I have a research plan and 5 references, and you can add one or two references. Academic writing is general. - Management
I want you to write a paper on a topic ( What impact does kidney disease have on the patient, his / her family, and the healthcare providers?) 1500 words. I have a research plan and 5 references, and you can add one or two references. Academic writing is general. Attached references and research plan. I don't need generic medical terms. One or two references can be added. Title What impact does kidney disease have on the patient, his/her family, and the healthcare providers ? Introduction · a definition of 'kidney disease' (with a source). What kinds of healthcare providers are involved? Is it only hospitals? · to explain why this question is important these days.  Thesis statement We will go through the effect of health care providers and a good family relationship on the psychological state of the kidney patient and coexistence with the disease naturally. Main Body 1. Paragraph 1 impact does kidney disease have on the patient. 1.1- The psychological impact on the kidney patient. 1.2- Discovering kidney disease and entering the stage of depression. 1.3- The effect of kidney disease on the patient's general life. 1.4- Provide emotional support from the family and health care providers to help the patient accept the disease. 1.5- The positive effect of the psychological on acceptance of dialysis and coexistence with kidney disease. 2. Paragraph 2 impact does kidney disease have on his / her family. 2.1- The psychological impact of a kidney patient on the family. 2.2- The social and financial impact of a kidney patient on the family. 2.3- The positive impact when providing emotional support to the family of a kidney patient. 3. Paragraph 3 impact does kidney disease have on the healthcare providers. 3.1- Provide psychological and emotional support to the patient and his family. 3.2- 3.3- Conclusion In kidney disease, a person may develop a state of panic when learning of his injury. The family's intervention and their emotional influence greatly helps in accepting treatment and coping with the disease Wang and Yang Int J Ment Health Syst (2018) 12:33 https://doi.org/10.1186/s13033-018-0212-4 International Journal of Mental Health Systems Does chronic disease influence susceptibility to the effects of air pollution on depressive symptoms in China? Qing Wang1† and Zhiming Yang2*† Background The Chinese government encouraged the growth of industries and urbanization since 1978. However, the associated rapid economic development has caused environmental issues, and China is now one of the most polluted countries in the world [1–3]. For example, the annual average Total Suspended Particulates (TSP) con- centration regularly exceeds 400 μg/m 3 in China [4], which is significantly higher than that in large European cities (e.g. Oslo, 15 μg/m 3 ; Marseille, 18 μg/m 3 ) [5] and World Health Organization (WHO) primary (80 μg/m 3 ) and secondary (60 μg/m 3 ) standards [6, 7]. Air pollution is believed to be associated with depres- sive symptoms [8]. Potential biological mechanisms *Correspondence: [email protected] †Qing Wang and Zhiming Yang are Joint first authors 2 Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China Full list of author information is available at the end of the article relating to depressive symptoms include reactivity to exogenous stressors; alterations of neurohumoral, immune, and autonomic regulation; dysfunction of neuro transmitter systems; and oxidative stress [9]. Cell © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. mailto:[email protected] http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/publicdomain/zero/1.0/ http://creativecommons.org/publicdomain/zero/1.0/ Wang and Yang Int J Ment Health Syst (2018) 12:33 Page 2 of 12 cultures and experimental animals studies have shown neuropathological effects from air pollution exposure [10–12], and previous empirical studies have observed that air pollution increases the prevalence of depressive symptoms in Korea, Japan, and the Netherlands [8, 13– 15]. Furthermore, an increasing number of emergency department visits for depression in Canada and Korea have been documented [16, 17]. Depression is a serious problem in China [18, 19 ]: in 2013, 36 million years of healthy life were lost to mental illness in China, and estimates suggest that by 2025, 39.6 million years of healthy life will be lost (10% increase) [20]. Although little is known about the asso- ciation between air pollution and depression, several Chinese studies have found a relationship between expo- sure to air pollution and happiness [21, 22], depressive symptoms [23], cognitive functions [24, 25] and hospi- tal admissions for mental disorders [26], when results were adjusted for demographics and socioeconomic status. It is considered that a further decline in air qual- ity could cause an increased risk to health and an asso- ciated increase in depressive symptoms. Therefore, this study uses nationally representative data to estimate the association between air pollution and depression meas- ured by the Center for Epidemiologic Studies Depression (CES-D) scale. Air pollution regulations based on observed health effects in the general population may be insufficient to protect exceptionally vulnerable subgroups. Incon- sistent study results have been found within past study cohorts. For example, no significant association between air pollution exposure and depressive symp- toms was found in a Boston-area study [27], although other American studies reported that exposure to air pollution was related to anxiety symptoms [28], which often have a comorbidity with depression [29]. One American study found that stroke victims were more susceptible to the effects of air pollution with respect to cognitive functions [30]. Thus, it is believed that chronic disease (e.g. hypertension), which is often regarded as a marker of inflammation and vascular dysfunction, may mediate an association between air pollution and depressive symptoms [31, 32]. Compared to people in good physical health, the well-known adverse mental health effects of air pollution may mean that respondents with chronic disease are likely to believe that their physical health is being damaged [33– 35]. However, the role of an individual’s physical health status in the association between air pollution and depression symptoms has not yet been addressed in China. Therefore, this study aims to assess which individuals have a greater vulnerability to the adverse effects of air pollution [21]. Data and methods Data Individual sample data and a group of city-level vari- ables were obtained to evaluate the relationship between air pollution, chronic disease, and depressive symptoms. Individual data were collected from CHARLS 2011 and 2013, which were national representative surveys con- ducted with middle-aged and elderly Chinese residents (aged 45 years and above) using face-to-face computer- assisted personal interviews. The CHARLS question- naire included the following modules: demographics, family structure/transfer, health status and functioning, biomarkers, health care and insurance, work, retirement and pension, income and consumption, assets (individual and household), and community-level information. These surveys were approved by the ethics committee of the Institutional Review Board of Peking University. Using multi-stage stratified probability-proportionate- to-size sampling, the sample in CHARLS represented approximately 10,000 households in 150 counties/dis- tricts (a total of 450 villages/resident communities). The baseline survey was conducted between June 2011 and March 2012 with a response rate of 80.5% and a total sample of 17,545 respondents. A total of 15,020 (86%) respondents participated in the follow-up survey in 2013, but 2525 (14%) respondents had died or declined partici- pation in the study. In this study, CHARLS 2011 and 2013 panel data were constructed to estimate the relation- ship between air pollution and depressive symptoms for 15,020 respondents (15,020 × 2 = 30,040 samples). Of the respondents, 47% were male with a mean age of 60 years. Ages and gender distribution were very similar to those in the 6th national census conducted in 2010 [36]. City-level variables included monthly temperature, monthly relative humidity, and annual air pollution. Daily meteorological data from 839 stations in 2011 and 2013 were collected from the China Meteorological Science Data Sharing Service Network—China Ground Climate Daily Data. The station-level data were aggregated at a city level by matching stations to the closest city based on the exact longitude and latitude of the weather station and the longitude and latitude of the county centroid. The average monthly temperature and relative humidity of CHARLS 125 sample cities were then calculated from daily data. Based on survey city and month, the results from 15,020 respondents in the two CHARLS waves were combined with the meteorological data from 125 cities. The annual sulfur dioxide (SO2) and TSP emissions from 273 cities in 2011 and 2013 were obtained from the 2012 and 2014 China City Statistical Yearbook. Based on survey year and city, 12,046 respondents of the 15,020 respondents in the two CHARLS waves were matched to the air pollution data from 101 cities. After excluding 412 Wang and Yang Int J Ment Health Syst (2018) 12:33 Page 3 of 12 respondents that provided missing values from 12,046 respondents, 11,634 respondents were included, and the final sample size was 23,268 (11,634 × 2) samples from 101 cities. Figure 1 presents a flow chart of the study process. Variables Depressive symptoms A modified seven-item version of the CES-D scale was constructed to measure depressive symptoms [37]. Respondents reported the frequency of experiencing the following seven depressive symptoms during the past week: (1) “was bothered by things,” (2) “had trouble keep- ing mind on what was doing,” (3) “felt depressed,” (4) “felt everything he/she did was an effort,” (5) “felt fearful,” (6) “sleep was restless,” and (7) “felt lonely.” Each answer was encoded from 1 to 4: 1 = rarely or none, 2 = some or a lit- tle, 3 = occasionally or a moderate amount, and 4 = most or all of the time, with total scores ranging from 7 to 28. A summed score of the seven items was calculated, with lower scores indicating fewer depressive symptoms. This shortened seven-item CES-D scale is a widely used indicator for depressive symptoms [38, 39]. Its validity, reliability, and cultural equivalence have been proven in China [40]. In our data set, CES-D was also demon- strated to have high internal consistency (Cronbach’s alpha = 0.82) and to construct validity (Kaiser–Meyer– Olkin = 0.87) according to the standards of Meulen et al. [41], Kara [42], and Aly [43], which suggest that if the Cronbach’s alpha and Kaiser–Meyer–Olkin test value exceeds the recommended level of 0.70 then data is con- sidered to be highly reliable [41–43]. Air pollution Following previous studies, SO2 and TSP emission inten- sity, SO2 and TSP emissions per capita, and SO2 and TSP emissions per unit area were calculated to measure air pol- lution [44–47]. Pollution intensity refers to the indicator of pollution emissions per industrial gross domestic product (GDP) (industrial economic output). Log transformation of air pollution data was applied to minimize skewness [45]. Chronic disease A categorical variable for a doctor to use in diagnosing chronic disease was created based on the question, “Have you ever been diagnosed with hypertension, dyslipidemia, diabetes or high blood sugar, cardiovascular disease (heart attack, coronary heart disease, angina, congestive heart failure, stroke or other heart problems), cancer or malignant tumor, liver disease, chronic lung disease, kid- ney disease, stomach or other digestive disease, arthritis or rheumatism and asthma by a doctor?” The variable equaled 1 or 0 for respective replied of “yes” or “no”. Estimation Strategy Descriptive analysis was first conducted to describe sam- ple characteristics of the total sample and for chronic dis- ease status. Frequencies with percentages were presented for categorical variables (gender, marital status, educa- tion, employment status, insurance status) and means with standard deviations for continuous variables (CES- D, air pollution indicators, climate indices, income, and age). P-values were calculated using the Chi square test for categorical variables, and one-way Analysis of Vari- ance (ANOVA) for continuous variables between groups (with or without chronic disease). A random effects model was then applied to link air pol- lution intensity with depressive symptoms. Omitted varia- ble bias was controlled using the random effects model. The individual random effects model is presented as follows, Depressiveijt = a0 + Airjta1 + Xijta2 + ui + vt + eijt , (1) where a0, a1, a2 are the parameters to be estimated; ui and vt are the individual effects and year fixed effects, respec- tively; eijt is the idiosyncratic error term; and Depres- siveijt is the depressive symptoms of person i in city j in year t; Airjt is a variable indicating the log of air pollution intensity, Xijt represents an individual’s demographic, socioeconomic status, health behavior, and city-level cli- mate variables in the living area. To be more specific, the demographic variables included whether male or female, marital status [reference group: married with spouse present (common-law marriage was considered mar- ried)], and age; socioeconomic status was measured by Wang and Yang Int J Ment Health Syst (2018) 12:33 Page 4 of 12 ijt ijt ijt ijt ijt ijt household income per capita, education level, employ- ment status, insurance status, and rural/urban residence; educational attainment was defined at four levels (infor- mal education, informal education but can read and write, primary school, and junior high school and above), and a categorical variable for educational attainment with four values was constructed, with informal educa- The total CES-D scale used to evaluate depressive symptoms of middle-aged and elderly individuals ranged between 7 and 28, which represents a limited dependent variable. Therefore, least square regression was directly applied to render inconsistent estimates [50, 51]. The Tobit model was used for robust analysis in this respect, and marginal effects were reported, tion serving as the reference group; household income was divided by the number of household members and household income per capita was subsequently ranked and divided into five pentiles, with the lowest group Depressive ∗ = c0 + Airjtc1 + Chronicijtc2 + Airjt × Chronicijtc3 + Xijtc4 + ui + vt + eijt , (3) serving as a reference; employment status was catego- rized into three groups: unemployed (including retired), Depressiveijt = 7 if Depressive ∗ ≤ 7, (4) self-employed, and wage earner; for health insurance coverage, respondents were recoded into a dummy vari- able with three values [the urban employee-based basic Depressiveijt = Depressive ∗ if 7 < Depressive ∗ < 28, (5) medical insurance scheme (UEBMI), the rural new coop- erative medical scheme (NCMS), and the urban resident- Depressiveijt = 28 if Depressive ∗ ≥ 28, (6) based basic medical insurance scheme (URBMI)], with where c0, c1, c2, c3, c4 are the parameters to be estimated; uninsured respondents as the reference group; current Depressive∗ is a latent variable and Depressiveijt is its smoker and drinker were included as indicators of the respondents’ current health behaviors; and city-level average monthly temperature, relative humidity, and city dummy variables were also controlled. The interaction between chronic disease and air pollu- tion intensity was then controlled in multivariate regres- sion to establish whether chronic disease influences an individual’s susceptibility to depressive symptoms with respect to air pollution, Depressiveijt = b0 + Airjtb1 + Chronicijtb2 + Airjt × Chronicijtb3 + Xijtb4 + ui + vt + eijt , (2) where b0, b1, b2, b3, b4 are the parameters to be esti- mated; Chronicijt is a dummy variable indicating whether a respondent has a chronic disease; and Airjt× Chronicijt is the interaction between chronic disease and air pol- lution intensity after decentralization. Decentralization of air pollution indicators was calculated by subtracting the mean of city-level air pollution intensity from air pol- lution intensity in each city and then dividing it by the standard deviation of city-level air pollution intensity using the center-command in Stata 14 [48]. Analyses were then stratified according to chronic disease characteristics. Depressive symptoms may also affect an individual’s physical health status and lead to endogenous issues [49]. Stratification was conducted to eliminate any possible endogenous issues by excluding respondents with chronic diseases (hypertension, dys- lipidemia, diabetes or high blood sugar, cardiovascular diseases, arthritis and asthma) because such diseases may stem from depressive symptoms. Under these conditions no other possible methods were available for now. Wang and Yang Int J Ment Health Syst (2018) 12:33 Page 5 of 12 observable variable. A robust standard error was derived using bootstrapping methods and conducting 500 boot- strap replications. In addition, by using the Tobit model with stratified samples, the effects of SO2 and TSP emission per capita/ per unit area on depression were regressed (and are pre- sented in Appendix: Table 4). The results were consistent with those using air pollution emission intensity. Stata version 14 was used for all analyses [48]. Results Participant characteristics and average air pollutant intensity across chronic disease are shown in Table 1. On average, SO2 and TSP emissions accounted for 82.950 (SD = 78.355) and 45.571 (SD = 49.025) tons per 100 million Chinese yuan of industrial GDP, respec- tively. SO2 emissions per unit area and per capita were 6.812 (SD = 8.307) tons/km2 and 135.137 (SD = 120.211) tons/10,000 people; and TSP emissions per unit area and per capita were 3.079 (SD = 3.495) tons/km2 and 70.938 (SD = 81.064) tons/10,000 people; and average tem- perature and humidity were 26.599 °C (SD = 3.935) and 73.253% (SD = 7.603), respectively. The mean age of respondents was 60 (SD = 9.989) years; 48% of respondents (11,108/23,268) were male; 88% (20,414/23,268) were married or cohabit- ing; 39% (9016/23,268) lived in an urban area; 44% (10,191/23,268) of respondents had no formal edu- cation; 33% (7734/23,268) were unemployed; 44% (10,162/23,268) were self-employed; and the major- ity had health insurance [94% (21,813/23,268)]. A total of 33% (7713/23,268) reported smoking and 33% (7756/23,268) reported drinking alcohol. The Wang and Yang Int J Ment Health Syst (2018) 12:33 Page 6 of 12 a Frequencies with percentages were presented for categorical variables. P-values were calculated by Chi square test between groups having chronic disease or not b Means with standard deviations were presented for continuous variables, and P-values were calculated one-way ANOVA between groups having chronic disease or not respondents earned an average of 8175 (SD = 14,912) Chinese yuan per year per capita. The average depres- sive symptoms score was 11.623 (SD = 4.664). Com- pared to participants with chronic disease, those without chronic disease were more likely to report lower depressive symptoms [12.176 (SD = 4.858) versus 10.538 (SD = 4.043)] but not more likely to be exposed to air pollution. Models 1 and 3 from Table 2 show the correlation between air pollution and depressive symptoms in China after adjusting for multiple covariates. Increasing lev- els of air pollution were found to be significantly asso- ciated with higher depressive symptoms: an increase in SO2 and TSP emission intensities of 1% was associated with increasing depressive symptoms scores by 1.266 (SE = 0.107, P < 0.001, 95% CI 1.057–1.475) and 1.318 Table 1 Statistical description Variable All sample (N = 23,268) Group with chronic disease (N = 15,412) Group without chronic disease (N = 7856) Group with chronic disease VS Group without chronic disease Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. P-valuea Air pollution emission intensity (tons per 100 million Chinese yuan) SO2 82.950 78.355 82.602 74.980 83.632 84.587 < 0.001 TSP 45.571 49.025 46.510 50.816 43.729 45.253 < 0.001 Air pollution emission per unit area (tons/km2) SO2 6.812 8.307 6.667 8.728 7.097 7.403 < 0.001 TSP 3.079 3.495 2.998 3.576 3.236 3.326 < 0.001 Air pollution emission per capita (tons/10,000 people) SO2 135.137 120.211 132.127 118.256 141.042 123.753 < 0.001 TSP 70.938 81.064 70.173 80.964 72.440 81.243 < 0.001 Climatic indexes Average monthly temperature (0.1 °C) 265.990 39.353 266.038 39.678 265.894 38.710 < 0.001 Average monthly relative humidity (%) 73.253 7.603 73.077 7.634 73.599 7.529 < 0.001 Depressive symptoms 11.623 4.664 12.176 4.858 10.538 4.043 < 0.001 Age 60.101 9.989 61.101 9.834 58.139 10.000 < 0.001 Income (Chinese yuan/year) 8175 14,912 7970 13,343 8576 17,583 0.011 n % n % n % P-valueb Male 11,108 47.739 7165 46.490 3943 50.191 0.010 Unmarried 2854 12.266 1991 12.919 863 10.985 0.022 Living in urban area 9016 38.748 5947 38.587 3069 39.066 0.730 Education < 0.001 No education 5973 25.670 4145 26.895 1828 23.269 No education but can read/write 4218 18.128 2946 19.115 1272 16.191 Primary school 5181 22.267 3498 22.696 1683 21.423 Junior high school and above 7896 33.935 4823 31.294 3073 39.117 Employment status < 0.001 Unemployed 7734 33.239 5623 36.485 2111 26.871 Self-employed 10,162 43.674 6710 43.537 3452 43.941 Wage earner 5372 23.087 3079 19.978 2293 29.188 Insurance 0.037 Uninsured 1455 6.253 854 5.541 601 7.650 NCMS and URBMI 18,635 80.089 12,389 80.385 6246 79.506 UEBMI 3178 13.658 2169 14.074 1009 12.844 Health behavior Current Smoker 7713 33.149 4757 30.866 2956 37.627 < 0.001 Current Drinker 7756 33.333 4932 32.001 2824 35.947 0.005 Wang and Yang Int J Ment Health Syst (2018) 12:33 Page 7 of 12 Table 2 Association of air pollution intensity and depressive symptoms and the role of chronic disease (N = 23,268) Variables Influence of SO2 emission intensity on depressive symptoms Influence of TSP emission intensity on depressive symptoms Model 1 Model 2 Model 3 Model 4 Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Log of SO2 intensity 1.266*** 0.107 1.093*** 0.116 – – – – Log of TSP intensity – – – – 1.318*** 0.082 1.115*** 0.092 Chronic disease – – 1.384*** 0.068 – – 1.388*** 0.068 Log of SO2 intensity × Chronic disease – – 0.217*** 0.084 – – – – Log of TSP intensity × Chronic disease – – – – – – 0.281*** 0.071 Log of average monthly temperature 0.189** 0.085 0.176** 0.085 0.201** 0.087 0.191** 0.087 Log of average monthly relative humidity − 0.690** 0.333 − 0.693** 0.332 − 0.445 0.335 − 0.451 0.333 Age group 50–59 0.248*** 0.090 0.134 0.089 0.263*** 0.090 0.148* 0.089 60–69 0.148 0.105 − 0.057 0.104 0.174* 0.104 − 0.031 0.103 More than 70 Male − 0.396*** 1.270*** 0.131 0.091 − 0.606*** 1.269*** 0.130 0.090 − 0.368*** 1.282*** 0.131 0.091 − 0.578*** 1.283*** 0.130 0.090 Unmarried 0.680*** 0.121 0.701*** 0.119 0.682*** 0.121 0.701*** 0.119 Living in urban area Education − 0.400*** 0.104 − 0.398*** 0.103 − 0.395*** 0.104 − 0.387*** 0.103 No education but can read/write 0.414*** 0.118 0.373*** 0.116 0.416*** 0.118 0.376*** 0.116 Primary school − 0.043 0.112 − 0.081 0.110 − 0.039 0.112 − 0.077 0.110 Junior high school and above − 0.470*** 0.114 − 0.454*** 0.112 − 0.461*** 0.114 − 0.448*** 0.112 Employment status Self− employed − 0.165* 0.089 − 0.109 0.088 − 0.152* 0.088 − 0.096 0.088 Wage earner − 0.351*** 0.090 − 0.262*** 0.089 − 0.354*** 0.090 − 0.265*** 0.089 Insurance NCMS and URBMI − 0.061 0.130 − 0.123 0.129 − 0.052 0.129 − 0.113 0.128 UEMBI − 0.432*** 0.152 − 0.520*** 0.151 − 0.418*** 0.151 − 0.503*** 0.150 Income group 21–40th percentile 0.328*** 0.100 0.335*** 0.099 0.340*** 0.100 0.349*** 0.099 41–60th percentile 0.078 0.096 0.068 0.095 0.091 0.096 0.082 0.095 61–80th percentile − 0.073 0.096 − 0.068 0.095 − 0.063 0.096 − 0.056 0.095 81–100th percentile − 0.289*** 0.101 − 0.296*** 0.100 − 0.288*** 0.101 − 0.295*** 0.100 Health behavior Current drinker 0.040 0.072 0.108 0.072 0.0459 0.072 0.114 0.072 Current smoker Constant − 0.196** 7.165*** 0.081 1.548 − 0.156* 7.025*** 0.080 1.562 − 0.186** 7.219*** 0.081 1.538 − 0.144* 7.079*** 0.080 1.544 City dummy variables YES YES YES YES Adjusted R2 0.139 0.165 0.139 0.165 Wald Chi square 2126*** 2596*** 2228*** 2707*** Models 1–4 are estimated using the xi:xtreg-command in Stata 14. Decentralization was calculated using the center-command * P < 0.10; ** P < 0.05; *** P < 0.01 (SE = 0.082, P < 0.001, 95% CI 1.157–1.480), respec- tively. Models 2 and 4 from Table 2 present the interac- tion between air pollution and chronic disease and their effect on depressive symptoms. After controlling for the interaction of air pollution and chronic disease, a posi- tive correlation between air pollution and depressive symptoms was observed, as expected. An 1% increase in the intensities of SO2 and TSP emissions was associ- ated with 1.237 (1.093 (SE = 0.116, P < 0.001, 95% CI 0.866–1.320) + 0.217 (SE = 0.084, P = 0.009, 95% CI 0.053–0.380) × 15,412/23,268 = 1.093 + 0.217 × 66%) and 1.301 (1.115 (SE = 0.092, P < 0.001, 95% CI 0.934– 1.296) + 0.281 (SE = 0.071, P < 0.001, 95% CI 0.143– 0.420) × 66%) higher depressive symptoms scores, Wang and Yang Int J Ment Health Syst (2018) 12:33 Page 8 of 12 respectively. In addition, due to an 1% increase in the intensities of SO2 and TSP emissions, the depressive symptoms scores for respondents with chronic disease increased by 1.903 (1.384 (SE = 0.068, P < 0.001, 95% CI 1.250–1.518) + 0.217 (SE = 0.084, P = 0.009, 95% CI 0.053–0.380) × log(82.950)) and 1.854 (1.388 (SE = 0.068, P < 0.001, 95% CI 1.254–1.522) + 0.281 (SE = 0.071, P < 0.001, 95% CI 0.143–0.420) × log(45.571)), respec- tively. Given the same intensities of SO2 and TSP emis- sions, respondents with chronic disease had higher scores for depressive symptoms by 0.217 (SE = 0.084, P = 0.009, 95% CI 0.053–0.380) and 0.281 (SE = 0.071, P < 0.001, 95% CI 0.143–0.420) than those without chronic disease. Models 1–4 from Table 3 show the results strati- fied using chronic disease characteristics; models 5–8 show results using the Tobit model; models 9–12 show the results stratified using chronic disease character- istics and the Tobit model. Robust analysis shows that the results obtained were consistent with those using the random effects model. According to models 10 and 12 from Table 3, for individuals with cancer or malig- nant tumor, chronic lung diseases, liver diseases, kid- ney disease, and stomach diseases, when the SO2 and TSP emission intensities increased by 1% individu- als showed an increase in depressive symptom scores of 0.844 (0.788 (SE = 0.128, P < 0.001, 95% CI 0.537– 1.039) + 0.221 (SE = 0.091, P = 0.015, 95% CI 0.044– 0.399) × 2669/10,508 = (0.788 + 0.221 × 25%) and 0.818 (0.765 (SE = 0.118, P < 0.001, 95% CI 0.534–0.997) + 0.208 (SE = 0.107, P = 0.051, 95% CI 0–0.417) × 25%), respec- tively. In addition, due to an 1% increase in the intensi- ties of SO2 and TSP emissions, respondents with these chronic diseases scored higher for depressive symp- toms by 1.292 (0.869 (SE = 0.102, P < 0.001, 95% CI 0.668–1.069) + 0.221 (SE = 0.091, P = 0.015, 95% CI 0.044–0.399) × log (82.000)) and 1.208 (0.866 (SE = 0.114, P < 0.001, 95% CI 0.643–1.090) + 0.208 (SE = 0.107, P = 0.051, 95% CI 0–0.417) × log(43.885)), respectively. Given the same intensities of SO2 and TSP emissions, individuals with chronic disease had higher scores for depressive symptoms by 0.221 (SE = 0.091, P = 0.015, 95% CI 0.044–0.399) and 0.208 (SE = 0.107, P = 0.051, 95% CI 0–0.417) than those without chronic disease. However, the impacts of air pollution were reduced after eliminat- ing the endogenous variable, which supports the hypoth- esis that depressive symptoms influence physical health. Discussion To the best of the authors’ knowledge, this is the first published article to elucidate the role of chronic disease in an association between air pollution and depressive symptoms within the Chinese population, who prefer to acknowledge poor mental conditions … Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. T Six Dealing with Emotions The Psychological Impact of Dialysis rue or false: people who are on dialysis are unhappier than people who are not on dialysis? If you answered true you’ll probably be surprised to hear that a carefully designed research study has proven otherwise. The study, led by a psychologist, Jason Riis, while he was completing graduate work at the University of Michi- gan, compared forty-nine individuals on hemodialysis, three times weekly, with forty-nine healthy individuals of the same age, race, ed- ucation, and sex.1 All of the subjects were given electronic devices that prompted them to record their moods throughout the day. Moods were rated on a 5-point scale from “very pleasant” to “very unpleasant” and subjects were given the opportunity to answer these questions privately and repeatedly over time. When the results of the two groups were compared, the re- searchers found that the levels of happiness were about the same for the two groups. The study also found that the dialysis patients over- estimated how happy the healthy people would be and the healthy people underestimated how happy the dialysis patients would be. Why is it that we are so quick to assume that dialysis leads to unhap- piness? On the contrary, we the authors have come to believe that if C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. Dealing with Emotions 115 you were relatively happy before dialysis, in time, you will be happy after. Alternatively, if you were relatively unhappy before dialysis, you will still be unhappy after. How a person copes with dialysis and the attitude he or she adopts toward it is often reflective of how someone has managed to cope and the attitudes he or she has learned to adopt throughout life. Of course, dialysis is initially shocking for everyone. This initial shock can cause a serious crisis for many individuals. Going on dialy- sis can result in depression, anger, anxiety, and even occasionally an emotional breakdown. It can also result in severe crisis in family rela- tionships, which occasionally can result in separation and divorce. However, in these cases the marriage was suffering to begin with. Dialysis is simply the straw that breaks the camel’s back. There is no question that individuals who have no other physical illnesses (such as diabetes, strokes, heart disease) often do better emotionally than individuals who have other major physical illnesses for the simple fact that their burden is lighter. But after the initial shock has passed and a person has become used to the new routines of the dialysis, he or she settles down to live life within the constraints of the treatment. During this initial period of shock, what are the tools that a per- son can use to help ease this emotional distress? In this chapter we will identify and discuss some of the most common emotional re- sponses to dialysis. In addition, we will recommend ways to help you deal with this emotional turbulence. The good news is that like most kinds of turbulence, eventually this too subsides. By addressing and tending to these emotional bumps, you may eventually, as the afore- mentioned study shows, find yourself just as happy as the next guy. Throughout the years that Daniel has been visiting dialysis clinics we’ve met many rather well-adjusted, seemingly happy individuals, but most of these acquaintances rarely opened up to us about their trials and tribulations when first starting dialysis. Nor did they tell us much about the sources of strength they used to help them survive the tough times. But in the course of researching this book, Susan C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. 116 D i a l y s i s w i t h o u t F e a r met Jeffrey, a pastor for a medium-sized interdenominational church who spoke candidly about the physical and emotional trauma of first starting dialysis and the important role that his faith played in help- ing him to cope. Jeffrey’s Story, a Hemodialysis Patient’s Perspective When Susan meets with Jeffrey, a middle-aged African American gentleman, he strikes her as just that—a gentle man. Jeffrey has been on dialysis for only sixteen months and he explains that he is still adapting to the transition. Like his father before him, Jeffrey suffers from diabetes that eventually led to his renal failure. His father, one of twelve children, had begun dialysis many years before. Jeffrey in- forms Susan that he also has six uncles who have gone on dialysis, and he says that he can identify at least four generations of diabetics in his family. Because of this genetic disposition Jeffrey surmises that he is the first, but likely not the last, of the second generation of fam- ily members to undergo dialysis. Just four years earlier Jeffrey had been diagnosed with diabetes. And one year after that, he was referred to a nephrologist who told Jeffrey that his kidneys were operating at 40%. Jeffrey attempted to watch his sugar levels, but he didn’t think he was headed toward re- nal failure or dialysis. Then two years later he noticed swelling in his legs and ankles. Every evening he would elevate his legs and every morning the swelling would be gone. What Jeffrey, who admits he was in denial, didn’t realize was that the fluid was simply moving around from one place to another. This routine continued until one morning, as he was walking into the building where he worked, Jef- frey collapsed. Paramedics rushed him to the hospital and the next thing he knew he was being dialyzed. At first, Jeffrey says he really didn’t think about what it meant to C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. Dealing with Emotions 117 be on dialysis. He just wanted the doctors and nurses to do whatever it took to make him feel better. But he soon realized, he did not like the catheter or the cramps he suffered as fluid was removed from his lungs and body. All told, during his week-long hospital stay the medical professionals removed forty-five pounds of liquid. After that week, Jeffrey says he was a different person physically. It wasn’t until he went to his local dialysis clinic for the first time after leaving the hospital that dialysis began to impact him emotionally. How were you affected emotionally? “Well, my father has been on dialysis for about eight years, so I had been around it. I had helped him deal with his emotional roller- coaster, but now I had to face dialysis myself. I think what bothered me the most was watching my family deal with my illness. My kids told me that I’d always been the strong one. I’d never been sick. I’d always visited other people in the hospital and comforted them. So for my children to see me flat on my back made them feel very help- less. Having them see me this way was difficult for me. When I was in the hospital, my daughter didn’t even want to come to see me. She didn’t want to deal with it. Just now she has started to write some po- etry about her experience when I went on dialysis. Finally, she is learning to express herself more. “I think dialysis was also traumatizing for my wife. We were get- ting ready to travel, to buy a new home and do a lot of things we’d dreamed of when the children were grown. I think she just had never imagined herself in that predicament in her life.” What was dialysis like for you when you first began? “When I first started I had a lot of problems with my graft. Not just anybody could stick me, and that was upsetting too. I have a high pain tolerance, but it was frustrating when I would get a less ex- perienced technician. Also the trial and error of trying to find my dry weight was the most difficult part. I didn’t really know how much fluid I could have in between sessions, how much would neg- atively impact me during and after my sessions. When I first began, C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. 118 D i a l y s i s w i t h o u t F e a r I was arriving ten to twelve pounds over my dry weight. That wasn’t good. I would cramp during and after the session. Now when I come in, they take off two or three pounds. Unfortunately, I had to learn how to control my liquids the hard way. Until you start learning what fluid does to you and what certain foods do to you, you can feel pretty bad. Adjusting to a new diet was a whole other can of worms that I had to deal with. Over time I learned about my potas- sium, phosphorus, and calcium.” What advice would you give to someone who is new to dialysis? “Really spend a lot of time talking. Talk about how you feel phys- ically and emotionally. When I first went on dialysis I read some pamphlets, but honestly it was as if they were written in Chinese. They were filled with information. I think it would have been help- ful for me to read more about the psychological aspects of what a person goes through in the beginning. I think visiting with a support group or seeing a counselor might have also been beneficial. I didn’t do either of these things, although I did regularly read a newsletter that included personal testimonials. I found reading about other people’s stories and what they went through to be extremely helpful. I also had my wife read the testimonials too. They were helpful for both of us. “I would also recommend that new patients speak with the veter- ans in the clinic. Some of the folks here, the older folks (I’m the new kid on the block), they really helped me through a lot. They would ask me ‘How are you feeling? What are you going through?’ And they would tell me what questions I should be asking the medical staff. Having that kind of support and friendship was really very advantageous.” What advice would you give to a family member of someone new to dialysis? “Talk to somebody about what you are going through emotion- ally. At first there are a lot of emotions that the family and especially the spouse are going through. But they don’t want to share these C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. Dealing with Emotions 119 emotions with you because they feel that you have enough to worry about. Despite this, family members also need an outlet or someone to talk to. I wish initially my wife had done that more. She held a lot of her emotions in for a long time. I think possibly talking to my fa- ther and mother, or somebody who had gone through the same thing, would have helped her a great deal.” Jeffrey says that when he first began dialysis his wife took time off from work to drive him dialysis. Because he didn’t want her to feel like she had to spend so much time caring for him, he tried to get back on his feet as quickly as possible. Jeffrey tells Susan, “I think getting back to a relative state of normal where I could drive myself has helped a lot. I also think it helped that I opened up and said to her, ‘Tell me how you feel.’ I think she wanted to know what I was going through emotionally as well. This was important for her. It was difficult for me, at first, to share my feelings with her. In the be- ginning I didn’t really like to talk about it. I would just say ‘I’m feel- ing pretty good!’ ” Interestingly enough, both Jeffrey and his wife were trying to pro- tect one another from the distress that they individually were en- countering. Jeffrey didn’t want to burden his wife with having to take care of him. He didn’t want to tell her truthfully how he was do- ing and felt that he had to rebound and adjust just as quickly as pos- sible. Likewise, his wife felt angry and sad that their life was no longer what she had envisioned, but since she was the healthy one, she felt she couldn’t share these emotions with her husband. During a stressful time the two tended to keep their feelings to themselves. Eventually when they began communicating more openly and hon- estly with each other they began to cope better emotionally. In addition to addressing your emotions, what are some additional key success factors to living well on dialysis? “Really, every individual is different. I think if it wasn’t for my faith, perhaps I would have a very different outlook on dialysis and on life. Most of my life I’ve tried to encourage people to live well C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. 120 D i a l y s i s w i t h o u t F e a r despite adversity. Suddenly I had to live as I’ve always preached. Along with my faith, I also have a strong support system in both my family and my community, which has helped me to stay positive and optimistic.” Are there any benefits to being on dialysis? “Sure—I’m glad we have it! Dialysis is doing what my kidneys can’t do. I also think it has made me a better pastor. I’m more pas- sionate about habits that affect our lives in a negative way. I’ve only missed one Sunday at church since I’ve been on dialysis. The week I left the hospital I missed preaching, but the following week I was there. That first Sunday after I began dialysis I looked out at the con- gregation. I really looked at the people who had been sick. Many of the congregants had been ill for years. And I realized that our health issues are a collective problem. We live in a society that promotes unhealthy lifestyle habits. Now I’m much more conscious about healthy living and am an advocate of better health. I’ve even started a wellness program at the church for people to get their blood sugar checked regularly.” Jeffrey tells Susan he credits his faith, his motivation to help oth- ers, and the support of those around him as giving him the strength to cope, but he acknowledges that going on dialysis was tough. Phys- ically it has been hard on him. Emotionally he has grappled with a sense of failure and weakness, fearful that he has let his family down. But fortunately Jeffrey’s sense of accountability to his congregants whom he has preached to for so long has been his saving grace. As he tells Susan, “For many years I had talked the talk. Now I had to walk the walk.” Like the veterans he speaks of, Jeffrey strikes Susan as a man who has gone to battle with his physical and emotional demons and who has now crossed over to a safer place. In order to be a role model, Jef- frey was forced to find a way to cope. He admits his new schedule and lifestyle still require adjustments, but he also tells Susan he hopes to start traveling with his wife more, he is working full time, C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. Dealing with Emotions 121 and he’s looking forward to seeing his daughter graduate from high school soon. Susan can’t help noticing that he is living well and en- joying life despite dialysis. Before they part ways, Susan finds herself contemplating what sources of strength or coping mechanisms she would draw upon if she were ever to walk in Jeffrey’s shoes. Once the Shock Subsides: Coping with Psychological Aftershocks Like Jeffrey, most patients whom we met told us that it took some time for their physical health to improve significantly before they could begin to feel, much less deal, with the substantial emotions as- sociated with this enormous life change. When they begin to feel bet- ter physically is when many patients start to feel anxious, depressed, or angry. Family members are also highly susceptible to these emo- tions. It is normal and understandable to experience them. But the people who do not do well on dialysis are the ones who cannot, over a normal course of time, address and move past these emotional states. Some individuals never cope well with dialysis. They think their life has been forever limited and they absolutely hate the thought of having to go to dialysis three times each week as long as they live—or until they receive a transplant. Emotionally, these are the people who do not do well. Now let’s look at some of the most com- mon emotions that can negatively impact dialysis patients and their families, what happens to those who do not cope well, and what cop- ing mechanisms a person can rely on when working through these emotions. Denial Denial is often the very first reaction of many dialysis patients. De- nial is a state of nonacceptance. When in denial, a person refuses to accept the fact that he or she is on dialysis. Obviously the person can C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. 122 D i a l y s i s w i t h o u t F e a r see himself or herself receiving the treatment but chooses to believe that it is temporary and that all will return to normal in a few weeks or months. In this state a patient typically refuses to follow the diet or acknowledge the liquid restrictions. He or she continues to act and behave as before starting dialysis. The patient is neither angry nor depressed; he or she simply refuses to believe that life on dialysis is now a reality. As we all know, innocence can be bliss, but dialysis patients cannot stay in this state forever. It is only a matter of time before their denial causes their health to decline precipitously. Sadly, many of the individuals whom we interviewed claimed not to have believed what the doctors told them regarding their diet and liquid restrictions. Too many said they had to learn to take care of themselves and heed their doctor’s advice the hard way. This was un- fortunate, because this learning path usually meant jeopardizing their lives. Denial, while common, is not a particularly helpful re- sponse to the newness of dialysis. As one physician we interviewed said, “Like so many things in life, dialysis is a head game. Most pa- tients won’t do well if they struggle and fight against dialysis rather than work with it. Denial or the inability to come to terms with dial- ysis prevents some people from doing as well as they might. Can you get by when you are messy and inattentive and don’t comply with in- structions? Yes you can, but if you want to do better you need to have your thoughts together and understand what is being asked of you. And by understand I generally mean you have to do what you are told.” Patients are much better served the sooner they can accept their reality and work within the guidelines that are set forth by their medical team. One way or another, reality will eventually sink in and when it does patients are then most often confronted with feelings of anxiety, depression, or anger. Anxiety Anxiety makes one feel uneasy, fearful, nervous, and worried. Physi- cally one can experience a quickened pulse, lethargy, irritability, and C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. Dealing with Emotions 123 increased sweating. There are numerous sources of anxiety that pa- tients associate with dialysis. Let’s start with the whopper, the big kahuna of them all: anxiety about death. One patient we spoke with had the very terrifying and unfortunate experience of watching as a woman who was sitting across from him at dialysis went into cardiac arrest. Sadly, he witnessed her death. And of course, one of the first thoughts to cross his mind was, “That could be me. I could die.” And that was an extremely frightening thought. It shook him to his core. His experience that day was extreme and unusual, but even without having such a jarring experience you too may be growing anxious over the thought that dialysis has brought you a bit closer to your mortality. Before dialysis, you might have thought you were in- vincible (although in reality you weren’t) and now you know you are not. “True, now that you are on dialysis, statistically speaking, your chances of dying are greater than they were before your kidneys failed and you needed dialysis.” There we have said it: you may die. Dwelling on this fact can be paralyzing and unhealthy. Now it is time to move on. The good news about facing your mortality is that once you realize you won’t be on this earth forever you may actually appreciate certain aspects of life more than you ever did before dial- ysis. However, becoming accustomed to this new level of awareness can and does often heighten levels of anxiety. Dialysis patients are often anxious about death, but this is not the only common cause of anxiety. Many times they are anxious about the actual dialysis process itself; they are afraid of the needles, of see- ing their blood outside their body, of feeling pain, of sitting among other patients who are significantly sicker than they, wondering if the treatment actually will work as intended. Feeling acutely anxious about all of the above is normal—for a time—but human beings are remarkably adaptable. As the novelty of dialysis wears off, you should become increasingly comfortable with what goes on inside the clinic and the patients who frequent the clinic. No one wants to get used to dialysis, but many people do. Or at least they do enough C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. 124 D i a l y s i s w i t h o u t F e a r to muddle through while taking ample pleasures from life. However, if feelings of anxiety persist indefinitely, it may be time for you to seek out additional sources of assistance. We’ll discuss these re- sources shortly. Now that you are dependent on dialysis to live, you may also be- come anxious about what would happen to you in the event of a nat- ural or terror disaster. Of course, it is not likely that you’ll ever have to deal with either of these happenings, but even so, this is not an un- reasonable fear to have. In times of crisis basic needs must be met. For most people, their basic needs are food, water, shelter, clothing, and medical care. For someone on dialysis, being able to access electricity or supplies for peritoneal or home hemodialysis or a hemodialysis center is another basic need that must be met. As you listen to the world news and hear of the latest natural disaster it is normal to think, “What would happen if the power were to go out, the roads were to be washed out, or I was to be snowed in? What would happen to me, if I could not get to the clinic or perform my own dialysis? How long could I survive without dialysis?” These thoughts are scary, and while we can find comfort by being prepared for emergencies (see Chapter 10 regarding travel and emergency preparations), we can still get worked up and nervous by constantly imagining doomsday scenarios. These types of “what if ” questions bring us to another common source of anxiety: a fear of losing control. Many of us like to have a sense of control over our lives, days, actions. We think that by mak- ing lists, schedules, plans, routines, or goals we can influence the course of our lives. This may be so, but there are also events we can- not control that impact us profoundly. Going on dialysis is one such event. Losing this real or perceived sense of control is often the pri- mary anxiety trigger for many individuals. For people who demand control, the best course of action is to gain knowledge and under- standing and in some cases even pursue a modality that allows for greater self-management and care. C o p y ri g h t © 2 0 0 7 . O x fo rd U n iv e rs it y P re s s , In c o rp o ra te d . A ll r ig h ts r e s e rv e d . http://ebookcentral.proquest.com/lib/leicester/ Offer, Daniel, et al. Dialysis Without Fear : A Guide to Living Well on Dialysis for Patients and Their Families, Oxford University Press, Incorporated, 2007. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/leicester/ Created from leicester on 2020-11-08 23:22:36. Dealing with Emotions 125 Last, many individuals experience worry and anxiety about how and if they will be able to continue to work and be a provider for their family. Financial concerns are a huge source of anxiety for many dialysis patients. Or, as we saw with Jeffrey, some people may be anxious about how dialysis will affect their family not just finan- cially but emotionally as well. This sense of concern and responsibil- ity for the well-being of their loved … Hemodialysis International 2017; 21:557–565 Original Article Pediatrics Psychosocial aspects of children and families treated with hemodialysis Anna MEDYN, SKA,1 Danuta ZWOLIN, SKA,1 Ryszard GRENDA,2 Monika MIKLASZEWSKA,3 Maria SZCZEPAN, SKA,4 Agnieszka URZYKOWSKA,2 Katarzyna ZACHWIEJA,3 Katarzyna KILIS,-PSTRUSIN, SKA1 1 Department of Pediatric Nephrology, Wroclaw Medical University, Wroclaw, Poland; 2 Department of Nephrology, Kidney Transplantation and Hypertension, Children’s Memorial Health Institute, Warsaw, Poland; 3 Polish-American Children’s Hospital, Jagiellonian University, Krakow, Poland; 4 Clinic of Pediatrics, Nephrology and Endocrinology, Silesian Medical University, Zabrze, Poland Abstract Introduction: The aim of this study was to analyze the selected psychosocial aspects of chronic kidney disease in children treated with hemodialysis (HD). Methods: The study included 25 children treated with HD aged 2 to 18 years and their parents. Data concerning the illness and socio-demographic parameters was collected. We used the Paediatric Quali- ty of Life Inventory (PedsQL) for patients and for their parents the PedsQL-proxy version, General Health Questionnaire (GHQ-12), Berlin Social Support Scales (BSSS), and the Caregivers Burden Scale (CBS) to evaluate health-related quality of life (QoL) of HD children and their primary caregivers. Findings: In the PedsQL test, the QoL of HD children was lower than in healthy children. Children treated with HD assessed their QoL on the PedsQL questionnaire higher than the primary care- givers, on all subscales as well as an overall health-related QoL. Scoring below 2 on the GHQ-12 test was reported in 56% of mothers, which may indicate that psychological symptoms have inten- sified. There was no correlation between BSSS, CBS, and GHQ-12. Discussion: The assessment of QoL in pediatric patients would allow for the earliest possible identification of their nonsomatic problems and irregularities. This could, consequently, contribute to improving QoL in both children with chronic kidney disease and their families. Key words: Children, hemodialysis, quality of life, parents’ perceived burdens Correspondence to: A. Medyn,ska, MD, PhD, Department of Pediatric Nephrology, Wroclaw Medical University, Ul. Borowska 213; 50-556 Wrocław, Poland. E-mail: anna. [email protected] Conflict of Interest: The authors declare that they have no con- flict of interest. Disclosure of grants or other funding: None Ethical approval: All procedures performed in studies involv- ing human participants were in accordance with the ethical standards of the institutional and/or national research com- mittee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent: Informed consent was obtained from all individual participants included in the study. VC 2017 International Society for Hemodialysis DOI:10.1111/hdi.12526 INTRODUCTION Today, owing to advances in the area of dialysis treatment as well as in other medical procedures, children with chronic kidney disease (CKD) have a significantly longer survival rate. However, despite being provided with an increasingly effective treatment, they can never be cured, notwithstanding successful kidney transplantation.1 Con- sequently, proper care over pediatric patients with CKD must combine both medical and psychosocial aspects. Already in 1994, Kurtin et al. stated that treating children with CKD cannot be successful if it is narrowed only to improving the mortality and/or comorbid conditions of 557 mailto:[email protected] Medyn,ska et al. 558 Hemodialysis International 2017; 21:557–565 the disease.2 According to these authors, physical devel- opment and achieving the same or similar general condi- tion as healthy peers (with regard to school life, contacts with peers, hobbies, and so forth.) should be also taken into consideration. Every chronic disease changes family functioning. It increases stress levels and burdens the family members. Moreover, it may influence family relationships. Besides, being diagnosed with a chronic disease greatly increases children’s dependency on parents/caregivers. As a conse- quence, caregivers (usually mothers), face new problems associated with caring for an ill child. The chosen method of renal replacement therapy (RRT) impacts both patients’ and their family’s quality of life (QoL). Watson et al. reported that 34% of children began RRT from HD or hemodiafiltration, and HD constitutes the main therapeutic option for children aged 10–18 years.3 Schipper recognizes health-related quality of life (HRQoL) as effects of chronic disease and its treatment perceived by patients. This feeling is always subjective and therefore difficult to assess. A study conducted in the United States among 2500 children with chronic diseases showed that patients with ESRD had significantly worse HRQoL scores compared to children with other diseases.4 Polish studies proved that school-aged children with chronic diseases assess their QoL remarkably worse com- pared to healthy peers.5 QoL in HD patients has been assessed many times before, but mainly in adults. QoL in children treated with repeated hemodialysis has been assessed only in individual studies. According to Glazebrook et al., 20% of CKD chil- dren have a probable psychiatric disorder.6 Kogan et al. reported that 30% of patients with CKD aged 9–18 years fulfill the criteria for depression.7 The results published so far do not allow for formulating recommendations regard- ing psychological effects on HD patients and their families. The assessment of QoL in pediatric patients would allow identifying nonsomatic problems and irregularities as soon as possible, which could contribute to improving QoL in CKD pediatric patients and their families. Con- cerning above mentioned remarks, we have conducted a multicenter national study evaluating HRQoL in pediatric patients treated with repeated HD and their families. Such study has never been carried out in the Polish population. MATERIAL AND METHODS Eleven out of 12 pediatric dialysis centers in Poland par- ticipated in the cross-sectional national study. The study was conducted on HD children and their parent-proxies between September 2011 and January 2012. The study protocol adhered to the Declaration of Helsinki. The study was approved by the Ethics Committee of Wroclaw Medical University prior to study initiation. We obtained written informed consent from all patients over 16 years of age and all parents of all participants before their enrollment in the study. Verbal consent was obtained from patients under 16 years of age where possible. The inclusion criteria for children were as follows: CKD diagnosed at least 12 months prior to the study, HD treat- ment at least 3 months prior to the study, age 2 or older, and informed consent. All dialysis patients were without acute illnesses and in stable psychophysical condition at the time of the study. Patients with known history of severe to profound mental retardation, renal, other solid-organ, bone marrow, or stem cell transplantation, cancer/leukemia diagnosis, and hospitalization within 14 last days (exclud- ing hospitalization due to HD because of other reasons than HD session), a significant life event unrelated to their kidney disease in the past 30 days, such as losing a family member were excluded. Methods Medical files were analyzed to obtain the following data: primary diagnosis of kidney disease, patient’s age at the time of CKD diagnosis, duration of illness, HD duration, duration of nephrology care, additional non-renal comor- bidities, place of living and its distance from a nephrologi- cal center, and family history. Additionally, school-age children and their parents were asked about schooling level and special education requirements (supplementary tutoring or an individualized education program). Then, both parents were invited to fill out questionnaires regarding changes in their families after the child’s CKD diagnosis and their relationship with the people in their immediate surroundings. The questionnaires were com- pleted on a visit to the renal center and each parent filled out the questionnaire individually. In the next step, we used Paediatric Quality of Life Inventory (PedsQL) 4.0 Generic Core Scales.8,9 We obtained the user agreement from Mapy Research Insti- tute in Lyon, France. In addition, the parents underwent the following tests: the 12-item General Health Question- naire (GHQ-12),10 Berlin Social Support Scales (BSSS),11,12 and the Caregiver’s Burden Scale (CBS).13 All tests were translated and validated in Poland.14–16 Cron- bach‘s a for GHQ-12 is 0.72 and for the four subscales of BSSS ranges from 0.70 to 0.86. Cronbach‘s a is 0.88 for the total scale of CBS and ranges from 0.74 to 0.82 for the subscales. The tests used in the study were thoroughly presented in our other work.17 All tests were designed Children in hemodialysis 559 Hemodialysis International 2017; 21:557–565 Gender (or home-classes) median (quartiles) HD 5 hemodialysis; CKD 5 chronic kidney disease. aIn the past 6 months. according to the general protocol and administration guidelines. Statistical analyses Statistical analyses were performed using R for Windows, version 2.15.1 (The R Foundation for Statistical Comput- ing, Vienna, Austria) and MedCalc for Windows, version 12.3.1.0 (MedCalc Software, Mariakerke, Belgium). Medians, quartiles, frequencies and percentages were reported to describe the data, as appropriate. Qualitative analyses were conducted using a chi-square test or Fish- er’s exact test. Quantitative variables were tested for nor- mality distribution by a Kolmogorov–Smirnov test. For comparison between groups, the Mann–Whitney test and the Kruskal–Wallis test were used, as appropriate. Spearman’s correlation analysis was used to determine the correlation between parameters. A P value of less than 0.05 was considered statistically significant. RESULTS The analysis included test results received from 25 children treated with repeated HD and 25 mothers—patients’ prima- ry caregivers. The study did not include test results gathered from fathers/patients’ second caregivers because of insuffi- cient sample size (only 6 fathers submitted filled tests). Survey results The characteristics of the studied group of patients are presented in Table 1. All patients, except for 3 children Table 1 Basic characteristic of hemodialysis children Parameter n 5 25 % Age, mean 6 SD, years 13.15 6 4.58 Children< 5 3 12 5 22 88 Female 15 60.0 Male 10 40.0 Cause of CKD Chronic glomerulonephritis 2 8 Anomaly of kidney and urinary tract and chronic pyelonephritis 11 44 Hereditary kidney disease 2 8 Others 9 36 Unknown cause 1 4 Comorbidity Yes 3 12 No 22 88 Family renal history Yes 2 8 No 23 92 Place of residence (size) Village or town < 50,000 residents 19 76 Town 50,000 – 100,000 residents 0 0 Town > 100,000 residents 6 14 Age at CKD diagnosis, median (quartiles), years 4.0 (1–10) CKD duration, median (quartiles), years 7.5 (3.0–13.84) Nephrological care duration, median (quartiles), years 6.04 (2.25–11.5) HD therapy, median (quartiles), years 4 (3.75–4.0) Distance from nephrology centre, median (quartiles), km Number of hospitalizationsa median (quartiles) 59.0 (28.75–72.5) 2 (1–4) The number of missed school-days in the past 6 months 8 (8–32) Medyn,ska et al. 560 Hemodialysis International 2017; 21:557–565 Table 2 Basic characteristics of parents and families of hemodialysis children Parameter n % Mothers 25 100 Age, mean 6 SD, years 37.96 6 6.74 Mother's education level Elementary/trade school 16 64 High school 6 24 University degree 3 12 Employment diagnosis according to patients’ mothers are presented in Table 3. In the majority of families (52%), the financial situation has changed; in 44% of cases the situation got worse. Besides, in 44% of cases mothers declared deterio- ration of their social contacts. Test results The results of PedsQL were lower in the group of HD children compared to healthy children described in the literature, both in terms of overall HRQoL (50.54 6 7.82 vs. 82.87 6 13.6) and in individual domains: physical Table 3 Changes in the family observed by the mothers after chronic kidney disease diagnosis in the child Mothers’ evaluation n 5 25 Yes No Employment n % n % Yes 20 80 Change of location of residence 1 4 24 96 No 5 20 Changes made to current residence 3 12 22 88 Healthy Change in financial status 13 52 12 48 Yes 23 92 Deterioration 11 44 No 2 8 Improvement 2 8 Family Full 19 76 The change of the source of income Caring for the child 5 20 20 80 Single-parent family 6 24 Mother 19 Sibling Father 0 Yes 24 94 Both parents 6 No 1 4 Participation of other people 9 36 16 64 in child care under the age of 5 years, were subjected to compulsory schooling (22 patients—88%). The majority of patients were home-schooled (15 children—68%), the remaining children attended classes in school (7–32%). Nine pupils (36%) required no help with their studying; the remain- ing 16 children (64%) received assistance from their parents. The characteristics of HD patients’ families are pre- sented in Table 2. Most children were brought up in full families; only 6 patients had only one parent (a mother). Almost all children had siblings, only one was an only child. The primary caregivers of patients were mothers (in 19 cases), and both parents (in 6 cases). In 9 cases (36%), additional family members assisted with a care for a sick child, and they were usually patients’ grandparents. Dif- ferences that have occurred in families after disease Changes in relations among children 4 16 21 84 Improvement 4 16 Deterioration 0 0 Changes in social contacts 11 44 14 56 Improvement 0 0 Deterioration 11 44 New friendship 12 48 13 52 Yes 8 32 No 17 68 Healthy Yes 23 92 No 2 8 Fathers 25 100 Age (mean 6 SD), years 40.92 6 7.42 Father's education level Elementary/trade school 20 80 High school 2 8 University degree 3 12 Grandparents 7 28 Siblings 1 4 Cousins 1 4 Changes in attitude toward the ill child 6 24 19 76 Improvement 6 24 Deterioration 0 0 Changes in attitude toward 2 8 23 92 other children Improvement 1 4 Deterioration 1 4 Children in hemodialysis 561 Hemodialysis International 2017; 21:557–565 Table 4 PedsQL 4.0 generic core scales from child’s self-report (for ages 5–18; n 5 25) and parent-proxy report—primary caregivers HD children Primary caregivers of HD children Characteristic n 5 25 n 5 25 Physical functioning 40.63 (18.75–65.63) 51.56 (20.31–68.75) Emotional functioning 52.5 (35.0–75.0) 50.0 (37.5–65.0) Social functioning 67.5 (50.0–80.0) 62.5 (45.0–85.0) School functioning 47.5 (35.0–65.0) 40.0 (35.0–60.0) Overall HRQoL 50.54 (40.22–64.13) 49.46 (40.22–62.5) The data are presented as a median and quartiles (first–third quartile). HD 5 hemodialysis; HRQoL 5 health-related quality of life. functioning (40.63 6 6.46 vs. 86.86 6 13.88) emotional functioning (52.5 6 10.42 vs. 78.21 6 18.64), social functioning (67.5 6 11.46 vs. 84.04 6 17.43), school functioning (47.5 6 9.46 vs. 79.92 6 16.93).8 The test results regarding the evaluation of QoL in HD children by their primary caregivers were lower in all domains compared to caregivers of healthy children (physical functioning: 51.56 6 10.24 vs. 83.26 6 19.98, emotional functioning: 50.0 6 9.83 vs. 80.28 6 16.99, social functioning: 62.5 6 12.25 vs 82.15 6 20.08 and school functioning: 40.0 6 9.36 vs 76.91 6 20.08) and overall (49.46 6 9.46 vs. 81.34 6 15.92). Functioning in the physical domain was assessed higher by caregivers than by children, but in other domains the caregivers’ evaluation of QoL was lower than children’s assessment. The results of PedsQL tests in HD children and their pri- mary caregivers are presented in Table 4. The results of CBS, BSSS, and GHQ-12 tests received from HD children’s primary caregivers are presented in Table 5. The overall level of burden on the CBS scale was 2.39 (1.77–2.57) that means “medium burden.” On the sub- scales we noted low levels regarding the emotional involve- ment and the environment, whereas the other parameters were medium. The highest score was reported on the sub- scale “disappointment.” The average value equaled 2.6, but such result does not indicate high levels of burden. The level of social support assessed by primary care- givers varied from 2.78 to 3.5 on individual scales. The lowest scoring concerned “the need for support” and the highest “perceived available information support”—3.75. In the GHQ-12 test the average score was 3. The higher values indicated more psychological symptoms. Score above 2 points, which indicated the possible occurrence education, professional career, the family structure (com- plete/single parent), having or not having other children, and the source of income (professional career vs. welfare benefits). There was no correlation between scoring on all scales and the hometown population size, and between CBS results and CKD duration. A statistically significant negative correlation was found between PedsQL parent-proxy (overall HRQoL) and CBS: total burden index, environment, disappointment and general strain (r 5 20.55, P 5 0.006; r 5 20.74, P < 0.001; r 5 20.42, P 5 0.045; r 5 20.45, P 5 0.03, Table 5 Berlin Social Support Scale, Caregiver Burden Scale, and General Health Questionnaire test results among the mothers (primary caregivers) of hemodialysis children Berlin Social Support Scale (BSSS) Perceived available support: Emotional 3.50 (2.63–4.00) Instrumental 3.75 (2.88–3.75) Need for support 2.78 (2.50–3.25) Support seeking 2.90 (2.40–3.38) Actually received support: Emotional 2.80 (2.60–3.00) Informational 3.20 (2.70–3.40) Instrumental 3.60 (3.00–4.00) Caregiver Burden Scale (CBS) General strain 2.38 (1.88–2.69) Social isolation 2.17 (1.33–3.00) Disappointment 2.6 (2.3–2.9) Emotional involvement 1.67 (1.33–2.17) Environment 1.67 (1.5–2.25) Total burden index 2.39 (1.77–2.57) of abnormal mental functioning, was observed in 14 (56%) of mothers. General Health Questionnaire (GHQ-12) 3 (2–5) There was no significant correlation between BSSS, CBS and GHQ-12 results and the parents’ age, their The data are presented as a median and quartiles (first–third quartile). Medyn,ska et al. 562 Hemodialysis International 2017; 21:557–565 respectively). Positive correlation between BSSS subscale: perceived available emotional support and PedsQL parent-proxy were observed (emotional functioning r 5 0.46, P 5 0.03 and social functioning r 5 0.52, P 5 0.01). We did not note any correlation between GHO-12 and PedsQL parent-proxy. DISCUSSION Our research comprehensively assessed the psychosocial situation of HD pediatric patients. The HRQoL was assessed both by HD children and by their parents. More- over, we studied selected aspects of parents’ psycho-social functioning when facing child’s illness. The studies that evaluate QoL in children undergoing RRT are relatively few and they usually involve small groups of patients treated with various methods. In the available literature, QoL was compared in CKD children on different stages (predialysis vs. RRT) or undergoing various methods of RRT (HD, peritoneal dialysis-PD, transplantation-Tx).18–26 In some of the above-mentioned studies the authors analyzed QoL in children on dialysis (both PD and HD), whereas the type of dialysis also influ- ences QoL.27,28 The available literature lacks a study car- ried out both on children undergoing repeated hemodialysis and on their caregivers. We have demonstrated that HD children assessed their HRQoL (in the overall assessment and in all QoL domains) worse than general population of healthy chil- dren. In our study the patients provided the lowest scores on the subscale “physical functioning,” which can be associated with the fact that both disease itself and the therapy lead to numerous changes in children’s appear- ance. The patients’ appearances such as short height or bone deformities, which appear most of all during the puberty period, are a significant element of self- acceptance. Riano-Galan et al. reported that patients’ height itself constitutes an independent indicator of health-related satisfaction.25 We also received very low results on the subscale “school functioning” which may partly result from the method of treatment itself. Transportations and many hours in hospitals make difficult or even impossible to integrate with school peers. Transportation and many hours spending in hospital may be the reasons for leaving lessons and learning difficulties. Another factor contribut- ing to the scoring on the subscale “school functioning” may be a due to disorders associated with the impact of HD on the patients’ central nervous system (declines in blood pressure, anemia, and disturbances in acid-base and calcium-phosphate balances). Our patients provided the highest scores on the subscale “social functioning,” although the scoring was lower than in healthy children. The above results may be connected with the use of defense mechanisms or with narrow the perceived group of peers only to the closest environment. Similarly to our study, Goldstein et al. reported that children with ESRD (among them 32 HD children) pre- sent a significantly lower HRQoL compared to healthy peers both in the overall scoring and on all subscales.26 Lopes et al., having adopted the same research instru- ment, presented comparable results. Dialysis patients (including 25 children, 12 of them treated with HD) assessed their QoL lower in the physical, social, and school functioning domains compared to healthy peers.19 Moreover, other researchers having adopted different research instruments, reported lower QoL compared to the control group.18,22,23,25 Heath et al. presented differ- ent results. They reported that children with CKD (n 5 124, including 8 children with HD) have significant- ly higher QoL than the general population.21 Maxwell et al. reported that children with CKD have significantly higher QoL compared to healthy population, but it partic- ularly concerned males.20 The authors suggest that HD children “live with the disease” and have lower life expectations since they accept their reality as it is. Both parents and children assess the same situation according to individual standards. In our study, the pri- mary caregivers assessed QoL of their children lower on all subscales and overall compared to the healthy group described in the literature, which is in accordance with many other authors’ reports.22,24 The diagnosis of chronic disease in child significantly changes caregivers assess- ment of children’s lives and possibilities. Our study showed that primary caregivers assessed QoL lower than children in overall and on all subscales without regarding physical functioning. Similar results were also presented by other researchers such as Goldstein et al., Park et al., and McKenna et al., who emphasized this fact particularly clearly in children on dialyses.22,24,26 Such an attitude may consequently lead to a situation in which parents become “over-protective,” children are not self-reliant, but they dependent on their caregivers. On the other hand, Lopes et al. presented different results.19 According to these authors, primary caregivers assessed QoL higher than patients in all areas except for school functioning. The discrepancy between patients and caregivers was sig- nificantly higher than in the control group (a child—a parent). The older the child, the differences in assessing QoL were higher. Such discrepancies may lead, particu- larly during the adolescence, when a need to become Children in hemodialysis 563 Hemodialysis International 2017; 21:557–565 independent is strong, to isolation, psychological imbal- ances and, consequently, to noncompliance. It should be emphasized that children with ESRD and their parents present similar HRQoL as children with newly-diagnosed cancer and those undergoing chemo- therapy and radiotherapy treatments.29 Therefore, it must be concluded that having a child with CKD in a family is a very difficult experience, not always sufficiently acknowledged both by the medical personnel and by the surrounding environment. What is more, it suggests that there is a need of monitoring and providing such patients with ongoing psychological care. The socio-economic situation of Polish families with children treated with repeated HD appears to be difficult. In the examined families, 68% of mothers did not work. We associated this primarily with the fact that mothers devoted their time to care over ill children, transporting them to dialysis center as well as subsequent, several- hour stays in hospital during the treatment itself. In Poland commuting to nephrology centers is troublesome since transportation, due to financial reasons, cannot be individualized, and it often involves travelling long distan- ces, which is very time-consuming. Besides, 20% of our patients’ fathers were unemployed. Following the disease diagnosis, 52% of mothers observed that the financial sit- uation of their families had deteriorated. According to the data from the Polish Central Statistical Office (2013), chil- dren with chronic illnesses constitute only 5.5% of all children that receive social assistance. Marciano et al. observed that a difficult socio-economic situation in fami- lies with children with CKD was not correlated with low- er HRQoL.18 Adversely, von Rueded et al. stated that low economic status may lower HRQoL.30 In our study, we did not directly study the relationship between the above- mentioned factors, but taking into consideration the reported decline in the economic situation, it can be stat- ed that this tendency seems highly probable. All children subject to compulsory schooling participat- ed in classes. In our study the vast majority of children (15 children, i.e., 68%) were home-schooled. Buyan et al. reported that 50% of dialyzed children (including HD and PD) leave school.23 In the American study, 53% of children were able to successfully achieve full-time school attendance.31 School prepares children for adult life, allows their independence from parents and serves as a best indicator of socializing children with chronic ill- ness.32 Therefore, it is especially essential for HD children to ensure their optimal educational opportunities suited to the RRT. The present study demonstrated that according to CB scale, the overall burden of primary caregivers was at the medium level. Therefore, contrary to the expected results, it was not high. Perhaps being primary caregivers leads to the satisfaction with the care they can provide. We recorded the highest values of burden on the subscale “disappointment.” This may result from the fact that mothers, because of relentless care they provide, had abandoned their own plans and dedicated themselves to the ill child. We also observed an excessive burden on the subscale “the overall effort,” which probably resulted from the physical and mental fatigue and from the sense of responsibility for an ill child. This seems even more sig- nificant in view of the fact that only 1/3 of mothers/care- givers stated that they receive help from other people so that they are most exposed to an excessive burden. The GHQ-12 can determine mental health, experienced distress, and identify people who are likely to develop mental health problems. In our study, more than half of the patients’ mothers received the score … Pediatr Nephrol (2013) 28:2157–2167 DOI 10.1007/s00467-013-2532-6 Psychosocial aspects of children and families of children treated with automated peritoneal dialysis Katarzyna Kiliś-Pstrusińska & Anna Wasilewska & Anna Medyńska & Irena Bałasz-Chmielewska & Ryszard Grenda & Agnieszka Kluska-Jóźwiak & Beata Leszczyńska & Ilona Olszak-Szot & Monika Miklaszewska & Maria Szczepańska & Marcin Tkaczyk & Agnieszka Tkaczyk & Katarzyna Zachwieja & Maria Zajączkowska & Helena Ziółkowska & Ilona Zagożdżon & Danuta Zwolińska Received: 28 January 2013 / Revised: 21 May 2013 / Accepted: 31 May 2013 / Published online: 16 August 2013 # The Author(s) 2013. This article is published with open access at Springerlink.com Abstract Background The aim of this study was to analyze psycho- social aspects of chronic kidney disease (CKD) in children treated with automated peritoneal dialysis (APD). Methods The study assessed 41 children > 2 (range 2.1–18) years of age and their parents. Data concerning the illness and sociodemographic parameters were collected. Patients completed the Paediatric Quality of Life Inventory (PedsQL) and their parents the PedsQL-proxy version, General Health Questionnaire (GHQ-12), Berlin Social Support Scales (BSSS), and Caregiver’s Burden Scale (CBS). Results Parents rated their children’s overall health-related quality of life (QoL) as well as their physical and emotional functioning lower than the patients themselves. The majority of primary caregivers had a medium level of the total burden index in the CBS and higher values in the scales need for support and perceived available support than in the received support (BSSS). In the GHQ-12, 51.2 % of primary care- givers had scores >2 points, which indicated the possible occurrence of abnormal mental functioning. Conclusions Financial support for patients’ families is nec- essary. Parents who provide primary care to children on PD require, above all, emotional support and assistance in self- fulfilment. More than half of them may have impaired men- tal function. There is the strong need to provide continuous psychological care for caregivers. Differences in perception K. Kiliś-Pstrusińska (*) : A. Medyńska : D. Zwolińska Department of Paediatric Nephrology, Wrocław Medical University, ul. Borowska 213, 50-556 Wrocław, Poland e-mail: [email protected] A. Wasilewska Department of Paediatrics and Nephrology, Medical University of Białystok, Białystok, Poland I. Bałasz-Chmielewska : I. Zagożdżon Department of Paediatric & Adolescent Nephrology & Hypertension, Medical University of Gdansk, Gdansk, Poland R. Grenda : A. Urzykowska Department of Nephrology, Kidney Transplantation and Hypertension, Children’s Memorial Health Institute, Warsaw, Poland A. Kluska-Jóźwiak Department of Paediatric Cardiology and Nephrology, Poznan University of Medical Sciences, Poznan, Poland B. Leszczyńska : H. Ziółkowska Department of Paediatrics and Nephrology, Medical University of Warsaw, Warsaw, Poland I. Olszak-Szot Department of Nephrology, Children Hospital, Toruń, Poland M. Miklaszewska : K. Zachwieja Polish-American Children’s Hospital, Jagiellonian University, Krakow, Poland M. Szczepańska Clinic of Paediatrics, Nephrology and Endocrinology, Silesian Medical University, Zabrze, Poland M. Tkaczyk Nephrology Division, Polish Mothers’ Memorial Hospital Research Institute, Łodź, Poland M. Zajączkowska Department of Paediatric Nephrology, Medical University of Lublin, Lublin, Poland ORIGINAL ARTICLE mailto:katarzyna.kilis-pstrusins[email protected] 2158 Pediatr Nephrol (2013) 28:2157–2167 of the children’s activity in varied areas by the patients themselves and their caregivers may contribute to further problems within families. Keywords Children . Peritoneal dialysis . Health-related quality of life . Parents’ perceived burdens . Primary caregivers Introduction Home peritoneal dialysis (PD) is the preferred chronic dialysis modality for children with end-stage renal disease (ESRD) [1]. Thanks to technological advances, inter alia, various PD regimens and solutions, as well as clinical experience, patient survival and somatic condition has improved [1, 2]. Never- theless, impaired health-related quality of life (HRQoL) among patients on dialysis remains a challenge [3]. Patient’s QoL is closely related to the family, especially when the patient is on PD. In addition to the typical parental responsi- bilities and activities of providing support, parents must also be engaged in the therapeutic process [4, 5]. In many cases, the home environment is medicalized, with family members becoming the main caregivers burdened with many responsi- bilities related to PD and thus affects the life of the patient’s family. On the other hand, each parent’s perception of their psychosocial situation, as well as their reaction to it, may affect the relationship between parents and their children and the child’s functioning [6, 7]. Before the decision concerning renal replacement treatment (RRT) is made, it is necessary to assess the family’s social, psychological, and economic background and recognize the needs of parents/caregivers [2, 8]. Disregarding those factors creates the risk of complicating the method. Thus far, psycho- social aspects of children with chronic kidney disease (CKD) treated with automated peritoneal dialysis (APD) have rarely been analyzed, and never in Poland. Therefore, we conducted a multicenter national study with the aim of analyzing the psychosocial situation in families of children treated with APD. We gave particular attention to parents’ perceived burdens. We considered children’s HRQoL as perceived by themselves and as by their parents, because perceiving the QoL of sick children is one element of assessing the family situation. Another aim was to determine in which areas of everyday life the families of children treated with APD require support. Methods Eleven of 12 pediatric dialysis centers in Poland participated in the cross-sectional national study. The research was conducted on children with ESRD treated with APD and their parent–proxies between September and December 2011. The study protocol adhered to the Declaration of Helsinki and was approved by the Ethics Committee of Wrocław Medical University. Written informed consent was obtained from all participants >16 years of age and all parents before enrollment in the study. Verbal consent was obtained from patients <16 years where possible. Inclusion criteria for children were as follows: 1. CKD diagnosed at least 12 months prior to the study, 2. PD beginning at least 3 months prior to the study, 3. age ≥2 years, and 4. informed consent. Exclusion criteria for children comprised: 1. a history of severe to profound mental retardation, 2. renal, other solid-organ, bone marrow, or stem cell transplantation, 3. cancer/leukemia diagnosis, 4. hospitalization within 14 days (excluding hospitalization due to peritoneal dialysis control visit), and 5. a significant life event unrelated to their kidney disease in the past 30 days, such as losing a family member. In Poland, there is a common treatment protocol for managing children on APD, with PD nurses who meet the families predialysis. The nurses work in a dialysis center. Home visits prior to dialysis are done by district nurses who also do the follow-up visits. The district nurses are in constant contact with the PD nurses. The PD family has access to district social workers and psychologists. Medical files were analyzed to obtain the following data: primary diagnosis of kidney disease, patient’s age at time of CKD diagnosis, illness duration, APD duration, nephrologic care duration, additional nonrenal comorbidities, place of living and distance from a nephrologic center, and family history. Additionally, school-age children and their parents were asked about schooling level and special education requirements (supplementary tutoring or an individualized education program). Then, both parents were invited to fill out questionnaires regarding changes in their families after the child’s CKD diagnosis and their relationship with the people in their immediate surroundings. Questionnaires were completed on a visit to the renal center, and each parent filled out the questionnaire separately. In the next step, we used Pediatric Quality of Life Inventory (PedsQL) 4.0 Generic Core Scales [9, 10]. We obtained the user agreement from Christelle Berne, Mapy Research Institute in Lyon, France. In addition, parents underwent the following test studies: the 12-item General Health Questionnaire (GHQ-12) [11], Berlin Social Support Scales (BSSS) [12, 13], and the Caregiver’s Burden Scale (CBS) [14]. All tests were translated and validated in Poland [15–17]. Cronbach’s α for GHQ-12 is 0.72 and for the four subscales of BSSS ranges from 0.70 to Pediatr Nephrol (2013) 28:2157–2167 2159 0.86. Cronbach’s α is 0.88 for the total scale of CBS and ranges from 0.74 to 0.82 for the subscales. The PedsQL assesses physical, emotional, social, and school functioning in children and adolescents. The mea- sure comprises a report from children 5–18 years of age and a parent report for children between 2 and 18 years of age regarding the child’s HRQoL. The PedsQL 4.0 Ge- neric Core Scales were specifically designed to measure the core health dimensions outlined by the World Health Organization. The GHQ-12 measures psychological distress and is used to detect nonpsychotic psychiatric disorders such as depres- sion or anxiety in adults [11]. The scale asks whether the respondent has experienced a particular symptom or behav- ior recently. Each item is rated on a four-point scale (less than usual, no more than usual, rather more than usual, or much more than usual). The GHQ-12 is brief, easy to complete, and its application in research settings as a screening tool is well documented. We used the original scoring method in our study (response categories score: 0, 0, 1, and 1, respec- tively). This produces scores ranging from 0 to 12; the higher values indicate more psychological symptoms. The original BSSS includes six independent subscales (perceived available support, need for support, support seek- ing, actual received support, provided support, and protective buffering) and measures both the cognitive and behavioral aspects of social support [12, 13]. With the authors’ consent, four subscales were used for this study: perceived available support (8 items), need for support (4 items), support seeking (5 items), and actual received support (15 items). The per- ceived support subscale comprises items of emotional and instrumental support; the overall received support includes items of emotional, instrumental, and informational support. The response format is the same for all subscales. Individuals rate their agreement with the statements on a four-point scale [strongly disagree (1), somewhat disagree (2), somewhat agree (3), and strongly agree (4)]. An average mean within the range of 1–4 was calculated for each subscale. A higher score indicated greater burden. The CBS uses 22 items to assess the subjective burden of caregivers to chronically ill individuals [14]. All items are scored between 1 and 4 (not at all, seldom, sometimes, often) and cover areas such as the caregiver’s health, feeling of psychological well-being, relationships, social network, physical workload, and environmental aspects that might prove important. The scale was divided into five indices: general strain (8 items), socialization (3 items), disappoint- ment (5 items), emotional involvement (3 items), and envi- ronment (3 items). The total burden index is the mean of all 22 items. The higher the score, the greater the burden. The overall mean of a caregiver’s burden score was defined as low burden (1.00–1.99), medium burden (2.00–2.99), and high burden (3.00–4.00) [14]. All tests were designed according to the general protocol and administration guidelines. Statistical analyses Statistical analyses were performed using R for Windows, version 2.15.1 (The R Foundation for Statistical Computing, Vienna, Austria) and MedCalc for Windows, version 12.3.1.0 (MedCalc Software, Mariakerke, Belgium). Medians, quartiles, frequencies, and percentages were reported to describe data, as appropriate. Qualitative analyses were conducted using a chi-squared test or Fisher’s exact test. Quantitative variables were tested for normality distribution by a Kolmogorov–Smirnov test. For comparison between groups, the Mann–Whitney and Kruskal–Wallis tests were used, as appropriate. Spearman’s correlation analysis was used to determine the correlation between parameters. A p value <0.05 was considered statistically significant. Results Taking into consideration inclusion and exclusion criteria, except for parents’ consent, 50 children were qualified for inclusion in the study/examination. Final studies were conducted among 41 children with APD whose parents gave their consent. Among the 82 parents and/or their guardians (all Polish), data from 40 mothers (one mother maintains no contact with her sick child) and 39 fathers were analyzed. Four fathers do not live with their families, but two mothers provided the fathers’ information. In subsequent parts of the analysis, only the results of fully completed surveys were taken into consideration. Survey results Characteristics of the examined children are presented in Table 1. All children at their compulsory school age (> 5 years, n =30) carried on their education. Thirteen children (44.8 %) went to school (including two attending special schools); 16 patients were home-schooled (55.2 %). One child did not provide information with regard to the type of learning. Eleven pupils (37.93 %) required no help with their studying; the remaining 18 children (62.07 %) received assistance from their parents. The number of school days (or lesson days at home) missed in the previous 6 months was (median, quartiles) 10 (0–30). The characteristics of APD children’s families, their par- ents in particular, are presented in Table 2. Most children were growing up in complete families; only five of them lived with one parent (four with the mother and one with the father). Thirty children had siblings (26 of them one or two; four had three to six). Family household incomes come from 2160 Pediatr Nephrol (2013) 28:2157–2167 Table 1 Basic characteristics of automated peritoneal dialysis (APD) children Parameter Number= 41 Percentage Age, mean ± SD, (years) 9.24± 5.09 Children <5 10 24.4 ≥ 5 31 75.6 Gender Female 14 34.15 Male 27 65.85 Cause of CKD Chronic glomerulonephritis 13 31.71 Anomaly of kidney and urinary tract and chronic pyelonephritis 15 35.58 Hereditary kidney disease 9 21.95 Others 3 7.32 Unknown cause 1 2.44 Comorbidity Yes 6 14.6 No 35 85.4 Family renal history Yes 4 9.76 No 37 90.14 Place of residence (size) Village or town <50,000 residents 27 65.85 Town 50,000–100,000 residents 3 7.32 Town > 100,000 residents 11 26.83 Age (years) at CKD diagnosis, median (quartiles), 1.5 (0.02–6.0) CKD duration (years), median (quartiles) 4.17 (2.21–8.15) Nephrological care duration (years), median (quartiles) 4.0 (2.25–8.18) PD therapy (years), median (quartiles) 1.98 (0.71–2.25) PD peritoneal dialysis; CKD Distance from nephrology center (km), median (quartiles) 65.0 (21.5–102.5) chronic kidney disease Number of hospitalizationsa, median (quartiles) 6.0 (3.0–6.0) a In the previous 6 months various sources but mostly from professional careers, indi- cated by 82.5 % of parents (multiple choice options). Other sources of income included annuity and/or pension, which were indicated by 15 % of parents, and social welfare in 47 % of respondents. Parents’ perceived change in their families’ situation after the child’s CKD diagnosis is summarized in Table 3. No statistically significant differences were found with respect to the parents’ gender. Use of social welfare and unemployment, and deterioration in financial situation in parents’ evaluation (Tables 2 and 3) showed a harsh economic situation for the family. Each parent was asked to evaluate their relationships with the people in their immediate surroundings and with medical staff by assigning points from 1 (very bad) to 5 (very good). Results are shown in Table 4. Differences between fathers’ and mothers’ assessments were not statistically significant. In each family, parents indicated the sick child’s main care- giver. The group of primary caregivers comprised 40 mothers and one father. Guardians (henceforth referred to as primary caregivers) were asked to share their expectations toward medical personnel. Twelve individuals (29.3 %) described their expectations toward nurses. In addition to general terms, such as “providing care” and “help”, attention focused on the assistance provided during the hospital stay, sharing more information regarding PD, greater professionalism, and better contact with the child. With respect to physicians, nine individuals (22 %) expected “good care” and more detailed information about the patient, mainly about the projected course of the disease and their child’s future. Only 15 primary caregivers (36.59 %) asserted that their child’s kidney transplantation was discussed. Test results The PedsQL test results in the entire group of parents who provide primary care for APD children (n =41) were signif- icantly lower in relation to results among parents of healthy children published in the literature, both within the scope of overall HRQoL (51.0 ±16.42 vs 81.34±15.92, p <0.01) and Pediatr Nephrol (2013) 28:2157–2167 2161 Table 2 Basic characteristics of parents and families of children on automated peritoneal dialysis PedsQL test results among children between 5 and 18 years of age (n=31) and both parents. All primary guardians and 13 “secondary parents” completed the tests. Both parents rated their children’s physical and emotional functioning as well as their overall HRQoL as significantly lower than the sick children did themselves. The patients rated their social func- tioning higher than did their primary caregivers. No signifi- cant differences were found in the evaluation of school func- tioning between the studied groups. The intraclass cor- relation coefficient (ICC) between primary parent and child reports was calculated to be 0.74. The ICC between secondary parent and child reports and between primary and secondary parent reports were calculated to be 0.68 and 0.64, respectively. Parents’ test results are demonstrated in Table 6. There were no significant differences within the scope of social support (perceived available support, the need for such sup- port, support seeking, and received support) between prima- ry and secondary parents (BSSS results). The CB scale demonstrated that the average total burden index in primary caregivers was medium. Results obtained also correspond with medium burden in the following subscales: general strain, social isolation, and disappointment. Low levels of burden were observed in the emotional involvement and environment subscales. The results in the secondary parents group indicate lower general strain than in primary guard- ians; no significant differences were demonstrated with re- spect to the remaining subscales; however, the average total burden index (2.0) borders on low and medium burden. GHQ-12 results in the group of primary caregivers were significantly higher than in the group of secondary care- givers. In addition, scores >2 points, which indicated the possible occurrence of abnormal mental functioning, were observed in 51.2 % of primary parents and in only 23.53 % of parents who did not provide primary care. There was no SD standard deviation a One mother does not live with her child (no contact). b Four fathers do not live with their families, but in the case of two fathers, the mothers provided their information. c No information was provided for two fathers in individual subscales: physical functioning (49.24±18.75 vs 83.26±19.98, p<0.01), emotional functioning (55.12±18.5 vs 80.28±16.99, p<0.01), social functioning (55.24±22.11 vs 82.15±20.08, p<0.01), and school functioning (55.7±28.93 vs 76.91±20.08, p<0.01) [9]. Similarly, PedsQL test results among APD patients (5–18 years of age) were significantly lower sta- tistically (p<0.01) than in a group of healthy children: phys- ical functioning (61.19±18.57 vs 86.86±13.88), emotional functioning (66.29±14.08 vs 78.21±18.64), social function- ing (69.19±22.11 vs 84.04±17.43), school functioning (65.83±28.93 vs 79.92±16.93), and overall HRQoL (65.83±28.93 vs 82.87±13.6) [9]. Table 5 summarizes the significant correlation between BSSS, CBS, and GHQ-12 and parents’ age, education, professional career, family structure (complete/single parent), having or not having oth- er children, and source of income (professional career vs welfare benefits). The level of general strain (CBS) declared by women was significantly higher than that declared by men (2.63, 1.91–3.0 vs 1.94, 1.75–2.75, p = 0.03). Guardians who live in medium-sized cities demonstrated a higher level of social isolation (3, 2.33–3.42) and total burden index (2.59, 2.0–2.77) than residents in rural areas and in large cities (social isolation 2.0, 1.33–2.75 and 2.33, 1.37–2.84, respectively; p = 0.02; total burden index: 1.82, 1.58–2.48 and 2.16, 1.7–2.73, respectively; p= 0.01). No significant differences were found between residents in rural areas and large cities in this regard. Perceived available instrumental support was lowest among small-town residents (3.25, 2.19–4.0) in comparison with village residents (3.75, 3.75–4) and city residents (4.0, Parameter Number Percentage Mothers 40a 100 Age, mean ± SD, (years) 28.16±6.0 Mother’s education level Elementary/trade school 14 35 High school 15 37.5 University degree 11 27.5 Employment Yes 29 72.5 No 11 27.5 Healthy Yes 34 85 No 6 15 Fathers 39b 100 Age, mean ± SD, (years) 40.03±9.27 Father’s education level Elementary/trade school 24 61.54 High school 7 17.95 University degree Employmentc 8 20.51 Yes 30 81.1 No 7 18.9 Healthy Yes 33 84.62 No 6 15.38 Family Full 36 87.8 Single-parent 5 12.2 Sibling Yes 30 73.17 No 11 26.83 2162 Pediatr Nephrol (2013) 28:2157–2167 Table 3 Changes in the family observed by the parents after chronic kidney disease (CKD) diagnosis in the child Mothers’ evaluation n=40a Fathers’ evaluation n =35a P valued Yes No Yes No n % n % n % n % Change of location of residence 3 7.5 37 92.5 1 2.86 34 97.14 0.61 Changes made to current residence 24 60 16 40 20 57.14 15 42.86 0.81 Change in financial status 16 40 24 60 16 45.71 19 54.29 0.64 Deterioration 16 40 16 45.71 Improvement 0 0 Change of income source 9 22.5 31 77.5 7 20 28 80 1 Caring for the child 0.14 Mother 34 85 24 68.57 Father 1 2.5 1 2.86 Both parents 5 12.5 10 28.57 Participation of other people in child care 22 55 18 45 18 51.34 17 48.57 0.81 Grandparents 18 15 Siblings 2 3 Cousins 2 0 Changes in attitude toward the ill child 15 37.5 25 62.5 9 25.71 26 74.29 0.32 Improvement 14 35.0 9 25.71 Deterioration 1 2.5 0 Changes in attitude toward other children b4 13.33 26 86.67 c4 16.0 21 84.0 1 Improvement 4 13.33 3 12 Deterioration 0 1 4 Changes in relations among children b10 33.33 20 66.67 c6 24 19 76 0.55 Improvement 9 30.0 6 24 Deterioration 1 3.33 0 Changes in social contacts 25 62.5 15 37.5 17 48.57 18 51.43 0.25 Improvement 1 2.5 0 Deterioration 24 60.0 17 48.57 New friendship 28 70 12 30 17 48.57 18 51.43 0.09 Data shown as a number of responses (percent) a Data collected from 75 surveys (40 mothers, 35 fathers); missing surveys (7; 7.32 %): 4 fathers, 1 mother, who do not live in the same household; 2 fathers did not fill out this part of the survey b n =30, c n =25; d differences between mothers’ and fathers’ groups, p value Table 4 Evaluation of parents’ relationships with other people: 1 (very bad), 5 (very good) Mother Father n 1 2 3 4 5 n 1 2 3 4 5 Father/mother of the child 38 3 (7.9) 1 (2.6) 5 (13.2) 14 (36.8) 15 (39.5) 35 2 (5.7) 1 (2.9) 2 (5.7) 17 (48.6) 13 (37.1) Child with CKD 40 0 0 1 (2.5) 10 (25) 29 (72.5) 35 0 0 3 (8.6) 14 (40) 18 (51.4) Other children 30 0 1 (3.3) 0 11 (36.7) 18 (60) 25 0 0 2 (8) 13 (52) 10 (40) Friends 40 3 (7.5) 3 (7.5) 10 (25) 12 (30) 12 (30) 35 0 0 8 (22.9) 18 (51.4) 9 (25.7) Nurses 40 1 (2.5) 0 0 15 (37.5) 24 (60) 25 1 (4) 0 1 (4) 13 (52) 10 (40) Doctors 40 1 (2.5) 0 1 (2.5) 13 (32.5) 25 (62.5) 25 1 (4) 0 2 (8) 12 (48) 10 (40) Social workersa 40a 3 (7.5) 0 1 (2.5) 8 (20) 11 (27.5) 25b 3 (12) 2 (8) 0 3 (12) 3 (12) CKD chronic kidney disease Data shown as a number (%) a 17 mothers (42.5 %) did not deal with social workers; b 14 fathers (56 %) did not deal with social workers Pediatr Nephrol (2013) 28:2157–2167 2163 Table 5 Paediatric Quality of Life Inventory (PedsQL) 4.0 generic core scales from child’s self-report (for ages 5–18; n= 31) and parent–proxy report (main caregivers and second parents) Characteristic APD children n =31 Main caregivers of APD children n=31 Second parents of APD children n=13 Physical functioning 62.5 (50.0–75.0) a,b 56.24 (40.63–62.5) 53.13 (39.84–65.63) Emotional functioning 70.0 (56.25–73.75) a,b 55.0 (40.0–70.0) 55.0 (50.0–71.25) Social functioning 70.0 (50.0–90.0) a 55.0 (40.0–70.0) 65.0 (53.75–81.25) School functioning 62.5 (50.0–75.0) 55.0 (35.0–65.0) 60.0 (47.5–70.0) Overall HRQoL 64.13 (51.09–75.0) a,b 54.35 (38.87–64.13) 54.35 (48.91–63.32) Data are presented as median and quartiles (first–third quartile) APD automated peritoneal dialysis a APD children vs. main caregivers, p< 0.05 b APD children vs. second parents, p< 0.05 3.25–4.0) (p= 0.03). Parents living in small towns also per- ceived less available emotional support and sought it to a lesser extent than did others; however, differences were not statistically significant. There was no correlation between BSSS, CBS, and GHQ-12 results and duration of CKD, remaining under the care of a nephrology specialist and the duration of renal replacement therapy, or distance between place of residence and a nephrology center. The method of teaching a child (general; home school) had no effect on parents’ test results. Parents who helped their children with their studying differed significantly from parents who did not help their children in terms of currently received information support (2.9, 2.4–3.2 vs 3.4, 3.0–3.6; p=0.004) and instrumental support (3.2, 2.4–3.8 vs 4.0, 3.2–4.0; p=0.02), which they rated lower. A statistically significant negative correlation was found between PedsQL (total score) and CBS (total burden index) (r= −0.51, p= 0.001) and GHQ-12 (r= −0.55, p = 0.0002); a positive correlation was found between PedsQL (total score) and certain BSSS subscales: need for support (r = 0.31, p =0.05), support seeking (r= 0.36, p =0.02), perceived avail- able emotional support (r= 0.65, p= 0.001), and instrumental support (r = 0.32, p= 0.04). Also, the following correlations were observed: a positive correlation between CBS (total burden index) and GHQ-12 (r= 0.73, p= 0.001) and negative Table 6 General … T The Effects of Kidney-Disease-Related Loss on Long-Term Dialysis Patients’ Depression and Quality of Life: Positive Affect as a Mediator Ramony Chan,*† Robert Brooks,‡ Jonathan Erlich,§ Josephine Chow,† and Michael Suranyi† *Consultation Liaison Psychiatry, †Renal Unit, and ‡Centre for Population Mental Health Research, Liverpool Hospital, and §Department of Nephrology, Prince of Wales Hospital, Sydney, New South Wales, Australia Background and objectives: In kidney disease, the concept of loss is widely discussed but minimally researched. It appears that dialysis patients who grieve a range of losses suffer increased depression and reduced quality of life (QoL). Limited research is partly due to the lack of a relevant loss measure. The study presented here developed a measure and tested the criterion validity of loss in relation to depression and QoL. Design, setting, participants, & measurements: In a cross-sectional observational study, 151 long-term dialysis patients were interviewed using standardized psychometric measures and the Kidney Disease Loss Scale (KDLS), developed for the study. Factor, path and multigroup analyses were conducted. Results: The factor structure and reliability of KDLS were supported. The path analyses supported the criterion validity of loss. It was a stronger contributor to depression than other clinical variables. Its effect on QoL was fully mediated by depression and positive affect (coping). The magnitude of the paths from loss to QoL through depression and positive affect was larger in home-based dialysis patients than in hospital-based patients. Conclusions: KDLS is a promising measure of loss. Patient-defined losses may contribute to the high level of depression and in turn a reduction in patients’ coping and QoL. These findings suggest several points of intervention to improve long-term dialysis patients’ QoL. Clin J Am Soc Nephrol 4: 160 –167, 2009. doi: 10.2215/CJN.01520308 he concept of Kidney-Disease-Related Loss (KDRL) in ESRD has been clinically and theoretically significant for decades (1– 4). ESRD patients experience multiple losses, both tangible and symbolic; for example, loss of physical strengths, freedom, employment, and social life, resulting in grief throughout the course of ESRD and dialysis (1,2,4). Re- solving loss successfully is identified as one of the adaptational factors in ESRD (3). Although widely discussed, there exists no clear definition or measure of KDRL. Loss, traditionally discussed in the context of death, has recently been broadened to comprise loss of significant ele- ments in a person’s life due to chronic illness (5,6). In chronic- illness-caused losses, individual grief responses, rather than actual losses, are of conceptual importance (6). These grief responses, which can persist for many years and cause signif- icant dysfunctions, are shown to be empirically and conceptu- ally different from depression and anxiety in several studies (7– 10). The grief symptomatology is characterized by cognitive preoccupation or rumination, yearning, disbelief, stunned re- sponses, and nonacceptance of losses (7,9,11), which could be summarized as cognitive and affective grief responses (6). Thus, the study presented here defines KDRL as the cognitive and affective grief responses after tangible and symbolic losses due to kidney disease and its treatments. This definition will guide the development of a measure for KDRL. KDRL has traditionally been seen as one of the causes of depression in ESRD patients. In the psychodynamic perspec- tive, depression may be an extension of patients’ grief re- sponses (1) or KDRL may increase patients’ vulnerability to developing depression (4). In the cognitive-behavioral perspec- tive, patients’ cognitive rumination over their losses may lead to depression, as negative rumination has been found to be associated with depression (12,13). There exists a strong inverse relationship between depression and quality of life (QoL) in ESRD patients (14,15). If KDRL is a significant cause of depression, it may have a mediated effect on QoL through depression or KDRL may also independently affect both depression and QoL. Although the literature sug- gests a direct relationship between depression and QoL, posi- tive affect as a way of coping (16,17) may mediate the effect of depression and loss (18). Positive affect may have adaptive values in dealing with chronic stress (16,17) and thus moderate Received March 31, 2008. Accepted July 23, 2008. Published online ahead of print. Publication date available at www.cjasn.org. Correspondence: Ramony Chan, Consultation Liaison Psychiatry, Liverpool Hos- pital, Locked Bag 7103, Liverpool BC, New South Wales 1871, Australia. Phone: 61- 2-9616-4680; Fax: 61-2-9616-4691; E-mail: [email protected] the effect of depression and KDRL on QoL. The clinical validity of KDRL can be understood not only by measuring it, but also by examining its relations to clinical variables, including medical comorbidity, length of time on dialysis, and level of hemoglobin and its effects on hospital- Copyright © 2009 by the American Society of Nephrology ISSN: 1555-9041/401–0160 http://www.cjasn.org/ mailto:[email protected] Clin J Am Soc Nephrol 4: 160 –167, 2009 Role of Loss in Kidney Disease 161 and home-based dialysis patients. It is hypothesized that pa- tients’ KDRL will covary with these clinical variables influenc- ing QoL through depression and positive affect (15,19 –23). Moreover, the clinical observation suggests that hospital-based patients may experience more losses and become accustomed to their effects, whereas home-based patients may regain or min- imize some losses through the advantages of home treatments. Thus, it is assumed that each additional loss for home-based patients will have a greater effect on their well being and QoL, and thus the clinical validity of the KDRL can be demonstrated. The aim of this research is to show the criterion-related validity of the KDRL construct by developing a measure for KDRL, to examine its relationship with relevant psychologic and clinical variables, and its effect on home-based dialysis patients. It is hypothesized that (1) the proposed scale of KDRL will consist of cognitive and affective grief responses and that (2a) loss will lead to depression, (2b) covary with other clinical variables to influence QoL through depression and positive affect, and (2c) influence the home-based patients more. Materials and Methods Participants Participants were recruited from two major university teaching hos- pitals in Sydney South West Area Health Service (SSWAHS) and South Eastern Sydney & Illawarra Area Health Service (SESIAHS) Sydney, Australia. The inclusion criteria were a diagnosis of ESRD, receiving dialysis treatment for approximately 2 yr or more and aged 18 or above. The main exclusion criterion was incapacity to complete questionnaires and/or the semistructured interview with reasonable assistance. Of 209 eligible patients, 31 (14.8%) refused, 7 (3.4%) withdrew during the interview as being too sick to continue, 16 (7.7%) did not return the questionnaires, and 4 (1.9%) did not complete the data collection be- cause of death, transplant, acute medical problems, or cognitive im- pairment. Thus, 151 (72.2%) patients participated in the interview and returned the questionnaires. The sample consisted of 90 (60%) men and 61 women (40%) with the mean age 58 ± 14.28 (SD) yr, the mean duration of dialysis was 67.97 ± 42.84 (SD) mo (range 22 to 248 mo). Approximately half (n 68, 45%) of the participants were doing home- based dialysis, including home hemodialysis (n 26, 17%) and peritoneal dialysis (n 42, 28%), and the others (n 83, 55%) were on hospital-based dialysis including satellite (n 56, 37%) and in-center hemodialysis (n 27, 18%). Procedures This study was approved by the SSWAHS and SESIAHS Ethics Committees. After being informed of the study details and having signed a consent form, participants completed the semistructured in- terview and returned completed questionnaires by mail. One reminder letter and spare questionnaire were sent to those who did not return the questionnaires. Two interviewers were trained in the application of measures before the initiation of the study to ensure the quality of the data collection. Measures Seven variables were examined in the study: QoL, depression, KDRL, positive affect (a key component of coping), medical comorbidity, length of time on dialysis, and hemoglobin. In addition to developing a scale to measure KDRL, standardized measures were used in the study—the Schedule for Evaluation of Individual Quality of Life— Direct Weighting (SEIQoL-DW) (24), the Depression Scale of Depres- sion Anxiety Stress Scale 21 (DASS21) (25), the Positive Affect Scale (PAS) (18), and the Comorbidity Index (CMI) (26,27). Additional ques- tions were included to collect participants’ demographic and dialysis related information including length of time on dialysis (the total number of months). Hemoglobin level was an average over 3 mo, including the month of the research interview. The Kidney Disease Loss Scale The measurement context in which an individual considers their losses will in part determine the validity of the measurement. The con- text can be determined from individual-defined losses or from a stan- dard set of losses. The type and importance of losses varies widely between patients and thus a predefined set of losses may only be partially relevant to any individual’s experience (6,24). The Kidney Disease Loss Scale (KDLS) was constructed to first elicit the five most important individual KDRL and second to obtain cognitive and affec- tive grief responses. A second-order factor structure of KDLS was hypothesized with four statements measuring cognitive rumination and four measuring the affective response to loss. The SEIQoL-DW The SEIQoL-DW is a patient-centered semistructured interview to measure individual QoL (24). It was chosen because of known limita- tions in multidimensional measures of QoL (28) and its ability to produce both qualitative and quantitative data. Of particular impor- tance for renal patients are that preselected life domains may not be relevant, and equal weighting of life domains is inconsistent with patients’ own values (29,30). In the SEIQoL-DW, the five most important areas of a respondent’s life are elicited, then the level of satisfaction and relative importance of each area is determined. Its global index score, ranging from 0 to 100, is the sum of a product of the ratings and weightings of each nominated area. Its reliability, validity, and utility in the medical and ESRD pop- ulations are excellent (24,30 –33). The DASS21 The DASS21 is a 21-item scale, comprising of three subscales: depres- sion, anxiety, and stress (seven items each), a total score for each subscale ranging from 0 to 21. Only scores on the depression subscale were used in the analyses. The DASS21 focuses on the cognitive and affective aspects of depression, limiting the methods bias of using a measure that contains somatic elements common to depression and kidney disease (2,34,35). Additionally, it was developed in the Austra- lian population (the site of this study); it has strong psychometric properties in both general and clinical populations (25,36,37); it is relatively short, reducing administrative burden on patients; and dif- ferentiates depression, anxiety, and stress. PAS The PAS is a four-item scale on a Likert scale ranging from 0 (not at all) to 10 (very much), with a total score ranging from 0 to 40 to measure individual positive feelings. Its reliability and discriminant and conver- gent validities have been well established (18). CMI The CMI was compiled on the basis of Friedman’s Index (26) and Charlson’s Index (27). It is in a checklist format, with scores ranging from 0 to 15, higher scores indicating more comorbid conditions. 162 Clinical Journal of the American Society of Nephrology Clin J Am Soc Nephrol 4: 160 –167, 2009 Data Analyses Analyses were performed with SPSS 15 (38) and LISREL 8.72 (39). Missing data were rare and nonsystematic and thus replaced using EM (expectation-maximization) method (38,40). The first set of analyses examined and validated the factor structure of the KDLS using confir- matory factor analysis (CFA) and exploratory factor analysis (EFA). Standard techniques of correlation, ANOVA, and t test were used with a critical value of alpha set to 0.05. The final set of analyses used structural equation modeling (SEM) to test, develop, and examine alternative models. Multigroup analyses were used to compare hospital and home dialysis. The two-step approach was used with SEM (41). Composite scores of the observed variables, using the unit-weighted addition method, were calculated and error variances fixed in the measurement model (42,43) before the structural model was tested. Because the distributions of the observed variables were skewed, SEM was undertaken using “asymp- tomatic distribution free covariance” matrices using the robust maxi- mum likelihood and the Satorra-Bentler statistic for parameter estima- tion (44 – 46). Several goodness-of-fit (GFI) indices were chosen to evaluate the overall model fit (40): Satorra-Bentler x2 test (P > 0.05, in SEM nonsignificant x2 indicates a good model fit), the GFI (>0.90), adjusted GFI (AGFI) (>0.90), the root mean square residual (RMR; close to 0), the root mean square error of approximation (RMSEA; <0.05, 90% confidence interval <0.08), and the comparative fit index (CFI; >0.90). Results Development of KDLS The hypothesized factor structure of KDLS was not sup- ported using CFA [x2 73.44, degrees of freedom (df) 19, P 0.00, RMSEA 0.09, GFI 0.89, AGFI 0.80, CFI 0.99, RMR 0.05; LISREL 8.72 39]. Re-examining the data, EFA using SPSS (38) indicated two factors with 72.24% of the total variance explained. There were two items loading onto both factors and therefore excluded (42). The first factor consisted of four items and resembled cognitive responses and the second factor consisted of two items reflecting affective responses. The second factor was retained for its theoretical importance and the items’ correlation was greater than 0.7 (47). The two factors were strongly correlated (r 0.71, P < 0.01), suggesting the previously hypothesized second-order factor. The new factor structure and possible second-order factor model were exam- ined using CFA (x2 12.63, df 8, P 0.128, RMSEA 0.00, GFI 0.97, AGFI 0.93, CFI 1.00, RMR 0.03) (LISREL 8.72 39). The first-order factors measure cognitive and affective responses and a second-order factor reflects an overall sense of loss re- garding self-defined KDRLs. Therefore, the KDLS comprises an overall loss scale by summing the six items (48) and two sub- scales (see Table 1). High scores are indicative of greater sense of loss, with more rumination and stronger affect. The internal consistence of KDLS was good (a 0.88 for both the cognitive and affective subscales). The convergent and discriminant validity of KDLS were supported by its significant positive correlation with depres- sion (r 0.60, P < 0.01), and negative correlation with QoL (r -0.20, P < 0.05) and positive affect (r -0.36, P < 0.01). It was unrelated to clinical variables (hemoglobin r 0.07, comorbid- ity r 0.04, length of time since dialysis r -0.15). Construct validity was examined by conducting a two-factor EFA of the six KDLS and the seven DASS21 depression items. The depres- sion items loaded onto one factor and KDRL items loaded onto another without cross-loading items. Patients’ nominated losses on KDLS were codified by two independent coders by iteratively examining the data. The intercoder agreement was 95% and the differences in the re- maining 5% were resolved by consensus. In total, 109 of 151 respondents nominated 431 losses. Of the 23 types of losses identified, the seven most common were travel (18.56% of the total nominated losses), leisure activities (12.06%), physical functioning (10.90%), employment/work (9.74%), family/per- sonal relationships (6.50%), freedom (perception of being free from constraints; 4.87%) and social life (4.87%). The mean score difference on KDLS between those who did not nominate losses (x- 5.41) and those who did (x- 5.84) was nonsignificant (t 0.49, df 149, P > 0.05). Univariate Analyses There was no gender differences in the variables used in the study. An examination of differences between the two hospitals identified a significant difference in hemoglobin levels (SS- WSAH x- 123.84 (13.88), SESIAHS x- 117.13 (14.05), P < 0.01); there were no differences on other variables. There were no treatment modality (in-center hemodialysis, home hemodi- alysis, peritoneal dialysis, satellite hemodialysis) differences on any variable. Path Analyses Model Testing and Modification. The structural relation- ships between length of time on dialysis, hemoglobin, comor- bidity, loss, depression, positive affect, and individual QoL were examined using SEM. The hypothesized path model was not supported (x2 16.57, df 8, P 0.04, RMSEA 0.09; for all fit statistics see Table 2). Therefore, the model modification process was conducted to improve the model fit by examining the t-values of path coefficients, standardized residual values, and modification indexes. The path from hemoglobin to de- pression was insignificant and thus deleted, and an additional path from comorbidity to positive affect added (x2 7.91, df 13, P 0.85, RMSEA 0.00; see Table 2 and Figure 1), indi- cating a plausible model for the observed data. As shown in Table 3, each variable explained a small pro- portion of variance in QoL with positive affect (9.6%) and hemoglobin (4.8%) having the highest direct effect. The effects on positive affect from comorbidity and length of time since dialysis were moderate whereas depression explained the larg- est proportion (29.2%) of variance in positive affect. Loss ex- plained 38.4% of variances in depression, larger than comor- bidity (2.3%) and length of time since dialysis (5.3%), and only had a small effect on QoL fully mediated by depression and positive affect. Alternative Models In covariance structure modeling, several equivalent mod- els may exist (40). Two theoretically based alternative mod- Clin J Am Soc Nephrol 4: 160 –167, 2009 Role of Loss in Kidney Disease 163 Table 1. The final version of the Kidney Disease Loss Scale (KDLS)a When you consider life as it is now with kidney disease and dialysis treatments, it is clearly different from what your life used to be or would have been. You might find yourself having lost many things. Please consider LOSSES: things that you used to do before kidney disease/dialysis and now you cannot do anymore or things that you would have been doing if you did not have kidney disease/dialysis. Please list below the five most important things you have lost because of the kidney disease/dialysis. 1: 2: 3: 4: 5: In regard to the five losses described above, please read each of the following statements carefully and circle a number 0, 1, 2 or 3 that indicates how much the statement applied to you The rating scale is as follows: 0 Did not apply to me at all 1 Applied to me to some degree, or some of the time 2 Applied to me to a considerable degree, or a good part of time 3 Applied to me very much, or most of the time 1. I think about these losses so much that it is hard for me to do the everyday things I normally do 0 1 2 3 2. Memories of the losses upset me 0 1 2 3 3. I am preoccupied with thoughts of the losses 0 1 2 3 4. I feel myself longing for regaining what I have lost 0 1 2 3 5. I feel disbelief over what happened 0 1 2 3 6. I feel stunned or dazed over what happened 0 1 2 3 aThe first part of the KDLS that requires respondents to nominate the five most important losses must be retained when the KDLS is used, because it sets the context for rating the six items. els were also tested. Alternative model 1 was to examine if depression has a direct effect on QoL, and alternative model 2 was to investigate the ordinal relations between KDRL and depression. The x2 difference statistics showed that alterna- tive model 1 was not a better model (x2D 1.85, dfD 1, nonsignificant, P < 0.05; also see Table 2). Alternative model 2 was rejected by the fit statistics (Table 2); depression does not precede KDRL. Table 2. The goodness-of-fit statistics of the hypothesized, modified, and alternative modelsa Path Models Goodness-of-Fit Statistics Hypothesized path model x2 df P GFI AGFI RMR RMSEA 90%CI CFI 16.57 8 0.04 0.97 0.89 16.25 0.09 0.02 to 0.14 0.95 Modified path model x2 df P GFI AGFI RMR RMSEA 90%CI CFI 7.91 13 0.85 0.99 0.97 15.81 0.00 0.00 to 0.05 1.00 Alternative model 1b x2 df P GFI AGFI RMR RMSEA 90%CI CFI 6.06 12 0.91 0.99 0.98 17.42 0.00 0.00 to 0.03 1.00 Alternative model 2c x2 df P GFI AGFI RMR RMSEA 90%CI CFI 41.20 13 0.00 0.93 0.84 13.33 0.12 0.08 to 0.16 0.84 ax2, Satorra-Bentler scaled chi-square; df, degrees of freedom; GFI, goodness-of-fit index; AGFI, adjusted GFI; RMR, root mean square residual; RMSEA, root mean square error of approximation; NNFI, non-normed fit index; CFI, comparative fit index. bAdditional path from depression to quality of life was added in the model. cKidney-disease-related loss precedes depression, given all other parameters being constant. 164 Clinical Journal of the American Society of Nephrology Clin J Am Soc Nephrol 4: 160 –167, 2009 Figure 1. Path diagram of the final modified model of KDRL. QoL, quality of life; PA, positive affect; KDRL, kidney-disease-related loss; CM, comorbidity; LT, length of time since dialysis (months); Hb, hemoglobin level. Figures in gray are standardized coefficients. Figures in brackets are estimates. KDRL in Relation to the Treatment Location Effect To further demonstrate the criterion validity of KDRL, a multigroup analysis on the hospital- and home-based dialy- sis patients was conducted. The poor global fit statistics (x2 135.66, df 38, P 0.00, RMESA 0.19) suggested differences between the two groups. A reasonable fit (x2 43.87, df 34, P 0.12, RMSEA 0.06) of the re-specified model suggested that the main difference was a greater strength of the relations between KDRL, depression, positive affect, and QoL in home-based dialysis patients, although Table 3. Standardized direct, indirect, total effects of the variablesa CMI Loss Hemoglobin Length of Time Since Dialysis Positive Affect Depression Direct effects QoLb - Positive affect -0.23 Depression 0.16 Indirect effects QoL -0.10 -0.11 - -0.04 - -0.17 Positive affect -0.08 -0.34 - -0.12 - - Depression - - - - - - Total effects QoL -0.10 -0.11 0.22 -0.04 0.31 -0.17 Positive affect -0.31 -0.34 - -0.12 - -0.54 Depression 0.16 0.62 - 0.23 - - aStandardized total effect is the sum of direct and indirect effects of one variable on another variable. Its value ranges from 0 to 1 with either negative or positive direction. The larger the value is, the stronger the effect is. bQoL, quality of life. - - 0.22 - - - 0.31 - - -0.54 0.62 - 0.23 - - Clin J Am Soc Nephrol 4: 160 –167, 2009 Role of Loss in Kidney Disease 165 mean score differences on these variables between the groups were nonsignificant. Discussion The study presented here provides empirical support for KDLS and the hypotheses that loss leads to depression, cova- ries with length of time since dialysis to influence QoL through depression and positive affect, and has greater effect on home- based patients. Moreover, the moderate direct effect that he- moglobin has on QoL is consistent with previous clinical trials showing erythropoietin treatment enhances ESRD patients’ QoL (49). The concept of KDRL is operationalized by KDLS, which has encouraging psychometric properties. Consistent with previ- ous research, depressive and loss symptoms loaded onto sep- arate factors, and the path analyses demonstrated that KDRL precedes depression (7–10). Thus the KDRL is empirically dis- tinct from depression. The cognitive rumination, yearning, dis- belief, and stunned responses remain the key symptomatology that contributes to depression. KDRL as a strong contributor to depression is consistent with the previous theories that loss is a significant cause of depres- sion. Although the findings presented here may not support depression as being an extension of KDRL, whether depression is due to increased vulnerability or cognitive rumination over negative contents of loss remains equivocal. Perhaps, more cognitive rumination items contributing to the total score of KDLS may suggest that cognitive rumination is the underlying mechanism between KDRL and depression. Nevertheless, the findings that travel, leisure activities, and physical functioning are the most nominated types of losses may not be surprising clinically, because many dialysis patients commonly describe their dialysis experiences as being restrictive. Therefore, these results may suggest that to improve patients’ depression and QoL, psychosocial interventions could target loss; for example, helping patients to regain losses by helping them to travel or perform activities more, or to process their related thoughts and feelings by reducing their cognitive ruminations. Encour- agingly, these findings have already changed the educational practice of one of the renal units where the study was con- ducted. Another interesting finding of the study is that the effect of both KDRL and clinical variables on QoL is mediated by de- pression and positive affect. This shows that disease-specific variables may influence QoL indirectly through psychologic states (50). However, the type of psychologic states has not been explicitly specified, but rather implicitly assumed to be depression in the ESRD literature. The findings presented here suggest that both positive and negative psychologic states could act as mediators. Positive affect may be a distinct factor and has adaptive values buffering the effect of loss and depres- sion on QoL (17,18). The criterion validity of the KDRL construct is also illustrated by the multigroup analyses showing that a stronger magnitude of the relations between KDRL and other psychologic variables exists for home-dialysis patients. For a small increase in their sense of loss, home-based patients experience more depression and greater decline in positive affect and QoL than do the hospital-based. This may mean that psychosocial interventions for home-based dialysis patients, especially on the KDLS and depression, could result in greater improvement in their QoL and potentially delay the need for hospital-based treatment. The study presented here has several limitations. The KDLS is a newly developed scale and awaits further research to crossvalidate its validity and reliability. Future research may also focus on item generation for the affective subscale of KDLS to improve its construct validity. Because the main purpose of the path analyses results was to examine the construct validity of the KDLS, the substantive meaning of the model requires replication in different samples. The sample size for the multi- group analyses is considered small in SEM, and although con- sistent with preliminary expectations, the interpretation of these results should be cautious. Overall, the study presented here demonstrated the construct and criterion validity of KDRL and the promising psychometric properties of KDLS. KDRL may lead to depression and through it reduces QoL. The effect of depression is mediated by the coping mechanism of positive affect. The development of any new scale requires multiple studies to fully understand its properties. Studies in different populations (e.g., pre- and early- dialysis patients) will also add to the construct validity. Acknowledgments The results of this paper were presented at the American Society of Nephrology 40th Annual Scientific Conference, San Francisco, Califor- nia, 2007 and the 43rd Annual Scientific Meeting of the Australian and New Zealand Society of Nephrology, Gold Coast, Australia, 2007. The abstract of this paper has been published in Nephrology (Chan, R, Brooks, R, Erlich, J, Chow, J, Suranyi, M: The role of kidney disease related loss in dialysis patients’ quality of life: depression and positive affect as mediating …
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