, primary, or lower secondary), medium (secondary or

postsecondary), or high (first and second tertiary). Age will be measured on a scale of 30100.

Retirement status will be measured on a scale of retired, can retire but working, and too young to

retire as of now. Frailty will be measured on the dimensions including, exhaustion, shrinking,

weakness, slowness, and low activity. Proactive personality is measured by those who show

initiative, take action, and persevere. Cognitive ability will be measured using fluid intelligence

(short term memory, and processing new information) and crystallized intelligence (general

knowledge and vocabulary). Openness to experience will be measured on whether either age


group is open to new experiences. All of these measurements will be on a likert scale and coded.

There will also be situational questions at the end of the survey to help better understand

stereotypes.

I am only interested in those who are in the age range of 3065+ years of age. The sample

will then be the neighborhood and the 700 initial surveys I receive. If I do not receive at least 200

surveys from the 3064 year old group and/or 200 from the 65+ age group, I will send out a

second wave of surveys to the remaining 631 households. The advantage to using this sample is

that I can get views from all different age groups. The disadvantage is that it may take some time

to receive the number of responses I am looking for. This is because initially I know that there

are 340 65+ year old residents in the neighborhood (figure 1), but I don’t know exactly where

they are located. This means that the likelihood of having to send a second wave of surveys is

almost unavoidable. Once the data is collected I will then use SPSS provided by Augustana

College for my data analysis. The data will take up to 3 weeks to fully analyze. Upon completion

those who provided the necessary information will receive a copy of the final work. To ensure

that I will make budget, I will ask if those who want a copy of the finished product to provide an

email address if applicable so I can conserve cost.

Budget To fund this study, I will need a majority of the funds for my envelopes and stamps. I

have indicated in table 1 that I need 1500 envelopes and stamps, but I went over the 1,331

because there will be some who want the results sent to them directly through the mail. Travel

expenses are non existent considering all of the information I need is at my fingertips. Augustana

will provide means of SPSS computer programming for my content analysis and a space to

conduct my work. I will need to hire 2 extra staff members for labor and data analysis help. I will


be paying each staff member $400 a piece for their contributions to my study. I am looking for

$3,300 total to complete my study. The extra $430 that was added on to the total is in case I need

to print and send out the finished study to more people than predicted. A table of expenses can be

found on (table 1).

Timeline

For the completion of this study all I will need is the addresses to send the surveys, which

can be found online. Some of the respondents will want a debrief of the data, this will take

around a week to accomplish. The survey that will be sent out can be seen in (appendix 2). The

surveys should be completed within the first month they are distributed. The data analysis will

take 3 months to accomplish. A full report of the data collected will be completed and sent out

June 1st, 2016. A monthly outline of the study can be seen on (table 2).

Conclusion

How delayed retirement is impacting workforce productivity is derived from many

different variables. My research project will not only find what these variables are but also what

both groups think of one another physically, mentally, and socially. Not being able to retire at the

age of 65 puts these men and women in a vulnerable position. The results will help to develop

new ideas for programs to assist individuals if need be. Without this study we will not

understand the full reasoning behind delayed retirement. Also, it is important for every person to

understand the stereotypes put upon them because of age. The information will be beneficial for

virtually every institution in Sioux Falls, South Dakota.


References Bosma, H., Peter, R., Siegrist, J., Marmot, M., (1998). Two alternative job stress models and the

risk of coronary heart disease. Am. J. Public Health, 88, 6874. CabanMartinez, A., Lee, D., Fleming, L., Tancredi, D., Arheart, K., Leblanc, W., McCollister,

K., Christ, S., Louie, G., Muennig, P. (2011). Arthritis, Occupational Class, and the Aging US Workforce. American Journal of Public Health , 101(9), 17291734. doi:10.2105/AJPH.TEST.2011.300173

Coleman, J. (1990). Foundations of Social Theory. Cambridge, MA: Belknap Press. Curl, A. L., & Havig, K. (2014). A Case Study of Missouri’s Deferred Retirement Incentive for

State Employees. Journal of Aging & Social Policy, 26(3), 249265. doi:10.1080/08959420.2014.899186

Fried, L. P, Xue, Q., Ferrucci, L., Chaves, P., Varadhan, R., et al., (2009). Nonlinear multisystem

physiological dysregulation associated with frailty in older women: implications for etiology and treatment. J. Gerontol. A Biol. Sci. Med. Sci., 64, 10491057.

Ganong, L. H. & Coleman, M. (2006). Multiple segment factorial vignette designs. Journal of

Marriage and the Family, 68, 455468. Ghilarducci, T., Turner, J., (2007). Work options for older Americans. Notre Dame, IN:

University of Notre Dame Press . Hobbs, F., Damon, B., Taeuber, C., (2006). 65+ in the United States. Washington, DC; US

Department of Commerce, Economics and Statistics Administration. ILO & WHO Committee on Occupational Health. (1986). Psychosocial Factors at Work:

Recognition and Control. International Labour office, Geneva. Kalousova, L., & Mendes de Leon, C. (2014). Increase in Frailty of Older Workers and Retirees

Predicted by Negative Psychosocial Working Conditions on the Job. Social Science & Medicine, 124, 275283

Karpinska, K., Henkens, K., & Schippers, J. (2013). Retention of Older Workers: Impact of

Managers' Age Norms and Stereotypes. European Sociological, 29, 13231335. doi:10.1093/esr/jct017


"Sioux Falls: Population Profile." Sioux Falls: Population Profile. N.p., n.d. Web. 14 May 2015. Truxillo, D., Bertolino, M., Fraccaroli., (2012). Perceptions of older versus younger workers in

terms of big five facets, proactive personality, cognitive ability, and job performance, Journal of Applied Social Psychology, 42, 26072639.

Van Vegehel, N., De Jonge, J., Bosma, H., Schaufeli, W., (2005). Reviewing the effortreward

imbalance model: drawing up the balance of 45 empirical studies. Soc. Sci. Med, 60, 11171131.

Wahrendorf, M., Sembajwe, G., Zins, M., Berkman, L., Goldberg, M., Siegrist, J., (2012).

Longterm effects of psychosocial work stress in midlife on health functioning after labor market exit results from the GAZEL study. J. Gerontol. Ser. B Psychol. Sci. Soc. Sci. 67B, 471480.


Table 1:

ITEM COST PER ITEM QUANTITY TOTAL COST

ENVELOPES $10 Per 50ct box 30 boxes $300

RETURN ENVELOPES $10 Per 50ct box 30 boxes $300

POSTAGE STAMPS $0.44 Per stamp 1500 stamps $660

RETURN STAMPS $0.44 Per stamp 1500 stamps $660

PRINTING $0.10 Per page 1500 copies $150

STAFF MEMBERS $400 Per staff member 2 staff members $800

TOTAL COST $2870

Table 2:

SURVEYS MAILED/DELIVERED (1ST WAVE) 1 Day Jan 1, 2016

COMPLETED SURVEYS OBTAINED 1 Month Jan/Feb, 2016

SURVEYS MAILED/DELIVERED (2ND WAVE) 1 Day Feb 1, 2016

COMPLETED SURVEYS OBTAINED (2ND

WAVE)

1 Month Feb/Mar, 2016

ANALYSIS AND WRITTEN REPORT 3 Months Apr/May/Jun, 2016


Figure 1:

Appendix 2: My name is Nick Pappas and I am a student at Augustana College in Sioux Falls, South Dakota. I am conducting a research study on the impact of delayed retirement on workforce productivity. The purpose of this study is to help better understand why those who are able to retire do not retire. Also, the study is seeking to understand what the perceptions of different age classes are. I obtained your address through an online resource. The survey that you complete and send back in the provided envelope will be confidential. I will know your address but my published final product will keep all your information confidential. This information that you provide will be beneficial for not just Sioux Falls, South Dakota, but the whole United States. The survey should take you more than 5 minutes to complete. Thank you for your contribution! Part A:

1. What is your Age? ______ 2. Please indicate your sex (Circle): Male ____ Female ____ Other ____ 3. Are you currently employed? Yes____ No_____ I'm not sure_____


4. How much schooling have you completed? Less than elementary ____ Elementary ____ Middle school ____ High School ____ GED ____ Highschool Diploma ____ Some College ____ College Degree ____ More (Indicate) ____

5. Do you believe that you will be able to retire at age 65? (Explain, skip if retired already) 6. Do you find it difficult to accomplish activities due to physical demands? (i.e joint pain, muscle aches, stiffness, slowness) Explain. (Skip to #9 if younger than 65 years of age)

7. Would you be willing to learn a new occupation? Yes ___ No ___ I Don’t Know ___ 8. How would you describe your technology knowledge?

Not much at all ___ A little bit ___ Caught up with it ___ Know a little but want to learn ___ Alot ___

(Skip to #10 if 65yrs old or older) 9. What do you think of 65+ age workers work ethic? (Indicate all that apply) Lazy __

Slow __ Weak __

Unwilling to learn __ Stubborn __ Other __ (Please indicate below) _____________________________________________________________

10. Are you financially prepared for retirement? Yes _____ No _____


I don’t Know ____ I am retired ____

11. Have you gotten any advice on how to prepare for retirement? Yes ___ No ___ I don’t know ___

12. Do you believe that you are or have been discriminated against because of your age? Explain.

(If you are younger than 65 years skip to #14)

13. Do you have a hard time taking orders from a person(s) younger than you?

Yes ____ No ____ I don’t know ____

( **** Situational questions: If you are 65 years of age or more skip to #18. If you are 3064

years of age please read the following profile descriptions and indicate whether you would

hire that individual.****)

14. John is 67 years old, struggles with elbow and knee joint pain, and has applied to work at your private landscaping business. The job requires you to work with your hands in harsh weather along with harsh terrain. John owned and ran his own landscaping business for 33 years. Would you hire John as a full time employee? Explain. 15. Helen is 73 years old and struggles from diabetes, high blood pressure, and starting to show signs of dementia. She is applying for the greeting job at the local bank. The job requires the individual to greet individuals at the front door needing assistance and making sure they get the help they need. Would you hire Helen? Explain.


16. Tom is 86 years old and struggles from alzheimer's. Although it has attacked his body at a late age he shows signs of memory loss and shakiness at times. Tom has applied for the front help desk at the local Sanford Hospital. The job consist of answering phone calls to assist families on where patients are located along with guiding those who have questions to the right location. Would you hire Tom? Explain. 17. Kathy is 92 years old and just ran her 5th marathon in 5 years. Kathy has not had any health problems but at times gets tired and loses her train of thought. She is applying for a job as manager at a local grocery store. The job consist of managing other schedules and dealing with stressed upset customers. Would you hire Kathy? Explain.

18. Would you like a finished copy of the study conducted? Yes ____ (Provide email address if applicable > _______________________) No____

grant review & proposal 2015

Documents