Journal of Diabetes Research

Journal of Diabetes Research / 2016 / Article
Special Issue

Psychological Aspects Related to Diabetes Mellitus

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Research Article | Open Access

Volume 2016 |Article ID 6343927 | 16 pages | https://doi.org/10.1155/2016/6343927

Demographical, Clinical, and Psychological Characteristics of Users and Nonusers of an Online Platform for T2DM Patients (e-VitaDM-3/ZODIAC-44)

Academic Editor: Nitin Gupta
Received07 Jan 2015
Accepted30 Apr 2015
Published22 Nov 2015

Abstract

Background. Online platforms offer opportunities for support in changing lifestyle and taking responsibility for one’s health, but engaging patients with type 2 diabetes is challenging. Previous studies have shown that patients interested in platforms were more often male, younger, and higher educated. This study aims to investigate differences in clinical and psychological characteristics between users and nonusers of a newly developed platform. Methods. A prospective study started in the Drenthe region of Netherlands. Participants in the study concerning quality of care and quality of life were additionally invited to use the platform. Results. 633 patients were registered after they opted for platform use. Of these patients, 361 (57.0%) never logged on, 184 (29.1%) were labeled “curious” users, and 88 (13.9%) were identified as “active” users. Users had lower HbA1c levels and more often hypertension compared to nonusers, and reported higher quality of life, better well-being, lower diabetes-related distress, and better medication adherence. Discussion. Platform use was associated with more favorable clinical and psychological characteristics relative to nonuse. Those with greater severity of disease, lower mood, and progression of disease used the platform the least. Other approaches need to be developed to reach these patients. Furthermore, improving the platform could also help to reach them. This trial is registered with Clinicaltrials.gov NCT01570140.

1. Background

Type 2 diabetes mellitus (T2DM) in itself is associated with poorer health-related quality of life (HRQoL) [1]. People with T2DM are susceptible to develop long term complications, such as retinopathy, neuropathy, nephropathy, and chronic heart disease, which negatively influence HRQoL [2]. To prevent or delay development of these long term complications, adequate treatment modalities are necessary which mainly involve lifestyle changes and pharmacological treatment. Adherence to medication prescription and implementing life style changes are often better maintained and facilitated, when patients consider themselves more responsible for their treatment and have more knowledge regarding the causes and consequences of their disease. Improvements in knowledge about their disease can be described as promotion of health literacy. e-Health applications, such as web-portals, teleconsultation, and online care platforms, have the potential to support patients in changing lifestyle and taking more responsibility for their own health [3]. However, varying effects on clinical outcomes, quality of life, degree of self-care, perceived stress levels, patient satisfaction, and costs have been reported [410].

Previous studies showed that patients who were interested in using an online care platform were more often male, younger, and higher educated [11, 12]. However, within the subgroup of interested patients these differences were not found between actual users and nonusers [11]. In addition, other factors associated with higher portal enrollment and utilization are higher income, nonblack race, higher self-efficacy, and having better regulated diabetes [13]. Identifying the differences between platform users and nonusers could provide information to help target and support nonusers in becoming more active in their diabetes self-management.

The aim of the present, explorative study was to investigate possible differences in demographic, clinical, and psychological characteristics between users and nonusers of the platform e-Vita.

2. Methods

2.1. Study Design

We performed a cross-sectional analysis of baseline data of users and nonusers of the online patient platform e-Vita. Data was obtained from a prospective observational cohort study. Detailed information about the methods and design of the study as a whole can be found elsewhere [14].

2.2. Study Population and Setting

Forty-three out of 110 general practices in the Drenthe region of the Netherlands invited their T2DM patients for participation in a prospective observational cohort study concerning quality of care and HRQoL. Patients were also invited to use the online care platform e-Vita, in addition to their usual treatment. Patients interested in using the platform were registered by their practice nurse (PN) and received a user ID. In this ongoing study, participants were recruited from May 2012 onward. The current analysis includes patients recruited from May 2012 till March 2014.

2.3. Measurements

Demographic and clinical data were obtained from the personal health record systems of the general practitioners (GP), based on a core dataset of T2DM related information as advised by the Dutch Diabetes Federation and the Dutch College of General Practitioners [14]. All T2DM patients participating in the study filled in a range of validated questionnaires concerning perceived quality of life measured by the EuroQol Five Dimension (EQ-5D) Scale [1517], emotional well-being measured by the World Health Organization Wellbeing Index 5-Item (WHO-5) questionnaire [18, 19], diabetes-related distress measured by the Problem Areas in Diabetes 5-Item (PAID-5) questionnaire [20], diabetes self-care behavior measured by 7 Dimensions of the Summary of Diabetes Self-Care Activities (SDSCA) questionnaire [21], and quality of received care measured by the Europep [22]. Suboptimal emotional well-being was defined by a raw score lower than 13 on the WHO-5 [23]. Additional questions about smoking habits, employment, and educational background were also included. To identify users and nonusers, registration data from the application software and log-files were used.

2.4. Description of e-Vita Platform

The e-Vita platform for T2DM patients (accessible through the login button on https://www.e-vita.nl/) [11, 14, 24] contains the following components: (1) an overview of health data concerning annual check-ups from 2009 onward, (2) educational modules meant to support care through self-management by setting person-specific goals and actions [25], (3) prompting patient self-monitoring of clinical values, (4) educational modules aimed at increasing diabetes knowledge, and (5) providing reliable information on T2DM in general.

2.5. Users and Nonusers

Information about login status and log-data were used to group patients into nonusers and users. All patients who logged in at least once were considered as users. Patients who had been online for at least two sessions with a minimum of five minutes per session were defined as “active” users; other patients were defined as “curious” users. A session included all logins to the platform within thirty minutes [24].

2.6. Statistical Analyses

Statistical analyses were performed using SPSS version 20 (IBM Corporation, Somers, NY, USA). Quantitative variables are described in means and standard deviations when normally distributed; otherwise medians and interquartile ranges are also described. Categorical variables are described in numbers and percentages. To identify differences in the domains of interest between the different groups of users, the Linear Mixed Models procedure was used, with groups of users being fixed factors (nonusers being the reference group), while adjusting for age and sex. Fisher’s exact test was used for categorical data. Differences were considered to be significant at a value of <0.05. In addition, results are adjusted for age and gender. Because of the explorative design of this study, no corrections for multiple testing were made [26]. Instead, the calculated values are only used as an indication of to what extent a difference could be interesting for further research.

2.7. Ethics

This study was approved by the Medical Ethical Review Committee of Isala, Zwolle, the Netherlands, and registered in Clinicaltrials.gov under number NCT01570140.

3. Results

In the period from May 2012 to March 2014, 3191 patients were invited to participate in the cohort study and to use the e-Vita platform. 633 patients were registered for care platform use. See Figure 1 for the patient flow.

Table 1 shows all differences and other notable characteristics for the comparison between nonusers, curious users, and active users of the platform. No differences were found in demographical characteristics between nonusers, curious users, and active users. HbA1c level of nonusers was higher compared to curious users () and to active users (). Curious and active users were more often known with hypertension compared to nonusers (). Curious users assessed the GP better on one question of the Europep compared to nonusers and active users (). Curious users scored higher on EQ-5D () and EQ-VAS (0.032) compared to nonusers, with no significant differences between curious users and active users or nonusers and active users. In addition, curious users’ WHO-5 score as well as their answers to the individual WHO-5 questions reported less depressive symptoms compared to nonusers and active users. Curious users scored lower on PAID-5 compared to nonusers (), with no significant differences between curious users versus active users and nonusers versus active users. Curious users performed better on one dimension of self-reported self-management activities (medication intake) compared to nonusers (), with no significant difference between curious users versus active users and nonusers versus active users. Table 2 shows the Cronbach’s alpha for all the multi-item scales.


n (%) or mean (SD) 
Demographic and clinical parameters
Nonusers ()MissingCurious users ()MissingActive users ()MissingUnivariate 
value

Men214 (59.3)0 (0)113 (61.4)0 (0)50 (56.8)0 (0)0.760
Age in years62.1 ± 9.5 
63.0 (56.5–68.0)
0 (0)61.8 ± 9.5 
62.0 (56.3–68.0)
0 (0)62.0 ± 9.4 
63.0 (57.0–67.0)
0 (0)0.935
Ethnicity
 Caucasian292 (99.0)66 (18.3)143 (100)41 (22.3)65 (100)23 (6.1)0.706
 Other3 (1.0)0 (0)0 (0)0.382
Employment
 Fulltime/part-time working 99 (34.3)72 (19.9)61 (39.6)30 (16.3)20 (23.8)4 (4.5)0.063
 Retired134 (46.4)70 (45.5)46 (54.8)
 Unemployed/housekeeper38 (13.1)20 (13.0)9 (10.7)
 Incapacitated 18 (6.2)3 (1.9)9 (10.7)
Educational level
 None 0 (0)73 (20.2)1 (0.7)31 (16.8)0 (0)4 (4.5)0.125
 Primary school24 (8.3)9 (5.9)4 (4.8)
 Low127 (44.1)52 (34.0)27 (32.1)
 Intermediate86 (29.9)51 (33.3)30 (35.7)
 High51 (17.7)40 (26.1)23 (27.4)
T2DM duration in years 6.2 ± 4.6 
6.0 (2.0–9.0)
9 (2.5)5.7 ± 4.4  
5.0 (2.0–8.0)
1 (0.5)5.4 ± 4.4 
4.5 (2.0–8.0)
0 (0)0.165
HbA1c in mmol/mol 50.6 ± 9.5 
50.0 (45.0–54.0)
3 (0.8)48.7 ± 7.4 
48.0 (43.0–54.0)
0 (0)47.0 ± 7.0 
46.0 (43.0–50.8)
0 (0)0.001
BMI29.8 ± 4.9 
29.0 (26.5–32.5)
3 (0.8)30.0 ± 4.8 
29.3 (26.9–32.3)
0 (0)29.9 ± 8.0 
28.0 (26.0–32.6)
2 (2.3)0.921

Comorbidities/complications
 Hypertension191 (84.1)134 (37.1)113 (93.4)63 (34.2)51 (92.7)33 (37.5)0.025

Items of Europep: patients who scored 4 (good) to 5 (excellent) 
What is your assessment of the general practitioner over the last 12 months with respect to the following?
 Making it easy for you to tell him or her about your problem345 (93.5)18 (4.7)187 (97.9)17 (8.2)84 (93.3)2 (2.2)0.047

EQ-5D index-score0.9 ± 0.272 (19.9)0.9 ± 0.132 (17.4)0.9 ± 0.24 (4.5)0.030
EQ-VAS 74.7 ± 17.4 
80.0 (60.0–90.0)
74 (20.5)79.3 ± 13.8 
80.0 (73.0–90.0)
35 (19.0)76.9 ± 16.5 
80.0 (0.0–90.0)
5 (5.7)0.032

WHO-5 score indicates suboptimal well-being, screening depression advised36 (12.6)76 (21.1)8 (5.3)33 (17.9)9 (10.8)1 (1.1)0.018
WHO-5 answers advise screening depression 43 (15.5)76 (21.1)6 (4.0)33 (17.9)11 (13.3)1 (1.1)0.002

PAID-5 total score2.8 ± 3.1 
2.0 (0.0–4.5)
76 (21.1)1.8 ± 2.4 
1.0 (0.0–3.0)
32 (17.4)2.2 ± 2.5 
1.0 (0.0–4.0)
1 (1.1)0.016

SDSCA
 Medication in number of days 6.7 ± 1.0 
7.0 (7.0–7.0)
73 (20.2)7.0 ± 0.2 
7.0 (7.0–7.0)
30 (16.3)6.8 ± 0.8 
7.0 (7.0–7.0)
4 (4.5)0.020


Multi-item scaleα

Europep
 Total0.963
 Subscale general practice0.966
 Subscale general practitioner0.840
EQ-5D0.652
WHO-50.872
PAID-50.867
SDSCA
 Total0.517
 Subscale general diet0.875
 Subscale specific diet01
 Subscale total diet0.4462
 Subscale exercise 0.663
 Subscale blood-glucose testing0.912
 Subscale foot-care0.593

Because of the negative intercorrelation between the two items Cronbach’s alpha is reported to be 0.
2The alpha for the subscale total diet is lower than that for the subscale general diet due to the low reliability of the subscale specific diet.

See Appendix A for tables with all characteristics as mentioned in the methods section for the comparison between nonusers and users. See Appendix B for tables with all characteristics for the comparison between nonusers, curious users, and active users.

The differences in characteristics between nonusers, curious users, and active users have also been adjusted for age and gender in a multivariate analysis. The results are shown in Table 3. values below 0.05 were found for differences regarding HbA1c between active users and nonusers (−3.624 mmol/mol) as well as between curious users and nonusers (−1.989 mmol/mol) and for differences between curious users and nonusers regarding EQ-5D (0.044), EQ-VAS (4.611), WHO-5 (3.609), PAID-5 (−0.929), and medication intake (0.236).


-coefficient95% CI value
Lower boundUpper bound

T2DM duration in years
 Intercept 0.018−2.3252.3600.988
 Platform use0.186
 Active users−0.845−1.8760.1860.108
 Curious users−0.511−1.3000.2770.203
 NonusersRef. Cat.
 Male−0.121−0.8320.5890.738
 Female Ref. Cat.
 Age 0.1010.0640.138<0.0005
HbA1c in mmol/mol
 Intercept53.43148.93157.931<0.0005
 Platform use<0.0005
 Active users−3.624−5.627−1.621<0.0005
 Curious users−1.989−3.516−0.4620.011
 NonusersRef. Cat.
 Male 1.103−0.2702.4770.115
 FemaleRef. Cat.
 Age−0.055−0.1270.0160.126
BMI
 Intercept37.43034.65840.202<0.0005
 Platform use0.924
 Active users0.079−1.1591.3170.900
 Curious users0.189−0.7471.1240.692
 NonusersRef. Cat.
 Male −1.087−1.931−0.2440.012
 FemaleRef. Cat.
 Age−0.113−0.156−0.069<0.0005
EQ-5D
 Intercept0.8660.7730.958<0.0005
 Platform use0.022
 Active users0.008−0.0310.0470.674
 Curious users0.0440.0130.0760.006
 NonusersRef. Cat.
 Male 0.0560.0270.085<0.0005
 FemaleRef. Cat.
 Age−0.001−0.0020.0010.343
EQ-VAS
 Intercept71.00761.66380.350<0.0005
 Platform use0.019
 Active users2.291−1.6916.2750.259
 Curious users4.6111.3847.8380.005
 NonusersRef. Cat.
 Male 2.9770.0955.8590.043
 FemaleRef. Cat.
 Age0.030−0.1180.1780.690
WHO-5
 Intercept58.13848.91167.365<0.0005
 Platform use0.065
 Active users−0.089−4.0083.8290.964
 Curious users3.6090.4466.7730.025
 NonusersRef. Cat.
 Male 5.7662.9328.600<0.0005
 FemaleRef. Cat.
 Age0.142−0.0040.2890.057
PAID-5
 Intercept5.1293.5206.737<0.0005
 Platform use0.004
 Active users−0.511−1.1950.1730.143
 Curious users−0.929−1.480−0.3780.001
 NonusersRef. Cat.
 Male −0.143−0.6390.3530.571
 FemaleRef. Cat.
 Age−0.037−0.062−0.0110.005
SDSCA-medication
 Intercept6.0875.5756.600<0.0005
 Platform use0.028
 Active users0.081−0.1320.2960.458
 Curious users0.2360.0630.4080.008
 NonusersRef. Cat.
 Male 0.096−0.0580.2500.222
 FemaleRef. Cat.
 Age0.0100.0020.0180.020

4. Discussion

In this exploratory study we found that only a small amount of clinical and psychological characteristics were associated with platform use. Curious users as well as active users had lower HbA1c compared to nonusers, which is in agreement with other studies [27, 28]. The more frequent presence of hypertension in curious and active users, however, contradicts with these studies. Curious users scored higher on EQ-5D and EQ-VAS and lower on PAID-5. Curious users scored also better on medication intake, which may reflect higher self-efficacy, in agreement with the study by Sarkar et al. [29]. After adjustment for age and gender, the difference in WHO-5 score between curious users and nonusers was also significant.

We observed that most of the patients, who were registered for platform use, never logged on. This could be influenced by (an insufficient) intrinsic motivation and (no) intention to change behaviours. Another explanation could be that patients do not see the platform as useful or as an added value to regular treatment. As an alternative explanation, login procedures might be too difficult and after trying for some time they might give up.

Previous research showed that web-portals and online care platforms are susceptible to implementation problems, low participation rates, and nonadherence, which, amongst others, can be caused by a mismatch in expectations between software developers, health care providers, and users [3037]. Other reasons for limited use of care platforms or nonadherence rates are as follows: abundance of functionalities on a platform, no connection with the needs of patients, implementation by management only without active involvement of care providers, no embedding in the regular care process, no space for habituation, underestimation of the complexity of lifestyle changes in general [38], and barriers to easy access to a portal (e.g., complicated login procedures). Despite the use of focus groups for designing and testing, these reasons might also be applicable to the e-Vita platform and improvements could be made.

The current study has some limitations. A preselection of participants could in part have influenced results. Only patients who expressed their interest received a user-ID [14]; see also Figure 1. Relevant and significant differences might be more difficult to find.

Data were not complete for all patients, especially with regard to complications and risk factors (complete for 50–60%; see Tables 6 and 11). This may have led to an underestimation of presence of complications and risk factors. In addition, not all patients were seen by their GP or PN for the regular yearly check-up in the year 2012, which contributed to missing values in clinical parameters. Some questions about the assessment of the general practice and the general practitioner were poorly answered in general. A reason for this could be social desirability; patients may not like to be negative about their GP and prefer not answering these questions.

Although the online care platform e-Vita was designed for being suitable for all T2DM patients, a general assumption is that those with greater severity of disease, lower mood, progression of the disease, and complications would probably benefit most from an online care platform. However, when assessing the presented results, these patients use the platform the least.

Possibly, the current users were already more in control of their life and health and could therefore be more open to other forms of support, including e-Health facilities. Challenges to reach other patients remain manifold. A patients’ passive attitude may not be overcome by only providing e-facilities, since one’s interest and the sense of disease burden are low or even absent in the majority of the T2DM population. Factors as knowledge, motivation, and intention could be considered in future research.

Appendices

A. Results of Users and Nonusers of the Online Care Platform e-Vita

See Tables 4, 5, 6, 7, and 8.


Demographic and clinical parameters  
(%)/mean ± SD/median (25–75 quartiles)
Nonusers ()MissingUsers ()MissingUnivariate 
value

Men214 (59.3)0 (0)163 (59.9)0 (0)0.95
Age in years62.1 ± 9.5  
63.0 (56.5–68.0)
0 (0)61.8 ± 9.4 
62.5 (57.0–68.0)
0 (0)0.732
Ethnicity
 Caucasian292 (99.0)66 (18.3)208 (100)64 (2.5)0.271
 Other3 (1.0)0 (0)
T2DM duration in years 6.2 ± 4.6 
6.0 (2.0–9.0)
9 (2.5)5.6 ± 4.4 
5.0 (2.0–8.0)
1 (0.4)0.068
HbA1c in mmol/mol 50.6 ± 9.5 
50.0 (45.0–54.0)
3 (0.8)48.2 ± 7.3 
47.0 (43.0–53.0)
0 (0)<0.0005
BMI29.8 ± 4.9 
29.0 (26.5–32.5)
3 (0.8)30.0 ± 6.0 
28.7 (26.3–32.4)
2 (0.7)0.724
Systolic blood pressure in mmHG 135.6 ± 15.50 (0)136.5 ± 16.04 (1.5)0.463
Cholesterol in mmol/L 4.4 ± 1.04 (1.1)4.4 ± 0.92 (0.7)0.499
HDL in mmol/L 1.3 ± 0.4 4 (1.1)1.3 ± 0.43 (1.1)0.581
Cholesterol/HDL ratio3.6 ± 1.1160 (44.3)3.6 ± 1.392 (33.8)0.899
LDL in mmol/L 2.4 ± 0.912 (3.3)2.3 ± 0.86 (2.2)0.240
Triglycerides in mmol/L 1.7 ± 1.0 
1.5 (1.0–2.1)
7 (1.9)1.8 ± 1.2 
1.5 (1.1–2.1)
2 (0.7)0.482
Creatinine in µmol/L78.6 ± 17.2 
77.0 (67.0–88.0)
6 (1.7)79.9 ± 17.5 
79.0 (67.0–90.0)
1 (0.4)0.359
Alb./creat. ratio in mg/mmol
 Men2.0 ± 4.4 
0.7 (0.3–1.5)
23 (10.7)1.9 ± 5.8 
0.5 (0.3–1.5)
25 (15.3)0.853
 Women1.6 ± 3.5 
0.7 (0.3–1.5)
31 (21.1)0.9 ± 1.1 
0.6 (0.4–1.2)
18 (16.5)0.070
MDRD in mL/min/1.73 m2 79.1 ± 49.0 
75.0 (61.0–88.0)
5 (1.4)76.0 ± 16.6 
74.0 (61.0–87.0)
1 (0.4)0.329
Smoking
 Yes54 (15.1)3 (0.8)41 (15.1)1 (0.4)0.306
 Before158 (44.1)104 (38.4)
 No146 (40.8)126 (46.5)
Alcohol consumption in units/day
 0166 (58.9)79 (21.9)139 (60.7)43 (15.8)0.870
 161 (21.6)52 (22.7)
 239 (13.8)30 (13.1)
 311 (3.9)7 (3.1)
 44 (1.4)1 (0.4)
 50 (0)0 (0)
 61 (0.4)0 (0)
Employment
 Fulltime/part-time working 99 (34.3)72 (19.9)81 (34.0)34 (12.5)0.909
 Retired134 (46.4)116 (48.7)
 Unemployed/ housekeeper38 (13.1)29 (12.2)
 Incapacitated 18 (6.2)12 (5.0)
Educational level
 None 0 (0)73 (20.2)1 (0.4)35 (12.9)0.017
 Primary school24 (8.3)13 (5.5)
 Low127 (44.1)79 (33.3)
 Intermediate86 (29.9)81 (29.8)
 High51 (17.7)63 (23.2)


Medication prescription
(%)
Nonusers ()Missing Users ()MissingUnivariate
value

Diabetes-related
 Oral treatment only251 (71.3)9 (2.5)192 (71.9)5 (1.8)0.702
 Insulin treatment only4 (1.1)9 (2.5)1 (0.4)5 (1.8)0.931
 Mix of oral and insulin treatment40 (11.4)9 (2.5)23 (8.6)5 (1.8)0.248
 No medication57 (16.2)9 (2.5)51 (19.1)5 (1.8)0.417
Comorbidity or complication related
 Calcium channel blockers50 (14.2)9 (2.5)47 (17.6)5 (1.8)0.236
 Beta blockers128 (36.4)9 (2.5)110 (41.2)5 (1.8)0.145
 Diuretics121 (34.4)9 (2.5)94 (35.2)5 (1.8)0.870
 Ace and RAAS inhibitors196 (55.7)9 (2.5)141 (52.8)5 (1.8)0.480
 Other blood pressure lowering medications3 (0.9)9 (2.5)1 (0.4)5 (1.8)0.637
 Lipid lowering medication280 (79.5)9 (2.5)213 (79.8)5 (1.8)0.847


Complications and risk factors
(%)
Nonusers ()Missing Users ()MissingUnivariate
value

Cardiovascular, total225 (96.2)127 (35.2)187 (98.4)82 (30.1)0.240
Cardiovascular, specific
 Angina pectoris 41 (21.7)172 (47.6)28 (19.7)130 (47.8)0.787
 Myocardial infarct29 (15.3)172 (47.6)23 (16.0)128 (47.1)0.880
 Other/chronic ischemic heart diseases 34 (16.1)150 (41.6)24 (13.6)96 (35.3)0.569
 Hypertension191 (84.1)134 (37.1)164 (93.2)96 (35.3)0.008
 TIA 12 (6.4)174 (48.2)7 (5.0)133 (48.9)0.642
 CVA 13 (7.0)176 (48.8)10 (7.1)132 (48.5)1.000
 Intermittent claudication 7 (3.3)150 (41.6)7 (4.0)96 (35.3)0.788
 Aortic aneurysms 4 (1.9)150 (41.6)2 (1.1)96 (35.3)0.693
 CABG 15 (5.1)68 (18.8)11 (5.4)68 (25.0)1.000
 PTCA 28 (9.6)68 (18.8)14 (6.8)67 (24.6)0.327
 Heart failure 14 (8.1)189 (52.4)10 (7.4)136 (50.0)0.834
Retinopathy19 (9.3)156 (43.2)18 (10.2)95 (34.9)0.863
Renal impairment35 (18.6)173 (47.9)26 (18.6)132 (48.5)1.000
Albuminuria
 Men 30 (14.5)7 (3.3)20 (12.6)4 (2.5)0.647
 Women 8 (5.8)8 (5.4)1 (1.0)5 (4.6)0.082
Neuropathy49 (22.2)140 (38.8)39 (22.4)98 (36.0)1.000
Foot complication
 SIMMs 0228 (77.6)67 (18.6)161 (76.7)62 (22.8)0.783
 SIMMs 157 (19.4)40 (19.0)
 SIMMs 2 or 39 (3.1)9 (4.3)
Psychiatric disorders19 (9.0)150 (41.6)9 (5.1)96 (35.3)0.124

SIMMS refers to risk factors in the diabetic foot, the number is the stage which ranges from 0–3.
0: no loss of protective sensibility (PS) & Peripheral arterial disease (PAV).
1: loss of PS or PAV, with no signs of increased local pressure.
2: loss of PS in combination with and/or PAV and/or signs of local elevated pressure.
3: ulcer or amputation in history.

Items of Europep: patients who scored 4 (good) or 5 (excellent) 
(%)
Nonusers ()Missing Users ()MissingUnivariate
value

What is your assessment of the general practitioner over the last 12 months with respect to the following?
Making you feel you have time during consultation337 (97.4)15 (4.2)256 (98.1)11 (4.0)0.622
Showing interest in your personal situation324 (94.5)18 (5.0)246 (94.6)12 (4.4)0.864
Making it easy for you to tell him or her about your problem323 (93.4)15 (4.2)245 (96.5)18 (6.6)0.110
Involving you in decisions about your medical care311 (92.3)24 (6.6)239 (94.1)18 (6.6)0.290
Listening to you322 (92.3)12 (3.3)243 (94.6)15 (5.5)0.270
Keeping your records and data confidential310 (95.7)37 (10.2)236 (95.9)26 (9.6)0.846
Providing quick relief of your symptoms272 (87.5)50 (13.9)201 (85.9)38 (14.0)0.635
Helping you to feel well so that you can perform your normal daily activities265 (89.8)66 (18.3)196 (91.2)57 (21.0)0.483
Thoroughness of the approach to your problems308 (91.4)24 (6.6)227 (89.7)19 (7.0)0.786
Your physical examination292 (90.1)37 (10.2)222 (92.1)31 (11.4)0.327
Offering services for preventing diseases (screening, health checks, and immunizations)286 (91.4)48 (13.3)225 (92.6)29 (10.7)0.655
Explaining the purpose of examinations, tests, and treatments307 (93.0)31 (8.6)240 (93.8)16 (5.9)0.518
Telling you enough about your symptoms and/or illness306 (92.2)29 (8.0)238 (93.3)17 (6.3)0.448
Helping you deal with emotions related to your health status198 (86.8)133 (36.8)133 (84.7)115 (42.3)0.888
Helping understand why it is important to follow the GP’s advice295 (89.7)32 (8.9)219 (89.4)27 (9.9)0.894
Knowing what has been done or told during previous contacts in the practice270 (84.9)43 (11.9)219 (89.4)27 (9.9)0.071
Preparing you for what to expect from specialists, hospital care, and other care providers199 (85.4)128 (35.5)156 (83.5)85 (31.3)0.513

What is your assessment of the general practice over the last 12 months with respect to the following?
The helpfulness of the practice staff (other than the doctor) to you313 (93.4)26 (7.2)235 (92.9)19 (7.0)0.878
Getting an appointment to suit you301 (88.5)21 (5.8)224 (86.5)13 (4.8)0.639
Getting through to the practice on telephone249 (73.0)20 (5.5)180 (69.5)13 (4.8)0.662
Being able to talk to the general practitioner on the telephone167 (70.5)124 (34.3)106 (63.1)104 (38.2)0.150
Waiting time in the waiting room246 (71.3)16 (4.4)170 (65.4)12 (4.4)0.175
Providing quick services for urgent health problems241 (90.3)94 (26.0)171 (86.8)75 (27.6)0.398


EQ-5D, WHO-5, PAID-5, and SDSCA  
(%)/mean ± SD/median (25–75 quartiles)
Nonusers ()Missing Users
()
MissingUnivariate 
value

EQ-5D index-score0.9 ± 0.272 (19.9)0.9 ± 0.136 (13.2)0.028
EQ-VAS 74.7 ± 17.4 
80.0 (60.0–90.0)
74 (20.5)78.4 ± 14.9 
80.0 (71.0–90.0)
40 (14.7)0.014
WHO-5 index-score 70.4 ± 17.9 
76.0 (60.0–80.0)
76 (21.1)72.7 ± 14.2 
76.0 (68.0–80.0)
38 (14.0)0.096
WHO-5 score indicates suboptimal well-being, screening depression advised36 (12.6)76 (21.1)17 (7.3)38 (14.0)0.018
WHO-5 answers advise screening depression 43 (15.5)76 (21.1)17 (7.3)38 (14.0)0.004
PAID-5 total score 2.8 ± 3.1 
2.0 (0.0–4.5)
76 (21.1)2.0 ± 2.5 
1.0 (0.0–3.0)
38 (14.0)0.005
PAID-5 score indicates distress 15 (5.3)76 (21.1)6 (2.6)38 (14.0)0.058
SDSCA
 General diet in number of days 5.4 ± 1.8 
6.0 (5.0–7.0)
76 (21.1)5.6 ± 1.8 
6.0 (5.0–7.0)
37 (13.6)0.269
 Specific diet in number of days 5.6 ± 1.1 
5.7 (4.7–6.3)
73 (20.2)5.7 ± 1.0 
6.0 (5.3–6.7)
34 (12.5)0.056
 Exercise in number of days 4.0 ± 2.0 
4.0 (2.5–5.5)
72 (19.9)4.0 ± 1.8 
4.0 (2.5–5.5)
34 (12.5)0.919
 Blood-glucose in number of days2.1 ± 2.2 
1.0 (0.0–4.0)
74 (20.5)2.0 ± 2.2 
1.0 (0.5–3.5)
34 (12.5)0.675
 Foot-care in number of days 1.9 ± 2.0 
1.5 (0.0–3.5)
72 (19.9)1.9 ± 2.0 
1.0 (0.0–3.5)
34 (12.5)0.695
 Medication in number of days 6.7 ± 1.0 
7.0 (7.0–7.0)
73 (20.2)6.9 ± 0.5 
7.0 (7.0–7.0)
34 (12.5)0.013
 Smoking 54 (25.1)146 (40.4)38 (22.8)105 (38.6)0.418

B. Results of Curious Users, Active Users, and Nonusers of the Online Care Platform e-Vita

See Tables 9, 10, 11, 12, and 13.


Demographic and clinical parameters  
(%)/mean ± SD/median (25–75 quartiles)
Nonusers
()
MissingCurious users
()
MissingActive users
()
MissingUnivariate 
value

Men214 (59.3)0 (0)113 (61.4)0 (0)50 (56.8)0 (0)0.760
Age in years62.1 ± 9.5 
63.0 (56.5–68.0)
0 (0)61.8 ± 9.5 
62.0 (56.3–68.0)
0 (0)62.0 ± 9.4 
63.0 (57.0–67.0)
0 (0)0.935
Ethnicity
 Caucasian292 (99.0)66 (18.3)143 (100)41 (22.3)65 (100)23 (6.1)0.706
 Other3 (1.0)0 (0)0 (0)0.382
T2DM duration in years 6.2 ± 4.6 
6.0 (2.0–9.0)
9 (2.5)5.7 ± 4.4  
5.0 (2.0–8.0)
1 (0.5)5.4 ± 4.4 
4.5 (2.0–8.0)
0 (0)0.165
HbA1c in mmol/mol 50.6 ± 9.5 
50.0 (45.0–54.0)
3 (0.8)48.7 ± 7.4 
48.0 (43.0–54.0)
0 (0)47.0 ± 7.0 
46.0 (43.0–50.8)
0 (0)0.001
BMI29.8 ± 4.9 
29.0 (26.5–32.5)
3 (0.8)30.0 ± 4.8 
29.3 (26.9–32.3)
0 (0)29.9 ± 8.0 
28.0 (26.0–32.6)
2 (2.3)0.921
Systolic blood pressure in mmHG 135.6 ± 15.50 (0)137.2 ± 16.32 (1.1)135.1 ± 15.32 (2.3)0.463
Cholesterol in mmol/L 4.4 ± 1.04 (1.1)4.4 ± 0.80 (0)4.4 ± 0.92 (2.3)0.775
HDL in mmol/L 1.3 ± 0.4 4 (1.1)1.2 ± 0.31 (0.5)1.3 ± 0.42 (2.3)0.071
Cholesterol/HDL ratio3.6 ± 1.1160 (44.3)3.7 ± 1.457 (31.0)3.4 ± 1.035 (39.8)0.185
LDL in mmol/L2.4 ± 0.912 (3.3)2.4 ± 0.83 (1.6)2.3 ± 0.83 (3.4)0.473
Triglycerides in mmol/L 1.7 ± 1.0 
1.5 (1.0–2.1)
7 (1.9)1.8 ± 1.3 
1.5 (1.1–2.1)
0 (0)1.7 ± 1.0 
1.4 (1.0–2.0)
2 (2.3)0.531
Creatinine in µmol/L78.6 ± 17.2 
77.0 (67.0–88.0)
6 (1.7)80.9 ± 17.4 
79.0 (68.0–92.0)
1 (0.5)77.8 ± 17.8 
75.5 (66.0–85.8)
0 (0)0.259
Alb./creat. ratio in mg/mmol
 Men2.0 ± 4.4 
0.7 (0.3–1.5)
23 (10.7)2.2 ± 6.9 
0.5 (0.3–1.5)
18 (15.9)1.3 ± 1.7 
0.7 (0.3–1.5)
7 (14.0)0.636
 Women1.6 ± 3.5 
0.7 (0.3–1.5)
31 (21.1)1.1 ± 1.3 
0.7 (0.4–1.5)
8 (11.3)0.6 ± 0.5 
0.6 (0.3–0.9)
10 (26.4)0.155
MDRD in mL/min/1.73 m2 79.1 ± 49.0 
75.0 (61.0–88.0)
5 (1.4)75.7 ± 16.2 
73.0 (61.0–87.0)
1 (0.5)76.7 ± 17.4 
75.5 (61.0–89.0)
0 (0)0.610
Smoking
 Yes54 (15.1)3 (0.8)30 (16.4)1 (0.5)11 (12.5)0 (0)0.382
 Before158 (44.1)73 (39.7)31 (35.2)
 No146 (40.8)80 (43.7)46 (52.3)
Alcohol consumption in units/day
 0166 (58.9)79 (21.9)98 (60.9)23 (12.5)41 (60.3)20 (22.7)0.646
 161 (21.6)8 (23.6)14 (20.6)
 239 (13.8)17 (10.6)13 (19.1)
 311 (3.9)7 (4.3)0 (0)
 44 (1.4)1 (0.5)0 (0)
 50 (0)0 (0)0 (0)
 61 (0.4)0 (0)0 (0)
Employment
 Fulltime/part-time working 99 (34.3)72 (19.9)61 (39.6)30 (16.3)20 (23.8)4 (4.5)0.063
 Retired134 (46.4)70 (45.5)46 (54.8)
 Unemployed/housekeeper38 (13.1)20 (13.0)9 (10.7)
 Incapacitated 18 (6.2)3 (1.9)9 (10.7)
Educational level
 None 0 (0)73 (20.2)1 (0.7)31 (16.8)0 (0)4 (4.5)0.125
 Primary school24 (8.3)9 (5.9)4 (4.8)
 Low127 (44.1)52 (34.0)27 (32.1)
 Intermediate86 (29.9)51 (33.3)30 (35.7)
 High51 (17.7)40 (26.1)23 (27.4)


Medication prescription
(%)
Nonusers
()
Missing Curious users
()
MissingActive users
()
MissingUnivariate
value

Diabetes-related
 Oral treatment only251 (71.3)9 (2.5)128 (71.5)5 (2.7)64 (72.7)0 (0)1.000
 Insulin treatment only4 (1.1)9 (2.5)1 (0.5)5 (2.7)0 (0)0 (0)0.899
 Mix of oral and insulin treatment40 (11.4)9 (2.5)18 (10.1)5 (2.7)5 (5.7)0 (0)0.242
 No medication57 (16.2)9 (2.5)32 (17.9)5 (2.7)19 (21.6)0 (0)0.521
Comorbidity or complication related
 Calcium channel blockers50 (14.2)9 (2.5)31 (17.3)5 (2.7)16 (18.2)0 (0)0.415
 Beta blockers128 (36.4)9 (2.5)74 (41.3)5 (2.7)36 (40.9)0 (0)0.324
 Diuretics121 (34.4)9 (2.5)63 (35.2)5 (2.7)31 (35.2)0 (0)0.979
 Ace and RAAS inhibitors196 (55.7)9 (2.5)94 (52.5)5 (2.7)47 (53.4)0 (0)0.738
 Other blood pressure lowering medications3 (0.9)9 (2.5)0 (0)5 (2.7)1 (1.1)0 (0)0.357
 Lipid lowering medication280 (79.5)9 (2.5)141 (78.8)5 (2.7)72 (81.8)0 (0)0.868


Complications and risk factors
(%)
Nonusers
()
MissingCurious users
()
MissingActive users
()
MissingUnivariate
value

Cardiovascular, total225 (96.2)127 (35.2)128 (98.5)54 (29.3)59 (98.3)28 (31.8)0.506
Cardiovascular, specific
 Angina pectoris 41 (21.7)172 (47.6)21 (21.4)86 (46.7)7 (15.9)44 (50.0)0.698
 Myocardial infarct29 (15.3)172 (47.6)15 (15.3)86 (46.7)8 (17.4)42 (47.7)0.932
 Other/chronic ischemic heart diseases 34 (16.1)150 (41.6)18 (14.9)63 (34.2)6 (10.9)33 (37.5)0.750
 Hypertension191 (84.1)134 (37.1)113 (93.4)63 (34.2)51 (92.7)33 (37.5)0.025
 TIA 12 (6.4)174 (48.2)4 (4.2)88 (47.8)3 (7.0)45 (51.1)0.747
 CVA 13 (7.0)176 (48.8)6 (6.1)86 (46.7)4 (9.5)46 (52.3)0.745
 Intermittent claudication 7 (3.3)150 (41.6)4 (3.3)63 (34.2)3 (5.5)33 (37.5)0.689
  Aortic aneurysms4 (1.9)150 (41.6)1 (0.8)63 (34.2)1 (1.8)33 (37.5)0.731
 CABG 15 (5.1)68 (18.8)7 (5.0)43 (23.4)4 (6.3)25 (28.4)0.916
 PTCA 28 (9.6)68 (18.8)9 (6.4)43 (23.4)5 (7.8)24 (27.3)0.588
 Heart failure 14 (8.1)189 (52.4)9 (9.4)88 (47.8)1 (2.5)48 (54.5)0.409
Retinopathy19 (9.3)156 (43.2)14 (11.7)64 (34.8)4 (7.0)31 (35.2)0.640
Renal impairment35 (18.6)173 (47.9)15 (15.5)87 (47.3)11 (25.6)45 (51.1)0.350
Albuminuria
 Men 30 (14.5)7 (3.3)14 (12.6)2 (1.8)6 (12.5)2 (4.0)0.908
 Women 8 (5.8)8 (5.4)1 (1.4)1 (1.4)0 (0)4 (10.5)0.226
Neuropathy49 (22.2)140 (38.8)30 (24.6)62 (33.7)9 (17.3)36 (40.9)0.594
Foot complication
 SIMMs 0228 (77.6)67 (18.6)105 (73.4)41 (22.3)56 (83.6)21 (23.9)0.524
 SIMMs 157 (19.4)31 (21.7)9 (13.4)
 SIMMs 2 or 39 (3.1)7 (4.9)2 (3.0)
Psychiatric disorders19 (9.0)150 (41.6)7 (5.8)63 (34.2)2 (3.6)33 (37.5)0.317


Items of Europep: patients who scored 4 (good) to 5 (excellent)
(%)
Nonusers ()MissingCurious users ()MissingActive users ()Missing Univariate
value

What is your assessment of the general practitioner over the last 12 months with respect to the following?
Making you feel that you have time during consultation737 (95.1)105 (11.9)174 (99.4)9 (4.9)82 (95.3)2 (2.3)0.159
Showing interest in your personal situation707 (91.6)108 (12.3)165 (94.8)10 (5.4)81 (94.2)2 (2.3)0.970
Making it easy for you to tell him or her about your problem694 (92.2)127 (14.4)165 (98.2)16 (8.7)80 (93.0)2 (2.3)0.047
Involving you in decisions about your medical care680 (90.7)130 (14.8)159 (93.5)14 (7.6)80 (95.2)4 (4.5)0.489
Listening to you709 (92.0)109 (12.4)163 (94.8)12 (6.5)80 (94.1)3 (3.4)0.579
Keeping your records and data confidential661 (93.8)175 (19.9)161 (97.0)18 (9.8)75 (93.8)8 (9.1)0.764
Providing quick relief of your symptoms588 (83.9)179 (20.3)137 (86.2)25 (13.6)64 (85.3)13 (14.8)0.863
Helping you to feel well so that you can perform your normal daily activities599 (89.7)212 (24.1)135 (91.8)37 (20.1)61 (89.7)20 (22.7)0.780
Thoroughness of the approach to your problems675 (90.7)136 (15.5)153 (90.5)15 (8.2)74 (88.1)4 (4.5)0.769
Your physical examination639 (90.8)176 (20.0)153 (92.7)19 (10.3)69 (90.8)12 (13.6)0.577
Offering services for preventing diseases (screening, health checks, and immunizations)653 (92.5)174 (19.8)151 (91.5)19 (10.3)74 (94.9)10 (11.4)0.539
Explaining the purpose of examinations, tests, and treatments677 (92.4)147 (16.7)163 (94.8)12 (6.5)77 (91.7)4 (4.5)0.402
Telling you enough about your symptoms and/or illness662 (90.2)146 (16.6)158 (92.4)13 (7.1)80 (95.2)4 (4.5)0.579
Helping you deal with emotions related to your health status424 (84.8)380 (43.2)89 (86.4)81 (44.0)44 (81.5)34 (38.6)0.659
Helping understand why it is important to follow the GP’s advice631 (89.1)172 (19.5)146 (89.6)21 (11.4)73 (89.0)6 (6.8)0.965
Knowing what has been done or told during previous contacts in the practice601 (86.8)188 (21.4)148 (90.2)20 (10.9)71 (87.7)7 (8.0)0.158
Preparing you for what to expect from specialists, hospital care, and other care providers424 (82.8)368 (41.8)107 (8.3)54 (29.3)49 (86.0)31 (35.2)0.577

What is your assessment of the general practice over the last 12 months with respect to the following?
The helpfulness of the practice staff (other than the doctor) to you313 (93.4)26 (7.2)158 (92.9)14 (7.6)77 (92.8)5 (5.7)0.953
Getting an appointment to suit you301 (88.5)21 (5.8)152 (86.9)9 (4.9)72 (85.7)4 (4.5)0.867
Getting through to the practice on telephone249 (73.0)20 (5.5)120 (68.6)9 (4.9)60 (71.4)4 (4.5)0.777
Being able to talk to the general practitioner on the telephone167 (70.5)124 (34.3)71 (62.8)71 (38.6)35 (63.6)33 (37.5)0.306
Waiting time in the waiting room246 (71.3)16 (4.4)119 (68.4)10 (5.4)51 (59.3)2 (2.3)0.148
Providing quick services for urgent health problems241 (90.3)94 (26.0)118 (86.8)48 (26.1)53 (86.9)27 (30.7)0.658


EQ-5D, WHO-5, PAID-5, and SDSCA 
(%)/mean ± SD/median (25–75 quartiles)
Nonusers
()
MissingCurious users
()
MissingActive users
()
MissingUnivariate 
value

EQ-5D index-score0.9 ± 0.272 (19.9)0.9 ± 0.132 (17.4)0.9 ± 0.24 (4.5)0.030
EQ-VAS 74.7 ± 17.4 
80.0 (60.0–90.0)
74 (20.5)79.3 ± 13.8 
80.0 (73.0–90.0)
35 (19.0)76.9 ± 16.5 
80.0 (0.0–90.0)
5 (5.7)0.032
WHO-5 index-score 70.4 ± 17.9 
76.0 (60.0–80.0)
76 (21.1)74.1 ± 12.7 
76.0 (68.0–80.0)
33 (17.9)70.2 ± 16.5 
76.0 (60.0–80.0)
1 (1.1)0.080
WHO-5 score indicates suboptimal well-being, screening depression advised36 (12.6)76 (21.1)8 (5.3)33 (17.9)9 (10.8)1 (1.1)0.018
WHO-5 answers advise screening depression 43 (15.5)76 (21.1)6 (4.0)33 (17.9)11 (13.3)1 (1.1)0.002
PAID-5 total score 2.8 ± 3.1 
2.0 (0.0–4.5)
76 (21.1)1.8 ± 2.4 
1.0 (0.0–3.0)
32 (17.4)2.2 ± 2.5 
1.0 (0.0–4.0)
1 (1.1)0.016
PAID-5 score indicates distress 15 (5.3)76 (21.1)4 (2.6)32 (17.4)2 (2.4)1 (1.1)0.183
SDSCA
 General diet in number of days 5.4 ± 1.8 
6.0 (5.0–7.0)
76 (21.1)5.5 ± 1.9 
6.0 (5.0–7.0)
32 (17.4)5.8 ± 1.7 
6.0 (5.5–7.0)
5 (5.7)0.258
 Specific diet in number of days 5.6 ± 1.1 
5.7 (4.7–6.3)
73 (20.2)5.7 ± 1.0 
6.0 (5.0–6.7)
30 (16.3)5.7 ± 1.0 
6.0 (5.3–6.6)
4 (4.5)0.160
 Exercise in number of days 4.0 ± 2.0 
4.0 (2.5–5.5)
72 (19.9)4.1 ± 1.8 
4.0 (2.9–5.6)
30 (16.3)3.8 ± 1.8 
3.8 (2.5–5.0)
4 (4.5)0.612
 Blood-glucose in number of days2.1 ± 2.2 
1.0 (0.0–4.0)
74 (20.5)2.1 ± 2.4 
1.0 (0.0–4.0)
30 (16.3)1.8 ± 1.8 
1.0 (0.5–2.3)
4 (4.5)0.241
 Foot-care in number of days 1.9 ± 2.0 
1.5 (0.0–3.5)
72 (19.9)1.9 ± 2.0 
1.0 (0.0–3.5)
30 (16.3)1.8 ± 2.0 
1.0 (0.0–3.5)
4 (4.5)0.924
 Medication in number of days 6.7 ± 1.0 
7.0 (7.0–7.0)
73 (20.2)7.0 ± 0.2 
7.0 (7.0–7.0)
30 (16.3)6.8 ± 0.8 
7.0 (7.0–7.0)
4 (4.5)0.020
 Smoking 54 (25.1)146 (40.4)24 (21.8)74 (40.2)14 (24.6)31 (35.2)0.704

Abbreviations

EQ-5D:EuroQol-5 Dimensions
EQ-VAS:EuroQol Visual Analogue Scale
GFR:Glomerular filtration rate
GP:General practitioner
HRQoL:Health-related quality of life
MDRD:Modification of Diet in Renal Disease
PAID-5:Problem Areas in Diabetes-5 questions
PN:Practice nurse
SDSCA: Summary of Diabetes Self-Care Activities
T2DM:Type 2 diabetes mellitus
WHO-5:WHO-Five Item Measure of Well-Being.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

The authors wish to thank all the participating patients and primary health care workers in the Drenthe region of the Netherlands. Thanks also are due to Jurriaan Kok for his support and for managing the DM part of the e-Vita research program and all coordinators and supporters within the foundation Care Within Reach (in Dutch: stichting Zorg Binnen Bereik). The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this paper: the study has been funded by foundation Care Within Reach (in Dutch: stichting Zorg Binnen Bereik).

References

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Copyright © 2016 Yvonne Roelofsen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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