TITLE: Sensitivity of Three Widely Used Questionnaires for measuring Psychological Distress among patients with Type 2 Diabetes Mellitus Tan LSM, 1 Khoo EYH, 2 Tan CS,1 Griva K, 3 AMIR Mohamed 3, NEW Michelle 2, Lee YS, 4 Lee Jeannette, 1 Tai ES, 1,2 Wee Hwee-‐lin 5,6 1.
School of Public Health, Yong Loo Lin School of Medicine, Singapore
2.
Department of Medicine, National University Health System, Singapore
3.
Department of Psychology, National University of Singapore, Singapore
4.
Department of Pediatrics, Yong Loo Lin School of Medicine, Singapore
5.
Department of Rheumatology & Immunology, Singapore General Hospital, Singapore
6.
Department of Pharmacy, National University of Singapore, Singapore
For correspondence: Assistant Professor Wee Hwee Lin Department of Pharmacy National University of Singapore 10 Kent Ridge Crescent Singapore 119260 Singapore Tel: 65-‐ 6516-‐5530 Fax: 65-‐ 6778 5698 e-‐mail:
[email protected]
This is the accepted manuscript version for posting on personal website. The final publication is available at http://link.springer.com/article/10.1007/s11136-014-0747-z
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ABSTRACT Background: Although a range of generic and diabetes specific instruments are available to assess emotional distress, no studies have evaluated sensitivity in relation to sample size requirement. The present study sets out to compare the sensitivity among the Diabetes Health Profile psychological distress scale (DHP – PD), Problem Areas in Diabetes (PAID) and Kessler-‐10 Psychological Distress scale (K10). We hypothesized that the diabetes-‐specific measures (DHP-‐PD and PAID) would require smaller sample sizes than the generic measure (K10) yet remain specific. Research Design: A total of 208 patients with type 2 diabetes mellitus (mean age 45.2 (12.4) years; 63.1% males, 45.8% Chinese, 11.3% Malay and 26.6% Indian), recruited from a Singapore tertiary hospital diabetes clinic, completed the English DHP-‐PD, PAID and K10. Clinical information derived from medical records and HbA1c was recorded. Effects sizes (ES), ratio of ES and sample size requirement relative to the most sensitive questionnaire were computed. Results: A comparison of patients with good versus poor glycaemic control (HbA1c≥7.0) revealed that using K10 will require 4 times the sample size of a study using the PAID in order to detect the same level of psychological distress. The DHP-‐PD and PAID had similar sensitivity when comparing between patients with good versus poor glycaemic control. Conclusions: As hypothesised, sample size requirement is largest for K10 and remarkably similar for PAID and DHP-‐PD. This information is useful for designing clinical trials and studies.
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INTRODUCTION Diabetes Mellitus (DM) is a chronic disease associated with psychological distress such as withdrawal, anger, anxiety and depression (1-‐3). Prevalence of psychological distress in patients with DM range from 18% to 52% (1, 4) globally and is approximately 30% (5, 6) in Singapore. Two forms of psychological distress exist for patients with DM, namely depressive symptoms (DS) and DM-‐related distress (DRD). DS is associated with clinical depression, encompassing sadness, frustration, anxiety, and other negative mood states. Generic questionnaires are often used as screening tools to identify DS. Kessler-‐10 Psychological Distress scale (K10) is one such questionnaire that is growing in popularity globally (7-‐9). DRD, on the other hand, is attributed to the burden of living with DM. It encompasses physician-‐related stress, treatment-‐related stress, interpersonal distress, emotional burden of disease, food-‐related problems, etc. Only DM-‐specific questionnaires, which are targeted to identify distress related to DM can be used to identify such distress. Two examples of DM-‐specific questionnaires are the Diabetes Health Profile (DHP) and Problem Areas in Diabetes (PAID). While reliability and validity are typical considerations for selecting a questionnaire, a less commonly used, yet important criteria, is sample size requirement (sensitivity). Sensitivity, here, describes the ability of an instrument to detect differences between populations or subgroups. Hence, a sensitive questionnaire can efficiently differentiate between subgroups, leading to significant reduction in the number of subjects but yet detect meaningful results, which is especially useful for clinical trials. The aim of our study is to compare the sensitivity of three questionnaires (DHP, PAID and K10) in discriminating psychological distress among subgroups of patients with type 2 diabetes mellitus (T2DM). In particular, a comparison of DHP and PAID will aid clinicians in making a choice between these two widely used diabetes-‐specific questionnaires. We hypothesised that the DM-‐ specific measures (DHP-‐PD and PAID) would require smaller sample sizes than the generic measure (K10), yet retain their specificity. 3
METHODS Study Design and Participants This study was approved by the National Healthcare Group Domain Specific Review Board (Protocol No.: 2011/02018). Multi-‐ethnic patients with T2DM between 21 and 65 years old, with at least one year of being diagnosed with DM were recruited from the diabetes clinic at the National University Hospital, Singapore, from 2011 to 2012. Patients were selected by convenience sampling at the clinic waiting area. Only English literate patients were included in the study. Excluded patients consisted of those with severe heart, kidney, and liver disease, those who were mentally incapacitated, and alcohol or drug abusers. Informed consent was obtained from all participating patients. In the analysis, we only presented data on T2DM patients (Figure 1). Data collection Data on demographic factors were collected using self-‐administered questionnaires. Ethnic group was classified as Chinese, Malay, Asian Indian or Others. Marital status was classified as “never married”, “currently married” or “separated/divorced/widowed”. Education level was determined based on the number of schooling years and was categorized into 10 years. Psychological distress questionnaires Kesseler-‐10 Psychological Distress scale (K10) The K10 (10) is a generic questionnaire, consisting of 10 items designed to measure the level of distress and severity associated with psychological symptoms in population surveys. Each item in K10 is scored 1 to 5 (“None of the time” to “All of the time”). Item responses are summed to produce an overall score. It is popular worldwide because the instrument is short, simple to administer, had been validated (7) and is used in the world mental health survey (11). 4
Diabetes Health Profile (DHP) The DHP-‐18 items (DHP-‐18), was adapted from the DHP-‐1 (12) to identify psychosocial dysfunction among non-‐insulin-‐dependent patients (13). It consists of 18 items covering three dimensions: psychological distress (DHP-‐PD), barriers to activity (DHP-‐BTA) and disinhibited eating (DHP-‐DE). Each item in DHP-‐18 is scored 0 to 3 (“Never” to “Very much”). Item responses within each subscale are summed to produce a score for the respective subscales (14). A manuscript reporting the validity and reliability of DHP-‐18 in Singapore has been submitted (15). Only the DHP-‐ PD subscale (containing 6 items) was used in this analysis. Problem Areas in Diabetes (PAID) The PAID (16) is a commonly used instrument for mapping diabetes-‐related problem areas. It comprises 20 items covering frequently reported emotional states. Each item in PAID is scored 0 to 4 ("Not a problem" to "Serious Problem"). The sum of the items is multiplied by 1.25 to yield a final score of 0-‐100 (17). The PAID had been validated globally (18) as well as in Singapore (19). In all three aforementioned questionnaires, higher scores indicate higher levels of psychological distress. Definitions Glycemic control was determined by measured glycated hemoglobin (HbA1c). We classified patients with good control of HbA1c as achieving the standard of ≤7.0% (20). Medications were classified into treatment types, such as oral, insulin or both. Presenteeism, which is a measure of effectiveness of an individual who goes to work despite having an illness, was measured using a single question “On a scale of 0 to 10, how effective are you at work?” We arbitrarily considered a score ≤5 (mid-‐point of the scale) as not effective at work. The Family Functioning Measure (FFM) is a 1-‐item question used to determine the level of family support the patient is getting. The item response ranges from 1 “Poor” to 5 “Excellent”. We considered a score ≥3 as having the presence of family support (21). 5
Statistical analysis The missing item scores were imputed where possible based on the recommendations by the developers of each instrument (17, 22, 23). Participants with missing overall DHP-‐PD, PAID or K10 scores were excluded list wise from the analysis (Figure 1). Mean and standard deviations were used to describe continuous variables while percentages were used on categorical variables. Sensitivity Sensitivity was determined by effect size (ES), derived by dividing the differences in the mean scores between the two groups by the pooled standard deviation (PSD) (24, 25). Based on our literature review of Pubmed using terms “type 2 diabetes mellitus”, “Diabetes Health Profile”, “Problem Areas In Diabetes” and “Kessler-‐10”, the minimum important difference (MID) had not been determined for any of the instruments used in the study. However, several studies had shown that the ES across various patient sub-‐groups had ranged between 0.3 and 0.5 (24, 26). Hence we decided to use Cohen’s ES of 0.3 to be the minimum effect size to detect a MID for this study (25). Relative effect size (RES) was used to determine the sensitivity of the DHP-‐PD compared to PAID and K10 as well as PAID to K10. RES was expressed as the ES of DHP-‐PD over ES of PAID and K10 separately as well as the ES of PAID over ES of K10. RES values greater (less) than 1 will suggest that the DHP-‐PD was more (less) sensitive than PAID or K10, or the PAID was more (less) sensitive than K10, in discriminating the level of psychological distress between various sub-‐groups. Relative sample size was determined from the RES, defined as the square of the RES (27). Sub-‐groups based on clinical, demographic and socio-‐economic and social functioning variables were evaluated on the basis that they would allow for identification of patients who may benefit from tailored programmes to reduce psychological distress, e.g., gender-‐specific programmes. Simulation
To determine the power of the different instruments under various scenarios in a systematic
fashion and to determine the generalizability of findings from the data analyses, we conducted 1000
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simulations iterations on the DHP-‐PD, K10 and PAID scores based on the empirical distribution of the individual scores from the data collected. We varied the following factors: 1)
Effect sizes using, 0.2 as a small effect, 0.5 as moderate effect and 0.8 as a large effect
2)
Sample size of the smaller group with n=10, 30, 50 and 100
3)
Ratio of the sample size of the larger group to the smaller group with the following specified values: 1, 1.5, 2, 2.5.
Based on the variations of these three factors, we obtained 48 possible combinations for each of the three instruments. We counted and tabulated the percentage and number of times the individual instruments (untied) had the highest power to detect a difference in scores. Higher power is preferred because this suggests the instrument is more likely to produce a statistically significant result under the alternative hypothesis given the same sample size. Simulation was performed in R, version 3.0.3 (http://www.r-‐project.org/), using functions, such as, sample and t.test (28). All other analyses were performed in Stata version 12 (29).
RESULTS
Table 2 describes the socio-‐demographic, co-‐morbidity and DM control of 208 patients with
T2DM included in the study (Figure 1). The mean (SD) age of the population was 45.5 (11.9) years with 63% males. 50% of the subjects were Chinese, followed by Indian (28%) and Malay (12%). Most of the subjects had at least one co-‐morbidity with retinopathy and cardiovascular disease at 13%, followed by nephropathy (8%) and neuropathy (7%), to name a few. 71% of the subjects had poor control of their disease (i.e., HbA1c ≥7.0%). Sensitivity As expected, all measures of psychological distress were sensitive in detecting significant differences between patients with co-‐morbidities versus those without (ES>0.3), with the exception of K10 in detecting those with retinopathy, cardiovascular and cerebrovascular disease comorbidity and both DM-‐specific questionnaire in detecting patients with anaemia comorbidity respectively (Table 3). The K10 detected significant differences in psychological distress between males and
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females (ES=0.39). While only PAID was sensitive in detecting psychological distress across educational status (ES=0.32), all instruments were sensitive when comparing across sub-‐groups of socio-‐economic status (housing type and household income) of patients. Of the three variables available to measure modifiable social determinants (presenteeism, effective outside work and FFM), we found that the DHP-‐PD was most sensitive (ES>0.3 for all 3 variables) in detecting significant differences in psychological distress, followed by PAID (ES>0.3 for 2 out of 3 variables). K10 was not sufficiently sensitive in detecting any significant differences among the modifiable social determinants. RES results between each questionnaire pair and ratio of sample size requirements relative to the most sensitive instrument are depicted in Table 4. Generally, across most subgroups, DHP-‐PD and PAID tended to be more sensitive than K10 at detecting psychological distress. For example, when comparing between patients with good versus poor glycaemic control, the RES between DHP-‐ PD and K10, PAID and K10 and DHP-‐PD and PAID were 1.22, 1.67 and 0.73, respectively. In terms of sample size requirement, if a study uses the K10 questionnaire, it will require 2.8 times the sample size of a study using the PAID to detect the same level of psychological distress. However, there were two exceptions where the K10 was more sensitive at detecting psychological distress: 1) among patients with anemia co-‐morbidities; and 2) in some demographic and socio-‐economic variables (specifically age, gender, marital status housing type and household income). Simulation
Of the three instruments, DHP-‐PD had the highest power the most number of times (15 out of 41 combinations), while PAID and K10 tied in 13 out of 41 combinations (Table 5). There were combinations where the instruments were tied for the highest power, i.e.at least two of the instruments had exactly the same power, indicating that the instruments were no different from each other and hence no instrument was deemed superior than the other two instruments. However, these were rare and hence not reported (all three instruments were tied in 5 out of 48 combinations and two instruments were tied in 2 combinations). 8
When we varied the effect size, at low levels of effect size (ES=0.2), DHP-‐PD most frequently
reported the highest power (43.8% of the time). At larger effect sizes (ES=0.5) DHP-‐PD and K10 tied with each reporting the highest power 37.5% of the time. At small sample sizes (n=10), DHP-‐PD and K10 were seen to have equal numbers of highest power (41.7% of the time). However, as the sample size increases to n=30, we found that the PAID and DHP-‐PD instruments were more likely to report highest power (45.5% and 36.4% respectively). The simulation results suggest that when the sample sizes increase further, we find no differences between the DM-‐specific instruments from the generic instrument, suggesting that both types of instruments would be able to detect significant levels of psychological distress when the sample size is large. DISCUSSION As hypothesized, in this first-‐of-‐its-‐kind study that concurrently evaluated three questionnaires of psychological distress, the DHP-‐PD and PAID were generally more sensitive than K10 at detecting psychological distress among sub-‐groups of patients with T2DM. This translates to having to recruit fewer patients. There were two instances where the K10 was observed to be more sensitive than the DHP-‐ PD and PAID, the first being comparisons between patients with and without anaemia. This may be attributed to the symptoms of anaemia being closely associated with the symptoms of diabetes, hence the DM-‐specific instruments might not be adequate in detecting psychological distress due to anaemia (30). The second instance was observed across subgroups defined by socio-‐demographic or socio-‐economic variables. Age, gender and marital status, housing type and household income are not disease-‐specific variables. Hence it is not surprising that K10 was better at detecting psychological distress between the various categories. PAID was more sensitive at detecting psychological distress with regards to the clinical variables but was equally as sensitive as the DHP-‐PD where social functioning variables were 9
concerned. This may be partly explained by the larger number of clinical items in PAID compared with DHP-‐PD. However, it should be noted that DHP-‐PD is not a stand–alone questionnaire. Thus, by just including the DHP-‐PD sub-‐scale, we have missed the benefits of measuring two other aspects of DM-‐related well-‐being. Nonetheless, given that this paper was focusing on detecting psychological distress, it was necessary for us to extract the relevant sub-‐scale to ensure equivalent comparisons. A sensitive questionnaire, which can detect differences between groups, can sometimes be used to describe the responsiveness of a questionnaire, which can detect significant changes across time (31). This is particularly useful as most studies evaluating psychometric properties of patient reported outcome questionnaires are cross-‐sectional rather than longitudinal in nature. To date, of the three questionnaires analysed in our study, only the PAID had been specifically tested for responsiveness (32). Based on the findings of our study, it is reasonable to extrapolate that DHP will exhibit responsiveness while K10 would not. Based on the simulation results stratified by ES in Table 5, DHP-‐PD is frequently having the highest power when the ES is small (ES=0.2) while PAID is frequently having the highest power when the ES is large (ES=0.8). The findings from simulation and data analysis thus support the recommendation to use DM-‐specific psychological distress questionnaires (DHP-‐PD and PAID) over K10 because of better power and sensitivity properties. It should be mentioned that there are scenarios where K10 would have the highest power, e.g., when the sample sizes between the two instruments are equal (i.e., ratio = 1). Our study is not without limitations. First, we only captured English-‐speaking patients, thus limiting the generalizability of our findings. However, based on the Singapore Census 2010, 75% of the Singapore resident population aged 25 to 65 was English-‐literate (33). Second, the Malays were slightly under-‐represented in our patient population. Nonetheless, we managed to recruit a large proportion of Indians, which was predicted to be the most likely to have diabetes of the three ethnic groups (34). Lastly, the presenteeism item was dichotomised based on the mid-‐point of the scale (≤5). We acknowledge that the median and mean values were generally higher than the mid-‐point 10
(8 and 7.5 out of 10 points respectively). However, we decided to use the mid-‐point (≤5) because we do not suspect that social desirability effect would be present due to the following reasons: 1) the response scale had a series of 10 categories. If the response category was just “yes/no”, there would be higher level of response bias (35); 2) the questionnaire was self-‐completed and anonymous, hence social desirability effect would be negligible (36). CONCLUSION
Overall, based on the results from the data analysis, DM-‐specific psychological distress
questionnaires (DHP-‐PD and PAID) were more sensitive than K10, inferring smaller sample size requirements. Separately, PAID was more sensitive than DHP-‐PD at detecting psychological distress among subgroups of patients with T2DM. Simulation results suggest that DHP-‐PD and PAID have better power for small and large ES respectively. The results from the data analysis and simulation supports the usage of DM-‐specific psychological distress questionnaires (DHP-‐PD and PAID) over K10 because of better sensitivity and power properties. In conclusion, our study has presented information that would be useful in helping clinicians and researchers decide on the instruments to be included when designing clinical trials and studies. ACKNOWLEDGEMENTS This work was supported by the grant from Ministry of Education Singapore Academic Research Fund Tier 1 (Grant No.: FY2011-‐FRC3-‐007). REFERENCES 1. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-‐analysis. Diabetes care. 2001;24(6):1069-‐78. Epub 2001/05/26. 2. Katon WJ. The comorbidity of diabetes mellitus and depression. The American journal of medicine. 2008;121(11 Suppl 2):S8-‐15. Epub 2008/10/29. 3. Pawaskar MD, Anderson RT, Balkrishnan R. Self-‐reported predictors of depressive symptomatology in an elderly population with type 2 diabetes mellitus: a prospective cohort study. Health and quality of life outcomes. 2007;5:50. Epub 2007/08/09. 11
4. Ali S, Stone MA, Peters JL, Davies MJ, Khunti K. The prevalence of co-‐morbid depression in adults with Type 2 diabetes: a systematic review and meta-‐analysis. Diabetic medicine : a journal of the British Diabetic Association. 2006;23(11):1165-‐73. Epub 2006/10/24. 5. Chong SA, Subramaniam M, Chan YH, Chua HC, Liow PH, Pek E, et al. Depressive symptoms and diabetes mellitus in an Asian multiracial population. Asian journal of psychiatry. 2009;2(2):66-‐70. Epub 2009/06/01. 6. Verma SK, Luo N, Subramaniam M, Sum CF, Stahl D, Liow PH, et al. Impact of depression on health related quality of life in patients with diabetes. Annals of the Academy of Medicine, Singapore. 2010;39(12):913-‐7. Epub 2011/01/29. 7. Andrews G, Slade T. Interpreting scores on the Kessler Psychological Distress Scale (K10). Australian and New Zealand journal of public health. 2001;25(6):494-‐7. Epub 2002/02/05. 8. Cairney J, Veldhuizen S, Wade TJ, Kurdyak P, Streiner DL. Evaluation of 2 measures of psychological distress as screeners for depression in the general population. Canadian journal of psychiatry Revue canadienne de psychiatrie. 2007;52(2):111-‐20. Epub 2007/03/23. 9. Furukawa TA, Kessler RC, Slade T, Andrews G. The performance of the K6 and K10 screening scales for psychological distress in the Australian National Survey of Mental Health and Well-‐Being. Psychological medicine. 2003;33(2):357-‐62. Epub 2003/03/08. 10. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, et al. Short screening scales to monitor population prevalences and trends in non-‐specific psychological distress. Psychological medicine. 2002;32(6):959-‐76. Epub 2002/09/07. 11. Kessler RC. The World Health Organization International Consortium in Psychiatric Epidemiology (ICPE): initial work and future directions -‐-‐ the NAPE Lecture 1998. Nordic Association for Psychiatric Epidemiology. Acta psychiatrica Scandinavica. 1999;99(1):2-‐9. Epub 1999/03/05. 12. Meadows K, Steen N, McColl E, Eccles M, Shiels C, Hewison J, et al. The Diabetes Health Profile (DHP): a new instrument for assessing the psychosocial profile of insulin requiring patients-‐-‐ development and psychometric evaluation. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation. 1996;5(2):242-‐54. Epub 1996/04/01. 13. Meadows KA, Abrams C, Sandbaek A. Adaptation of the Diabetes Health Profile (DHP-‐1) for use with patients with Type 2 diabetes mellitus: psychometric evaluation and cross-‐cultural comparison. Diabetic medicine : a journal of the British Diabetic Association. 2000;17(8):572-‐80. Epub 2000/11/10. 14. Meadows K. Scoring the DHP-‐18. DHP Research & Consultancy. 113 Lower Camden, Chislehurst, Kent BR7 5JD 2010. 15. Tan L, Khoo E, Griva K, Lee Y, Amir M, Zuniga Y, et al. Reliability, Validity and Sensitivity of the Diabetes Health Profile-‐18 in Singapore. 2014. 16. Snoek FJ, Pouwer F, Welch GW, Polonsky WH. Diabetes-‐related emotional distress in Dutch and U.S. diabetic patients: cross-‐cultural validity of the problem areas in diabetes scale. Diabetes care. 2000;23(9):1305-‐9. Epub 2000/09/08. 17. Polonsky WH, Anderson BJ, Lohrer PA, Welch G, Jacobson AM, Aponte JE, et al. Assessment of diabetes-‐related distress. Diabetes care. 1995;18(6):754-‐60. Epub 1995/06/01. 18. Welch GW, Jacobson AM, Polonsky WH. The Problem Areas in Diabetes Scale. An evaluation of its clinical utility. Diabetes care. 1997;20(5):760-‐6. Epub 1997/05/01. 19. Rajaram R. Validation of the Problem Areas in Diabetes Questionnaire among patients with Type 2 Diabetes Mellitus in Singapore: A Pilot Study. Singapore: National University of Singapore, Department of Pharmacy, 2012. 20. Ismail-‐Beigi F. Clinical practice. Glycemic management of type 2 diabetes mellitus. The New England journal of medicine. 2012;366(14):1319-‐27. Epub 2012/04/06. 21. Sherbourne C, Kamberg C. Measuring Functioning and Well-‐Being: The Medical Outcomes Study Approach. Durham, North Carolina: Duke University Press 1992:183–93. 1992 22. Meadows K. Scoring the DHP-‐18. 2010. 12
23. Australian Mental Health Oucomes and Classification Network: Kessler-‐10 Training Manual. Commonwealth of Australia 2005: NSW Institute of Psychiatry; 2005. 24. Kazis LE, Anderson JJ, Meenan RF. Effect sizes for interpreting changes in health status. Medical care. 1989;27(3 Suppl):S178-‐89. Epub 1989/03/01. 25. Cohen J. Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, New Jersey: Lawrence Erlbaum. 1988. 26. Wyrwich KW, Nienaber NA, Tierney WM, Wolinsky FD. Linking clinical relevance and statistical significance in evaluating intra-‐individual changes in health-‐related quality of life. Medical care. 1999;37(5):469-‐78. Epub 1999/05/21. 27. Machin D, Campbell M, Fayers P, Pinol A. Sample Size Tables for Clinical Studies, 2nd Edition. Blackwell Science. Malden, Mass.1997. 28. Team RC. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-‐900051-‐07-‐0, URL http://www.R-‐project.org/. 2013. 29. Support ST. StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP. 2011. 30. Thomas MC, MacIsaac RJ, Tsalamandris C, Power D, Jerums G. Unrecognized anemia in patients with diabetes: a cross-‐sectional survey. Diabetes care. 2003;26(4):1164-‐9. Epub 2003/03/29. 31. Beurskens AJ, de Vet HC, Koke AJ. Responsiveness of functional status in low back pain: a comparison of different instruments. Pain. 1996;65(1):71-‐6. Epub 1996/04/01. 32. Welch G, Weinger K, Anderson B, Polonsky WH. Responsiveness of the Problem Areas In Diabetes (PAID) questionnaire. Diabetic medicine : a journal of the British Diabetic Association. 2003;20(1):69-‐72. Epub 2003/01/10. 33. Singapore Census of Population 2000. Singapore. Department of Statistics Singapore: Oct 2001. Report No. 34. Information Paper on Diabetes in Singapore. In: Board HP, editor. National Registry of Diseases Office2011. 35. Krosnick JA. Survey research. Annual Review of Psychology. 1999;50:537-‐67. 36. Jena AB, Press VG, Arora VM. Social desirability bias in self-‐rated presenteeism among resident physicians-‐-‐reply. JAMA internal medicine. 2013;173(2):166. Epub 2013/01/30.
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Figure 1: Graphical representation of the study recruitment of Singapore patients with T2DM
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Table 2: Demographic, Socioeconomic, Clinical and Social Functioning characteristics of patients with Type 2 Diabetes Mellitus n=208
45.48
11.87
Gender (n, %)
Male
132
63.46
Female
76
34.54
Ethnicity (n, %)
Chinese
104
50.00
Malay
24
11.54
Indian
59
28.37
Others
21
10.10
Education (n, %)
< 7 yrs
16
7.69
7-‐10 yrs
67
32.21
> 10 yrs
110
52.88
Missing
15
7.21
Marital status (n, %)
Single
41
19.71
Married
131
62.98
Age, in years (mean, SD)
15
Divorced/Widowed
20
9.62
Missing
16
7.69
Co-‐morbidities (n, %)
Retinopathy
28
13.46
Cardiovascular Disease
27
12.98
Nephropathy
17
8.17
Neuropathy
14
6.73
Cerebrovascular Disease
12
5.77
Anemia
13
6.25
PVD
6
2.88
Hepatic
5
2.40
Renal
1
0.48
Poor Control (n, %)
No: HbA1c (≤7.0)
60
28.85
Yes: HbA1c (>7.0)
148
71.15
Presenteeism (n, %)
Yes
172
87.76
No
24
12.24
Effectiveness outside work (n, %)
Yes
148
74.37
No
51
25.63
16
Family Functioning Measure (n, %)
Good
184
89.76
Poor
21
10.24
Psychological Distress Scales (mean, SD)
DHP-‐PD
21.26
22.02
K10
23.71
17.60
PAID
28.73
21.73
17
Table 3: Comparison of DHP's psychological distress domain with K10 and PAID Physical determinants Complications None Retinopathy Cardiovascular Disease Nephropathy Neuropathy Cerebrovascular Disease Anemia Control (hba1c) Yes No Medication type Oral Insulin Oral & insulin Social determinants Age < 45 yrs >=45 yrs Gender Male Female
n 59 28 27 17 14 12 13 60 148 122 7 75 87 120 132 76
Mean 19.21 22.02 29.42 34.31 37.70 25.00 17.52 13.80 24.29 17.12 26.98 28.15 22.86 20.09 20.79 22.08
DHP-‐PDa SD ESd 21.84 18.61 -‐0.13 25.77 -‐0.44 23.59 -‐0.68 21.15 -‐0.85 23.03 -‐0.26 17.55 0.08 15.66 23.50 -‐0.49 19.63 0.51 19.88 0.05 24.51 23.52 20.99 0.13 22.78 20.75 -‐0.06
pe 0.27 0.04 0.01 0.00 0.21 0.62 0.00 1.00 0.56 0.81 0.34
Mean 23.56 26.25 28.70 36.18 35.54 26.25 30.58 18.29 25.91 21.52 21.43 27.27 26.09 21.96 21.27 27.96
K10b SD ES 18.27 22.19 -‐0.14 20.03 -‐0.27 15.31 -‐0.71 17.71 -‐0.66 16.67 -‐0.15 19.04 -‐0.38 15.84 17.84 -‐0.44 17.33 0.32 10.49 0.33 18.40 17.06 17.91 0.24 16.75 18.32 -‐0.39
p 0.29 0.13 0.00 0.01 0.31 0.11 0.00 0.98 0.90 0.95 0.00
Mean 25.64 31.94 38.15 43.56 39.91 36.88 24.85 20.19 32.19 26.43 23.93 32.86 31.15 26.51 28.16 29.71
PAIDc SD ES 20.70 20.24 -‐0.31 24.95 -‐0.57 20.86 -‐0.86 21.36 -‐0.69 21.78 -‐0.54 15.85 0.04 19.52 21.69 -‐0.57 21.77 0.30 18.78 0.43 20.90 21.22 21.48 0.22 21.06 22.96 -‐0.07
p 0.09 0.01 0.00 0.01 0.05 0.56 0.00 0.98 0.88 0.94 0.32 18
Ethnicity Chinese Malay Indian Others Marital status Single Married Divorced/Widowed Socio-‐Economic Status Education < 7 yrs 7-‐10 yrs > 10 yrs Housing type HDB 1-‐4 rm flat HDB 5 rm/executive maisone Private housing Household income Low (
