Diabetes mellitus (DM) is a significant health problem throughout the world. DM prevalence among adults worldwide was about 4% (195 million) in 1995; a number that is expected to rise to 5.4% (300 million) by 2025 (King, Aubert, & Herman, 1998). Prevalence and incidence increase with age (Burke et al., 1999). In Taiwan, DM is the fourth leading cause of death, with a DM death rate of 44.6 per one hundred thousand. One-tenth of people over 40 years old suffer from diabetes. Prevalence and incidence rates of 4.0% and 0.5˜1.0% have been reported (Chou, Li, & Tsai, 2001; Department of Health, Executive Yuan, ROC [Taiwan], 2008). It has been suggested that the negative consequences of late diabetes complications may impact an individual's health-related quality of life (QOL) (Goldney, Fisher, Philips, & Wilson, 2004; Woodcock, Julious, Kinmonth, & Campbell, 2001), which in turn places an additional financial burden on society (Chen, Yen, & Tung, 2001; Lin, Chou, Lai, Tsai, & Tai, 2001). DM patent daily activities such as diet, exercise, and medications contribute to the control of disease; loss of control over DM may eventually result in complications in terms of retinopathy, nephropathy, neuropathy, cardiovascular disease (Bloomgarden, 2002; Tsai, 2000) and/or mental illness (Lyu & Lin, 2000).
Moreover, type II DM is about four times as prevalent as type I diabetes. Almost one quarter of type I and type II DM patients (combined) have been reported to suffer from mental health problems (Eaton, 2002; Musselman, Betan, Larsen, & Phillips, 2003). Meta-analysis of the literature indicate a significant relationship between metabolic control, DM-related complications, and mental health problems in DM patients (deGroot, Anderson, Freedland, Clouse, & Lustman, 2001; Lustman et al., 2000). Psychosocial factors including negative life events, lack of social support, or emotional problems may influence DM patient quality of life (Lia, 2002; Chung, 2002) and may consequently result in depression, isolation, cognitivebehavioral problems, curtailment of daily living activities or even suicide (Lyu & Lin, 2000).
The high prevalence of diabetes challenges DM patients as well as healthcare providers. Better understanding quality of life as perceived by DM patients in general may give nurses better insight into the health status perceptions of their DM patients. Such may then facilitate healthcare providers to achieve better patient metabolic control. Several studies have examined the impact of DM upon quality of life, Woodcock et al. (2001) found, using an SF-36 survey, that older DM patients have worse physical health than younger patients (Ware, 1990). Hirsh, Bartholomae, and Volmer (2000) indicated female DM patients had worse QOL than males and that those with a large number of DM complications had worse QOL than those without. In Taiwan, Chung (2002) indicated that self-care efficacy for DM patients may be affected by psychosocial factors such as daily life stress, social support, emotional problems, and may also impact on their effectiveness at metabolic control. They concluded that ability to managing diabetes and achieving acceptable metabolic control may be associated with an individual's coping strategies and thus may impact upon personal quality of life. Additionally, Huang and Hung (2007)'s survey of 131 middle-aged type II diabetic patients reported average scores of 53.93 (SD = 8.47) for quality of life measured by the World Health Organization Quality of Life (Short Version) [WHOQOL-BREF]. Predictors included diabetic self-care behavior (β = .13, p = .00), economic status (β = 5.49, p = .00) and frequency of hospitalization (β = −3.95, p = .03). Demographic factors including age, gender, education, religion, marital status, duration of DM, number of complications and HbA1C were not significantly related to quality of life.
Learned resourcefulness, a cognitive-behavior change skill, may help individuals to use internal processes including cognition, emotions, and perception to perform daily activities (Rosenbaum, 1980). Resourcefulness is defined as the ability to self-regulate psycho-physiological stress responses and involves an individual's ability to engage in positive thinking to deal with negative thoughts or behavior. People may be taught or learn from experience, study, or instruction to master resourcefulness. The Rosenbaum's Self-Control Schedule is recommended as a useful measure to assess resourcefulness skills, which include problem-solving strategies, self-instructions, postponement of needs satisfaction and belief in coping effectiveness (Zauszniewski, 1995). Several studies of learned resourcefulness have been conducted to understand various phenomena. Lai (2005) found that learned resourcefulness had a direct, rather than moderating or mediating, effect on adaptive function in depressive adults. Vealadee (2006) revealed that in a sample of older adults, depressive cognitions were negatively correlated with learned resourcefulness and personal care. Also, learned resourcefulness and personal care were slightly positively correlated. Furthermore, in a quasi-experimental study that examined the effect of learned resourcefulness training on the health of elders, researchers found that elders receiving resourcefulness training may enhance their perception of health and functions over time (Zauseniewski, Eggenschwiler, Preechawong, Roberts, & Mrrris, 2006). Such findings implied that nursing interventions that teach resourcefulness skills may enhance patient adaptation process to life changes.
Few studies have examined learned resourcefulness in DM patients. White, Tata, and Burns (1996) found that diabetic patients with high resourcefulness levels reported fewer hypoglycemic episodes. Learned resourcefulness was a partial mediating factor between depressive symptoms and health practices of individuals with diabetes (Zauszniewski & Chung, 2001). Individuals with diabetes who had greater learned resourcefulness and better glycemic control also had fewer depressive symptoms. Learned resourcefulness was a mediator between glycemic control and depressive symptoms (Huang et al., 2007). However, to date, there remains limited knowledge on the relationship between learned resourcefulness and quality of life in DM patients. Therefore, the adequacy of diabetic patient resourcefulness, and how such relates to quality of life were subjects examined in this study.
Specific aims of this study included:
- Examine relationships between demographic factors, diabetic factors, learned resourcefulness, and quality of life in diabetic patients.
- Determine whether mediating or moderating effects of learned resourcefulness occur in the relationship between metabolic control and DM patient quality of life.
Design and Population
This study was designed to test relationships among demographic characteristics, disease factors (duration, complications, and HbA1C), learned resourcefulness, and quality of life in type II diabetic patients. A sample of 105 was required based on the sample size calculation recommended by Cohen (1988) for correlation and regression analysis to achieve a power of .80 with a medium effect size of .15 and an alpha level of .05. A sample of 131 subjects from an adult population with diabetes (aged 18-65) was recruited. To be eligible for the study, subjects were required to meet the following criteria (a) aged 18 to 65 years old and diagnosed with diabetes mellitus; (b) diagnosed by physicians as type II DM; (c) free of other co-morbidity medical conditions; (d) ability to communicate in Chinese or Taiwanese. Subjects were approached in three outpatient primary care settings at three teaching hospitals in southern Taiwan.
A demographic information sheet and two measurements, including the Self-Control Schedule (SCS; Rosenbaum, 1990) and the WHOQOL-BREF, both had been used and have demonstrated acceptable reliability in Taiwan.
The demographic information sheet was used to measure specific demographic variables, including age, gender, level of completed education, monthly income (in NT dollars), duration of diabetes, number of DM-related complications, and metabolic control by level of glycemic control (HbA1C).
Learned resourcefulness was measured using Rosenbaum's Self-Control Schedule (SCS; Rosenbaum, 1990). The SCS consists of 36 items ranked on a six-point scale that indicate the extent to which individuals evaluate the item as characteristic of his/her personal condition (−3 = very uncharacteristic to +3 very characteristic). Eleven items (4, 6, 8, 9, 14, 16, 18, 19, 21, 29, 35) were reversed. Possible scores ranged from −108 to +108. The score expected in the general population is +25 with a standard deviation of 20. Reliability and validity have been well established and reported internal consistency estimates were from .78 to .95 (Rosenbaum, 1990; Zauszniewski & Chung, 2001). The SCS was previously translated in Chinese to measure self-control in adolescents in Taiwan (Huang, Sousa, Tu, & Hwang, 2005). It achieved a reliability of .79 in a study of 404 adolescent girls in southern Taiwan. In this study, Cronbach's alpha value was .78.
3.Quality of life
Quality of life was measured using the WHOQOLBREF Chinese version, which includes four subscales with 26 items and an additional 2 items measuring comprehensive quality of life and general health perceptions. The WHOQOL-BREF is divided into four sections, including physical health (7 items measuring pain, fatigue, activity, etc.), psychological state (6 items measuring body image, personal perceptions, spiritual/religious/personal beliefs, etc.), social relationships (4 items measuring social support, sexual life, etc.), and environmental features (9 items measuring physical environment, house environment, finances, etc.). Both reliability and validity of the WHOQOLBREF were reported as excellent (The WHOQOL-Taiwan Group, 2000; Yao, 2002). Cronbach's alpha values were .93 for menopausal women (Chen et al., 2005) and .93 for type II DM patients (Huang & Hung, 2007). In this study, participants were asked to rate on a 5-point scale how satisfied they were with their health during the previous two week period (1 = very bad or extremely unsatisfied; 2 = bad or not satisfied; 3 = moderate good or moderate satisfied; 4 = good or satisfied; 5 = very good or absolutely satisfied). Three items (3, 4, 26) were recoded for this study. Total scores were calculated by adding up all ratings, with higher scores reflecting better quality of life. For this study, the Cronbach's alpha for comprehensive quality of life was .93, and .75, .84, .72, and .80 for physical, mental, social and environmental quality of life.
The study was reviewed and approved by the Meiho Institute of Technology Institutional Review Board. Directors of the three sample hospitals were contacted and given an explanation of the purpose of the study and a description of data collection procedures. After receiving their preliminary approval, researchers approached potential participants in a private area in outpatient clinics to introduce the purpose of the study, data collection procedures, confidentiality assurance measures and freedom to join or withdraw at any time. Participants who met the inclusion criteria and agreed to participate in the study signed a consent form. One hundred and fifty-five diabetic patients were approached. Twenty-two did not complete the entire questionnaire and two type-I DM patients were also excluded from data analysis, 131 participants completed valid surveys, which gave a 85% response rate.
Data included descriptive statistical analysis, preliminary data analysis, and research questions testing using the Statistical Package for the Social Sciences (SPSS) version 13.0. Pearson product-moment correlation, simple regression, and hierarchical multiple regression were used to analyze outcome predictors. Summary statistics for each variable were obtained to examine the shape of the distribution, central tendency, and score dispersion for descriptive statistical analysis. The centering technique was also performed prior to creating the interaction term in order to test for the presence of moderating effects of learned resourcefulness between metabolic control and quality of life had occurred (Aiken & West, 1991).
The convenience sample included 131 type II diabetic patients aged 24-65 years (see Table 1). Seventy two of the patients were male and 59 were female. About 40 (30.5%) of the sample reported holding an elementary or lower level of education. The greatest percentage of subjects was in the lowest socio-economic band, with monthly income below NT 20,000. The average duration since diagnosis of type II DM for these subjects was 6.33 years. Fifty-five percent of subjects had at least one diabetes-related complication. Average Glycosylated hemoglobin (HbA1C) was 8.04.
Descriptive Analyses of Study Variables
The average score of learned resourcefulness was 35.19 (SD = 22.15), with highest and lowest scores −33 and 99, respectively. Seventy percent of subjects earned a score of 25 or higher.
Quality of life
Descriptive analysis of scores on quality of life is presented in Table 2. Respondent scores on total quality of life ranged from 36 to 74.9, with an average score of 56.4 (SD = 7.70). Percentages for comprehensive quality of life of DM patients and individual health perception satisfaction are shown in Table 3. For overall quality of life, the majority of DM patients (52.7%) considered they had moderate satisfaction with quality of life. Overall individual health perceptions demonstrated that a significant percentage of DM patients (38.9%) were not fully satisfied with their health and no respondents were absolutely satisfied their health. According to the scores of each item in quality of life, highest scores were recorded on item 3 “Do you feel that body pain interferes with normal activities?” One hundred and one subjects (77%) reported “none to a little” interference with normal activities, twelve (9.27%) reported “moderate to very much” interference with normal activities. On the other hand, lowest scores were recorded on item 5 “Do you enjoy life?” Twenty-nine (22%) subjects considered “much to exceptional” enjoyment of life, 39 (30%) considered “no to little” enjoyment of life.
Correlation of study variables
As shown in Table 4, age of DM patients was not associated with learned resourcefulness or quality of life. Education had a positive relationship to physical, mental, and environmental quality of life. Income had a positive relationship to mental and environmental quality of life, which indicated that better educated DM patients had better life quality. Patients with a longer history of DM reported poorer physical health. The level of glycosylated haemoglobin (HbA1C) for subjects was negatively related to learned resourcefulness and four sections of quality of life. Learned resourcefulness was strongly positive related to all four sections of quality of life. In addition, as shown in Table 5, males reported better quality of life than females'.
Effects of learned resourcefulness on quality of life
Multiple regressions were used to examine the direct effects of demographic factors (age, gender, education, and monthly income) and disease factors (duration of diabetes, number of complications, and HbA1C) on quality of life. As shown in Table 6, model I explained 15.4% of variance in DM patient quality of life. Among variables, gender (β = .301, p = .002) and HbA1C (β = −.245, p = .004) were significant predictors of quality of life in DM patients. Being male and having a lower HbA1C were significantly associated with having a relatively better quality of life.
A hierarchical regression was performed to examine the effect of learned resourcefulness on quality of life after controlling for the effect of demographic and disease variables. As shown in Table 6, this second model explained 35.2% of variance in quality of life. Learned resourcefulness (β = .452, p = .000) was a strong predictor of quality of life and gender (β = .262, p = .002) and HbA1C (β = −.165, p = .030) continued to be significant predictors of quality of life in DM patients. However, the reduced effect of HbA1C-“β” (from |−.245| to |−.165|) indicated that learned resourcefulness had some level of influence, especially for male diabetic patients. In other words, when male diabetic patients with lower HbA1C had more resourcefulness they were able to enjoy a relatively better quality of life.
(1) Mediating effect of learned resourcefulness
To test whether learned resourcefulness mediates the relationship between metabolic control (HbA1C) and quality of life, “learned resourcefulness” was added to the equation to determine if mediating variables can add significantly to explained variances in quality of life (Bennett, 2000).
To test the mediating effect for learned resourcefulness, three equations used were: (1). t = b1x, (2). y = b2x, (3). y = b3x + b4t, where “t” was the mediating variable (learned resourcefulness), x was the independent variable (metabolic control-HbA1C), and y was the dependent variable (quality of life). If “learned resourcefulness” was a mediator, all three equations should be significant and b3 must be less than b2 (Gogineni, Alsup, & Gillespie, 1995). If a complete mediator effect existed, b3 must be nonsignificant.
Figure 1 shows that learned resourcefulness mediated significantly the relationship between metabolic control-HbA1C and quality of life. Metabolic control (HbA1C), significantly affected learned resourcefulness (β = −.200, p = .022), metabolic control significantly affected quality of life (β = −.280, p = .001) and learned resourcefulness strongly affected quality of life (β = .469, p = .000). Additionally, the significance of the relationship between metabolic control and quality of life was reduced when learned resourcefulness was entered into the regression (β = −.186, p = .016).
(2) Moderating effects of learned resourcefulness
Hierarchical multiple regression analyses were applied to test whether learned resourcefulness moderated the relationship between metabolic control (HbA1C) and quality of life. The component term (learned resourcefulness *metabolic control) could result in a high correlation (e.g., greater than 0.8) between first order terms and the interaction term when entered into the regression. Therefore, prior to performing multiple regression, the centering procedure was used to reduce the high correlation of the component term (Aiken & West, 1991). No moderation occurred between metabolic control and quality of life in this study.
This study demonstrated that DM patient demographic factors, including duration of disease, income, and gender, were significantly related to quality of life. Patients with a relatively longer DM duration had worse physical health in quality of life, which may be due to their inadequate knowledge of metabolic control or the possibility of complications. A study by White et al. (1996) study suggested that longer DM durations increased patients' metabolic control. However, Coffey et al. (2002), Redekop et al. (2002), and Huang and Hung (2007) indicated a contrary result, an individual's level of income had a significant impact on mental and environmental quality of life, which is consistent with the findings of studies by Nau and Kumar (2002), Wang (2004), and Huang and Hung (2007). Male diabetic patients had significantly better quality of life than females. This result was consistent with Hirsh et al. (2000) and Woodcock et al. (2001), but was inconsistent with Huang and Hung (2007). Such controversial results require further study.
Age and education were not significantly correlated with quality of life in this study, which is consistent with Huang and Hung (2007). In terms of age, our insignificant finding was not consistent with previous studies (Woodcock et al., 2001). This may be due to subject age and adequate education, which lowered the impact on quality of life.
In terms of disease factors, average metabolic control (HbA1C) was high, which indicated inadequate DM patients' metabolic control. Moreover, level of glycosylated haemoglobin (HbA1C) was negatively related to four sections of quality of life (refer to Table 4). Poor metabolic control was found to impact upon DM patient quality of life, which is consistent with previous studies (Lo, 1997; Mata, Roset, Badia, Antonanzas, & Ragel, 2003; Nau & Kumar, 2002; Redekop et al., 2002). The difference of our result to that of Huang and Hung (2007) may be due to the following: our sample was younger (50.40 ± 8.72 vs. 57.42 ± 10.23); had a shorter DM duration (6.33 ± 5.13 vs. 8.91 ± 6.75); reported a higher quality of life (56.4 ± 7.70 vs. 53.93 ± 8.47); and had a lower HbA1C average value (8.04% vs. 8.21%).
More than half of our participants had above average quality of life scores (M = 56.4; SD = 7.7). Nurses can play an important role in facilitating metabolic control in diabetic patients and thus positively influence patient quality of life. Moreover, healthcare professionals may work more actively in intervention to increase resourcefulness and help DM patients to achieve better quality of life. This can be especially effective in females with higher HbA1C levels.
This study was the first to examine learned resourcefulness in diabetic research in Taiwan. The partial mediating effect of learned resourcefulness between metabolic control and quality of life was explored. Findings were consistent with those of previous researcher in that diabetic patients who were relatively more resourceful reported better metabolic control (White et al., 1996). Learned resourcefulness is a cognitive-behavior change skill, which may help individuals to use internal processes including cognition, emotions, and perceptions to perform their daily activities. It involves an individual's ability to engage in positive thinking to deal effectively with negative thoughts or behaviors. Findings can provide diabetic educators valuable references for use in cognitive-behavior change intervention work aimed at helping DM patients achieve better quality of life.
There were a number of methodological and sampling limitations in this study. Firstly, the cross-sectional design made it difficult to conclude that learned resourcefulness and quality of life had a causal relationship. Future studies using a prospective design are recommended. Secondly, the convenience sample may introduce bias. As this was the first such study in Taiwan, we employed convenience sampling with the anticipation that results would help identify behavioral cognitive therapies that can be employed in future intervention studies. However, the generalizability of study findings is, therefore, limited. To overcome this problem, future researchers may expand recruitment to different locations in order to better represent a cross-section of the Taiwan population. Thirdly, the sample was voluntary and, as such, may be less representative of the population at large. Such would negatively effect external validity (Cook & Campbell, 1979). Finally, self-reporting the duration of diabetes represents a limitation. Such may be overcome in the future by double checking self-reported numbers against medical records.
Findings of this study, the first of its kind in Taiwan, are consistent with previous researcher findings, which showed diabetic patience with relatively high levels of resourcefulness reporting fewer hypoglycemic episodes (White et al., 1996). Globally, diabetic patients have a relatively high prevalence of DM related diseasecomplications and other co-morbidity health problems. Additionally, almost half of the participants in this study reported a below average quality of life. Healthcare providers need to work on this point to build effective education for diabetic patients and promote better health. Moreover, DM patients who had both higher resourcefulness and adequate metabolic control enjoyed a better quality of life. The findings in this study support the need for further nurse education and the establishment of diabetic nurse specialists in Taiwan. Nurses may develop an intervention approach that combines cognitive-behavior change skills and metabolic control management to help DM patients achieve better life quality.
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