Predicting four types of service needs in older adults

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Abstract

Logistic regression analysis was used to predict four service need variables. A sample of nearly 5000 older Missourians were assessed on a comprehensive set of variables, representing all of the categories of the behavioral model. Variables in the behavioral model predicted perceived need for frail elderly services better than they predicted unmet need for frail elderly services, perceived need for community services, and unmet need for community services. Health need variables were better predictors of all of the service need variables than predisposing or enabling variables. Although the inclusion of interaction terms in the prediction models did not increase model fit, some of the interaction terms were significant and helped to clarify the relationship between certain predictor variables and the four service need variables.

Introduction

State Units on Aging and their affiliated Area Agencies on Aging are federally mandated to assess the needs of the older adults living in their catchment area. As Diwan and Moriarity (1995) point out, the task of defining needs is not a simple one. Perceived service need and unmet service need are the two most common definitions of service needs used in previous research predicting service needs of the elderly. Although these two concepts have often been used interchangeably in previous articles, they are conceptually and computationally quite different. Perceived service need measures simply ask respondents if they need specific services (e.g. home health care or telephone reassurance), regardless of whether they are currently receiving any services aimed at alleviating those needs. Unmet service need measures, on the other hand, only count those services which respondents report needing, but which they are not receiving currently. Both service need measures are worthy of study. For example, measure of perceived service needs often correlate as high with service utilization as objective health needs (Calsyn and Roades, 1993, Mindel and Wright, 1982, Starrett et al., 1989). Similarly, research has shown that a significant percentage of the older adult population report having unmet service needs even when they report no objective health needs (Jackson & Mittlemark, 1997). Although agency planners are primarily interested in measuring and predicting unmet service needs, other gerontological researchers are more interested in predicting perceived service needs.

This paper compares the ability of the behavioral model (Andersen, 1995) to predict both perceived service need and unmet service need. Although the behavioral model was originally developed to predict service utilization, several studies have used the behavioral model to predict either perceived service need (Calsyn and Roades, 1993, Coulton and Frost, 1982, Mindel and Wright, 1982, Richardson, 1992, Starrett et al., 1989, Starrett et al., 1989) or unmet service need (Calsyn et al., 1998, Jackson and Mittlemark, 1997). Unfortunately, these studies have only explained 10–15% of the variance of either perceived service needs or unmet service needs.

Prior researchers have also failed to distinguish between needs for different types of services. With the exception of a study by Coulton and Frost (1982), previous studies have predicted an aggregated measure of service needs. These aggregated measures combine needs for frail elderly services (e.g. meals on wheels, home health) with needs for community services (e.g. senior centers, health screening). In hopes that the behavioral model would explain more of the variance of specific service need variables than total service need, this study predicted four service need variables: perceived need for frail elderly services, unmet need for frail elderly services, perceived need for community services, and unmet need for community services.

For this study, predictor variables were classified into the following categories based on the behavioral model (Andersen, 1995): predisposing; enabling; and health needs. Predisposing variables include demographic characteristics as well as beliefs and attitudes about the causes of problems. Enabling variables include individual resources (e.g. income) and family and community resources (e.g. social support). Health need variables include physical health status, functional impairment, and mental health.

In this study we were particularly interested in determining what percentage of the variance of perceived service needs could be explained solely on the basis of health needs versus other variables. We expected health need variables would be the best predictors of all four service need variables. In addition, we hypothesized that predisposing and enabling variables would explain a significant percentage of the variance of both perceived need and unmet need for community services, but very little variance of both perceived need and unmet need for frail elderly services. Our rationale for these hypotheses is based on service utilization research which has found that predisposing and enabling variables have explained very little variance of the use of more non-discretionary services such as hospitalization and home health care; nearly all of the explained variance was accounted for by health need variables (Wolinsky & Johnson, 1991). In contrast, predisposing and enabling variables have explained a significant percentage of the variance of the use of more discretionary services such as attendance at a senior center (Mitchell & Krout, 1998). In the only study which has examined the prediction of multiple service need variables, Coulton and Frost (1982) did find that health need variables explained nearly all of the variance of more non-discretionary service needs such as outpatient medical care and in-home personal care, whereas predisposing and enabling variables explained a significant percentage of the variance of the need for recreational services, a discretionary service.

Another improvement of this study over previous research was the inclusion of interaction terms in the prediction models. Several authors have suggested that the performance of the behavioral model in predicting service utilization could be improved if interaction terms were included in the model (Kosloski and Montgomery, 1994, Rundall, 1981). Similarly, we believed that the inclusion of interaction terms would improve the prediction of the service need variables. All of the interaction terms in our models included health need as one of the variables. In general, we postulated that terms would have a multiplicative effect under conditions of greater health needs. Below, we review more specific findings of the studies predicting total service needs (perceived and unmet). Unfortunately, the study results are often contradictory. Differences in samples and operational definitions of constructs are also probably responsible for the lack of consistency in the study findings.

As a group, predisposing variables have explained very little of the variance of total service needs. Moreover, none of the specific predisposing variables have exhibited a strong and consistent relationship with service needs. Although age was positively related to service needs in two studies (Jackson and Mittlemark, 1997, Mindel and Wright, 1982), three other studies found no relationship between age and service need (Calsyn and Roades, 1993, Calsyn et al., 1998, Richardson, 1992). We hypothesized that age would be positively related to need for frail elderly services, but unrelated to need for community services. African-Americans have reported greater service needs than Caucasians in some studies (Calsyn et al., 1998, Coulton and Frost, 1982, Jackson and Mittlemark, 1997), but race was unrelated to service needs in other studies (Calsyn and Roades, 1993, Mindel and Wright, 1982). Women reported more service needs than men in two studies (Calsyn and Roades, 1993, Mindel and Wright, 1982), but two other studies found no gender differences (Calsyn et al., 1998, Richardson, 1992). In the Coulton and Frost (1982) study, women reported greater need for medical, mental health, and recreational services, but men reported greater need for frail elderly services. Education was not correlated with service needs in any of the previous studies (Calsyn and Roades, 1993, Calsyn et al., 1998, Mindel and Wright, 1982, Richardson, 1992).

Enabling variables also have not explained much of the variance of total service needs of the elderly. Individuals with less income reported more service needs in one study (Calsyn et al., 1998), but income was unrelated to service needs in two other studies (Calsyn and Roades, 1993, Richardson, 1992). Social contact variables have not explained much of the variance of service needs (Calsyn and Roades, 1993, Calsyn et al., 1998, Richardson, 1992), with the exception of the study by Coulton and Frost (1982) which found that persons who were less isolated were more likely to report needing the more discretionary mental health and recreational services. Thus, we predicted that persons who reported more social contacts would also report more need for community services, but not frail elderly services. On the other hand, we predicted that persons who lived alone and/or reported no one to assist them in an emergency would report a greater need for frail elderly services; however, we did not think living situation and the availability of emergency services would affect need for community services. Based on Mitchell's (1995) finding that length of time in the community affects service awareness, we predicted that respondents who had lived in their community for a shorter period of time, would be more likely to report more service needs. In this study we also examined the impact of perceived age discrimination on service needs. We hypothesized that respondents who felt that they had experienced age discrimination would report more service needs, consistent with the results of a previous study which had found that older adults who reported sex discrimination indicated having more needs (Starrett et al., 1989a).

Measures of health need (e.g. functional impairment, physical health status, and low morale) have typically been the strongest predictors of service needs (Calsyn and Roades, 1993, Coulton and Frost, 1982, Jackson and Mittlemark, 1997, Mindel and Wright, 1982, Richardson, 1992, Starrett et al., 1989), with only one study finding no significant relationship between health need indicators and service needs (Calsyn et al., 1998).

As noted earlier we postulated that the inclusion of interaction terms in the prediction models would explain additional variance of service needs. We created interaction terms between two of the social contact variables, living situation (alone, with others) and availability of emergency support (yes, no) with the four health need variables. We predicted that the impact of health needs on both perceived and unmet need for frail elderly and community services would be greater for those respondents who lived alone and those respondents who reported having no one to rely on in the case of an emergency. This prediction is based on prior research predicting service utilization among older adults which finds that in high need situations, respondents who live alone and/or have less emergency support available, are more likely to use formal services (Biegel et al., 1993, Logan and Spitze, 1994, Mitchell, 1995).

Section snippets

Sample and procedure

Data were collected for the 1994 needs assessment study of the Missouri Department of Social Service's Division of Aging and the 10 Missouri Area Agencies on Aging (Drainer, 1994). The sample was stratified by the 10 AAA regions in Missouri using the optimum allocation or disproportionate sampling method. Telephone interviews were conducted by trained interviewers at the Center for Advanced Social Research at the University of Missouri-Columbia. Questions were asked of the person in the

Results

As Table 1 indicates, 25% of the sample reported perceived need for frail elderly services, but only 7% of the sample had an unmet need for frail elderly services. Similarly, 37% of the sample reported a perceived need for community services, but only 16% of the sample reported an unmet need for community services. Correlations between the four service need variables ranged from 0.24 to 0.57 (see Table 2).

Relationship to prior research

The main conclusions of the study are: (1) the behavioral model predicts perceived need for frail elderly services moderately well, but predicts the following less well: unmet need for frail elderly services, perceived need for community services, and unmet need for community services; (2) most of the predictor variables were related to all four service need variables in the same way, but there were some interesting exceptions; (3) inclusion of interaction terms does not increase model fit, but

Acknowledgements

This study would not have been possible without the cooperation of those older adults who consented to be interviewed; we appreciate their time and thoughtfulness. We also wish to thank the staffs of the Missouri Division of Aging and the Missouri Department of Social Services, particularly Dr Ann Deaton and Ms Becky Viet, who made the data available to the authors. However, the analyses and conclusions presented in this paper are the sole responsibility of the authors and do not necessarily

Robert J. Calsyn is professor of psychology and director of gerontology at the University of Missouri-St. Louis.

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