Determinants of health-promoting lifestyle in ambulatory cancer patients

Sot. Sci. Med.Vol. 31,No.IO, 1990 pp.1159-1168, Printed

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DETERMINANTS OF HEALTH-PROMOTING LIFESTYLE IN AMBULATORY CANCER PATIENTS MARILYNFRANK-STROMBORG,NOLAJ.PENDER,SUSANNOBLEWALKER and KARENR.SECHRIST Health Promotion Research Program, Social Science Research Institute, Northern Illinois University. DeKalb, IL 60115, U.S.A. Abstract-The Health Promotion Model was tested as an explanatory framework for health-promoting lifestyle in a sample of 385 ambulatory cancer patients undergoing treatment in 13 clinical sites in the midwestern United States. The aim of this study was to determine the extent to which cognitive/perceptual and modifying variables identified in the Health Promotion Model explain the Occurrence of healthpromoting behaviors in adults with cancer. A secondary aim was to determine the potential of illness-specific cognitive/perceptual and modifying variables for further explaining the occurrence of health-promoting behaviors in adults with cancer. Multiple regression analyses revealed that 23.5% of the variance in health-promoting lifestyle was explained by the model cognitive/perceptual variables definition of health, perceived health status and perceived control of health and the modifying variables education, income, age and employment. When illness-specific variables were included in the analysis, initial reaction to the diagnosis of cancer was found to be a significant contributor to the regression. Study results support the importance of both general health-related and cancer-specific cognitive/perceptual factors in explaining the occurrence of health-enhancing behaviors among ambulatory cancer patients; these factors may therefore be suitable targets for interventions to encourage adoption of healthy lifestyles. Key words-health-promoting Model

lifestyle, ambulatory cancer patients, health behavior, Health Promotion

INTRODUCIION

In the last two decades, an unprecedented degree of cancer research has produced significant and even dramatic yields. Some types of cancers that were uniformly and rapidly fatal have been checked in their growth and cured in a large percentage of cases [l, 21. There have also been profound changes in the delivery of cancer treatments. It has become routine for treatments to be administered on an outpatient basis, thus allowing patients to continue to live in the community and maintain their lifestyle during therapy. The improved survival rates, more effective treatment modalities and the recent shift from inpatient to ambulatory settings for treatment have allowed health professionals to focus upon health promotion with cancer patients. Within the last 5 years, cancer patients themselves have started to form self-help groups with an emphasis on health promotion and wellness [3]. Illness behavior and sick-role behavior in people with cancer have been researched extensively and reported in the literature [4-71. The same is not true of health-promoting behavior in this population. Miller [S] stresses that ambulatory, chronically ill patients must be full participants, even managers, of their own care and details five goals for people with chronic disease, one of which is pursuing a health lifestyle. A healthy lifestyle has been described in many different ways including very specifically as avoiding bad health habits and very broadly as behaviors under personal control that have a significant impact on health status. Pender [9] suggested that healthprotecting behavior and health-promoting behavior

might be viewed as two complementary parts of a healthy lifestyle. The health-protecting part of lifestyle include the actions a person takes to decrease his/her chance of becoming ill or injured. In contrast, the health-promoting part of lifestyle is defined as “a multidimensional pattern of self-initiated actions and perceptions that serve to maintain or enhance the level of wellness, self-actualization and fulfillment of the individual” [ 10, p. 421. A health-promoting lifestyle is pursued because it is satisfactory, rewarding and enjoyable, not because of a wish to avoid disease. One of the few studies of health-promoting activities of cancer patients is that done by MacVicar [ll], who explored the effects of structured exercise on the functional status of women with stage II breast cancer undergoing chemotherapy. Exercise improved the functional ability of the cancer patients studied, suggesting that beneficial results can be achieved by aerobic training during chemotherapy [ 1I]. The majority of the research into health-related lifestyles has looked at the practices that health professionals recommended in terms of preventing disease/injury. In contrast to the research that has focused on illness prevention, this investigation is based on a wellness-oriented framework. The Health Promotion Model (HPM), proposed as a framework for explaining and predicting the health-promoting component of lifestyle, provides the theoretical framework for this study [lo, 111. The HPM (shown in Fig. 1) is similar in structure to the Health Belief Model [12-141 in that determinants of healthpromoting behavior are categorized into cognitive/ perceptual variables, modifying variables, and cues of action [l I]. The crucial difference between these two models is that in the Health Promotion Model the individual’s behavior is directed toward sustaining

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MARILYN FRANK-STROMBORG et al.

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COGNITIVEPERCEPTUAL FACTORS

DEFINITION OF HFMTH

MODIFYING FACTORS

PARTICIPATION IN HEALTH-PROMOTING BEHAVIORS

I-

PERCEIVEDHEALTH

Fig. I. Pender’s Health Promotion Model. Pender N. Health Promotion in Nursing Practice. 2nd min. Appleton-Lange,

or increasing the level of well-being, whereas in the Health Belief Model behavior is directed toward decreasing the chances of developing a specific disease [IS]. Because the HPM was developed primarily to explain health-promoting behavior, its application to ill individuals, is exploratory in nature. The underlying assumption of the model is that health promotion is applicable to populations regardless of their health status [lo]. The theoretical underpinnings of the model are provided by Bandura’s social learning theory in which cognition, effect, actions and environmental events are proposed as operating interactively in determining behavior [ 161. Since social learning theory emphasizes the central role of cognitive mediating processes in regulating behavior, the cognitive/perceptual variables are proposed within the model as the primary motivational mechanisms that directly affect the acquisition and maintenance of health-promoting behaviors. Modifying variables are proposed as variables that exert an indirect rather than a direct influence on the occurrence of health-promoting actions; the effects of modifying variables are considered to be mediated through cognitive/perceptual processes and can thus affect the likelihood of engaging in health-promoting behaviors. The third component of the model, cues to action, are transient stimuli that can serve as prompts to action. The intensity of the cue(s) needed to trigger action will depend on the level of readiness of the individual to engage in health-promoting activity. The cognitive/perceptual variables included in the HPM are all considered mutable, an important

Norwalk, CT. 1987.

consideration for variables in any model proposed as a basis for structuring interventions directed toward lifestyle change. Importance of he&h reflects the value placed on health in relation to other personal life values within his/her personal value hierarchy [17]. Perceiued control of health is the extent of belief or generalized expectation that health is determined by personal behavior and that one maintains health or wellness as a result of his/her own actions rather than being influenced primarily by powerful others, chance or fate [IS]. Perceived selfeficucy is the belief that desired outcomes can be attained through one’s own skill and competent actions [ 191.Four dimensions of the definition of health were described by Smith [20], including the clinical view of health as the absence of disease, the role performance view of health as the ability to carry out socially-sanctioned roles, the adaptive view of health encompassing the ability to adjust to life’s changing situations and the eudaimonistic view of health as exuberant well-being. Perceived health status is the subjective assessment or evaluation of one’s current state of health. Benefts of health-promoting behavior reflect the perceived effectiveness of behavior, whereas barriers to healthpromoting behaviors are blocks or hindrances to action. The model has important implications for the study of adults with cancer because their healthpromoting behaviors, that is, behaviors directed toward increasing their level of wellness, have not been extensively studied. The primary purpose of this descriptive, correlational ex post facto field study was

Ambulatory cancer clients to test the usefulness of the Health Promotion Model in explaining the occurrence of health-promoting lifestyles among ambulatory cancer patients receiving chemotherapy and radiation in outpatient settings. A second purpose was to determine the extent to which cancer-specific cognitive/perceptual and modifying variables not in the model might further explain the occurrence of health-promoting lifestyle in ambulatory cancer patients.

METHODS

Sample Responses to the instruments were obtained from a convenience sample of 385 ambulatory cancer patients undergoing treatment for their disease in 13 clinical sites in the midwestem United States. All subjects who met the study’s criteria were approached and asked to participate in the study, and 96% agreed to do so. Instruments in which responses to more than 10% of any of the items were missing were eliminated prior to analysis; 385 out of 392 initial participants were retained. Of the 385 subjects, 223 (57.9%) were females and 162 (42.1%) males. Their ages ranged from 21 to 85, with a mean of 53.7 years (SD = 12). As might be anticipated from the larger percentages of females in this sample, the largest number of subjects indicated their primary cancer site was breast cancer (115 or 29.9%). The next largest number had either lymphatic cancer (64 or 16.6%), colorectal cancer (61 or 15.8%), lung cancer (40 or 10.4%), or uterine/vaginal cancer (31 or 8.1%). To determine the representativeness of this sample, a comparison was made on age, gender and primary cancer site with American Cancer Society (ACS) national statistics [21]. The sample’s age range compared with national statistics from the ACS and reflects the fact that cancer is predominantly a disease of middle and old age. With the exception of prostate cancer, the most commonly occurring cancers in the U.S. were also found in the highest percentages in this sample. Females were over-represented in this sample compared to national statistics. Most of the subjects (191 or 49.7%), had been diagnosed with cancer within the past 6 months; 60 (15.7%) within the 1st year; and 17 (7.8%) within the last 18 months. The majority of the sample (284 or 73.8%) were receiving chemotherapy with a smaller number (98 or 25.5%) receiving radiation. Three subjects had just completed treatment. The largest number, 155 (40.3%), were employed full time and a smaller number were retired (94 or 24.4%) or homemakers (58 or 15.1%). The overwhelming majority of the subjects were married (277 or 71%) and Caucasian (375 or 97.4%). A diverse educational background was found in this sample: 19 (5%) had an 8th grade or less education, 43 (11.2%) had some high school, 127 (33%) were high school graduates, 108 (28.1%) had some college, 51 (13.2%) were college graduates and 36 (9.4%) had graduate or professional degrees. Family income was also diverse: 105 (27.3%) of the sample reported a family income below $20,000, 153 (39.7%) between $20,000 and S40,000, 68 (17.7%) between $40,001 and %60,000 and 35 (9.1%) above $60,000.

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Criteria Cancer patients participating in the study met the following criteria: (1) over the age of 21; (2) a known diagnosis of cancer; (3) English as a primary language; (4) physically, emotionally and mentally able to complete the research instruments; (5) a score of 60 or above on the Kamofsky Performance Scale (a scale of O-100 that assess functional status) [22]; and (6) receiving treatment for cure (not palliation) as defined by the physician. Measurement of variables In this initial test of the Health Promotion Model, not all variables could be measured due to the potential for subject fatigue in individuals undergoing treatment for cancer. Variables that were chosen were those believed to be most important conceptually and theoretically, as well as those for which reliable and valid measurement instruments were available. Four of the seven cognitive/perceptual variables in the Health Promotion Model measured at a health-specific rather than behavior-specific level were examined as possible factors influencing overall health-promoting lifestyle. In addition, a cancer-specific cognitive/ perceptual variable not in the model, the initial reaction to the cancer diagnosis, was measured. Several modifying variables in the model within the categories of demographic characteristics as well as some cancer-specific modifying variables, were assessed as indirect influences on lifestyle. Closedend self-report instruments were used to assess the cognitive/perceptual and modifying variables. Importance of health. This variable was measured by the Value Survey, a IO-item instrument that is an adaptation of Rokeach’s Terminal Value Survey (231. The subject is asked to rank the values in order of personal importance from 1 to 10. Each ranking of health is subtracted from 11 so that high scores represent high health value. The test-retest reliability of the instrument when administered 4 weeks apart to a group of hypertensive clients was reported to be 0.92 [24]. Perceived control of health. Measurement of this variable was accomplished by using Forms A and B of the Multidimensional Health Locus of Control Scales developed by Wallston et al. [18]. The combined forms consist of three scales of 12 items each to measure the three dimensions of internality, chanceexternally and powerful others-externality. A 6-point Likert response format is used. In this study, coefficient alphas were 0.814 for the internality scale, 0.825 for powerful others-externality, and 0.808 for chance-externality. Definition of health. The L.zflrey Health Conception Scale (LHCS), which was used to measure this variable, contains 28 items scored on a 6-point Likert scale. There are 7 items for each of the four subscales of the definition of health: clinical, role performance, adaptive and eudaimonistic. Laffrey reported alpha coefficients for the four subscales ranging from 0.867 to 0.884 and a 1 week test-retest reliability of 0.84. Walker and Volkan [25] conducted a factor analytic study of health conception among adults 55 years of age and older and found a presence of a wellness dimension and an absence of illness dimension under-

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MARILYN FRANK-STROMBORGer

lying the four health conception scales. Because there were high intercorrelations (0.770-0.797) among the role performance, adaptive and eudaimonistic subscales in the present study, the three subscales were combined to form a wellness subscale of health conception as recommended by Walker and Volkan [25]. Coefficient alphas were 0.950 for the wellness subscale and 0.855 for the clinical subscale in the present study sample of ambulatory cancer patients. Perceived health status. This variable was assessed by using the single item, ‘How would you rate your overall health at the present time?’ This is assessed on a 4-point scale that ranges from ‘poor’ to ‘excellent’. Several studies using large samples have demonstrated the ability of the single item subjective health rating to detect variance in perceived health status among populations of non-institutionalized older adults [26]. Further, Ware et al. [27], after reviewing 39 studies of general health perceptions, concluded that such ratings appear both reliable and reproducible. Tissue [28] makes the point that self-rated health “represents a summary statement about the way in which numerous aspects of health, both subjective and objective, are combined within the perceptual framework of the individual respondents. Health ratings do not reflect only experienced psychic well-being as has sometimes been suspected, although neither are they commensurate with medical diagnosis” (p. 93). Reaction to the diagnosis of cancer. The Reaction to the Diagnosis of Cancer Questionnaire (RDCQ) [29] was used to assess this variable. The RDCQ is a 28-item questionnaire with a modified 5-point forcedchoice Likert format ranging from 1 = ‘no, I did not feel that way’ to 5 = ‘yes, I felt that way extremely’. Construct validity was assessed by a factor analytic study with 441 ambulatory cancer patients that verified the presence of two dimensions in the instrument, a distress dimension and a confronting dimension, which are measured by 19-item and 9-item subscales. Test-retest reliability over a 2-week interval with a convenience sample of 14 ambulatory cancer patients undergoing treatment was 0.923 for the distress subscale and 0.865 for the confronting subscale. In the present study, the alpha reliability coefficients were 0.916 for the distress subscale and 0.825 for the confronting subscale. Demographic measures. Demographic information was obtained with a questionnaire developed for this study and included age, gender, marital status, employment, education, income, residence, ethnic/ radical background, months since cancer diagnosis, primary cancer site, whether the individual was receiving chemotherapy or radiation, and Kamofsky score. Health-promoting lifestyle. The Health-Promoting Lifetyle Profile (HPLP) developed by Walker et al. [30] was used to measure the dependent variable, a health-promoting lifestyle. The HPLP contains 48 items and employs a Cpoint response format with 1 = never, 2 = sometimes, 3 = often and 4 = routinely. The authors reported that “items that content experts had questioned as possibly being oriented to illness prevention rather than health promotion were eliminated early on the basis of item analysis. Those items, which were concerned with the avoidance of undesirable health practices, appear to comprise a set

al.

of behaviors different from the set measured on the HPLP” [30, p. 801. Factor analysis with 952 adults in midwestem U.S. communities isolated six dimensions: self-actualization (13 items), health responsibility (10 items), exercise (5 items), nutrition (6 items), interpersonal support (7 items), and stress management (7 items). Second-order factor analysis yielded a single factor, interpreted as health-promoting lifestyle. Scores on the total instrument and on each of its subscales are computed as a mean of the responses to the items in each. Test-retest reliability with a sample of 63 adults over a 2-week period for the total scale was reported as 0.926 and ranged from 0.808 to 0.905 for the subscales [30]. In the present study, the alpha reliability coefficient for the total scale was 0.932 and alphas for the subscales ranged from 0.739 to 0.888. Procedure

The 13 clinical sites for data collection consisted of chemotherapy and radiation hospital-based clinics and physicians’ offices. At each clinical site, a trained research assistant (an oncology nurse who was usually employed in the setting): (1) identified those individuals who met the criteria for inclusion in the study; (2) explained the general purpose of the research and obtained permission from those interested in participating in the study; (3) interviewed each participant to obtain information concerning demographic information and assessed functional status by using the Kamofsky Performance Scale; and (4) explained how to use the instrument pack, that they were to complete it at their convenience and return at their next clinic visit. The instrument pack contained the instruments measuring the dependent and independent variables. The instruments were randomized into three different forms to minimize the effects of a given order. RESULTS

Because all study instruments except the RDCQ were developed with well populations, each instrument’s psychometric charactersitics were assessed with this sample of cancer patients. Psychometric evaluation revealed that the reliability and validity of each instrument were similar to all reported values and indicated this sample’s responses were similar to those reported with well populations. If less than 10% of the data on an instrument was missing, median sample values were substituted. Means, standard deviations, and range of scores for each of the cognitive/perceptual variables and lifestyle variables measured in the study appear in Table 1. An examination of health-promoting lifestyle patterns found that ambulatory cancer patients scored highest on the subscales of self-actualization and interpersonal support, lowest on exercise and in the middle range on health responsibility, nutrition and stress management. Prior to regression and canonical correlation analyses, scores on three highly negatively skewed variables, importance of health, definition of health, and the confronting dimension of the RDCQ, were power transformed by cubing and scores on one highly positively skewed variable, the exercise dimension of lifestyle, were log transformed [31]. A correlation

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Ambulatory cancer clients Table 1. Scores of ambulatory cancer clients on cognitive,‘perceptual variables and healthpromoting lifestyle dimensions (N = 385) Dimensions Cognitive/perceptual

Possible range of scores

Actual range of scores

M

I-IO

1.0&10.00

9.16

1.54

12-72 12-72 12-72

17-72 12-72 17-72

49.35 35.47 45.67

9.23 IO.91 10.72

21-126 742 14

21-109 14-40 l-4

39.54 15.11 2.44

16.19 7.53 0.77

19-95 9-45 1-l Ia l-4 IL-I 14 IL4 14

27-95 945 1.69-3.83 1.77~.00 1.00-3.70 1.00-4.00 1.004.00 1.7l-wO 1.29-4.00

67.54 34.35 2.79 3.16 2.41 1.87 2.9 I 3.17 2.68

16.55 7.45 0.42 0.51 0.53 0.68 0.69 0.55 0.56

SD

factors

Importance of health Control of health: Internal Chance Powerful others Definition of health: Wcllncss Clinical Health status Reaction to the diagnosis of cancer: Distress Confronting Health-promoting lifestyle Self-actualization Health responsibility Exercise Nutrition Interpersonal support Stress management

Values represent untransformed raw scores

matrix was generated to examine multicollinearity of the independent variables. All correlations were below 0.40, indicating that the variables were not redundant [32]. Regression analyses

Multiple regression analysis was first performed using only the cognitive/perceptual and modifying variables proposed in the Health Promotion Model to ascertain which variables contributed to the explanation of health-promoting lifestyle and the relative contribution of each variable. Hierarchical multiple regression analysis of health-promoting lifestyle on cognitive/perceptual variables in a first book and modifying variables in a second block with stepwise entry within blocks was employed [32]. The 2-block order of entry was selected to conform to the theoretical assertions underlying the model that cognitive/perceptual variables are the primary influences on lifestyle, while modifying variables contribute only indirectly to the explanation of lifestyle through their impact on cognitive/perceptual processes. The standardized regression coefficients, or betas, indicate the number of standardized units that the dependent variable changes given one standardized

unit change in a predictor variable, controlling for the other predictor variables in the model [33]. Heise [34] has suggested that only standardized regression coefficients that are GO.10 should be interpreted as being substantively important as predictor variables, with smaller coefficients explaining less than 1% of the variance in the dependent variable. Following this suggestion, the discussion that follows will emphasize the variables whose coefficients meet this minimum criterion. A total of 23.52% of the variance in healthpromoting lifestyle was explained by three cognitive/ perceptual and four modifying variables. As shown by Table 2, 15.80% of the variance was explained by three cognitive/perceptual variables in the Health Promotion Model and an additional 7.7% was explained by four demographic variables. The strongest predictors were positive health conception (/? = 0.216) and health self-rating (1 = 0.198), followed by educational level (B = 0.169) age (fi = 0.155), and employment status (/3 = -0.106). Thus, ambulatory cancer patients in outpatient chemotherapy and radiation settings were more likely to report a healthy lifestyle if they held a wellnessoriented definition of health, rated their personal

Table 2. Health-promoting lifestyle profile scores regressedon cognitive/perceptual and modifying variables of the Health Promotion Model (N = 385) Explanatory variables Cognitive/perceptual

R2

R2

changes

Beta

Univariate* F

Simple

0.074 0.117

0.074 0.043

0.198 0.216

IS.40 19.32


P

,

factors

Health self-rating Wellness health conception Control of health -external chance Control of health -internal Modtyying

Cumulative

-0.12s

0.272 0.234

0.144

0.027

6.42

0.012

0.158

0.014

0.144

8.33

0.004

-0.182 0.222

0.187 0.216 0.226 0.235:

0.029 0.028 0.01 I 0.009

0.169 O.lS5 0.141 -0.106

10.00 8.99 5.64 4.00

0.002 0.003 0.010 0.046

0.197 0.09s 0.165 -0.047

factors

Educational level Age Family income Employment statust

lUnivariate F values reflect the importance of each variable after all have entered the equation. tCoded as 0 = not employed, I = employed. $Adjusted R2 = 0.217.

MARILYN FRANK-STROMBORGet

1164 Table 3. Health-promoting

Explanatory

variables

01.

lifestyle profile scores regressed on model and illness related cognitive/perceptual Heaith Promotion Model (N = 385) Cumulative R’

R2 changes

Beta

0.073

0.188 0.182

and modifying variables of the

Univariate* F

P

Simple I

14.08


0.271

13.50

0.001

0.233

Cognitiw/percepluoI factors Health self-rating 0.073 Wellness health conception 0.117 Control of health -external chance 0.144 Control of health -internal 0.158 Reaction to the diagnosis of cancer: Confronting 0.198

4.64

0.032

0.014

0.106

4.53

0.034

0.221

0.039

0.187

14.01


0.306

Modifying factors Educational level Age

0.024 0.025

0.191 0.165

14.90 I I .47


0.200 0.093

0.222 0.247t

0.043 0.028

-0.106

-0.188

*Urnvariate F values reflect the importance of each variable after all have entered the equation. tAdjusted R’ = 0.232.

health status as high, expressed a belief that their health was controlled by themselves rather than by chance, were more well educated, older, had higher incomes, and were not employed outside the home. Multiple regression analysis was then conducted adding the cancer-specific cognitive/perceptual and modifying variables to determine what additional variance in health-promoting lifestyle they might explain beyond that accounted for by variables in the HPM. Hierarchical multiple regression analysis was performed with model cognitive/perceptual variables entered in a first block, the confronting and distress dimensions of reaction to the diagnosis of cancer, a cancer-specific cognitive/perceptual factor, in a second block, model modifying variables in a third block and the cancer-specific modifying variables of months since diagnosis, radiation and chemotherapy in the fourth block. A total of 24.73% of the variance in healthpromoting lifestyle was explained by four cognitive/ perceptual and two modifying variables. As shown in Table 3, 15.8% of the variance in health-promoting lifestyle was explained by three model cognitive/ perceptual variables and an additional 3.9% by one cancer-specific cognitive/perceptual variable. Overall, the strongest predictors were educational level (/I = 0.191), health self-rating (/? = 0.188), the confronting dimension of the reaction to the diagnosis of cancer (B = 0.187) and a positive health conception (jI = 0.182). Weaker predictors were age (b = 0.165) and the two dimensions of perceived control of health; externality-chance (B = -0.106) and internality (/9 = 0.106). With the addition of cancer-specific cognitive/ perceptual and modifying variables in the second regression equation, the confronting dimension of the reaction to the diagnosis of cancer emerged as a strong predictor of a health-promoting lifestyle. (No cancer-specific modifying variables were found to be statistically significant predictors.) The effects of the other variables including health self-rating and positive health conception were reduced. Thus, the addition of the cancer-specific variables increased the amount of variance explained in a health-promoting lifestyle by I .2%. The profile of ambulatory cancer clients in outpatient chemotherapy and radiation settings who reported health-promoting lifestyles was very similar to that found when only the model variables were

used: they were more well educated, rated their personal health status as high, held a wellness-oriented definition of health, held a confronting attitude toward the diagnosis of cancer, were older and expressed a belief that their health was controlled by themselves rather than by chance. Because of the criticism surrounding the stepwise entry procedure in the literature [351, the simultaneous entry procedure was used following the same hierarchical blocked order of entry (361. The results were compared with those from the stepwise procedures and found to be similar. Canonical correlation analysis

To further understand the nature of the relationship between the significant cognitive/perceptual and demographic variables from the Health Promotion Model in the first mentioned regression analysis and the six dimensions of health-promoting lifestyle, canonical correlation analysis was used to simultaneously consider the association between the two sets of variables. As shown in Table 4, two canonical Table 4. Canonical correlation summary table for lifestyle dimensions and model cognitive/perceptual and modifying variables Canonical variates

I

Variable sets Li/ctyk dimemion.s (HPLP subscales) Self-actualization Health responsibility Exercise Nutrition Interpersonal support Stress management

0.917’ 0.493 0.633 0.570 0.675 0.612

2

0.563 0.631

Cognilive/perccplual

and modifying variables Self-rated health Internal health locus of control Chance health locus of control Positive health conception Education Income Employmentt Age Canonical correlation (Rc’) Explained variance Total variance explained Canonical redundancy coefficient Total redundancy coefficient *Structure coefficient. tCodcd as 0 = not employed,

0.618 0.435 -0.418 0.399 0.507 0.439 0.108 0.514 26.4% 44.4% 0.116 0.142

1= employed.

0.346 0.420 -0.431 -0.595 -0.707 0.471 0.424 18.0% 0.026

Ambulatory cancer clients correlations met the criterion on meaningfulness by having an Rc’ > 0.10 [37]. Using a criterion of 0.30 or greater for meaningful structure coefficients [37], all six subscales comprised the lifestyle dimensions set and four cognitive/perceptual and two demographic variables comprised the other set of the first pair of canonical variates. Self-rated health, a wellness definition of health, internal health locus of control, education, income, and employment were positively related, and chance health locus of control was inversely related to all six of the health-promoting lifestyle dimensions. The first pair of canonical variates shared 26.4% of the variance and had a canonical correlation of 0.514. The first canonical redundancy coefficient, which provides an indication of the proportion of variance in the set of original lifestyle subscales that is explained by the relationship with a linear combination of the set of demographic and cognitive/perceptual variables [38], was 0.116. The second pair of canonical variates, which by definition was uncorrelated with the first pair, included only two of the health-promoting lifestyle subscales. Findings indicated that ambulatory cancer clients who were older in age with less education and lower income, were not employed, had a wellness conception of health, and perceived their health as controlled by themselves had high scores on the stress management and nutrition dimensions of health-promoting lifestyle. The second pair of canonical variates with a canonical correlation of 0.424, shared 18.0% of the variance. The second canonical redundancy coefficient was 0.026. The two pairs of canonical variates together accounted for 44.4% of the shared variance. Additional findings. Since some primary cancer sites have been linked with lifestyle [39,40], separate analysis was done to determine the relationship between primary cancer site and involvement in a health-promoting lifestyle. Six categories of sites were examined, including lung cancer, breast cancer, digestive cancer, cancer of the female reproductive organs, cancer of the lymph system, and ‘other’ sites. Because the groups had unequal n’s, F-tests were done and confirmed that the assumption of homogeneity of variance had not been violated. One-way analysis of variance of HPLP score by primary cancer site showed there was a significant difference (F = 2.62, P = 0.02) among the groups. The Scheffe’ procedure demonstrated that the difference (P -c 0.05) was between individuals with lung and breast cancer, with lung cancer patients having less health promoting lifestyles. Additional one-way analyses of variances were done including first only male and then only female lung cancer patients. While there were no significant differences between any of the other primary site groups and male lung cancer patients, there were significant differences (F = 4.11, P < 0.001) between the groups when only female lung cancer patients were included. The Scheffe’ procedure revealed that the differences (P < 0.05) in the groups were between breast cancer patients and patients in the ‘other’ grouping and female lung cancer patients. Female lung cancer patients had lower scores on the HPLP (mean = 2.44, SD = 0.435) than breast cancer patients

I165

(mean = 2.87, SD = 0.384) and patients in the ‘other’ grouping (mean = 3.00, SD = 0.341). CONCLUSION

In this investigation, perceptions of health status, definition of health, and control of heatlh emerged as a constellation of HPM constructs associated with reported health-promoting lifestyle behaviors among ambulatory cancer patients. An illness-specific nonmodel cognitive/perceptual variable that also contributed to explaining a health-promoting lifestyle was the initial reaction to the diagnosis of cancer. This was the only cancer-specific variable that was found to be predictive of a health-promoting lifestyle and was one of the four strongest explanatory variables. All of the model cognitive/perceptual variables that were studied, except importance of health, were associated with health-promoting lifestyle behaviors. The modifying factors of education, age, income and employment made a modest contribution to the explanation of health-promoting lifestyle after consideration of general and illness-specific cognitive/ perceptual processes. Of these modifying variables, education and age were the strongest predictors of a health-promoting lifestyle. Consistent findings from multiple regressions using model and illness-specific variables as well as canonical correlation analyses concerning relationships among model variables add strength to the conclusions drawn from this study. DlSCWSlON The findings of this study lend credence to the Health Promotion Model and indicate that this model merits further study as an explanatory and predictive framework for health-promoting behavior among adults with cancer, a group whose behaviors directed toward increasing their level of wellness have not been extensively studied. The most powerful explanatory cognitive/perceptive variables from the HPM for health-promoting behaviors among these ambulatory cancer patients were definition of health and perceived health status. This held true when cancer-specific variables were included in the equations. The findings that a positive evaluation of personal health is associated with a more health-promoting Iifestyle has been reported in other studies with essentially healthy individuals [41-441. It may be explained by the possibility that (1) the better a person believes his health to be, the more likely he will act in ways to maintain it, or (2) a person who engages in a healthpromoting lifestyle may then feel healthier. Defining health as the presence of wellness seemed to exert considerable impact on involvement in a health-promoting lifestyle, while defining health clinically as the absence of illness contributed nothing further to the explanation of lifestyle. This cognitive/ perceptual variable seldom has been included in studies of the determinants of health behavior. The ability to define health at least partly as the presence of wellness has important implications for individuals with cancer. According to Ardell, “It is possible to be ‘well’ at the same time that one has illness. One can still accept life at its fullest and strive for its highest potential” [45, p. 191. There is a healthy way to experience a disease

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as well as a constantly challenging way to be healthy [46,471. This study has shown that ambulatory cancer patients who define health as the presence of wellness are more likely to engage in health-promoting behaviors. It was expected that perceiving health to be controlled by luck or chance would be negatively associated with engaging in health-promoting lifestyle. It seems reasonable that individuals who believe they have little personal control over their health would have few reasons to engage in health-promoting behaviors. This finding is consistent with other studies that have looked at the relationship of health behaviors and locus of control [42,48,49]. Studies of locus of control with cancer patients have focused on the relationship between the individual’s perception of control of health and survival and adjustment to the disease. These studies have found that long-surviving cancer patients score higher on internal control than do a disease-free normative group. Achterberg et al. [SO-521 studies of cancer patients who outlived predicted life expectancies found that the ‘exceptional’ patients scored higher in internal control than did Levenson’s [53] control group of healthy adults. In a related study of breast cancer patients, Taylor et al. (541 found that those who believed that they or their physician could exert control over their illness showed better short- and long-term adjustment than did patients who did not hold these beliefs. A similar study that examined the role of locus of control and adjustment to cancer found that as beliefs in internalcontrol increased, depression decreased [55J To better understand these relationships, further studies might examine the role of health-promoting lifestyle as an intervening variable between health locus of control and cancer adjustment and survival. One non-model cancer-specific variable also was found to be predictive of health-promoting behaviors. The confronting dimension of the initial reaction to the diagnosis of cancer was as strong an influence on health-promoting lifestyle as were perceived health self-rating and definition of health. It should be addressed in any interventions designed to promote health-promoting behaviors in ambulatory cancer patients. Related research has shown that the initial reaction to cancer impacts on adjustment to cancer and length of survival. A research group at King’s Hospital in England did a prospective, multidisciplinary study of 69 women with early breast cancer and found significant differences in survival at 5 and 10 years based on the women’s initial response to cancer [56-581. They report that women who had reacted to the initial diagnosis by ‘denial’ or ‘frighting spirit’ had a more favorable outcome than those who showed ‘stoic acceptance* or ‘helpless/hopeless’ responses to the diagnosis. The confronting dimension of the RDCQ incorporates items that represent the ‘frighting spirit’ reported by the research group at King’s Hospital. Again, further studies might examine the role of health-promoting lifestyle as an intervening variable between reaction to the diagnosis of cancer and cancer adjustment and survival. The value placed on health was not a significant determinant of health-promoting lifestyle. There is conflicting information on the explanatory and predictive role of health value in terms of involvement in

health-related behaviors. Duffy [42], Wallston et al. [17], and Pender [lo] found that it was not predictive of involvement in a healthy lifestyle while many other researchers have found that it is predictive [59-611. One explanation for the failure of health value to explain variance in health-promoting lifestyle in this study may be related to the skewed distribution of the health value scores, with 63.8% of the ambulatory cancer clients rating health as their highest value and 81.3% ranking health as either first or second choice. The high value placed on health by ambulatory cancer patients is consistent with individuals who are confronted with a life threatening illness and who are suddenly faced with the possible loss of health, and the lack of variability severely limits correlation. The modifying variables of age, education, income and employment made a further contribution to the explanation of health-promoting lifestyle after consideration of cognitive/perceptual variables. Of these, the strongest predictor of involvement in a healthpromoting lifestyle was education. Age was also a strong predictor, but to a lesser degree than education. The finding that older subjects and those with more education were more likely to be involved in a healthpromoting lifestyle is congruent with the literature [62-641. While some of the modifying variables were shown to be strong predictors of a health-promoting lifestyle, they are of lesser interest than the cognitive/ perceptual variables because they are not amenable to modification by health care professionals. Although this study has shown that a partial set of Health Promotion Model variables were explanatory of involvement in health-promoting lifestyle behaviors, several variables proposed in the model were not investigated. It is important to note that the cognitive/ perceptual and demographic variables that were found to be strong influences on health-promoting behaviors among these cancer patients are the same variables that have been reported in similar research with healthy populations [42,44,65]. In addition, a non-model cancer-specific psychological variable played a significant role in explaining a healthpromoting lifestyle in this sample. Further research should focus on testing the full model, which may explain a greater amount of variance in healthpromoting lifestyle than observed in this investigation. Further testing of the model may result in some variables being eliminated because they are not found to be predictive of a health-promoting lifestyle. The results of this study and several others raise questions about the need to retain health value as a cognitive/perceptual variable [44]. On the other hand, it may be necessary to include additional variables to evaluate whether more variance is contributed by their addition. For instance, it has been suggested that the cognitive/perceptual variable of hardiness may influence some health-promoting behaviors such as stress management and self-actualizing behaviors [66]. In an earlier study of ambulatory cancer patients, Franck-Stromborg found that interpersonal influence, a modifying variable in the HPM, influenced the health-promoting behaviors of self-actualization, interpersonal support, and stress management [67]. Assessment of interpersonal influence may be an important variable to include in future studies of health-promoting behaviors.

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Ambulatory cancer clients This study has potential clinical relevance as it will help contribute an understanding of: (1) the healthpromoting self-care behaviors in which ambulatory cancer patients engage, and (2) what potentially modifiable variables explain a health-promoting lifestyle. This may eventually provide a basis for intervention. Health care professionals have major responsibility for instruction of cancer patients in self-care behaviors, including those which are healthpromoting, and for assisting patients to achieve the knowledge and competencies that can be used to maintain and enhance their health. In order to promote and facilitate health-promoting behaviors, it is necessary to understand the variables that impact on decisions to engage in such behaviors. The HPM has previously been used to explain health-promoting behavior among well individuals. Further research is needed to test the usefulness of the Health Promotion Model in explaining and predicting health-promoting behaviors among ill individuals, as well as to determine the relative importance of health-protecting and health-promoting motivational influences on their health-related lifestyle behaviors. By determining the relationships between the model cognitive/perceptual and demographic, as well as cancer-specific variables, this study has contributed to the development of theory in the area of health promotion. The findings from this study will facilitate identification of adults with cancer who are likely to incorporate health-promoting behaviors into their lifestyle or who would profit from behavior change programs such as training to foster a wellness orientation to health and evaluation of health within a wellness framework, and to encourage a ‘confronting’ orientation to the diagnosis of cancer. Increased competency in health-prompting behavior could enhance the quality of life as well as the level of personal health

for adults

with cancer.

Acknowledgements-This

research was funded by the National Center for Nursing Research, National Institutes of Health, Grant PGI NROI 121. We are indebted to Robert A. Karabinus for his assistance in data analysis.

REFERENCES 1. Myers M. and Hankey B. Cancer patients survival in the United States. In Cancer Epidemiology and Prevention (Edited by Schottenfeld D. and Fraumeni J.), pp. 138165. Saunders, Philadelphia, PA, 1982. _2. Curing Cancer. The National Coalition for Cancer Research, Capital Associates, Inc., 426 C Street, N.E., Washington, DC 20002, 1988. 3. Radner G. Gilder Radner’s answer to cancer. Healing the body with mind and heart. .r.ife Magazine 74-78, March 1988. 4. Coons H. L., Leventhal H., Nerenz D., Love R. and Larson S. Anticipatory nausea and emotional distress in patients receiving cisplatin-based chemotherapy. Oncol. Nurs. Forum 14, 31, 1987.

5. Johnson J., Nail L., Lauver D., King K. and Keys H. Reducing the negative impact of radiation therapy of functional status. Cancer 61, 46-51, 1988. 6. Daut R. L. and Cleeland C. S. The prevalence and severity of pain in cancer. Cancer SO, 1913-1918, 1982. 7. Ehlke S. Symptom distress in breast cancer patients receiving chemotherapy in outpatient settings. Oncol. Nurs. Forum IS, 343-346, 1988.

8. Miller J. F. Categories of self-care needs of ambulatory patients with diabetes. J. Adr. Nurs. 7, 25-31, 1982. 9. Pender N. J. Health Promotion in Nursing Practice, 2nd edn. Appleton & Lange, Norwalk, Cf. 1987. 10. Pender- N. J. Health Production in ,Vursing Practice. Appleton-CenturyCrofts, New York. 1982. 11. MacVicar M. Effect of aerobic training on functional status of women with breast cancer. Oncology Nurses Society Proceedings of the Annual Congress, 1983.

12. Hochbaum G. Public participation in medical screening programs: a sociopsychological study. Public Health Service Publication (No. 572). U.S. Government Printing Office, Washington, DC, 1986. 13. Kegeles S. Why people seek dental care: a test of a conceptual formation. J. Hlrh Human Behar. 4, 166, 1963. 14. Rosenstock I. The health belief model and preventive health behavior. Hith Educ. Monogr. 2, 1974. 15. Goodstadt M. S., Simpson R. and Loranger P. Health promotion: a conceptual integration. Am. J. Hlrh Promof. 58-63. Winter 1987. 16. Bandura A. Social Foundations of Thought and Action. Prentice-Hall, Englewood Cliffs, NJ, 1986. 17. Wallston K. A., Maides S. and Wallston B. S. Healthrelated information seeking as a function of healthrelated locus of control and health value. J. Res. Person. 10, 215-222, 1976. 18. Wallston K. A., Wallston B. S. and DeVellis R. Development of the Multidimensional Health Locus of Control (MHLC) Scales. Hlth Educ. Monogr. 6, 160-171,

1978.

19. Bandura A. Self-efficacy: toward a unifying theory of behavior chanae. Psvchol. Rev. 84. 119-215. 1977. 20. Smith J. A. fhe Idea of Health:‘lmplications for the Nursing Professional. Teachers College Press, New York. 1983. 21. Silverberg E. and Lubera J. Cancer Statistics, 1989. Ca-A

Cancer Journal for Clinicians 39, 3-20,

1989.

22. Karnofsky D. and Burchenal K. Karnofsky performance scale. In Evaluation of Chemotherapeutic Agenrs (Edited by MacLeod D.). Columbia University Press, New York, 1949. 23. Rockeach M. N. The Nature of Human Values. Free Press, New York 1973. 24. Pender N. J. Effects of progressive muscle relaxation training on state-trait anxiety and health locus of control among hypertensive clients. Res. Nurs. Hhh 8, 67-72, 1985.

25. Walker S. N. and Volkan K. Health conception among older adults. Unpublished manuscript, 1989. 26. Mossey J. M. and Shapiro E. Self-rated health: a predictor of mortality among the elderly. Am. J. publ. Hlth 72, 800-808,

1982.

27. Ware J., Davies-Avary D. and Donald C. Conceptualization and measurement of health for adults in the health insurance study. In General Health Perceptions, Vol. V. The Rand Corporation, Santa Monica, CA, 1978. 28. Tissue 1. Another look at self-rated health among the elderly. J. Geronrol. 27, 91-94, 1972. M. Reaction to the Diagnosis of 29. Frank-Stromborg Cancer Questionnaire: development and psychometric characteristics. Nurs. Res. 36, 1989. 30. Walker S. N., Sechrist K. R. and Pender N. J. The health-promoting lifestyle profile: development and psychometric characteristics. Nurs. Res. 36, 76-80, 1987.

31. Norusis M. J. SPSS-X: Advanced Stalisrics Guide. SPSS, CA, 1985. 32. Tabachnick B. F. and Fidel1 L. S. Using Mulricariare Statistics. Harper & Row, New York. 1983. 33. Eva S. B. and Friedsam H. J. Multivariate analysis of health care services utilization among older Texans. J. Hlth Human Resources Admin. 3, 169-191,

1980.

MARILYNFRANK-STROMBORG er al.

1168

34. Heise D. Problems in path analysis. In Sociological Methodology (Edited by Borgotta E.). Josey Bass, San

53. Levenson H. Activism and powerful other: distinctions

Francisco, CA, 1969. 35. Lewis-Beck M. S. Stepwise regression: a caution. Polir.

J. Person. Assessm 38, 377-383, 1974. 54. Taylor S. E., Lichtman R. R. and

Methodol. 5, 213-240, 1978. 36. SPSS, Inc. SPSS-X User’s Guide, 2nd edn. McGraw-

Hill, New York, 1986.

37. Pedhazur E. J. Multiple Regression in Behavioral Research. 2nd edn. Holt. Reinhart & Winston, Chicago,

IL, 1982: D. and Love W. A. A general canonical correlation index. Psychol. Bull. 70, 160-163, 1968. 39. DeVita V. Cancer as a preventable disease. Maryland

38. Stewart

Med. J. 34, 41, 1985. 40. Greenwald P. and Sondik

E. (Eds) Cancer control objectives for the nation: 1985-2000. NC1 Monographs Number 2 (NIH Publication No. 86-2880). U.S. Government Printing Office, Washington, DC, 1986. 41. Disham R. K., Sallis J. F. and Orenstein D. R. The determinants of physical activity and exercise. Publ. Hlth Rep. 100, 158-171, 1985. 42. Duffy M. Determinants of health promotion in midlife women. Nurs. Res. 37. 358-361, 1988. 43. Salminen S. Perceived health and exercise: a cross-lagged oanelcorrelation. Percept. MoforShilfs60,637-638,1985. 44. Weitzel M. A test of health promotion model with blue collar workers. Nurs. Res. 38, 99-103. 1989. 45. Ardell D. B. High Level Wellness. Bantum, New York, 1984. 46. Brooks N. Opportunities for health promotion: including the chronically ill and disabled. Sot. Sci. Med. 19, 405-409, 1984. 47. Lafferty S. C. Develoment of a health conception scales. Res. Nurs. Hlth 9, 107-133,

within

intemal-lxtemal

control.

J. Mental attitudes to cancer: an additional prognostic factor. The Lancer 1(8431), 750, 1985. 59. Brown N. J., Muhlenkamp A. F., Fox L. M. and Osbom M. The relationship among health beliefs, health values, and health promotion activity. West. J. Nurs. Res. 5, 155-163, 1983. 60. Laffrey S. C. and Isenberg M. The relationship

61. 62.

63.

Nineteenth Annual Meeting of the Society for Perspective Medicine 7, 18-19, 1983.- _

64.

tion of patients who outlive predicted life expectancies. Psychother. Ther. Res. Pratt. 14, 416-422, 1976. 51. Achterbern J.. Lawlis G. F.. Simonton 0. and Simonton

of

13, 787, Oct. 1979. 58. Pettingale K., Morris T., Greer S. and Haybittle

48. Muhlenkamp A., Brown N. and Sands D. Determinants

50. Achterberg J., Mathews S. and Simonton C. A descrip-

concept

Wood J. V. Attributions, beliefs about control, and adjustment to breast cancer. J. Person. sot. Psvchol. 46. 489-502. 1984. 55. Marks G., Richardson J., Graham J. and Levine A. Role of health locus of control beliefs and exoectations of treatment efficacy in adjustment to cancer. J. Person. JOC.Psychol. 51,443-450, 1986. 56. Morris T., Blake S. and Buckley M. Development of a method for rating cognitive responses to a diagnosis of cancer. Sot. Sci. Med. 20, 795-802, 1985. 57. Greer S., Morris T. and Pettingale K. Psychological response to breast cancer: effect on outcome. The Lancer

1986.

of health promoting activities in nursing clinic clients. Nurs. Res. 34, 327-332, 1985. 49. Zindler-Wemet P. Health locus of control beliefs as predictors of preventive health behaviors (Summary).

the

65.

S. Psychol&gicaI factors and blood chemistries as disease outcome predictors for cancer patients. Multivar. Clin. Exp. Res. 3, 107-122, 1977. 52. Achterberg J. and Lawlis G. F. A canonical analysis

66.

of blood chemistry variables related to psychological measures of cancer patients. Multivar. Clin. Exp. Res. 4, l-10, 1979.

67.

of internal locus of control, value placed on health, perceived importance of exercise, and participation in physical activity during leisure. Inr. J. Nurs. Stud. 20, 187-196, 1983. Zindler-Wemet P. and Weiss S. J. Health locus of control and preventive health behavior. West. J. Nurs. Res. 9, 160-179, 1987. Walker S. N., Volkan K., Sechrist K. R. and Pender N. J. Health-promoting life styles of older adults: comparisons with middle-aged and young adults, correlates and uattems. Ado. Nurs. Sci. 11, 76-90, 1988. Prohaska T. R., Leventhal E. A., Leventhal H. and Keller M. L. Health nractices and illness cognition in young, middle aged and elderly adults. J. G;ronr. 40. 569-578, 1985. Bausell R. B. Health-seeking behavior among the elderly. Gerontologbr 26, 556-559, 1986. Pender N. J. Multivariate explanation and prediction of health-promoting lifestyles among participants in workplace health promotion programs. Nurs. Res. In press. Bigbee J. L. Hardiness: a new perspective in health promotion. Nurse Pro&. 10, 51, 54-56, 1985. Frank-Stromborg M. Health promotion behaviors in ambulatory cancer patients: facts or fiction? Oncol. Nurs. Forum 13, 37-43, 1986.