Canadian Journal of Occupational Therapy 80(5) 284-294 DOI: 10.1177/0008417413501467

Article

Performance measures rather than self-report measures of functional status predict home care use in community-dwelling older adults

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Utiliser des mesures du rendement plutoˆt que des instruments d’autoe´valuation des capacite´s fonctionnelles pour pre´dire l’utilisation des soins a` domicile chez des aıˆne´s vivant dans la collectivite´

Cara L. Brown and Marcia L. Finlayson

Key words: Activities of daily living; Functional status; Home care; Performance measures; Self-report measures. Mots cle´s : activite´s de la vie quotidienne; capacite´s fonctionnelles; instruments d’autoe´valuation; mesures du rendement; soins a` domicile.

Abstract Background. Occupational therapists frequently assess functional status (FS) to determine the home care (HC) service requirements of older adults. However, it is unclear which type of FS measure is most effective for this purpose. Purpose. This study investigated the predictive ability of three measures of FS (a self-report measure of usual behaviour, a self-report measure of capacity, and an observational performance measure—the Performance Assessment of Self-Care Skills [PASS]) on formal HC utilization. Method. A secondary analysis of 2001 Aging in Manitoba Longitudinal Study (AIM) data was conducted. Findings. The odds of receiving HC within the 30-month follow-up period were 1.32 times (or 30%) higher for each increase in the number of dependent tasks based upon a standardized performance measure. The self-report measures did not predict HC utilization. Implications. This study suggests that standardized performance measures—in particular, the PASS—are more predictive of formal HC use in community-dwelling older adults than self-report measures. Abre´ge´ Description. Les ergothe´rapeutes e´valuent fre´quemment les capacite´s fonctionnelles des aıˆne´s en vue de de´terminer leurs exigences en matie`re de services de soins a` domicile. Cependant, on ne sait pas clairement quel type de mesure des capacite´s fonctionnelles est le plus efficace a` cette fin. But. Cette e´tude se penchait sur la valeur pre´dictive de trois mesures des capacite´s fonctionnelles pour e´valuer l’utilisation des soins a` domicile formels (un instrument d’autoe´valuation du comportement habituel, un instrument d’autoe´valuation de la capacite´ et une mesure du rendement fonde´e sur l’observation—le Performance Assessment of Self-Care Skills [PASS]). Me´thodologie. Une analyse secondaire des donne´es de l’e´tude longitudinale 2001 Aging in Manitoba (AIM) a e´te´ effectue´e. Re´sultats. Les possibilite´s de recevoir des soins a` domicile sur la pe´riode de suivi de 30 mois e´taient 1,32 fois (ou 30 %) plus e´leve´es pour chaque augmentation du nombre de taˆches de´pendantes base´es sur une mesure du rendement standardise´e. Les instruments d’autoe´valuation n’ont pas permis de pre´dire l’utilisation des soins a` domicile. Conse´quences. Cette e´tude sugge`re que les mesures du rendement standardise´es—en particulier le PASS—ont une meilleure valeur pre´dictive de l’utilisation des soins a` domicile formels chez les aıˆne´s vivant dans la collectivite´ que les instruments d’autoe´valuation.

Funding: No funding was received in support of this study. Corresponding author: Cara Brown, Department of Occupational Therapy, School of Medical Rehabilitation, University of Manitoba, R106 - 771 McDermot Avenue, Winnipeg, MB, Canada, R3E 0T6. Telephone: 204-480-1337. E-mail: [email protected]

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ssessment of need for assistance with activities of daily living (ADLs) is used to determine the home care (HC) service requirements of older adults (Landi et al., 2001). However, there is no consensus on how best to measure functional status (FS). FS has been defined by Wang (2004) as a person’s ability to perform activities that are necessary for daily living. Therefore, measures of FS refers to assessments that determine an individual’s level of independence in basic and instrumental activities of daily living (IADLs). Research to date has examined the correlation between performance and self-report FS measures (Coman & Richardson, 2006) with less focus on the differences between these tools in their ability to predict health care service provision. This gap in knowledge results in clinicians choosing measures with little information about the relationship between their assessment results and the client’s health service needs. Accuracy in FS assessment is important for the best allocation of HC resources; however, efficiency in the assessment process is also important. Should a resource-intensive performance assessment of function be used, or is a more efficient self-report assessment equally as accurate in assessing older adults?

measure of current ADL performance but will not necessarily capture an individual’s true physical or cognitive capabilities (Branch & Meyers, 1987). As a result, a measure of capacity and a measure of usual behaviour may obtain different results as to the level of activity limitation (Jenkins & Laditka, 2003). Studies examining the correlations between performance and self-report measures have produced variable results. In a review paper, Coman and Richardson (2006) suggest that this variation can be explained by the extent to which the construct being compared is consistent. For example, some measures assess an individual’s ability to perform a task out of context (such as picking up something from the ground), while others determine ability to perform a daily living task (such as getting dressed). There are few studies that have compared measures that address contextual daily living tasks and even fewer that have matched the FS tasks of the measure—for example, comparing a self-report measure that asks someone how he or she is managing laundry directly to a performance measure that observes the individual doing laundry (Coman & Richardson, 2006).

Comparing FS Measures

Ability of FS Measures to Predict Health Services Utilization

Self-report and performance measures each have advantages and disadvantages, in terms of both their clinical utility and their psychometric properties. The main advantage of selfreport measures is their clinical utility (Angel & Frisco, 2001; Schenkman, Scherer, Riegger-Krugh, & Cutson, 2002; Skruppy, 1993) since performance measures can be costly and time-consuming in their administration (Angel & Frisco, 2001; Applegate, Blass, & Williams, 1990; Kempen, Steverink, Ormel, & Deeg, 1996). However, performance measures are less influenced by external factors, such as education, language, and the use or non-use of aids (Albert et al., 2006; Angel & Frisco, 2001; Kempen et al., 1996). The main documented disadvantage of self-report measures is greater margins for error due to factors such as difficulty with recall, fluctuation of responses with fluctuations of emotional status, and vulnerability to response shift (Angel & Frisco, 2001; Daltroy, Larson, Eaton, Phillips, & Liang, 1999; Keller, Kovar, Jobe, & Branch, 1993), although these internal factors have not been well studied in performance measures to date. It has been suggested that performance measures are superior in their ability to detect change because they are sensitive to mild degrees of health impairment ‘‘before overt disability is apparent’’ (Rozzini, Frisoni, Bianchetti, Zanetti, & Trabucchi, 1993, p. 113), although further research is needed to validate this argument. An additional challenge is that self-report measures obtain different types of information depending on the wording of the question. Asking ‘‘Do you (e.g., do your laundry by yourself)?’’ provides a measure of the person’s usual behaviour, while asking ‘‘Can you (e.g., do your laundry by yourself)?’’ provides information on a person’s perceived functional capacity. Asking about someone’s usual activities is a more reliable

Studies that compare self-report and performance FS measures in their ability to predict health care services use are sparse and contradictory to date. Reuben, Siu, and Kimpau (1992) found that both self-report and performance measures predicted death or nursing home placement, while Angel, Ostir, Frisco, and Markides (2000) found that a performance measure was more predictive of mortality. No studies were found using HC as an outcome variable. In summary, difficulty managing ADLs is consistently found to be a predictor of HC utilization (Chappell, 1994; Hall & Coyte, 2001; Shapiro & Tate, 1997); however, there is a lack of knowledge of what type of FS measure is best to determine HC need. Neither self-report nor performance-based measures of functional disability have been found to be superior (Myers, Holliday, Harvey, & Hutchison, 1993), and some authors suggest that they may be complementary (Guo, Matousek, Sonn, Sundh, & Steen, 2000; Reuben et al., 2004). The purpose of this study was to investigate the ability of three different FS measures to predict formal HC utilization among community-dwelling older adults living in Winnipeg. Occupational therapists use assessments of FS in clinical and research contexts. While occupational therapists inherently value the information gleaned from performance assessments, the use of a performance measure over a self-report measure is not validated in the context of assessing for future care needs. Information on the predictive validity of self-report and performance FS measures would assist with guiding choice of outcome measures for community needs assessments, guide outcome measure choices in research contexts, and further validate the use of FS measures for making individual-level choices for HC service needs.

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Brown and Finlayson

Method This retrospective longitudinal study used secondary data from the Aging in Manitoba (AIM) 2001 interview. Facilitating the study was data on three measures of FS: (a) a self-report measure of functional capacity, (b) a self-report measure of functional usual behaviour, and (c) a performance assessment, the Performance Assessment of Self-Care Skills (PASS; Rogers & Holm, 1994), as well as linked Manitoba Health Home Care utilization data.

Data Source AIM examined aging and its impact on the quality of life of older adults (Mossey, Haven, Roos, & Shapiro, 1981). AIM has involved almost 9,000 older adults from Manitoba, Canada, with three independent cross-sectional samples who entered the study at three different times (1971, 1976, and 1983) and were then followed over time. The samples were randomly drawn from the computerized records of the Manitoba Health 1970 master registry of Manitobans and stratified by residence status (community or institutional) and region of residence (one of seven geographic regions of Manitoba). The 2001 interview from which the sample for this article was drawn included 53 individuals from the 1971 wave, 153 individual from the 1976 wave, and 806 people from the 1983 wave. Further details of the sampling design have been described elsewhere (Chipperfield, Havens, & Doig, 1997; Mossey et al., 1981; Finlayson, 2002). Interviewer-administered surveys were conducted in the participants’ residence. In addition to core questions on demographics, self-perceived health status, social networks, chronic illnesses, income, and ADLs, some topics were added to different interview years to address current issues and interests (Sylvestre, Havens, & Hall, 2004).

Participants The study sample for this work included AIM participants who completed both the standard AIM interview schedule in 2001 as well as an interview supplement that included the PASS (Rogers & Holm, 1994), thus completing all three FS measures in 2001. A total of 170 participants were eligible to complete the PASS supplement; 32 declined participation. To be eligible for a PASS interview, the participants had to be living in Winnipeg and could not be institutionalized. Participants were ineligible if any of the following was true from the AIM 1996 interview: (a) a proxy respondent had completed the interview; (b) the participant was identified as cognitively impaired; (c) the participant reported that a formal service provided assistance with mobility in the house, dressing, and light housework; (d) the participant had been hostile toward the interviewer; or (e) the interview was not conducted in English. Exclusion criteria (b) and (c) were to ensure that there was not undue risk in completing the PASS assessment (Finlayson, Havens, Holm, & Van Denend, 2003). In total, 138 participants completed all three FS measures. Of these individuals, 24 participants were excluded from the

current analysis since they were already receiving HC services at the time of the 2001 interview, and 4 participants were excluded because they died within the follow-up period of this study of 30 months. Of the final sample (N ¼ 110), 30 enrolled in the Manitoba Home Care Program during the follow-up period (Figure 1). Ethical approval for this study was granted from the first author’s university ethics board and from the appropriate Health Information Privacy Committee.

Dependent Variable: The Manitoba Home Care Program The provincial Manitoba Home Care Program supports people to remain independent in their own home for as long as possible (Winnipeg Regional Health Authority [WRHA], n.d.). To be eligible for formal HC services in Winnipeg, individuals must ‘‘require health services or assistance with activities of daily living, require service to remain safely in their homes and require more assistance than available from existing supports and community resources’’ (WRHA, n.d., Section 5). Services provided include case management, service coordination, nursing services, personal care assistance, meal preparation, cleaning and laundry services, occupational and physical therapy assessment and services, and respite/family relief (Roos, Stranc, et al., 2001). An individual’s eligibility for enrolment into the Manitoba Home Care Program is dependent upon an assessment made by a HC case coordinator, who may ask for additional assessments from other health professionals, such as occupational or physical therapists. For this study, WRHA HC utilization data were extracted from the Population Health Information System (POPULIS) that is housed by the Manitoba Centre for Health Policy (MCHP) and linked to the AIM data. The original source for the HC data is the Manitoba Support Services Payroll (MSSP) database, which includes a master file of the provincial HC clients. The MCHP examined the utility of this MSSP HC data in 2001 and found that it captures 90% of those receiving HC and 80% of the delivered HC services. A limitation in the system is lack of timely closure of cases of clients who are not receiving services (Roos, Mitchell, Peterson, & Shapiro, 2001). Participants were classified either as ‘‘enrolled’’ or ‘‘not enrolled’’ in the Manitoba Home Care Program for this study. To be considered enrolled, the participant must have been enrolled in the Manitoba HC system for at least 30 days in the 30 months following the 2001 AIM interview (and thus FS measure administration). A 30-month time frame was chosen to balance sample size needs while keeping the follow-up time as short as possible to reduce the probability of participants’ independence being affected by adverse events.

Independent Variables The independent variables were the scores from seven tasks that were common across the three FS measures: shopping,

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53 participants from 1971 AIM wave

287

153 participants from 1976 AIM wave

806 participants from 1983 AIM wave

Potential participant pool of 1012 participants

170 eligible to complete PASS

138 completed PASS (32 declined)

24 participants excluded due to enrolment in Manitoba home care program at time of PASS administration in 2001

4 deaths in follow-up period

n = 110 for this study

n = 80 did not enter home care in follow-up period

n = 30 entered home care program in follow-up period

Figure 1. Participant flow chart.

managing financial matters, laundry, taking medications, nursing care, use of telephone, and getting around the house. Self-report of capacity and usual behaviour. Two of the FS measures were self-report, one of capacity and the other of usual behaviour. According to AIM documentation (Mair, 2001), the items on the self-report of usual behaviour measure originated from the Index of Functional Status by S. Katz, Ford, Moskowitz, Jackson, and Jaffe (1963), the Shanas Index of Disability (SID; Shanas et al., 1968), and the IADL scale developed by Lawton and Brody (1969). The measure of selfreport of usual behaviour asked what the person actually does (‘‘Does anyone usually help you with . . . ?’’). The response options for these items in the AIM survey was a fivecategory ordinal scale that indicates if the older adult does the tasks and, if they receive help, who provides the help. For this study, the items for the self-report of usual behaviour measure were converted from a 5-point to a 2-point scale (1 ¼ no one helps me with this task, 2 ¼ someone helps me with this task) based on a Rasch analysis that indicated that the 2-point scale is more valid for making comparisons over time and setting (Finlayson, Mallinson, & Barbosa, 2005) as the original 5point scale is unable to classify needs in a hierarchical fashion. The measure of self-report of capacity was added to AIM in 1983 due to a concern over gender bias (Mair, 2001). The items from the self-report of usual behaviour are matched using the question stem ‘‘Are you capable of . . . without any help from anyone?’’ These items had the response options of yes or no.

Performance measure: PASS. The PASS (Holm & Rogers, 1999) is a performance-based observational measure. To determine the most appropriate performance measure to be added to the 2001 AIM survey, several measures were reviewed for their clinical utility, psychometric properties, and presence of matching FS tasks to the existing self-report measures in the AIM survey (Finlayson et al., 2003). The PASS is a criterion-referenced instrument with 26 items that can be used independently of each other; in addition, instructions are provided for the development of additional items. Each item specifies task conditions, critical sub-tasks, instructions, and materials needed, which allows for task performance to be observed in a controlled and standardized manner. The use of assistive technology is allowed in the performance of the tasks (Holm & Rogers, 1999). The PASS has undergone extensive testing on its reliability and validity (Holm & Rogers, 1999; Rogers, Holm, Beach, Schulz, & Starz, 2001) and has been found to have good psychometric properties, including content validity and inter-rater reliability (Finlayson et al., 2003). To directly match the PASS items to the self-report items, five items were selected from the existing PASS measure (mobility in the house, medication routine, paying bills, shopping, and use of telephone), and two additional items were developed (laundry and first aid) using an activity analysis approach and with input from the co-creator of the PASS (Finlayson et al., 2003). The Independence scale of the PASS was used for analysis in this study. For analysis, the original PASS scores were collapsed into a binominal value with each item being scored

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288 either as 1, indicating that the individual was completely independent in that task, or 0, indicating that the person was not completely independent in that task. The score of 1 was assigned if the individual did not require any assists at all and 0 if he or she did require some type of assist to complete the task (verbal or physical cueing or assistance). Collapsing of the FS measures for this study. It was initially hoped that analysis could occur at the individual item level for each of the three measures to determine the items most predictive of formal home care services. However, this was not possible as a result of low cell counts for many of the selfreport items. Therefore, to compare the three measurement types, the seven FS items for each measurement method were collapsed to result in one score for each participant. A count of the number of items for which each participant was dependent was completed. As a result, a higher score indicates that a participant is more dependent in functional tasks, and a lower score indicates that the participant is more independent in functional tasks. For example, if a participant were dependent in two of the seven PASS items, his or her performance score would be 2 (of a possible 7). However, the same individual may self-report that he or she is capable of performing all of these tasks independently, resulting in a score of 0 (of a possible 7) for self-report of capacity. Finally, perhaps the individual’s spouse always completes the laundry in their household, resulting in a score of 1 (of a possible 7) for self-report of usual behaviour. As such, each of the 110 participants was assigned a score out of 7 for each measurement method, resulting in three scores (ranging from 0 to 7) per participant. While the selfreport measures are not normally distributed, analysis was conducted with the self-report measures as categorical data and again as continuous data with no changes to the results of the study. Therefore, these measures were left as continuous data to maintain consistency among the independent variables.

Control Variables The Andersen-Newman Framework of Health Services Utilization (Andersen & Newman, 1973) was used to guide the selection of variables to represent the individual determinants that are associated with FS and HC utilization in the literature (Chappell, 1994; Diwan, Berger, & Manns, 1997; Evashwick, Rowe, Diehr, & Branch, 1984; Finlayson, 2002; Hall & Coyte, 2001; Kempen & Suurmeijer, 1991; Shapiro, 1986; Shapiro & Tate, 1997). Predisposing variables selected were age, sex, marital status, education, nationality (from a founding or non-founding nation), and health beliefs (response to the question ‘‘Do you get the kinds of illnesses that doctors can’t do much for?’’). Enabling variables were income and the Life Space Index (a scale accounting for the number of social contacts per month; Cumming, Henry, & Newell, 1961). Need variables were self-perceived health (answer to the question ‘‘How is your general health?’’), depression (as determined by the Centre for Epidemiological Studies Depression Scale [CES-D]; Andresen, Malmgren, Carter, & Patrick, 1994),

Brown and Finlayson number of health conditions, and mental status (as determined by the Mental Status Questionnaire 10 [MSQ 10]; Kahn, Goldfarb, Pollack, & Peck, 1960).

Data Analysis Data were analyzed and stored using the Statistical Package for Social Sciences (SPSS) Version 15.0 software. Handling missing data. Prior to completing descriptive analyses, data were reviewed for missing variables. For 16 missing variables for income, data were imputed using the last observation carried forward as this variable was present from the 1996 AIM survey. For the remaining three missing income variables and two missing ‘‘health beliefs’’ variables, data were imputed using logistic regression with a dependent variable of ‘‘HC use at the time of the 2001 AIM interview,’’ and the independent variables included all the control variables except for income and health beliefs (M. Katz, 1999). Refusals were present in the PASS data for the tasks of laundry (8.7%), paying bills (7.2%), and shopping (4.3%). To determine how to handle these missing values, logistic regression was undertaken with these variables coded in two ways. They were coded the first time as missing and then the second time as dependent, with HC use at the time of the 2001 interview as the outcome. Results for the analysis were similar, thus the code of dependent was maintained due to the first author’s clinical experience indicating that refusal to perform a task can be a protective strategy employed by individuals who doubt their ability to compete a task. Description of the sample. To describe the sample, control variables were examined for frequencies for categorical data and mean, standard deviation, and range for continuous data. The distribution of time to occurrence was calculated for participants entering HC within the study follow-up period. To determine if there were differences between the participants who were receiving HC at the time of the 2001 AIM interview and those who were not receiving HC, the Mann-Whitney U test was used for continuous variables, and chi-square testing was used for categorical variables. To select control variables for modeling with the independent variables in logistic regression, a multivariate logistic regression was performed using the Andersen-Newman theory as a guide. Due to the relatively small sample size in this study, the goal of this analysis was not to identify all the variables associated with formal HC use, but rather to select the variables most highly associated with formal HC use in this study. The Andersen-Newman model proposes that people first seek health services based on need; however, they then need to possess the ability to use the services (enabling variables) and be predisposed to their use (Andersen & Newman, 1973; Hawranik, 1998; Stoller, 1982). Thus the variables were entered into logistic regression in blocks with need variables entered first, then enabling variables, followed by predisposing variables and variables eliminated using stepwise backwards elimination.

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Table 1. Descriptive Statistics of the Sample (N ¼110) Characteristics

%

Age

Mean (SD); Range 84.42 (4.14); 78 to 98 yrs

Sex Female Male Marital status Single/divorced/separated/widowed Married Nationality Founding country Non-founding country Number of years of education Health beliefs Agree/neutral (negative health beliefs) Disagree/not applicable (positive health beliefs) Personal income Below $20,000 At or above $20,000 Social contacts High number social contacts/month Low number social contacts/month Self-rated health Excellent, good Fair, poor, bad Number of health conditions

60.9

and HC users and non-users. The purpose of this analysis was to determine if there are some tasks that are more related to HC use than others. For example, is the task of laundry better able to differentiate between HC users and non-users than the task of telephone use? This analysis was not performed with the self-report measures due to many instances of low cell counts, limiting the ability to analyze this data at a task level.

53.6

Results 60.9

Description of the Sample 10.37 (2.65); 3 to 18 yrs

37.3

49.1

10.9

64.5 4.1 (2.5); 0 to 11 conditions

Depression (CES-D) Score >10 (suggestive of depression) 26.4 Score 10 or less Cognition (MSQ 10) Score 9 or 10 (suggestive of intact status) 83.3 Score 8 or less Note. CES-D ¼ Center for Epidemiologic Studies Depression Scale; MSQ 10 ¼ Mental Status Questionnaire (10).

Modeling the research question. First, the relationship among the independent variables was explored using two-tailed Pearson correlation coefficients. Second, to understand the unadjusted relationship between the independent and dependent variables, univariate logistic regressions were conducted with each of the three independent variables with HC use as the dependent variable. Third, adjusted logistic regression models were run for each independent variable using previously chosen control variables and HC utilization as the outcome. Fourth, another adjusted model was run using the most significant self-report measure in previous analyses, and the performance measure, to determine if the predictive ability of the model would be improved with the inclusion of both performance and self-report measures. Following the primary analysis, chi-square testing (and, when appropriate, two-tailed Fisher test) was used to determine the relationship between the individual PASS items

In terms of predisposing characteristics, the participants (see Table 1) had a mean age of 84.42 years (SD ¼ 4.14 years) with a range from 78 to 98 years. The majority of participants were female (60.9%) and married (46.4%). Sixty-one percent of the sample was from a founding country (Canadian, British Isles, or French) versus a non-founding country (German, Scandinavian/Dutch/Belgian, Polish, Russian, or other European). The mean number of years of education was 10.37. About one third of the sample (37.3%) reported negative health beliefs by agreeing to the following statement: ‘‘Do you seem to get the kind of illnesses that doctors can’t do much for?’’. In terms of enabling characteristics, about half of the sample was at or below the poverty line for income (49.1%), and 10.9% of the sample had a large number of contacts per month. In terms of need characteristics, 64.5% of participants rated their health to be excellent or good. From of a listing of 22 health conditions, the mean number of health conditions reported was 4.1 (SD ¼ 2.6). The five most frequently reported health conditions in the last year were arthritis (67.3%), ear problems (43.6%), hypertension (40.9%), heart problems (39.1%), and eye problems (37.3%). Twenty-six percent of the sample had a score on the CES-D indicative of depression, while 83.3% had an intact cognitive status according to the MSQ 10. The 30 formal HC users were older (Mann-Whitney ¼ 1007.00, p ¼ .04) and had more health conditions (MannWhitney ¼ 958.50, p ¼ .02) than the other participants. There was no difference in sex, marital status, income, or self-rated health between the two groups. A distribution of time to occurrence (enrolment into HC) is shown in Figure 2 for the formal HC users. An FS profile of the participants was calculated using the three FS measures of interest. For the PASS, the mean number of tasks for which participants were dependent was 4.1 of a possible 7 (range 0 to 7). In contrast, the mean was 0.48 tasks dependent for the self-report of capacity (range 0 to 5) and 0.92 tasks (range 0 to 7) for the self-report of usual behaviour. Therefore, the performance measure depicts the sample as more dependent than the self-report measures (Figure 3).

Control Variable Selection The final control variable model (w2 ¼ 7.517, df ¼ 2, p ¼ .023) included two variables indicating that those who receive HC

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Brown and Finlayson 9 8 7 6 5 4 3 2 1 0

Self-report of capacity

100

3 6 9 12 15 18 21 24 27 30 Months elapsed between interview and onset home care

Figure 2. Time in months from the 2001 Aging in Manitoba interview to enrolment in Manitoba Home Care Program.

Number of parcipants (n = 110)

Count of parcipants

290

Self-report of behaviour 80 Performance Assessment of Self-care Skills (PASS)

60 40 20 0 1

services are more likely to have negative health beliefs (odds ratio [OR] ¼ 0.353; confidence interval [CI] ¼ [0.142, 0.879]), and be from a non-founding nation (OR ¼ 0.394; CI ¼ [0.149, 1.047]). These variables had little to no association.

Answering the Research Question The two self-report measures are highly correlated (r ¼ .71, p < .01). The performance measures and the self-report measures have a low correlation (r ¼ .37, p < .01 for performance and self-report of behaviour; r ¼ .26, p < .01 for performance and self-report of capacity). In unadjusted and adjusted univariate regression, the PASS contributed to the prediction of HC utilization, while the two self-report measures did not (unadjusted regression models available from first author; see Table 2). An adjusted model that included the self-report of behaviour and the performance measure (model w2 ¼ 14.329, df ¼ 4, p ¼ .006) did not produce a model fit that was significantly more predictive than the adjusted model with the performance measure alone (model w2 ¼ 14.090, df ¼ 3, p ¼ .003). Therefore, using a self-report measure in tandem with the performance measure did not result in better predictive ability in this study. The final logistic regression model (see Table 3) shows that participants who were more dependent in a performance assessment of FS did not believe that they had control over their health and were from a founding nation were most likely to receive formal HC services.

Secondary Analysis Between-group differences were found for three of the performance measure FS items with HC users being more dependent for the tasks of laundry, paying bills, and shopping (see Table 4). Since the PASS performance measure has several subtasks within each item (see example Figure 4), performance on the subtasks for each participant was descriptively reviewed to determine which subtasks were the most challenging to the study participants. For the paying bills subtask, 7 of the 30 HC users needed assistance to write the first cheque, while 3 needed help to write the second cheque. For the laundry task, 6 participants needed help with the first subtask (sorts items

2

3

4

5

6

7

8

Number of tasks dependent

Figure 3. Profile of functional status of participants according to three functional status measures.

efficiently and correctly), while 4 participants needed help with the second subtask (folds all items neatly). Only 0 or 1 participant needed help with the remaining tasks, which included matching socks, placing clothing in laundry basket, and lifting and carrying the basket. Finally, for the shopping task (simulated task completed in a seated position), 6 to 10 of the participants needed help for all subtasks.

Discussion In this study, a performance measure (the PASS) was significantly associated with entry into a formal HC program, while two self-report measures were not. The hypothesis that performance measures are superior at predicting needs has been discussed (Angel et al., 2000), but there is a paucity of literature to support this hypothesis in its application to HC use. Angel and colleagues (2000) found that despite a person’s report of his or her ability to perform a walking task, it was the actual inability to attempt or complete the walk that related to mortality within a 2-year period. This current study provides further support for the utility of a performance measure in predicting health services utilization. In the past, some authors (Reuben et al., 2004) have argued the combination of FS and performance measures may result in a tool that is better at predicting future functional decline or mortality. However, in the current study, the selfreport measures did not contribute to the predictive model. The results of this study supports evidence to date that performance measures are more predictive of functional decline than self-report measures (Guralnik, Branch, Cummings, & Curb, 1989; Kempen et al., 1996). When performing everyday activities, older adults may be unconsciously making small adaptations to compensate for declining physical and cognitive abilities. However, when being administered a performance measure with standardized equipment and instructions, they are

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Table 2 Adjusted Modeling of Functional Status Measures With Home Care Utilization Model Model 1: Performance (PASS) Model 2: Self-report of capacity Model 3: Self-report of behaviour

B

SE

p value

Odds ratio

CI

.28 –.01 .07

.12 .32 .19

.026 .989 .700

1.32 0.10 1.08

[1.03, 1.68] [0.53, 1.88] [0.74, 1.57]

Note. Control variables results are not reported here. All models include control variables health beliefs and nationality. Detailed results are available from first author. CI ¼ confidence interval; PASS ¼ Performance Assessment of Self-Care Skills.

Table 3 Final Logistic Regression Model With Home Care Utilization as Dependent Variable Variable Performance (PASS) (IV) Health beliefs (CV) Nationality (CV)

B

SE

p value

Odds ratio

CI

0.28 –1.06 –1.21

.12 .48 .53

.026 .026 .023

1.32 2.89 0.30

[1.03, 1.68] [1.14, 7.34] [0.11, 0.85]

Note. CI ¼ confidence interval; PASS ¼ Performance Assessment of Self-Care Skills; IV ¼ independent variable; CV ¼ control variable.

Table 4 Relationship Between PASS Tasks and Home Care Use Task Telephone Medication Paying bills Walking Nursing care Shopping Laundry

Pearson chi-square 0.33 2.43 11.12* 1.00** 1.12 4.30*** 6.82*

Note. PASS ¼ Performance Assessment of Self-Care Skills. *p  .01. **Fisher’s exact test (two tailed). ***p  .05.

forced out of their normal daily pattern and are not able to use the adaptations that they have developed. Thus, they may perform worse on these measures than they actually perform in day-to-day activities. The FS tasks that set apart the HC users from the non-users in this study were those of laundry, paying bills, and shopping. Review of the subtasks in these three items revealed that it seemed to be the novelty of the tasks and the cognitive aspects of the tasks that challenged the participants rather than the physical demands of the tasks. Evidence suggests that the specific cognitive skill area that predicts IADL abilities is that of executive functioning (Boyle et al., 2003). Ready, Ott, Grace, and Cahn-Weiner (2003) found that declines in executive functions are evident very early in the course of cognitive decline, even before impairments in self-reported ADLs and IADLs are evident, and hence the performance measure may be more apt to detect these changes. The results of this study need to be considered within the context of the population under study. This study is of community-dwelling older adults, and in addition, due to safety concerns, people with low levels of mobility or who required a proxy were not included in the PASS evaluation. Thus, the

Playing bills item: 1. Writes date correctly and legibly 2. Writes the name of the payee correctly and legibly 3. Selects the correct amount to be paid 4. Writes the bill in cursive correctly and legibly 5. Writes the bill amount in numeric correctly and legibly 6. Writes the signature correctly and legibly Figure 4. Sample of Performance Assessment of Self-Care Skills (PASS) task.

sample in this study comprised older adults with a fairly high level of physical and cognitive function and may not represent the range of function present in a community-dwelling population of older adults. This may explain why there was little range in the self-report measures, and it may be that within a population with a higher range of abilities, self-report measures may complement performance measures.

Implications for Practice, Research, and Policy This study provides evidence that the PASS has predictive validity for assessing risk of community-dwelling older adults. Clinicians who regularly administer performance assessments of function may want to consider their goals and purpose of assessment and consider the inclusion of the PASS if they are concerned with future care needs or are assessing an individual that does not have overt functional impairment. The IADL PASS items could be used to determine a communitydwelling older adult’s need for increased monitoring or preventative services to maintain FS and potentially prevent HC use. For example, this assessment may be helpful for an older adult who seems to be managing fairly well day to day but is concerned about his or her ability to continue to manage with IADL tasks or to screen a newly widowed older adult who previously shared home management tasks with his or her spouse.

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In addition, the ability to use everyday objects for the administration and to control the administration time makes the PASS attractive for clinical use. For researchers and policy makers, this study indicates that self-report FS measures may not be adequately reliable for conducting community needs assessments of older adults. The PASS is a good choice for this type of application, as the integration of the PASS into the AIM study has shown that it can be administered successfully by trained laypersons, does not need highly specialized equipment, and can be completed in people’s homes. In addition, further research at a task-specific level may be able to confirm that only a few tasks (such as laundry, paying bills, and shopping) are needed to predict future risk for service needs, rather than needing a lengthy battery of FS tasks.

Study Limitations A limitation of this study is that it is not known if enrolment into HC was synonymous with the need for formal HC. It is possible that some of the participants had a high need for HC but were being supported by informal caregivers or private care programs. Another limitation of this study is that time has elapsed between the collection, analysis, and reporting of this data, limiting its generalizability. However, there has been little occupational therapy literature published in recent years exploring the efficacy of self-report versus performance assessments. Since occupational therapists rely heavily on FS assessments, it is important to continue a dialogue on this topic and to generate evidence that will help clinicians, researchers, and policy makers make informed choices in FS measures. Some of the performance tasks in this study had high rates of refusal (up to 8.7%). Myers and colleagues (1993) also found high refusal rates for performance tasks, indicating that improvement of the clinical utility of performance assessments is an area for further investigation. Additionally, the method of administration of the performance measure in this study may have decreased the possible concordance between the performance and self-report tasks. Increased concordance may be found if the performance measure is completed first (Daltroy et al., 1999), which was not done in the AIM study. In addition, the administration of self-report measures in a face-to-face format (as was done in the AIM study) tends to elicit a higher rating of abilities from older adults (Reuben, Valle, Hays, & Siu, 1995).

Conclusion The focus of this study was to examine the predictive ability of FS measures on HC use in Manitoba community-dwelling older adults. This study supported the predictive validity of the PASS as it predicted future formal HC use while the two selfreport measures did not. Clinicians and researchers should consider the use of the PASS when an assessment with predictive validity in assessing community-dwelling older adults would be beneficial to practice or research applications.

Key Messages  While functional status assessments are integral to occupational therapy practice, there is little research that provides evidence on the benefits of performance-based measures as compared to self-report measures in predicting future service needs.  This study suggests that the performance measure, the Performance Assessment of Self-Care Skills, is a potentially useful tool in assessing the care needs of communitydwelling older adults.

Acknowledgements This study was completed as a part of the primary author’s master’s studies. The primary author would like to thank Malcolm Doupe, Donna Collins, and the late Barbara Payne for their contributions as master’s thesis committee members as well as the anonymous CJOT reviewers for their contributions to this manuscript. The authors acknowledge the Aging in Manitoba Longitudinal Study for use of data. The results and conclusions are those of the authors, and no official endorsement by the Aging in Manitoba Longitudinal Study or other data providers is intended or should be inferred.

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Author Biographies Cara L. Brown, MSc, OT Reg. (MB), is Instructor, Department of Occupational Therapy, School of Medical Rehabilitation, University of Manitoba, R106 - 771 McDermot Avenue, Winnipeg, MB, Canada, R3E 0T6. At the time of this study, Cara was working part-time with the Health Sciences Centre in the Occupational Therapy Department, Winnipeg, MB, and part-time as a sessional instructor at the University of Manitoba. Marcia L. Finlayson, PhD, OT Reg. (Ont.), OTR, is Vice Dean (Health Sciences), and Professor and Director, School of Rehabilitation Therapy, Queen’s University, 31 George Street, Kingston, ON, Canada, K7L 3N6. At the time of this study, Dr. Finlayson was Professor, Department of Occupational Therapy, University of Illinois at Chicago, Chicago, IL, USA.

Book Review Stewart, Debra. (Ed.). (2013). Transitions to Adulthood for Youth With Disabilities Through an Occupational Therapy Lens. Thorofare, NJ: Slack. 160 pp. US$51.95. ISBN: 978-1-61711-013-9 DOI: 10.1177/0008417413511953

Transitions to Adulthood is a well-edited, informative book that covers occupational therapy application in helping youth with disabilities to transition into adult roles in the areas of work, leisure, education, and self-care. It uses Canadian occupational therapy theoretical approaches, models, and assessments, such as the Person-Environment-Occupation model (PEO) and the Canadian Occupational Performance Measure (COPM), and covers physical, developmental, and mental health issues.

The authors of the eight chapters are well-known Canadian occupational therapists and include many personal examples from the youth they support, lending a personal touch. The use of peer support, technology, and adaptations is presented in such a way that it can be applied easily to practice. This clearly written book belongs on the bookshelf of Canadian occupational therapists who are working in the community supporting youth with disabilities to transition into meaningful adult roles with as much independence as possible so that a youth can say, ‘‘I have my own life now, and it’s pretty good!’’

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Sian Surridge

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.