Dietary therapy is the first line of treatment of high blood cholesterol to reduce risk of coronary heart disease (CHD) (Adult Treatment Panel II, 1994). However, lifestyle changes, especially as they relate to changing dietary behavior following a cardiac event, are difficult. According to Berry and Krummel (1998), "Eating habits can be extremely resistant to change because they are often formed early in life and are intricately woven into lifestyle, culture, and environment" (p. 203).
The National Cholesterol Education Program (NCEP) Step II diet combined with increased intake of water-soluble dietary fiber are recommended nonpharmacologic therapies that have a clinically important influence on the serum lipid profile (McDonald, Maki, & Davidson, 1998). The Step II diet limits total fat intake to 30% or less of total calories, saturated fat to less than 7% of calories, and cholesterol intake to less than 200 mg per day. A high soluble fiber diet is adjunctive to the dietary goals of the Step II diet. The American Heart Association recommends a total dietary fiber intake of 25 to 30 grams per day from foods (Van Horn, 1997).
Prescribing lifestyle change and dietary modifications is an essential secondary prevention strategy for patients with CHD. Nurses are able to prescribe what dietary changes need to be made. However, helping patients learn how to make necessary changes is more problematic. The NCEP guidelines provide some direction for assisting with dietary change, but recent evidence suggests some health care providers are poorly compliant with these guidelines (Frolklis, Zyzanski, Schwartz, & Suhan, 1998).
Because there is a rapidly increasing number of older adults with CHD in the United States, there is a growing need for this population to have the necessary dietary management skills to achieve healthy lifestyles (Smith, 1998). When the prevalence of CHD is greater, as in older patients, knowledge on which to build behavioral change strategies is important.
While many investigators have studied the efficacy of cholesterollowering diets, few have investigated the process of changing to a cholesterol-lowering diet (Denke, 1995). Several investigators have reported the difficulty patients and their families' experience while trying to adopt the low-fat diet prescribed after a cardiac event. In a qualitative study of 1 1 pos tmyocardial infarction patients and their spouses, Liddy and Crowley (1987) found patients took a long time to adjust to the prescribed diet because it was new and different. King, Martin, Morrell, Arena, and Boland (1986) surveyed 148 male patients shortly after admission to a cardiology unit. Eighty percent of the men on a prescribed diet reported they had experienced difficulty in following the diet. Hilgenberg and Crowley (1987) and Hilgenberg, Liddy, Standerfer, and Schraeder (1992) found that following myocardial infarction (MI), patients perceived their diet changes as difficult and reported they continued to struggle 6 months after the MI. One patient said, "The diet is the hardest thing to change; you have to deal with it every day" (Hilgenberg et al., 1992, p. 51).
Other investigators have focused on the difficulties associated with making modifications in coronary risk factors and lifestyle changes in general. Gulanick, Bliley, Perino, and Keough (1998) conducted a qualitative study with 45 patients who had undergone percutaneous transluminal coronary angioplasty (PTCA) 3 to 18 months earlier. They found patients experienced frustration with enacting lifestyle changes but believed risk modification strategies were a way to seek control of their disease.
Problem-solving skills have been described as an essential component of the behavior change process (D'Zurilla, 1986; Ewart, 1989; Grant & Evans, 1994; Watson & Tharp, 1993). Dietary problem-solving skill is a cognitive-affective-behavioral process through which individuals identify or discover effective means for coping with problems encountered in changing to and maintaining a prescribed health-related diet (Liddy & Crowley, 1987). Ewart (1989) describes dietary problem solving as a process through which the dieter invents, discards, and reinvents better ways to alter established eating patterns. Kumanyika and Ewart (1990) state that "no matter how strongly people want to change their eating habits, they are unlikely to succeed if they do not possess problem-solving skills" (p. 1156). These skills include recognizing problems posed by attempts to change dietary behavior, defining the nature of the problem, generating a list of alternative solutions to the problem, making a decision, implementing the solution, and evaluating the solution outcome (D'Zurilla, 1986).
Despite agreement about the centrality of problem-solving skills to making and sustaining dietary behavior change, few if any studies have examined the dietary problem-solving skills of patients following a cardiac event. Knowledge about dietary changes of older adults with CHD is limited. The purpose of this study was to describe the number and nature of solutions generated by older patients and their families to dietary problems commonly encountered when attempting to adopt and maintain a heart-healthy diet. An exploratory design was used to address the following research questions:
* How many solutions can older patients generate when faced with a dietary management problem?
* Are the solutions that are generated both safe and effective?
* What types of solutions are generated?
* Do problem-solving skills differ according to age and gender?
Setting and Sample
The setting for this study was a teaching hospital in a suburb of a large metropolitan city. Patients were conveniently selected from one of three units in the hospital: an interventional cardiology unit, an intermediate cardiology care unit, or an intermediate cardiac surgery unit. Criteria for inclusion in the sample were:
* Age older than 60 years.
* Diagnosis of CHD-related diagnosis including angina, acute myocardial infarction (AMI), or undergoing coronary artery bypass surgery.
* Living independently in the community within a 50-mile radius of the hospital (as opposed to living in an assisted living or extended care facility).
* Consent to participate.
* Ability to read, understand, write, and speak English.
Patients who had a history of mental impairment as documented in the medical record or who were not oriented to time, person, and place were excluded from the study.
From August 1997 to January 1998, 236 eligible men and women were selected conveniendy and given an explanation about the study. One hundred forty-seven (62%) individuals refused to participate in the study because of lack of interest or inconvenience. Eighty-nine (38%) older adults consented to participate with arrangements made to participate in a home interview 1 month after hospital discharge. One month later only 38 (43%) patients were willing to proceed with the home interview. Among the individuals willing to respond to a survey about their unwillingness to participate in the home interview, reasons for withdrawal included rehospitalization, "my wife doesn't want me to participate," "my husband is quite ill," or "I no longer have the time." After patients returned to work or other prehospital activities their willingness to participate decreased.
Thirty-eight patients (n = 20 men, n = 18 women) consented to participate in the study. Patients' ages ranged from 60 to 86 years, with a mean age of 69. The sample was 92% White and had a mean education level of 13 years (SD = 2.86, range = 3 to 22 years). Twenty-one patients were married, and 17 patients were unpartnered (i.e., never married, widowed, divorced). Fifty percent of the sample had a household annual income of $29,999 or less; the rernaining 50% had varying degrees of higher household incomes.
Almost half of the sample (n = 16, 42%) were hospitalized for medical treatment or interventional cardiology procedures, five patients (13%) were hospitalized for MI, and 14 patients (36%) underwent coronary artery bypass surgery. At the time of the interview, only 6 (16%) individuals reported they were participating in or about to participate in a cardiac rehabilitation program. When queried about ways they learned about lowfat and high-fiber diets, participants reported they received information from a booklet (n = 13, 34%), television (n = 7, 18%), a class (« = 2, 5%), a doctor (n = 5, 13%), a nurse (n = 7, 18%), or a dietician (n = 5, 13%). The majority of the sample denied receiving dietary information from any source. Among the minority, the most popular way to receive dietary information was from a booklet.
All participants were asked to give approximately 40 µ?. (1 to 2 drops) of fingerstick blood to measure total cholesterol using a single-use, noninstrumented quantitative test system called the AccuMeter Cholesterol Test (ChemTrak, Sunnyvale, CA). Cholesterol values obtained from fingerstick capillary specimens using the AccuMeter or by standardized enzymatic assay are in close agreement with venous results (within 1% to 1.7%) (Warnick, Leary, Ammirati, & Allen, 1994). The mean total cholesterol level in this sample was 214.49 mg/dL, with a range of 67 mg/dL to 351 mg/dL. On average, participants in this sample had borderline high blood cholesterol levels.
Patients who met inclusion criteria were contacted about participation and consent 1 to 2 days prior to anticipated hospital discharge. Information related to health history and current condition was obtained from the medical record before discharge. All other data were collected during a structured home interview 1 month after hospital discharge. Interviewers were given background information about the study and trained to promote standardization of procedures and data collection. Data collection was delayed until 1 month after discharge to allow for physical recovery as well as to provide an opportunity for patients and their families to attempt to make dietary modifications.
The Dietary Practical Problems Test (DPPT) was used as a domainspecific measure of problem solving. Two of the authors (N.T.A. and K.L.C.J.) developed this instrument which is an adaptation of a problemsolving questionnaire originally designed by Denney and Pearce (1989). The DPPT contains six short scenarios describing dietary management problems. Five of the six dietary management problems are common high-risk situations for dietary relapse. The sixth problem is related to a food habit that is difficult for people to change (i.e., switching from drinking whole milk to drinking only skim milk) (see the Sidebar on this page). Subjects were asked to generate as many safe and effective solutions as possible for each problem. Interviewers recorded all their solutions. Interviewers verbally prompted subjects during breaks in their solution generation to ensure they had generated as many solutions as they could.
Three judges, one nutrition expert and two nurses, coded each solution to each problem using the following categories: 4 (both safe and effective), 3 (only effective), 2 (only safe), and 1 (limited scope, neither safe nor effective). A score of zero was given if the subject was unable to generate any solutions. Solutions were considered safe if they were not harmful or potentially harmful to the individual's cardiac problem. Solutions were considered effective if they displayed evidence of the patient having some nutritional knowledge and if they led to resolution of the immediate problem. Each judge coded the solution data using the scale described above. Solutions were coded individually and then reviewed as a group. Data were examined and reexamined until 100% consensus was reached. Previously generated ratings were reviewed continuously by the group to facilitate consistency and arrive at consensus.
Four different scorings of the DPPT were performed. A fluency score was computed by adding up the total number of solutions across the six problems. This score ranged from 3 to 33, with a mean of 13.11 (SD = 5.37). The internal consistency reliability of the scale when scored in this way was .76.
The other scorings, three in all, were intended to reflect the overall safety and effectiveness of the solutions generated across the six problems. One score was calculated by adding up the number of problems for which subjects were able to generate both safe and effective solutions. This score ranged from 0 to 6, with a mean of 3.91 (SD = 1.93). A second safety and effectiveness score was calculated by first computing a mean safety and effectiveness score for each item and then averaging the mean safety and effectiveness scores for the six problems. This score ranged from 1.3 to 3.79, with a mean of 2.73 (SD = .61). A third safety and effectiveness score was calculated by determining the mean of each problem's best score. Real-life problem solving may not depend on the number of solutions generated or even on the number of effective solutions but on the ability to produce one effective solution. Some personality types may not be inclined to generate multiple effective solutions. After an effective solution is recognized, these individuals may be satisfied with it. The best score was not the best score judged by an individual rater; rather it was the best solution to a problem when the participant provided several solutions. This score ranged from 1 .5 to 4, with a mean of 3.19 (SD = .75). The reliabilities of the DPPT when solutions were scored in the various ways for safety and effectiveness ranged from .53 for the average of the mean scores to .68 for the mean of each problem's best score. Although these reliabilities are below the conventionally acceptable level of .70, they are considered satisfactory because the instrument measures solutions to different types of problems. High alpha scores evidence that the test as a whole only measures one attribute (Kraemer, 1981; Waltz, Strickland, & Lenz, 1991).
DESCRIPTIONS OF SOLUTION CATEGORIES
The intercorrelations among these three ways of scoring safety and effectiveness ranged from .86 to .93. Because of the high correlations among these three measures of safety and effectiveness it was decided to standardize and combine these scores into a fourth overall measure of problem-solving quality. This score ranged from -2.11 to 1.19, with a mean of 0 and a standard deviation of 1.0. Scores greater than zero indicate lower problem-solving quality than scores less than zero. The internal consistency reliability of this overall measure of problem-solving quality was .97. This quality of problem-solving score (i.e., DPPT quality score) was retained for further analyses.
A panel of experts established content validity. Descriptions of the high-risk situations were based on the literature and clinical experience. A nurse, a nutrition science expert, and a cardiac rehabilitation expert examined the scenarios to verify that they reflected dietary management problems that frequently cause dietary relapse.
Criterion-related validity was established by correlations of the DPPT fluency score with other measures related to dietary problem solving (i.e., dietary knowledge, waist-tohip ratio, perceptions of situational temptation for dietary relapse, perceived benefits of heart-healthy eating). Dietary knowledge is a necessary, but not sufficient, condition of successful problem solving. There was a positive correlation between dietary knowledge and problem-solving fluency (r = .33, p = .047). Knowledge was measured using an investigatordeveloped 24-item instrument containing multiple-choice and true or false questions challenging respondents to identify sources of fat and fiber in foods, interpret food labeling, make appropriate food purchase sélections, and evaluate menus and select low-fat options. Cronbach's alpha for this sample was .90.
The waist-to-hip ratio is an assessment of body fat distribution, and in general, larger ratios reflect more body fat and increased risk of CHD (Lee & Nieman, 1996). In this sample, individuals with larger waist-to-hip ratios had fewer dietary problemsolving skills (r = -.39, p = .02). The Situational Temptation Questionnaire (STQ) was used to measure situations that present an individual with temptation to continue consuming high-fat foods (Rossi & Rossi, 1994). The STQ for Dietary Fat Reduction is a 12-item inventory designed to measure temptation in three different situations (i.e., positive/social, negative/affective, difficult). Internal consistency (alpha coefficient) for the scale is at an acceptable level (.88). In the scale, participants are asked how tempted they would be to eat high-fat foods in each situation, responses ranging from not at all tempted (1) to extremely tempted (5). In this sample, older adults with greater levels of perceived temptation in high-risk situations had lower DPPT fluency scores (r = -.407, ? = .015). It is possible that adults who were able to generate more solutions would be less tempted. Finally, older adults who perceived more benefits associated with heart-healthy eating habits had higher DPPT fluency scores (r = .411, p = .014). Perhaps individuals who perceived benefits associated with dietary change tried harder to find solutions. The Benefits Scale measured perceived benefits for dietary fat and fiber consumption. This instrument was developed by two of the investigators (N.T.A. and K.-L.C.J.) to measure perceptions of individuals concerning the benefits of eating a low-fat, high-fiber diet. Items were measured using a four response, forced-choice Likert format ranging from strongly agree (4) to strongly disagree (1). The higher the score, the more positively the individual perceives low-fat, high-fiber dietary consumption. Cronbach's alpha reliability for this sample was .78.
SOLUTION SCORES FOR EACH PROBLEM
The DPPT quality score correlated positively with the patient's level of nutritional knowledge (r = .475, p = .003). In addition, individuals who generated higher quality solutions were less tempted to relapse in highrisk situations (r = -.348,/) = .041) and perceived more benefits associated with heart-healthy eating habits (r = .367,p = .030).
The analyses of problem-solving data were augmented by content analysis of the solutions created by participants. Manifest content analysis was used (Catanzaro, 1988). Each solution listed for each problem situation comprised the units of analysis. The purpose of the analysis was to code the lists of solutions using the predetermined subcategories within the larger categories of dietary management or self-management solutions suggested by the literature (KrisEtherton & Burns, 1998; Snetselaar, 1997; Watson & Tharp, 1993). Table 1 describes the two types of predetermined solution categories. When respondents provided more elaborate and complex solutions, their responses could be placed logically and conceptually into more than one category. Thus, solutions listed for all problems were coded for membership in either the dietary management or selfmanagement categories or both. The number of solutions that fell within each category were tabulated.
Ability to Produce Solutions: Problem-Solving Fluency
For the set of six problems, patients generated an average total of 13.1 solutions, with a range of 3 to 33. Table 2 describes the fluency scores for each high-risk situation presented to subjects. Patients were able to generate the greatest number of solutions for the situation involving having an argument with a close friend and feeling upset. They generated the fewest number of solutions related to the problem of switching from whole milk to skim milk.
Safety and Effectiveness of Solutions
Safety and effectiveness scores (i.e., mean of each problem's best score) ranged from 1.5 to 4, with a mean of 3.19 (SD = .75). Table 2 describes the mean safety and effectiveness scores for the six dietary management problems. Patients generated the highest mean safety and effectiveness scores in relation to the problem of maintaining a low-fat diet when attending a barbecue or picnic. The lowest mean safety and effectiveness scores related to the problem of switching from whole milk to skim milk.
Content Analysis: Categories of Solution Strategies
The bar graphs in Figures 1 and 2 describe the frequency of solutions that were classified into the predetermined categories of dietary management (Figure 1) and self-management (Figure 2) solutions suggested by the literature. Selecting low-fat foods was the most popular solution category, representing 18% to 53% of the solutions and spanning five of the problem areas. Although portion control was considered a solution for all of the problems, the frequency with which it was considered in each situation was low. Food substitutions usually was used when faced with switching from whole milk to skim milk. Altering food preparation was used most often when dining in a restaurant or switching from whole milk to skim milk.
Solutions in the food selection or food substitution categories rarely if ever reflected awareness of caloric intake in addition to consideration of the fat content of food. For example, many respondents solved the urge to binge on cookies or doughnuts in response to having an argument with a friend by "eating low-fat cookies" or "eating low-fat sweets." Respondents did not suggest eating only a limited amount of low-fat cookies or sweets.
Figure 2 describes the categories of self-management solutions used by participants. Of the self-management solutions, using stimulus control and, to a lesser degree, using self-control were solutions used for most of the problem situations. Being assertive was used to solve problems encountered when dining at a restaurant, party, or picnic. Using social support was not selected across all problems and most frequently was posed as a solution after arguing with a friend and feeling upset. For each problem there was some respondents (2% to 26%) who either were not able to generate any solutions or did not feel anything needed to be solved. Rather than actively confronting the problem, some participants stated, "just go ahead and enjoy the ribs" at a picnic, "just don't drink any milk" (rather than switch to skim milk), "don't make a scene with others, just enjoy it" (referring to a party buffet table), "don't eat" when dining at a restaurant, or "go ahead and binge, doing it one time doesn't mean it is forever" referring to a buffet table at a party. Solutions categorized as self-talk, self-monitoring, or planning ahead were mentioned infrequently in relation to any of the high-risk situations.
The Influence of Age and Gender on Problem-Solving Skill
Age and gender influenced problem-solving skill. Age negatively influenced the level of problem-solving quality (r = -.535, /> = .001) but not problem-solving fluency (r = -.229, ? = .179). Participants continued to be able to generate solutions as they grew older, but the quality of solutions declined.
Men displayed fewer problemsolving skills than women. Men had significantly lower mean problemsolving fluency scores (mean = 10.5, SD = 3.79) than women (mean = 16.0, SD = 5.57) (f = -3.43, p = .002). Additionally, the level of problem-solving quality was lower among men (mean = 2.92, SD = .737) than women (mean = 3.48, SD = .706) (r = -2.26, p = . 030).
The quantity principle suggests that the more solution alternatives produced, the more high-quality ideas will be made available, thus increasing one's chances of discovering the best solution (D'Zurilla, 1986). Patients in this sample were not particularly fluent, that is, they were not able to produce a large number of solutions when faced with a set of high-risk dietary situations. Patients were able to generate only an average of two solutions per problem, and these solutions were not necessarily high-quality solutions.
Problem-solving flexibility is the ability to produce a variety of kinds of ideas, and problem-solving originality is the ability to produce unusual or novel ideas (D'Zurilla, 1986). Respondents in this sample did not demonstrate strong problem-solving flexibility or originality. The lack of creative solutions may have been related to habits patients already had established, to lack of imagination, or to the tendency to judge ideas as inferior before expressing the idea as a potential solution.
Figure 1 . Dietary management solutions.
The variety principle states that the greater the range of solution ideas, the more high-quality ideas will be discovered (D'Zurilla, 1986). Patients in this sample had a limited range of solutions, relying heavily on the food selection category. Growing tired of one solution type without having other types to "fall back on" may contribute to "solution boredom," leading to lack of motivation to continue to handle the situation which puts the individual at high risk for relapse. Over time, individuals may try their solutions, determine the solutions on their limited list do not help them maintain their hearthealthy diet, and thus, relapse or give up trying to handle the high-risk situation.
It is not surprising that women have more dietary problem-solving skills than men. Traditionally women have been responsible for dietary management within families. In this sample, women may have benefited from more experience with thinking about how to handle dietary management problems. Findings in this study are supported by those of other investigators who have found differences in the ways men and women manage their dietary fat consumption or that women are more likely to be in later stages of dietary behavior change (Contento & Murphy, 1990; Glanz et al., 1994).
Findings in this study suggest that as older adults age they are less likely to generate high-quality solutions. Reports from other investigators support these findings. Denney and Palmer (1981) found that adult problem-solving performance related to typical everyday problems increased up to the 40-year-old and 50-year-old age groups, and decreased thereafter. Denney, Pearce, and Palmer (1982) presented adults ages 20 to 80 with three sets of practical problems (i.e., a set young adults may encounter in their daily lives, a set middle-aged adults may encounter, a set older adults may encounter). Performance on the older adult problems did not increase with age in the later adult years. Performance increased up to middle age and decreased thereafter.
LIMITATIONS AND IMPLICATIONS FOR FUTURE RESEARCH
Methodological limitations of this study decrease the generalizability of the findings. Two major problems are the low response rate and the small, nonrandom sample that contained predominantly White educated older adults who could understand, read, and write English. ? gap of 1 month between consent to participate and participation in the home interview was unwise. Subjects need to identify with the project and participate in some way as soon as possible after consent to rmnimize dropout rate. Future research needs to examine problem solving in larger, more diverse samples so there is knowledge on which to build culturally suitable problem-solving interventions. It also is recommended that future research focus on refinement and additional testing of the DPPT and on tests of interventions to increase the dietary problem-solving skills of older adults following a cardiac event.
Given the small, nonrandom sample in this study, implications for practice are tentative but worth considering. Because there is a rapidly increasing number of older adults with CHD in the United States, there is a growing need to find ways to assist them to achieve healthy dietary lifestyles. If patients' success at implementing demanding dietary changes is affected greatly by their ability to exercise critical problem-solving skills (E wart, 1990), then patients may benefit from problem-solving training to increase their ability to generate numerous and varied highquality solutions. Heightening awareness of the need to reinvent ways to alter established eating patterns seems crucial. The use of "real world" examples and problems in this study helped show the practical or working knowledge gained from previous dietary education and may assist patients in the application of dietary restrictions. The findings show that patients think they understand their dietary restrictions, yet often were unable to apply the restrictions in their everyday lives.
Figure 2. Serf-management solutions.
Although problem-solving training may be a usual part of patientdietician interactions, it often is not within the usual role of nurses working with patients who are struggling to make dietary changes. Limited resources prevent dieticians from seeing every patient during each hospital admission or clinic visit, yet regular follow up is essential to foster lifestyle changes and maintenance. If only a small number of patients receive dietary information from any one source (e.g., booklet, doctor, nurse, dietician), patients need to receive dietary problem-solving assistance from more than one provider. It is especially important for nurses to be able to provide this type of assistance.
Providing enough information for patients to understand potential dietary management problems, assisting patients to define dietary goals to help identify relevant solutions, and assisting patients to generate as many alternative safe and effective solutions as possible may prove useful. Older adults struggling to change lifelong habits may need assistance to break old habits, create new ideas, defer judgment on ideas, and evaluate solution outcomes.
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DESCRIPTIONS OF SOLUTION CATEGORIES
SOLUTION SCORES FOR EACH PROBLEM