Research in Gerontological Nursing

Instrument Development 

Food Expectations-Long Term Care Spanish Questionnaire: Pilot Testing with Older Mexican American Nursing Home Residents

Neva L. Crogan, PhD, GCNS-BC, GNP-BC, FNGNA; Bronwynne C. Evans, PhD, CNS, RN, ANEF, FNGNA

Abstract

Although little is known about nutrition care for Hispanic older adults in nursing homes, soon at least 4.5 million will reside there because of chronic disease. The purpose of this pilot study was to test the internal consistency reliability of a food and food service satisfaction instrument, the Food Expectations-Long Term Care Spanish (FoodEx-LTCSp) questionnaire with nursing home residents and to examine relationships between satisfaction and food intake, serum prealbumin, and functional status. Only two FoodEx-LTCSp subscales, Cooking Good Food and Providing Food Service, were significantly correlated with one another (r = 0.624, p = 0.002). No significant correlations were found between prealbumin and food intake (perhaps related to the small sample and the short duration of food weight measurement) or between prealbumin and functional status, and no significant difference was found in the subscales of Enjoying Food and Food Service and Exercising Choice. Additional qualitative work may be needed with Hispanic residents to examine items that evolved from interview data obtained from an Anglo population.

Abstract

Although little is known about nutrition care for Hispanic older adults in nursing homes, soon at least 4.5 million will reside there because of chronic disease. The purpose of this pilot study was to test the internal consistency reliability of a food and food service satisfaction instrument, the Food Expectations-Long Term Care Spanish (FoodEx-LTCSp) questionnaire with nursing home residents and to examine relationships between satisfaction and food intake, serum prealbumin, and functional status. Only two FoodEx-LTCSp subscales, Cooking Good Food and Providing Food Service, were significantly correlated with one another (r = 0.624, p = 0.002). No significant correlations were found between prealbumin and food intake (perhaps related to the small sample and the short duration of food weight measurement) or between prealbumin and functional status, and no significant difference was found in the subscales of Enjoying Food and Food Service and Exercising Choice. Additional qualitative work may be needed with Hispanic residents to examine items that evolved from interview data obtained from an Anglo population.

According to the Institute of Medicine (2000), malnutrition in U.S. nursing homes occurs at an alarming rate of 28%. As a result, research addressing this problem is a high priority, particularly in underserved, understudied ethnic groups. Currently, approximately 3% of Hispanic/Latino individuals are residents in U.S. nursing homes, compared with approximately 6% of Anglo individuals (Angel & Angel, 1997). However, there are more than 45 million Hispanic individuals in the United States (15.1% of the population) (U.S. Census Bureau, 2008), and the cohort older than 65 is expected to grow faster than any other racial or ethnic group, increasing 328% from 1999 to 2030, until there are 13 million by 2050 (Angel & Hogan, 1994; U.S. Administration on Aging, 2010). Although little is known about what happens when Hispanic older adults enter the nursing home, it is estimated that at least 4.5 million will require such care because of dementia and chronic disease (Markides, Rudkin, Angel, & Espino, 1997).

Description of the Problem: The Need for Culturally Congruent Nutrition Care

Although little is known about the nutrition status of Hispanic nursing home residents, nutrition deficiencies in the general resident population are frequent, unrecognized, and related to adverse outcomes such as increased morbidity and mortality, decreased function, health status, and quality of life (Abbasi & Rudman, 1994). No statistics are available regarding weight loss in Hispanic nursing home residents, but in general, 8% of U.S. nursing home residents lose too much weight (Centers for Medicare & Medicaid Services, n.d.). Even if residents eat enough food, protein consumption tends to be low, leading to protein-calorie malnutrition and increased death rates, making nutrition status a critical variable in their care (West, Ouellet, & Ouellette, 2003).

Mexican Americans are the largest ethnic minority in the United States (Marotta & Garcia, 2003; U.S. Census Bureau, 2008), yet nursing literature offers only one study that touches briefly on culturally sensitive food or food service for Mexican Americans. This qualitative study involved 24 informants, 6 of whom had family members in the nursing home (Gorek, Martin, White, Peters, & Hummel, 2002) but no residents themselves. The study found that families attempted to provide ethnic foods in an effort to approximate food and food service in their family homes. However, systematic incorporation of Mexican American residents’ preferences into food service delivery across nursing homes has not occurred.

Residents often express dissatisfaction with food and/or food service (Crogan, Evans, Severtsen, & Shultz, 2004; Evans, Crogan, & Shultz, 2003; Kayser-Jones, 1996). In one study, 47% of residents expressed ongoing complaints about food (e.g., variety, appearance, temperature), although none of those complaints were documented or attended to by staff (Simmons, Lim, & Schnelle, 2002). The major barrier to systematic assessment of such complaints has been the lack of a standardized instrument designed for the nursing home, such as the Food Expectations-Long Term Care (FoodEx-LTC) questionnaire. The FoodEx-LTC (Crogan & Evans, 2006; Crogan, Evans, & Velasquez, 2004; Evans & Crogan, 2005) is the only validated instrument to use residents’ perspectives on nutrition care. The recently completed translation of the FoodEx-LTC into Spanish (FoodEx-LTCSp) offers an opportunity for older Spanish-speaking residents to express their food preferences and improve their food and food service satisfaction, thereby increasing their food intake (Dubé, Trudeau, & Bélanger, 1994). The purpose of this study was to pilot test the FoodEx-LTCSp with nursing home residents and to examine the relationships between food and food service satisfaction and food intake, nutrition status (serum prealbumin), quality of life, and functional status.

The FoodEx-LTC and FoodEx-LTCSp

All studies associated with the testing and translation of these measures were approved by university institutional review boards before data collection commenced. The FoodEx-LTC, designed to measure resident satisfaction with nutrition care, was developed from 20 interviews of Anglo nursing home residents regarding positive memories of food and subsequent concerns with food and food services in the nursing home (Crogan, Evans, Severtsen, et al., 2004). Using procedures from Miles and Huberman (1994), five original domains of meaning were identified, and 44 questionnaire items that use a 4-point Likert response scale were derived from those domains. An index of content validity was calculated, and the instrument was revised and pretested with 10 nursing home residents. Revision included a secondary analysis that guided deletion of redundant items and those with inter-item correlations less than 0.25. The result was an instrument containing 28 items within four domains:

  • Enjoying Food Service: anticipating and appreciating well-prepared, delicious food; a pleasant atmosphere; and adequate service.
  • Exercising Choice: working with the system to satisfy desires for food and food service on the basis of personal food preferences and food history.
  • Cooking Good Food: being a good, experienced cook who produces a variety of foods that taste homemade and look appetizing.
  • Providing Food Service: offering sufficient, quality food, cooked safely and served on time at the correct temperature.
The revised FoodEx-LTC was tested with 61 residents in four nursing homes in the southwestern United States. Internal consistency reliability (Cronbach’s alpha coefficient) ranged from 0.72 to 0.80, dependent on domain (Crogan & Evans, 2006). Test-retest coefficients ranged from 0.79 to 0.88.

The FoodEx-LTC translation into Spanish focused on communication barriers experienced by Mexican American residents who may be unable to express food preferences to staff because Spanish is their only language. Cultural and language equivalence (Jones, Lee, Phillips, Zhang, & Jaceldo, 2001) were addressed through translation by a Mexican American native Spanish speaker, a blind back-translation by another translator of similar background, reconciliation of errors, and a final blind back-translation (Evans & Crogan, 2007). Functional equivalence (i.e., the burden of nursing home care for Anglo families compared with that for Mexican American families; Phillips et al., 1996) was difficult to establish because of the scarcity of literature regarding Hispanic residents.

Because of the frail nature of the Mexican American nursing home population, the FoodEx-LTCSp initially was tested in a community sample of bilingual adults who were asked to imagine that a Spanish-speaking older family member was in a nursing home and to answer each item as if they were that person (Evans & Crogan, 2007). One group of 23 completed the English version of the instrument, while a group of 29 completed the Spanish version; the groups were reversed after 1 week so all participants completed both versions. Analysis revealed no significant mean differences between Spanish and English items and acceptable Cronbach’s alpha coefficients (0.75 to 0.82), except for the domain of Exercising Choice (0.66). This domain demanded special scrutiny during subsequent testing because it could be viewed differently by traditional Mexican Americans who value interdependence over autonomy and individual choice.

The project was guided by an adaptation of the Quality of Health Outcomes Model (QHOM), developed by the American Academy of Nursing Expert Panel on Quality of Health Care, as a framework for outcomes research; the QHOM includes multiple contextual factors that influence health care delivery (Mitchell, Ferketich, & Jennings, 1998). The adaptation of the QHOM, the Quality Nutrition Outcomes-Long Term Care (QNO-LTC) model, is intended specifically for use in nursing homes (Figure) (Crogan & Pasvogel, 2003). The QNO-LTC posits a pathway whereby organizational issues influence nutritional status (indicated by prealbumin levels in this study) and subsequent quality of life, morbidity, and health care utilization. (The latter two variables were not addressed in this project.) As shown in the model, residents who are satisfied with food are likely to demonstrate higher food intake and therefore have improved nutritional status (Cassens, Johnson, & Keelan, 1996; Dubé et al., 1994; Lilley & Gaudet-LeBlanc, 1992; Mathey, Siebelink, de Graaf, & Van Staveren, 2001; Schiffman & Warwick, 1993; Taylor & Cronin, 1994;), essential for promoting functional independence (Bernstein et al., 2002).

The Quality Nutrition Outcomes-Long Term Care Model.Note. ADLs = Activities of Daily Living; BMI = Body Mass Index; MDS = Minimum Data Set; PCM = Protein-Calorie Malnutrition.

Figure. The Quality Nutrition Outcomes-Long Term Care Model.Note. ADLs = Activities of Daily Living; BMI = Body Mass Index; MDS = Minimum Data Set; PCM = Protein-Calorie Malnutrition.

The QNO-LTC model also incorporates Perrow’s (1979) Theory of Complex Organizations, which posits that the technology of an organization determines its structure. Perrow defined organizational technology as the knowledge needed to perform the work and the materials used to accomplish the task. In previous studies, resources such as staff and equipment problems were identified as important influences on food, food service, and resident food intake in nursing homes (Crogan, Evans, Severtsen, et al., 2004; Evans et al., 2003). This project focused on testing of a food and food service satisfaction instrument and comprised the first step toward overall QNO-LTC model testing.

Method

Sample and Setting

For this pilot study, we were able to recruit 22 Mexican American residents from three nursing homes in the southwestern United States. These residents were native Spanish speakers, 60 and older, living in the nursing home for at least 3 weeks (i.e., the duration of one nursing home meal cycle), who had scores of 16 or higher on the Mini-Mental State Examination (MMSE) (Folstein, Folstein, & McHugh, 1975), no terminal catabolic diagnoses, took no drugs that directly affected appetite, and were willing to participate. Most were born in the southwestern United States or in Mexico (Latin America); 10 were women (age range = 60 to 95), and 12 were men (age range = 80 to 96).

Data Collection

Facility staff initially invited residents who appeared to meet inclusion/exclusion criteria to speak to the researchers about participating in the study. After the resident consented verbally, he or she was screened for cognitive function. If adequate, written informed consent was obtained. Demographic and acculturation data, along with disease diagnosis information and medications, were collected from residents’ medical records.

Instruments. Data on acculturation were collected for demographic purposes. If these data could not be collected from the medical record, a research assistant (RA) administered the 5-item General Acculturation Index (GAI; selected to decrease respondent burden) (Balcazar, Castro, & Krull, 1995; Castro, Cota, & Vega, 1999). The GAI is an abbreviated version of the Acculturation Rating Scale for Mexican Americans (Cuéllar, Arnold, & Maldonado, 1995). This widely used GAI examines language preference, location of early development (i.e., United States or Latin American countries), current circle of friends, and pride in ethnic background. It exhibits good internal consistency, with a Cronbach’s alpha coefficient of 0.78 (Balcazar et al., 1995). GAI values of 1.00 to 2.39 identify less acculturated individuals, whereas higher values indicate greater acculturation: bilingual/bicultural (2.40 to 3.69) and highly acculturated (3.70 to 5.00) individuals.

Medical record information was used to complete the 6-item Katz Index of Independence in Activities of Daily Living (Katz ADL) (Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963). The tool has consistently demonstrated its utility in evaluating functional status in older populations (Sherwood, Morris, Mor, & Gutkin, 1977) and correlates highly with the MMSE (r = 0.76) (Foreman, 1997). A score of 6 indicates full function, 4 indicates moderate impairment, and 2 or less indicates severe functional impairment.

The FoodEx-LTCSp measures resident food and food service satisfaction. The instrument avoids many of the traditional problems associated with measuring resident satisfaction because it (a) is contextually relevant to the nursing home, (b) addresses the multidimensional construct of satisfaction, and (c) emerges from consultation with the residents themselves. Analysis in the preliminary study with a community sample, described above, revealed no significant mean differences between Spanish and English versions and acceptable Cronbach’s alpha coefficients (0.75 to 0.82), except for the domain of Exercising Choice (0.66).

Resident quality of life during the past 2 weeks was measured using the Alzheimer’s Disease-Related Quality of Life (ADRQL) (Rabins, Lyketsos, & Steele, 1999). After an RA obtained informed consent, English-speaking nursing assistants or licensed nurses completed the ADRQL anonymously on the basis of familiarity with each resident’s activities of daily living. A score was calculated using a preference-based weighting approach in each of the five domains (i.e., social interaction, awareness of self, feelings and mood, enjoyment of activities, response to surroundings), with higher scores reflecting better quality of life. Although quality of life may be culturally related, no literature could be found that addresses nursing assistants or nurses as proxy informants in nursing homes or the use of culturally and ethnically congruent proxy informants in such settings. However, most of the proxy informants in this study were nursing assistants, chosen because they provided the majority of “hands-on” care to residents, and were themselves Mexican American.

Measures. Actual food intake of participating residents was also measured. A gram food scale was used to compare the weight of filled plates with the weight of the plate with food left uneaten at the conclusion of the meal for 1 day’s breakfast, lunch, and dinner.

Prealbumin, a major plasma protein and the earliest laboratory indicator of nutrition status (Beck & Rosenthal, 2002), was used to determine resident protein stores because of its short half-life (1.9 days) and small serum pool that allows small changes to be identified in a short time frame. More important, it offers the most accurate assessment of catabolic states and nitrogen loss (Collins, 2001; Logan & Hildebrandt, 2003). Prealbumin was measured on the same day the FoodEx-LTCSp was administered.

Data Analysis

Data were analyzed using SPSS for Windows version 15. Pearson correlations were computed for FoodEx-LTCSp subscales and food intake at breakfast, lunch, and dinner. The relationships between prealbumin and food intake, functional status, and the FoodEx-LTCSp were also examined.

Results

Internal Consistency Reliability

Only two FoodEx-LTCSp subscales—Cooking Good Food and Providing Food Service—were significantly correlated with one another (r = 0.624, p = 0.002) and appear to measure the same underlying construct (Cronbach’s alpha coefficients for Cooking Good Food = 0.790 and Providing Food Service = 0.853).

Plate Waste

The overall FoodEx-LTCSp score, averaged over all 28 items, was significantly correlated with food intake at breakfast (r = −0.700, p < 0.001) and lunch (r = 0.776, p < 0.001). Two of four FoodEx-LTCSp Cooking Good Food subscale items had a significant relationship with food intake at both breakfast and lunch (Table 1), with one item (serve appetizing foods) showing a relationship to intake at breakfast and one item (serve a variety of foods) related to intake at lunch. Seven of 10 Providing Food Service subscale items (Table 2) had a significant relationship with food intake at one or more meals, and one item (right amount) showed a significant relationship with food intake across all three meals.

Correlations Between the FoodEx-LTCSp Questionnaire Cooking Good Food Subscale and Food Weight

Table 1: Correlations Between the FoodEx-LTCSp Questionnaire Cooking Good Food Subscale and Food Weight

Correlations Between the FoodEx-LTCSp Questionnaire Providing Food Service Subscale and Food Weight

Table 2: Correlations Between the FoodEx-LTCSp Questionnaire Providing Food Service Subscale and Food Weight

Serum Prealbumin

As shown in Table 3, no significant correlations were found between prealbumin and food consumed at any of the three meals. In addition, no significant correlations were found between prealbumin and functional status as measured by the Katz ADL (r = 0.131, p = 0.561). For the FoodEx-LTCSp, the only subscale correlation (r = 0.425, p = 0.05) was noted between prealbumin and the item “food freshly cooked and on time” (Providing Food Service subscale). The ADRQL item “clings to people” was the only item significantly correlated with prealbumin (p = 0.01; Total ADRQL: r = 0.242, p = 0.290), perhaps reflective of the Hispanic preference for warm, personal interactions (Evans, Coon, & Crogan, 2007).

Correlate Scores of Serum Prealbumin and Food Weight

Table 3: Correlate Scores of Serum Prealbumin and Food Weight

Discussion and Implications

Evaluation of Food Satisfaction: A Component of Nutritional Status

The performance of the two subscales, Enjoying Food and Food Service and Exercising Choice, was disappointing for a new culturally-specific instrument. No significant difference was found in these two subscales. It is notable that the subscale of Exercising Choice was also problematic in the preliminary testing with a younger Hispanic population (Evans & Crogan, 2007) and could be related to the family-oriented, interdependent Mexican American culture in which individual choice in not considered paramount. Although this preliminary testing was performed for cultural equivalency, it may be that some items were not culturally relevant for Hispanic nursing home residents because they were derived from an English version of the scale, constructed from the perspective of Anglo nursing home residents. Additional qualitative work with older Mexican American nursing home residents may be required to adequately access their perspectives. This could result in an entirely new qualitatively driven instrument or a revision of the FoodEx-LTCSp subscales Enjoying Food and Food Service and Exercising Choice, depending on the congruence of the Mexican American resident interviews with the previous Anglo resident interviews used for development of the FoodEx-LTC.

Three items (ample fresh fruits and vegetables [item-total correlation = −0.039]; monitor what I eat [item-total correlation = 0.230]; and friendly and courteous service [item-total correlation = 0.286]) could be deleted from the two scales that performed well: Cooking Good Food and Providing Food Service. The low correlation for the first item is partially explained by the fact that older Mexican American residents may not recognize the importance of fruits and vegetables in their diets because they are traditionally prepared in combination dishes, such as pescado viscayena, fish fillets with a hearty, smooth sauce made from bell peppers, potatoes, peas, carrots, garlic, and chiles (Benavides-Vaello, 2005). However, given the value on personal interaction, the lack of emphasis on monitoring and friendly service is surprising. Removing these items would further increase the reliability of these subscales and result in decreased respondent burden.

Correlations between Cooking Good Food and Providing Food Service suggest that a larger sample would be helpful in determining whether they might be part of a single construct: If the resident thinks the service is good, he or she may view the food as better. This possibility should be further tested in a larger psychometric study using exploratory factor analysis to determine what constructs are actually being measured by the items and which items measure which construct.

The Relationship Between Food Satisfaction and Actual Food Intake

Table 1 shows that according to residents’ perspectives, as the preparation, variety, and palatability of food improved, food intake increased. (Lower scores on these items mean better cooking: A score of 1 is true, while a score of 4 is false.) Although derived from a small sample and a short duration of food weight measurement, the correlations between FoodEx-LTCSp items and food intake at breakfast and lunch, displayed in both Tables 1 and 2, are supported by the literature. This result is depicted by the relationship in the QNO-LTC model between organizational technology and the predictors of protein-calorie malnutrition. Although there are no known documented variations in intake in Mexican American populations, it is known that older adults’ food intake peaks at breakfast and lunch, with lesser amounts usually consumed at dinner (Young, Binns, & Greenwood, 2001). Unfortunately, current meal delivery practices in nursing homes parallel the needs of healthy young adults in mainstream society, whose peak mealtimes tend to occur at noontime and in early evening, and it calls for reconsideration by dietitians of calories provided for each meal. Possible explanations of decreased intake at the evening meal could include fatigue, lack of palatability or desired foods, or staff offering a snack too close to dinnertime. Exploration of these questions should be added to the next phase of the investigation.

Table 2 also indicates that food intake decreased when food was the wrong temperature or if too much food (overwhelming the resident) or too little food (leaving the resident hungry) was served. In addition, although Anglo residents like having access to takeout food, the residents in the current study did not consider it important, perhaps because they did not know about their options or how to ask for them, or they may not have had money to pay for takeout food.

Food intake decreased if their food was cut up for them, raising questions of how long they had to wait for staff to help them, and the less satisfied they were, the more they ate, perhaps indicating a disinclination to complain. These results were congruent with Simmons et al.’s (2002) findings in a primarily Anglo population where feeding assistance did not increase food intake. However, those residents expressed more food quality complaints than those who did increase their food intake with assistance. The results also reflect the relationship in the QNO-LTC model, where organizational technology is depicted as affecting food intake.

The Relationships Among Nutritional Status, Food Intake, and Quality of Life

Although no significant correlations were found between prealbumin and food intake and functional status, and little correlation was found between prealbumin and good food service or quality of life, this study points to the need for additional investigation with larger samples and longer measurement periods. However, this pilot study does demonstrate patterns suggestive of relationships between good cooking and food service and maintenance of resident nutrition status. All of these patterns are represented in the QNO-LTC model by the interconnections among organizational technology (food preparation and service), predictors of protein-calorie malnutrition (food intake), nutritional status (prealbumin), and quality of life (functional status).

Conclusion

This pilot study points out differences in at least two areas that influence research studies with Hispanic populations. First, although it was initially thought that preliminary testing of this instrument to determine cultural equivalency could be done in a younger Hispanic sample, the difference was so marked between the well-acculturated sample and the current nursing home sample (GAI mean = 2.82) that equivalency may well have been affected. Compounding this difference is our suspicion that the true GAI score in nursing home residents may be even lower because of social desirability effects in self-reporting fluency in reading and writing English. Such self-reports sometimes did not coincide with performance of fluency on the MMSE. Moreover, it is worrisome that illiteracy in either Spanish or English casts doubt on MMSE results because of the instrument’s requirements that the resident must read and write responses to items.

Caution also must be used when applying findings based on one Hispanic subgroup to another. Not only do older Mexican American populations appear to be different in food and food service preferences than younger, more acculturated groups, but Cubans, Puerto Ricans, Dominicans, and other subgroups will be different from each other.

Second, the FoodEx-LTCSp was derived from the English version of instrument, the FoodEx-LTC, which was developed from interview data. However, those data came from an Anglo population, and the constructs that evolved into instrument items might be different for each Hispanic subpopulation. Attention to methodological issues such as these will be vital as we work to include larger numbers of diverse participants in nursing research. These emerging issues alert us to examine our work carefully for culturally appropriate methods and instruments that we need to adequately deliver culturally sensitive, effective nutrition services in nursing homes (Bermudez & Tucker, 2004).

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Correlations Between the FoodEx-LTCSp Questionnaire Cooking Good Food Subscale and Food Weight

Item Data Analysis Food Weight (grams)
Breakfast Lunch Dinner
Know how to prepare a meal Pearson correlation Significance (two tailed) n –0.720** 0.001 19 –0.537* 0.022 18 –0.235 0.333 19
Have experience in food service Pearson correlation Significance (two tailed) n –0.790** 0.000 19 –0.563* 0.015 18 –0.449 0.054 19
Serve a variety of foods Pearson correlation Significance (two tailed) n –0.288 0.232 19 –0.596** 0.009 18 –0.212 0.384 19
Serve appetizing foods Pearson correlation Significance (two tailed) n –0.521* 0.022 19 –0.447 0.063 18 –0.130 0.596 19
Subscale mean Pearson correlation Significance (two tailed) n –0.723** 0.000 19 –0.588* 0.010 18 –0.311 0.195 19

Correlations Between the FoodEx-LTCSp Questionnaire Providing Food Service Subscale and Food Weight

Item Data Analysis Food Weight (grams)
Breakfast Lunch Dinner
Ample fresh fruits and vegetables Pearson correlation Significance (two tailed) n –0.097 0.693 19 0.222 0.376 18 –0.054 0.827 19
Proper temperature Pearson correlation Significance (two tailed) n –0.547* 0.013 20 –0.589** 0.008 19 –0.294 0.209 20
Freshly cooked and on time Pearson correlation Significance (two tailed) n –0.424 0.062 20 –0.642** 0.003 19 –0.207 0.381 20
Right amount Pearson correlation Significance (two tailed) n –0.707** 0.000 20 –0.847** 0.000 19 –0.486* 0.030 20
Monitor what I eat Pearson correlation Significance (two tailed) n –0.309 0.185 20 0.285 0.237 19 0.170 0.474 20
Takeout food Pearson correlation Significance (two tailed) n –0.725** 0.000 19 –0.694** 0.001 18 –0.390 0.184 19
Cut my food Pearson correlation Significance (two tailed) n –0.597** 0.005 20 –0.582** 0.009 19 –0.310 0.184 20
Food everyone likes Pearson correlation Significance (two tailed) n –0.373 0.116 19 –0.575* 0.010 19 –0.099 0.678 20
Friendly and courteous service Pearson correlation Significance (two tailed) n –0.355 0.135 19 –0.094 0.703 19 0.101 0.671 20
Satisfied with service Pearson correlation Significance (two tailed) n –0.511* 0.025 19 –0.642** 0.033 19 –0.246 0.296 20
Subscale mean Pearson correlation Significance (two tailed) n –0.724** 0.000 19 –0.774** 0.000 19 –0.272 0.247 20

Correlate Scores of Serum Prealbumin and Food Weight

Data Analysis Food Weight (grams)
Breakfast Lunch Dinner
Pearson correlation 0.174 0.067 –0.163
Significance (two tailed) 0.463 0.784 0.492
n 20 19 20
Authors

Dr. Crogan is Research Associate Professor, College of Medicine, The University of Arizona, Tucson, and Dr. Evans is Associate Professor, College of Nursing and Healthcare Innovation, Arizona State University, Phoenix, Arizona.

The authors disclose that they have no significant financial interests in any product or class of products discussed directly or indirectly in this activity, including research support.

Address correspondence to Neva L. Crogan, PhD, GCNS-BC, GNP-BC, FNGNA, Research Associate Professor, College of Medicine, The University of Arizona, 1807 E. Elm Street, Tucson, AZ 85719; e-mail: ncrogan@aging.arizona.edu.

Received: November 13, 2008
Accepted: October 05, 2009
Posted Online: April 30, 2010

10.3928/19404921-20100330-02

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