Determinants of Productivity among Senior Citizens in Marikina CityInes Alcantara-de Guzman, PhD

ABSTRACT

This exploratory study was conducted to identify the variables that are possible determinants of productivity among senior citizens in Marikina City and to develop a productivity-scoring instrument. The respondents were 354 male and female senior citizens aged 60-79 from Barangka and Concepcion Uno/Tumana, Marikina City. Data gathering was done using a researcher-made survey questionnaire, which consisted of three parts of combined checklist and fill-in type questions. Results show that only life activities such as walking, managing money, shopping for own groceries/personal items, using public transportation, cooking, home decorating, ironing, caring for infants/children, washing clothes using washing machine, washing clothes by hand, and washing the dishes are the only specific indicators based on Havighurst’s paradigm that predict productivity among senior citizens. Two models of productivity were developed based on the results. The first model is a 14-Predictor Productivity Model which includes 14 variables such as employment status, preparation for old age, walking, managing own money, shopping for groceries/ personal items, riding public transport, washing clothes using washing machine, washing clothes by hand, washing the dishes, and volunteer work. The second model is an 11-Predictor Productivity Model, which includes all the variables in the 14-Predictor Productivity Model except employment status, preparation for old age, and volunteer work. Productivity-scoring instruments were formulated for these two models using the questions on the research questionnaire. The focus group discussion composed of 20 participants validated the findings of the study.

INTRODUCTION

In the face of changing times and greater emphasis on high productivity, there seems to be a tendency to regard senior citizens as unproductive and generally as burden to others. Although it is not obligatory for those under 60 or 65 years old to leave the work force because of mandatory requirements, they are usually seen as ineffective or unprepared to handle new tasks brought about by modernization and technology. They are also victims of outright discrimination when seeking work because employers prefer younger persons.

The most serious difficulties from which the senior citizens suffer are economic in nature. Because of reduced income or lack of it, a high percentage of senior citizens are living near or below the poverty level. Retirement plans are generally inadequate and inflation becomes their serious problem. Many of them do not have access to adequate health services (Ogena, 2006) and once they enter the retirement age, it is hard for them to get health insurance because of age limit and prevailing costs (Weller, Wenger, and Gould, 2004).

This concern over the plight of the senior citizens is an aftermath of the increasing number of older persons 60 years old and above. Although still a young population compared with other age groups, the National Statistics Office (NSO) has reported a notable increase in their number. Based on its March 18, 2005 Special Release, the total number of senior citizens 60 years old and above has reached 4.6 million, accounting for 5.97 percent of the country’s population of 76.5 million. It means a 22.18 percent increase from 1995 (3.7 million persons) and an average

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annual population growth rate of 4.39 percent during the 1995 to 2000 period. If this growth rate continues, the number of senior citizens is expected to reach seven million in 2010 and to double in approximately 16 years (NSO, 2005). Such scenario may result to having the “young old” (60-69 years old) taking care of the “old-old” (70-79 years old).

Many of the retired senior citizens continue to work in both formal and informal labor sectors according to their capacities and preferences. Studies conducted show retirees who are employed fulltime with an average of 40 hours per week (Cabigon, 1996 and NSO, 2005). These are indications that the senior citizens are still capable of productive endeavors. Hence, this study focused on accomplishing the following objectives:

1. to describe the socio-demographic and health profile of senior citizens in Marikina City;

2. to identify the variables that are possible determinants of productivity among senior citizens in Marikina City; and

3. to develop a productivity scorecard for senior citizens.

METHODOLOGY

This study is an exploratory research, which made use of a researcher-made questionnaire as the survey technique combined with face-to-face interview. A qualitative element in the form of a focus group discussion (FGD) was also used to complement the quantitative analysis performed on the survey responses.

The respondents were male and female 60-79 years old senior citizens from two barangays representing the two districts of Marikina City: Barangka of District 1 and ConcepcionUno/Tumana of District II. These two barangays were the most populous among the barangays in the two districts and they have the highest number of senior citizens. Barangka is the first of nine barangays in District 1 with 1,277 registered senior citizens while Concepcion Uno/Tumana is the third of five barangays in District II, with 2,917 registered senior citizens (Sira, 2006). A Focus Group Discussion (FGD) was conducted among 20 participants, who were not among the respondents, to validate the data gathered from the research respondents.

The data gathered was encoded in MSExcel, processed and analyzed using the Statistical Package for the Social Sciences (SPSS). Graphical, tabular representations as well as summary statistics were used in the presentation of the sociographic, demographic, and health profile of the respondents. Cluster analysis was utilized to determine the number used to classify the senior citizens into groups such that none in the same cluster have similar characteristics. The particular criterion used for clustering was the Ward method. In this method, the clusters that were fused at each stage in the agglomeration process were such that their merger gave the minimum possible increase in the within-cluster variation, which was an assurance of homogeneity within the newly formed cluster. The Dendogram is a graphical illustration of the groupings. It was used to generate two groups of respondents based on 25 variables - the “productive” and “non-productive” senior citizens.

Logistic regression analysis was also used to determine which among the 25 variables were predictors of productivity among the respondents. It was used to generate the productivity scoring for senior citizens. The score was actually a probability of being “productive” based on the estimated model as follows:

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The estimated quantities were the coefficients of regression. The variables X1, X2,..,X25 were the dichotomous characteristics (1=present, 0=absent) listed below.

X1 = Head of the FamilyX2 = EmployedX3 = IncomeX4 = Prepared for old ageX5 = DressingX6 = EatingX7 = BathingX8 = WalkingX9 = Light ChoresX10 = Managing Own MoneyX11 = Preparing Own MealX12 = Shopping for GroceriesX13 = Riding a Public TransportX14 = Cleaning the HouseX15 = CookingX16 = Home DecoratingX17 = Ironing ClothesX18 = Caring for ChildrenX19 = Washing Clothes (by washing machine)X20 = Washing Clothes (by hand)X21 = Washing the DishesX22 = Health Status (Perceived)X23 = Organization (Membership)X24 = Volunteer WorkX25 = Productive (Perceived)

After all 25 variables were fitted, backward deletion of non-significant variables was performed to arrive at the best subset of characteristics that would most likely separate “productive” and “non-productive” individuals. Cluster analysis was used to determine the number used to classify the senior citizens into groups such that none in the same cluster have similar characteristics. Each cluster thus described, in terms of the data collected, the class to which its members belonged; and this description may be abstracted through use from the particular to the general class or type. The particular criterion used for clustering was the Ward method. Here, the clusters that were fused at each stage in the agglomeration process were such that their merger gave the minimum possible increase in the within-cluster variation, which was an assurance of homogeneity within the newly formed cluster.

RESULTS AND DISCUSSIONS

Profile of Respondents

Majority of the respondents were 60-69 years old, females, married, elementary level or elementary graduates, laborers, living with spouses and their children, and heads of families (Table 1).

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Table 1. Demo-Sociographic Profile of Respondents (N=354)

Variable Category Frequency Percentage

Age 60-69 193 54.5070 and above 161 46.00

GenderFemale 249 70.30Male 105 29.70

Civil Status

Married 184 52.00Widow/Widower 147 41.50Single 17 4.80Separated 6 1.70

Educational Attainment

Elementary level/Graduate 173 48.90High School Level/Graduate 77 21.80College Units/Graduate 53 15.00Voc Tech/College Level 37 10.50No Formal Schooling 11 3.10Graduate Degree 3 0.80

Living Arrangement

Living with spouse/children 128 36.20Living with child/children 127 35.90Living with spouse 43 12.10Living alone 28 7.90Living with other relatives 28 7.90

Occupation Upon Retirement

Laborer 46 19.66Shoemaker 41 17.52Professional 32 13.68Service Worker 26 11.11Manager/Supervisor 21 8.97Clerk 12 5.13Sales Worker 11 4.70Machine Operator 7 2.99Vendor 6 2.56Technician 4 1.71Store Owner/Operator 4 1.71Farmer 4 1.71Underwriter 3 1.28Unskilled Worker 1 0.43Shop Worker 1 0.43Fisherman 1 0.43Corporate Executive 1 0.43Carinderia 1 0.43Corporate Executive 1 0.43Unskilled Worker 6 2.56No Data 5 14.71

Living Arrangement

Living with Spouse/Children 128 36.20Living with Child/Children 127 35.90Living with Spouse 43 12.10Living alone 28 7.90Living with Other Relatives 28 7.90

Head of the FamilyYes, Head of the Family 190 53.70No, Not Head of the Family 164 46.30

Health Status and Physical Well-Being

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Majority of the respondents were non-smokers and non-drinkers of alcoholic beverages; have poor vision; went to the city’s government hospital for medical attention; assessed their health condition as good to excellent; and spent their leisure time watching television and listening to music (Table 2).

Table 2. Health Status and Physical Well-Being of Respondents (N=354)

Variable Category Frequency Percentage

Smoking PatternsNo, I don't smoke 313 88.40Yes, I smoke 41 11.60

Drinking Patterns No, I don't drink alcoholic beverages 317 89.50Yes, I drink alcoholic beverages 37 10.50

Health Status*

Poor Vision 199 56.21Poor Hearing 51 43.80Arthritis 106 30.00Hypertension 84 23.90Cataract 51 14.41Heart Disease 37 10.45Asthma 20 5.65Kidney Problem 18 5.08Osteoporosis 17 4.80Pulmonary Disease 11 3.11Ulcer 10 2.82Emphysema 3 0.85Glaucoma 2 0.56

Medical Facility Used*

Government Hospital 141 39.80Health Center 130 36.70Private Clinic 65 18.40Private Hospital 41 11.60Home 41 11.60

Perceived Health AssessmentGood to Excellent 264 74.60Poor to Fair 90 25.40

Leisure Activities*

Watching Television 300 84.70Listening to Music 224 63.30Needlework 53 15.00Ballroom Dancing 23 6.50Playing Board Games 14 4.00Fishing 9 2.50Handicrafts 8 2.30Painting 4 1.10Collecting items 1 0.30

*Multiple Responses

Economic Activities

Most of the respondents were retirees and were receiving a monthly pension of Php 4,000.00 and below. A small percentage of the respondents were employed and were working in private companies and receiving an income of Php 4,000.00 and below. Majority of them claimed that the monthly income they received was insufficient for their daily needs. Most of the unemployed and non-retirees have plans of looking for a fulltime but home-based jobs. The unemployed and non-retirees identified several sources of income such as children, other relatives, friends, and colleagues; rentals; farmland; financial investment; spouse’s pension; and spouse’s

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income. Most of the respondents also claimed that they prepared for their old age by sending their children to school, a typical Filipino family value giving importance to education as a poverty-liberating factor. Those who claimed they did not prepare for old age pointed out some reasons such as: no extra income; it was not seen as a need; and they were too busy to think of saving for their old age (Table 3).

Table 3. Economic Activities of Respondents (N=354)

Variable Category Frequency Percentage

Employment StatusRetired 174 49.20Otherwise (Unemployed/Non-retiree) 120 33.90Employed 60 16.90

Type of EmploymentPrivate 144 62.30Self-employed 55 23.80Government 32 13.90

Monthly Income of Employed

Below P4, 000 38 63.334,001-8,000 13 21.678,001-15,000 4 6.6715,001-30,000 1 1.6730,001-50,000 1 1.6750,001 and above 1 1.67No data 2 3.33

Monthly Pension of Retirees

Below P4, 000 97 55.754,001-8,000 21 12.008,001-15,000 10 5.7515,001-30,000 2 1.1530,001-50,000 1 0.5750,001 and above 0 0No pension 43 29.71

Work Plans and Preferences ofUnemployed and Retirees

Have plans to look for work 136 46.25Fulltime 136 46.25Part-time 106 36.05Undecided 52 17.69Home-based 88 29.93Out-of-home 43 14.68Undecided 163 55.44

Life Activities

Most of the respondents could perform activities of daily life (ADLs) without any help from other people such as: dressing up or putting on clothes, eating, taking a bath, and walking around the house. Among the respondents, 1.4 percent expressed difficulty in walking around the house, 13.1 percent have difficulty dressing up and eating, while 2.5 percent have difficulty taking a bath. This could be attributed to the fact that there are more 60 to 69 years old (young old) than the 70 years old and above (old-old), thus younger and stronger respondents. Majority can also perform instrumental activities of daily life (IADLs) such as doing light household chores, managing own money, preparing own meal, shopping for own groceries/personal items, and using public transportation. Results also show that majority of the respondents were involved in household chores in their own homes. In fact, they considered these household chores as their contributions in their families (Figure 1).

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Figure 1. Engagement in Activities of Daily Living (ADL), Instrumental Activities in Daily Living (IADL), and Household Chores.

Volunteer Work

Volunteer work is a valuable and productive way for older people to stay engaged in society, to use their expertise, maintain, and nourish their sense of purpose, their innate value and their self-respect, which results in greater independence, health and well-being for older people (WHO, 2002). The results of this study show that most of the respondents (55.9%) were not involved in volunteer work due to poor health (28.8%). Other reasons given were lack of time (18.1%); they did not know how and where (12.1%); and they lacked funds to do volunteer work (1.4%). Those who were involved in volunteer work joined barangay activities; Homeowners’ Association activities; parish activities (church choir, lector, acolyte, catechist, lay minister, and mother butler); feeding programs; Gawad Kalinga projects; livelihood programs; family counseling; and traffic enforcer volunteer (Figure 2).

Figure 2. Involvement in Volunteer Work

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Membership in Organizations

Havighurst (1964) noted that establishing an explicit affiliation with one’s age group is one task of the elderly. It involves accepting one’s status in the community and becoming an active participant in one’s age group. Ageing slows down a person, such that it is now quite impossible for senior citizens to keep up with activities done in their younger years, thus they resort to giving up these activities. In this study, most of the respondents (63.3%) were members of organizations such as: church organizations, Homeowners/Neighborhood Association, Kababaihan, Civic Clubs, Samahang Caretakers, Senior Choir, Marikina Riverpark Runners, Loyola Civic Organizations, Senior Citizens’ Association, and Women’s Clubs. The senior citizens looked at membership in organizations as their chance to relate with other people especially those of their own age.

Community Involvement

Havighurst (1964) also added that one task of later maturity is meeting social and civic obligations. He said that older people are involved in the conduct of civic and political affairs both as citizens and office holders. In this study, the senior citizens were asked to identify top five problems in their respective communities. The results show that majority (66.6%) of the respondents considered unemployment problems as the number one problem followed by security (41.4%), substance abuse (33.1%), pollution (30.6%) and illiteracy (21.5%). They also identified some personal

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contributions to lessen these problems such as reporting incidents to authorities (63.2%), participating actively in community affairs (49.9%), becoming a more vigilant community member (34.3%), and conducting skills development programs (23.7%). Their knowledge about societal problems and what they could do to help solve these problems were clear indications of their desire to take part in community affairs (Table 4).

Table 4. Community Involvement of the Respondents (N=354)

Variable Category Frequency Percentage

Community Problems*

Unemployment 235 66.6Security 146 41.4Substance abuse 117 33.1Pollution 100 30.6Crime and Violence 76 21.5Illiteracy 76 21.5Juvenile delinquency 57 16.1Child Abuse 36 10.2Immorality 35 9.9

Possible Contributions of Respondents*

Report incidents immediately to authorities 223 63.2Participate actively in community affairs 176 49.9Become a more vigilant community member 121 34.3Conduct skills development program 73 23.7

Multiple Responses*

Perceived Productivity

Majority of the respondents (85.9%) claimed that they are productive. This personal assessment supports the argument that senior citizens are still at the height of their productivity and their desire to continue being a resource for their families and in the community where they belong.

“Productive” and “Non-Productive” Respondents

Using Cluster Analysis, 25 variables were chosen from the questionnaire and were tested using Statistical Package for the Social Sciences (SPSS). The objective was to group the respondents into “productive” and “non-productive” based on the chosen variables. The Dendogram showed two major clusters of respondents: the “productive” and the “non-productive” clusters. Results also show that almost an equal number of respondents were labeled as “productive” and “non-productive” (Figure 3), which did not cohere to the respondents’ actual perception of themselves. Thus, the results of the Cluster Analysis was only one way of classifying the senior citizens based on the variables chosen. However, the perceived productivity of the respondents based on their own personal assessment, which includes their capabilities cannot be ignored as another way of grouping them.

Figure 3. “Productive” and “Non-Productive” Respondents Based on the 25 Variables

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The groupings generated by the Cluster Analysis may lead to stereotyping the senior citizens so that other people may see them as “non-productive”. This stereotyping could be one of the reasons why after retirement the average senior citizen could hardly get a second employment or if unemployed, such stereotype makes it harder for him or her to participate in paid labor as evidenced by the respondent’s disclosure below.

“Dapat pantay-pantay ang pagtingin ng mga employers sa mga naghahanap ng trabaho matanda man o bata. Sa mga panahong ito, para bang wala nang kuwenta ang tao pag matanda na kasi ayaw ng tanggapin sa trabaho.”

(Employers should give equal chances to people looking for jobs, young or old. At present, it seems like senior citizens are useless because employers do not want to hire them anymore.)

The results could also be supported in terms of what the Johari Window by Joseph Luft and Harry Ingham (Yen, 1999) posits. It is one of the most useful models describing the process of human interaction. The four-paned window divides personal awareness into four different types represented by its four quadrants: open, hidden, blind, and unknown. The lines dividing the four are like window shades, which can move as an interaction progresses. The open quadrant is known to self and to others; the blind quadrant is not known to self but known to others; the hidden quadrant is known to self but not known to others; the unknown quadrant is not known to self and not known to others. Hence, the perceived productivity of the respondents could be compared to the hidden quadrant where information is known only to the self, while the result of the Cluster Analysis could be compared to the blind quadrant where information is unknown to the self but known to others. The Johari Window (Figure

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Head of the familyEmployedIncomePrepared for old ageDressingEatingBathingWalkingLight ChoresManaging Own MoneyPreparing Own MealShopping for GroceriesRiding a Public TransportCleaning the HouseCookingHome DecoratingIroning ClothesCaring for ChildrenWashing Clothes (by machine)Washing Clothes (by hand)Washing the DishesHealthy (Perceived)Organization (Membership)VolunteerProductive (Perceived)

Variables

4) aims at increasing the open area while reducing the blind, the hidden, and the unknown areas through feedback, disclosure, and self-discovery and mutual enlightenment respectively. Similarly, feedback, disclosure, self-discovery, and mutual enlightenment can be beneficial for the senior citizens and those working for their welfare.

Figure 4. Productivity and the Johari Window

Predictors of Productivity

Logistic regression analysis was used to determine which among the 25 variables were predictors of productivity among the respondents. It was also used to generate the productivity scorecard for senior citizens. The Full Model (Table 5) shows all 25 clustering variables entering the model. Though some variables were not significant on their own, logistic regression combined their predictive powers. From the Full Model, deletion was done starting with health, as most geriatric studies seem to point that this bears the least significance to the senior citizen’s productivity followed by eating with .999 significance. From here on, deletion continued beginning with the least significant predictor. The Full Model shows that 93.1 percent of “non-productive” are concordantly classified by the Logistic Model and 95 percent of “productive” are concordantly classified by the same model. The overall classification efficiency is 94.1 percent. Thus, 94.1 percent of the respondents were correctly identified into their respective clusters. The Classification Tablea (Table 6) with 14 variables has an effective p-value of alpha = 0.20, with 94 percent accuracy and a good mixture of predictors such as: employment status, preparation for old age, walking, managing own money, shopping for own groceries, using public transportation, cooking family meals, home decorating, ironing clothes, caring for infants/children, washing clothes using washing machine, washing clothes by hand, dishwashing, and doing volunteer work. The Classification Tableb (Table 7) with 11 predictors was a result of further deletion of the least significant variable. As a result, three other variables were deleted: employment status, preparation for old age, and volunteer work, leaving only life activities as predictors of productivity.

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KNOWN TO SELF

UNKNOWN TO SELF

UNKNOWN TO OTHERS

KNOWN TO OTHERS

OPEN BLINDCluster Analysis’ Result on Productivity

HIDDENPerceived

Productivity of

Respondents

UNKNOWN

Table 5. Full Model Showing the 25 Clustering Variables

Classification Table Logistic-Predicted  

Productivity GroupPercentage

Correct  NonProductive Productive  

Productivity Cluster NonProductive 161 12 93.0636Productive 9 172 95.0276

Overall Percentage 94.0678 The cut value is .500

Variables in the Equation

B S.E. Wald df Sig. Exp(B)Head of family -0.07360 0.55719 0.01745 1.00000 0.89491 0.92904Employment status 1.63568 0.81396 4.03823 1.00000 0.04448 5.13293Income 0.56825 0.60100 0.89399 1.00000 0.34440 1.76517Preparation for old age 1.20478 0.59663 4.07757 1.00000 0.04346 3.33604Dressing-up 19.85974 7202.85698 0.00001 1.00000 0.99780 421673546.89229Eating 9.32784 7202.85853 0.00000 1.00000 0.99897 11246.82413Bathing -2.03175 41.71401 0.00237 1.00000 0.96115 0.13111Walking 0.98608 41.69646 0.00056 1.00000 0.98113 2.68072Light household chores 0.22836 1.86287 0.01503 1.00000 0.90243 1.25654Managing 1.87337 0.72819 6.61851 1.00000 0.01009 6.51020Preparing for old age -3.21565 1.56648 4.21391 1.00000 0.04009 0.04013Shopping groceries 3.08804 0.87897 12.34281 1.00000 0.00044 21.93399Using public transportation 1.65616 0.84654 3.82744 1.00000 0.05042 5.23916Cleaning the house 0.72461 1.19682 0.36656 1.00000 0.54488 2.06392Cooking meals 3.20908 0.94830 11.45183 1.00000 0.00071 24.75642Home Decorating 1.11888 0.64857 2.97615 1.00000 0.08450 3.06142Ironing 4.27764 0.73252 34.10116 1.00000 0.00000 72.06987Caring for infants/children 2.26907 0.57065 15.81079 1.00000 0.00007 9.67039Washing Clothes-washing machine 1.51751 0.60944 6.20012 1.00000 0.01277 4.56087Washing clothes by hand 1.63393 0.60584 7.27355 1.00000 0.00700 5.12397Washing the dishes 1.83901 0.74201 6.14251 1.00000 0.01320 6.29030Perceived Health -2.09528 0.73078 8.22071 1.00000 0.00414 0.12304Membership in organization 0.66267 0.56741 1.36396 1.00000 0.24285 1.93997Volunteer work 0.94411 0.58968 2.56341 1.00000 0.10936 2.57052Perceived Productivity 0.11467 0.81185 0.01995 1.00000 0.88767 1.12150Constant -42.25201 10158.07219 0.00002 1.00000 0.99668 0.00000

Table 6. Classification Table with 14 Variables

Classification Table Logistic-Predicted  

Productivity GroupPercentage

Correct  NonProductive Productive  

Productivity Cluster NonProductive 160 13 92.5

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Productive 9 172 95.0Overall Percentage 93.8The cut value is .500Variables in the Equation

B S.E. Wald df Sig. Exp(B)Employment Status 1.4243 0.6753 4.4486 1.0000 0.0349 4.1549Prepared for Old Age 0.7588 0.5313 2.0396 1.0000 0.1532 2.1358Walking 4.5917 1.8519 6.1479 1.0000 0.0132 98.6625Managing own Money 1.9924 0.6743 8.7317 1.0000 0.0031 7.3331Shopping for Groceries 2.4659 0.8014 9.4679 1.0000 0.0021 11.7740Using Public Transportation 1.7397 0.7491 5.3938 1.0000 0.0202 5.6956Cooking family meals 2.4571 0.7743 10.0704 1.0000 0.0015 11.6707Home Decorating 1.0608 0.5535 3.6738 1.0000 0.0553 2.8888Ironing Clothes 3.6348 0.5710 40.5192 1.0000 0.0000 37.8941Caring for Infant/Children 1.9034 0.5034 14.2962 1.0000 0.0002 6.7090Washing Clothes by Washing Machine 1.2632 0.5375 5.5227 1.0000 0.0188 3.5366Washing Clothes by Hand 1.5427 0.5202 8.7955 1.0000 0.0030 4.6773Washing the Dishes 1.9588 0.6619 8.7569 1.0000 0.0031 7.0906Healthy-Perceived 0.6943 0.5054 1.8869 1.0000 0.1696 2.0022Constant -19.5457 3.2775 35.5637 1.0000 0.0000 0.0000

Table 7. Classification Table with 11 VariablesClassification TableObserved Predicted    

Productivity Group  

Percentage Correct

NonProductive Productive  Productivity Cluster NonProductive 157 16 90.8  Productive 9 172 95.0Overall Percentage       92.9The cut value is .500                                      Variables in the Equation            

B S.E. Wald df Sig. Exp(B)Walking 4.1218 1.7404 5.6088 1.0000 0.0179 61.6693Managing Own Money 2.0202 0.6503 9.6514 1.0000 0.0019 7.5401Shopping for Groceries 2.2135 0.7406 8.9321 1.0000 0.0028 9.1481Using Public Transportation 1.8509 0.7410 6.2391 1.0000 0.0125 6.3659Cooking Family Meals 2.2796 0.7473 9.3051 1.0000 0.0023 9.7730Home Decorating 1.0704 0.5386 3.9493 1.0000 0.0469 2.9165

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Ironing Clothes 3.4044 0.5350 40.4943 1.0000 0.0000 30.0950Caring for Infant/Children 1.9376 0.4875 15.7968 1.0000 0.0001 6.9422Washing Clothes Using Washing Machine 1.1254 0.5167 4.7440 1.0000 0.0294 3.0814Washing Clothes by Hand 1.5623 0.5111 9.3439 1.0000 0.0022 4.7696Washing the Dishes 1.5934 0.5923 7.2377 1.0000 0.0071 4.9204Constant -16.5552 2.6274 39.7021 1.0000 0.0000 0.0000

Based on the results of the study, two productivity-scoring instruments for senior citizens in Marikina City were proposed.

1. A 14-Predictor Productivity Model Scoring Instrument. This productivity-scoring instrument contains 14 variables. These are:

1. Employment status2. Preparation for old age3. Walking around the house4. Managing own money5. Shopping for own groceries6. Using public transportation7. Cooking family meals8. Home decorating9. Ironing clothes10. Caring for infant/children11. Washing clothes using washing machine12. Washing clothes by hand13. Washing the dishes14. Volunteer work.

This Productivity Model could be used if there is a need for more data to determine the productivity among senior citizens. Though it still contains three least significant predictors, it has a good mixture of various predictors that could give a more comprehensive productivity assessment. Moreover, the variables encompassed various contexts in which the elderly may find themselves engaged in. It consists of 14 questions based on the 14 variables with 94 percent accuracy level (Figure 5).

2. The 11-Predictor Productivity Model Scoring Instrument. This scoringinstrument contains 11 significant predictors, which are all life activities. It is recommended for Marikina senior citizens with similar profile as the respondents of this study. These are:

1. Walking around the house2. Managing own money3. Shopping for own groceries4. Using public transportation5. Cooking6. Home decorating

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7. Ironing clothes8. Caring for infant/children9. Washing clothes using washing machine10. Washing clothes by hand11. Washing the dishes

This productivity-scoring instrument has 93 percent accuracy. This is more preferred especially for the respondents of this study because it has only 11 questions representing the 11 highly significant variables that could be easily answered by the senior citizens. It is also easier when computing for the scores or results (Figure 6).

Figure 5. Scoring instrument for the 14-Predictor Productivity Model

PRODUCTIVITY SCORING INSTRUMENTFor Marikina City Senior Citizens

A. NAME: _________________________

Below are questions related to your ability to perform basic life and household activities. Read the questions carefully then put an x on the column that corresponds to your answer.

B. SCORECARDQuestions Yes No Score (1 if

yes, 0 if no)

1. Are you employed? x   1

2. Did you prepare for your old age when you were younger?   x 0

3. Do you walk around the house everyday? x   1

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4. Do you manage your own money? x   1

5. Do you shop for your own groceries or personal items? x   1

6. Do you use public transportation without help from others? x   1

7. Do you cook meals for the family? x   1

8. Do you like decorating your home?   x 0

9. Do you iron clothes for the family? x   1

10. Do you take care of infants or children/grandchildren?   x 0

11. Do you wash your clothes using a washing machine? x   1

12. Do you wash clothes by hand?   x 0

13. Do you wash the dishes?   x 0

14. Are you currently involved in volunteer work? x   1

Equation:

C. SCORE:

PRODUCTIVE NON-PRODUCTIVE (If score is >.50) (If score <.50)

Figure 6. Scoring instrument for the 11-Predictor Productivity Model

PRODUCTIVITY SCORING INSTRUMENTFor Marikina City Senior Citizens

A. NAME: _________________________

Below are questions related to your ability to perform basic life and household activities. Read the questions carefully then put an x the column that corresponds to your answer.

B. SCORECARD

Questions Yes No Score (1 if yes, 0 if

not)1. Do you walk around the house everyday? x   1

2. Do you manage your own money?   x 0

3. Do you shop for your own groceries or personal items? x   1

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4. Do you use public transportation without help from others? x   1

5. Do you cook meals for the family? x   1

6. Do you like decorating your home? x   1

7. Do you iron clothes for the family? x   1

8. Do you take care of infants or children/grandchildren?   x 0

9. Do you wash your clothes using a washing machine? x   1

10. Do you wash clothes by hand?   x 0

11. Do you wash the dishes? x   1

Equation:

C. SCORE

PRODUCTIVE NON PRODUCTIVE (If score is >.50) (If score <.50)

CONCLUSION AND RECOMMENDATIONS

At this age and time when senior citizens are increasing in number, plans on how to effectively address their needs are also underway. These plans include varied opportunities to sustain and improve further their productivity and maintain their contributions for their own welfare and those of others. They are aimed at encouraging them to strengthen their independence, prolong their spirit of productivity as they enjoy life to the fullest. The need for these programs has become more urgent because of the dramatic changes in family structures, roles and labor patterns, and migration, especially in the rapidly changing global environment.

The movement of young people to urban areas, the shift from extended to nuclear families, and the increasing number of women joining the workforce are all developments that brought about new adjustments especially on the senior citizens caring for themselves. Globally, the senior citizens are now regarded as beneficiaries and active participants and contributors of developments (WHO, 2002). In fact, they are authentic sources of information, tested family values, beautiful traditions, and actual experiences.

The senior citizens have fulfilled their part in creating the kind of life we are now enjoying. It is but just and fair to make them feel that we appreciate them for their own contributions through the programs designed to empower them even in their old age. No less than Pope John Paul II (Martino, 1999) in one of his celebrated prayers on July 25, 1999, calls us to always remember that:

“By their very presence, older people remind everyone, especially the young that life on earth is a ‘parable’ with its own beginning and end: to find its fulfillment, life must be based on values that are not transient and superficial, but solid and profound. The so called ‘third age’ is …a value in itself by the very fact that life is prolonged and life itself is a gift of God.”

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Based on the findings of this study, the following recommendations are presented:

1. Using the results of this study, the Office of the Senior Citizens’ Affairs (OSCA) that works for the welfare of Marikina City senior citizens, could plan and conduct skills and personality development programs (healthy lifestyle, art appreciation, and creative leisure activities) to increase the senior citizens’ capabilities, empower, and build-up further their self-confidence. The senior citizens in their desire to participate in economic and other worthwhile activities can also utilize such skills.

2. Through the findings and analyses being offered in this research, the Marikina City government and its private institutions could put their acts together to formulate public policy, maintenance, monitoring, and evaluation for the sake of sustaining the democratic and productive participation of the senior citizens in community and nation building.

3. The study aimed at providing continued avenues where the senior citizens could remain as productive members of society. Therefore, the results of this study could be used as bases for developing better working conditions, health, and retirement benefits or schemes. Also, by recognizing the potential contributions of senior citizens, labor and business sectors in the city could look into the possibility of adjusting existing labor practices and policies that apply to ageing workers like adopting a much later retirement age or making retirement optional at age 65, so that they continue to actively participate in community development as they prepare themselves for a more economically sound retirement.

4. To sustain a beautiful Filipino tradition of respect for old age and increase appreciation for their contributions, topics on the elderly or later maturity should be incorporated in the basic and tertiary education Home Economics curriculum. Hopefully, such inclusion of topics will enable the young to develop a better consciousness for the welfare of the senior citizens. In addition, this will enable them to adopt a more informed consciousness about ageing.

5. Using the productivity-scoring instrument, being the major contribution of this research, a pilot test could be conducted among Marikina senior citizens to ensure its validity and reliability for self-assessment or self-evaluation.

6. The Marikina City government may utilize the Productivity-Scoring Instruments to assess the senior citizens’ capabilities and preparedness to undergo programs designed to provide them with sustained stimulating external environment in which they may function at high levels of attentiveness and productivity. By using these for profiling purposes, policies, practices, and provisions for the elderly may better be designed and implemented.

7. Considering the limitations of this research, a more in-depth study using a larger and more varied sample should be conducted to get a better picture of possible predictors of productivity among senior citizens not only in Marikina City but also all over the Philippines. This may become the basis of further transnational and cross-cultural analysis of productivity among the elderly.

8. The 14-Predictor Productivity Model maybe studied further in terms of its applicability and comprehensiveness because it covers not just the daily life activities but also economic activities and community work of the senior citizens.

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REFERENCES

Cabigon, Josefina V. (1999). Idle, tired, and retired elderly– A myth the Filipino elderly: Towards a society for all ages. Rapid demographic change and the welfare of the elderly project, the 1996 Philippine elderly and near elderly survey. Demographic Research and Development Foundation (DRDF), Quezon City. Philippines.

Havighurst, Robert J. (1964). Developmental tasks and education. New York: David McKay Company, Inc. pp. 92-100.

Martino, Archbishop Renato R., Apostolic Nuncio (1999). Permanent Observer of the Holy See to the United Nations Before the Plenary of the General Assembly in its 54th session on the “Follow-Up to the international year of older persons.” New York, (October 5). http:/www.vatican.va/romancuria secretariatstate/documents/ rc seg-st doc 05101999 older-person en.html.

National Statistics Office (2005). Senior citizens comprised six percent of the population: A special release based on the results of census 2000. Special Release No. 151, Date Released: March 18, 2005. http://www.census.gov.ph/data press release/2006/pr0620tx.html

Ogena, Nimfa B. ( 2006). The low and slow ageing in the Philippines: Auspicious or challenging?. University of the Philippines Population Institute (UPPI).

Sira, Warren (2006). Data on the registered senior citizens per barangay. Office for Senior Citizens Affairs, Marikina City Hall, Marikina City.

Weller, Christian E., Wenger, Jeffrey, and Elise Gould (2004). Health insurance coverage in retirement: The erosion of retiree income security. http://www.epinet.org/content.cfm/books_health_ins_ret

World Health Organization Brasilia (2002). Older people new power for development. UN 2002 http://www.who.int/hpr/ageing/international_day_en.html

Yen, Duen His (1999). Johari Window. http:www.noogenesis.com/game_theory/johari/johari_window.html

About the Author

Ines Alcantara-de Guzman is the current Assistant Principal for Student Affairs of MCHS, where she has been serving in the last 29 years. She obtained her bachelor’s, master’s, and doctoral degrees in Home Economics from the College of Home Economics of the University of the Philippines. She has written several textbooks in Home Economics and Livelihood Education (HELE) Grades 4-6, Technology and Home Economics (THE) Years I-IV, and Technology and Livelihood Education (TLE) Years I-II. She writes a quarterly journal for TLE Years I-IV entitled Vitality Journal published by Innovative Educational Materials, Inc., She has conducted various seminars and workshops for HELE, THE/TLE teachers.

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