Published on in Vol 5, No 12 (2021): December

Preprints (earlier versions) of this paper are available at, first published .
The Impact of Patient Characteristics on Their Attitudes Toward an Online Patient Portal for Communicating Laboratory Test Results: Real-World Study

The Impact of Patient Characteristics on Their Attitudes Toward an Online Patient Portal for Communicating Laboratory Test Results: Real-World Study

The Impact of Patient Characteristics on Their Attitudes Toward an Online Patient Portal for Communicating Laboratory Test Results: Real-World Study

Original Paper

1Saltro Diagnostic Centre, Utrecht, Netherlands

2National eHealth Living Lab, Leiden University Medical Centre, Leiden, Netherlands

3Public Health and Primary Care Department, Leiden University Medical Centre, Leiden, Netherlands

4Unilabs Group, Geneva, Switzerland

Corresponding Author:

Rosian Tossaint-Schoenmakers, MSc

Saltro Diagnostic Centre

Mississippidreef 83

Utrecht, 3565 CE


Phone: 31 302361136


Background: Patient portals are promising tools to increase patient involvement and allow them to manage their health. To optimally facilitate patients, laboratory test results should be explained in easy language. Patient characteristics affect the usage of portals and the user satisfaction. However, limited research is available, specified for online communicating laboratory test results, on whether portal use and acceptance differ between groups.

Objective: The aim of this study was to assess the effect of patient characteristics (gender, age, education, and chronic disease) on the self-efficacy and perceived usability of an online patient portal that communicates diagnostic test results.

Methods: We used the online-administered eHealth impact questionnaire (eHIQ) to explore patients’ attitudes toward the portal. Patients visiting the portal were asked to complete the questionnaire and to answer questions regarding gender, age, education, and chronic disease. The subscale “information and presentation” of the eHIQ assessed the usability of the patient portal and the subscale “motivation and confidence to act” assessed self-efficacy to determine whether patients were motivated to act on the presented information. Age, gender, education, and chronic disease were the determinants to analyze the effect on usability and self-efficacy. Descriptive analyses were performed to explore patient characteristics, usability, and self-efficacy. Univariable and multivariable regression analyses were performed with age, gender, education, and chronic disease as determinants, and usability and self-efficacy as outcomes.

Results: The questionnaire was completed by 748 respondents, of which 428 (57.2%) were female, 423 (56.6%) were highly educated, and 509 (68%) had no chronic disease. The mean age was 58.5 years (SD 16.4). Higher age, high education, and asthma or chronic obstructive pulmonary disease were significant determinants for decreased usability; respectively, b=-.094, 95% CI -1147 to 0.042 (P<.001); b=-2.512, 95% CI -4.791 to -0.232 (P=.03); and b=-3.630, 95% CI -6.545 to -0.715 (P=.02). High education was also a significant determinant for a lower self-efficacy (b=-3.521, 95% CI -6.469 to -0.572; P=.02). Other determinants were not significant.

Conclusions: This study showed that the higher-educated users of a patient portal scored lower on usability and self-efficacy. Usability was also lower for older people and for patients with asthma or chronic obstructive pulmonary disease. The results portal is not tailored for different groups. Further research should investigate which factors from a patient’s perspective are essential to tailor the portal for different groups and how a result portal can be optimally integrated within the daily practice of a doctor.

JMIR Form Res 2021;5(12):e25498



The involvement of patients is important to allow them to manage their own health. When patients are more engaged, they tend to make better decisions on health behavior [1]. Patient involvement has increasingly been stimulated with digital possibilities [2], such as in patient portals [3,4]. A Dutch patient portal developed by Saltro Diagnostic Center provides patients access to laboratory test results, including explanatory information and visualization [3]. The aim of this portal is to increase patients’ knowledge and to facilitate them to take an active role in their diagnostic process (eg, to ask questions and share opinions to improve the diagnostic process and reduce the risk of diagnostic errors [5]). Patient portals conveying laboratory test results in understandable language can help patients to take a more active role in managing their own health [6]. Therefore, it is recommended to test how patients perceive online portals and test results, for example by using the eHealth impact questionnaire (eHIQ) [7].

In 2019, we investigated patients’ attitudes toward the same portal designed to communicate laboratory test results using the eHIQ [6]. The usability of this portal was rated positively, suggesting that the study participants found the patient portal easy to use, considered it trustworthy and appropriate, and that the provided information was easy to understand. The self-efficacy of the patients received a satisfying score, referring to whether patients were motivated to act on the presented information. It was concluded that the patients were generally positive toward the portal with opportunities to optimize self-efficacy; however, the impact of patient characteristics was not accounted for. Patient characteristics such as gender, age, education, and chronic disease can affect the usage of portals and the user satisfaction [8-10]. Limited research is available, specified for online communicating laboratory test results, on whether portal use and acceptance differ between groups. Further research on potential group differences is necessary to fine-tune the portal, making it acceptable for every user. We aim to replicate the previous study with larger numbers to examine how different groups of patients perceived the portal.

The main aim of this study is to evaluate the effect of gender, age, education, and chronic disease on the usability and self-efficacy of patients using a patient portal designed to communicate laboratory tests.

Design and Participants

A cross-sectional real-world study was conducted between December 2019 and July 2020 to explore the influence of patient characteristics on the usability of a patient portal and on self-efficacy. Patients who viewed their test results in the portal were automatically approached to complete the eHIQ. Age, gender, education level, and chronic disease were measured as well. There were no further inclusion or exclusion criteria.

No personal information was collected, and the data could not be traced back to the individual. Therefore, this study does not fall under the Medical Research Involving Human Subject Act (Wet medisch-wetenschappelijk onderzoek met mensen) and did not require approval from an ethics committee.

Patient Portal

In 2015, Saltro launched a web-based portal that gives patients access to their own laboratory test results, including understandable explanatory information [3]. The content was created by a team of patients, general practitioners (GPs), communication specialists, and clinical chemists. Researchers estimated the level of health literacy of the information at communication level 1B based on the scales of the Common European Framework of Reference for Languages [11]. Daily, approximately 300 unique individuals look up their laboratory test results with the option to share their results with others.

After blood withdrawal, the patients can look up their results by logging into the portal, with a username and password, through the website of the GP. The log-in procedure adheres to Dutch security legislation and guidelines (ie, the Dutch Personal Data Protection Act) and the General Data Protection Regulation guidelines. The patients can see an overview of all laboratory tests ordered by date (Figure 1). Each result has traffic-light–colored bullets and a visual.

This portal can be approached directly for laboratory test results but can also be approached within other portals as a plug-in; for example, a GP portal that functions as medication description.

Figure 1. Example of a test result with explanation. GP: general practitioner.
View this figure

Outcome Measures

Primary outcomes were “information and presentation” and “motivation and confidence to act” in the Dutch version of the eHIQ, part 2 (eHIQ2) [12,13]. The eHIQ2 is a self-reporting questionnaire measuring patients’ attitudes toward a specific health-related website. Each of the 26 items is scored on a 5-point Likert scale ranging from “strongly disagree (1)” to “strongly agree (5).” The questionnaire has three subscales: information and presentation; motivation and confidence to act; and identification. The “information and presentation” subscale has 13 items and measures whether people find the website easy to use, which includes items on understanding, trustworthiness, and whether images used were appropriate. This subscale relates to usability. The “motivation and confidence to act” subscale consists of 10 items and assesses whether an individual felt reassured after reading the information on the website and was motivated to manage their health. This subscale relates to self-efficacy. The final subscale, identification, consists of 3 items and measures whether individuals identify with others who use the website. An example item is the following: “I feel I have a sense of solidarity with other people using the website.” As users of the patient portal do not interact with other users, this subscale was considered irrelevant for the current study and is therefore not discussed further. The total scores per subscale were transformed to a 0-100 scale (higher scores representing a more positive attitude).

The determinants were age, gender, education, and chronic disease (Table 1), based on studies demonstrating that portal use was influenced inter alia by age, gender, presence of a chronic illness, education, and health literacy level [8,9,14]. Gender, instead of sex, was chosen because the patients’ attitude and experience were analyzed. There was no biological measurement involved. Education level was chosen, but not health literacy, in order to minimalize the participants’ number of questions. Relationships are proven between health literacy and education level, although health literacy is also common among the highly educated [15]. The choice for types of chronic diseases is based on the 5 most prevalent chronic diseases in the Netherlands: diabetes mellitus, asthma, chronic obstructive pulmonary disease (COPD), cardiovascular disease, and cancer [16,17]. Except for cancer, Saltro performs the blood test for these types of chronic diseases. People with asthma and COPD receive the same pulmonary function test and are therefore considered as 1 patient group in this research. Diabetes mellitus, Asthma or COPD, and cardiovascular diseases are the most prevalent chronic diseases in the population of Dutch GPs; these chronically ill patients are regularly monitored by GPs in a chronic care program with regular laboratory checks.

Table 1. Patient characteristics.
AgeAge at completing the questionnaire


Education [18]

Low (no education, high school)

Intermediate (intermediate vocational education)

High (bachelor’s degree, master’s degree, doctorate)
Chronic disease

Diabetes mellitus

Asthma or chronic obstructive pulmonary disease

Cardiovascular disease


Statistical Analyses

Descriptive analyses were performed to explore patient characteristics, usability, and self-efficacy. Univariable regression analyses were performed with age, gender, education, and chronic disease as determinants and usability and self-efficacy as outcomes. Significant (P<.10) determinants were included in multivariable models to examine which characteristics were independently related to the outcomes. To be rather inclusive than exclusive regarding the selection of variables for our multivariable model, P=.10 was chosen. A common level of P=.05 might fail to include relevant variables in those models [19]. For all other analyses and conclusion, P<.05 was considered statistically significant. The analyses were performed using the SPSS version 24 (IBM Corp) [20].

Participant Characteristics, Usability, and Self-efficacy

The questionnaire was completed by 748 respondents. Response rate was 1.9% (39,430 unique visitors during the study period). The participants had a mean age of 58.5 years (SD 16.4), and they were mostly female (428/748, 57.2%) and highly educated (423/748, 56.6%) (Table 2). Moreover, 509/748 (68%) had no chronic disease. The mean scores of usability and self-efficacy were 68.9 (SD 10.6) and 62.5 (SD 13.1), respectively (Table 3). The mean (SD) scores on all items of the “information and presentation” and “motivation and confidence to act” domains can be found in Multimedia Appendix 1.

Table 2. Patient characteristics (N=748).
Age (years), mean (SD)52.8 (16.4)
Gender, n (%)

Male314 (42.0)

Female428 (57.2)

Missing value6 (0.8)
Education, n (%)

Low (no education, high school)96 (12.8)

Intermediate (intermediate vocational education)220 (29.4)

High (bachelor’s degree, master’s degree, doctorate)423 (56.6)

Missing value9 (1.2)
Chronic disease, n (%)

Diabetes mellitus93 (12.4)

Asthma or COPDa54 (7.2)

Cardiovascular disease87 (11.6)

No chronic disease509 (68.0)

Missing value5 (0.7)

aCOPD: chronic obstructive pulmonary disease.

Table 3. Mean scores on the eHealth impact questionnaire (eHIQ); N=747.
Usabilitya, mean (SD) (1 missingb)68.9 (10.6)
Self-efficacyc, mean (SD) (1 missing)62.5 (13.6)

aUsability is measured with the eHIQ subscale "information and presentation".

bMissing value: one respondent gave the same answer to every question, including reversed questions, which indicates false responding.

cSelf-efficacy is measured with the eHIQ2 subscale “motivation and confidence to act.”

Determinants for Perceived Usability

Age, education level, and chronic disease were relevant determinants with P<.10 for usability in the univariable analysis; they and where subsequently added in the multivariable model (Table 4). Multivariable analysis showed that higher age and high education were associated with a decreased usability: respectively, b=-.094, 95% CI -1147 to -0.042 (P<.001); and b=-2.512, 95% CI -4.791 to -0.232 (P=.03). Chronic disease affected usability, with patients with asthma or COPD scoring significantly lower compared with those without a chronic disease (b=-3.630, 95% CI -6.545 to -0.715; P=.02).

Table 4. Determinants for perceived usability.
DeterminantUnivariable analysisMultivariable analysis
Reference groupDeterminantba (95% CI)P valueb (95% CI)P value
Age per yearAge-.067 (-0.114 to -0.021).004-.094 (-1.147 to -0.042)<.001
MaleGender1.322 (-0.234 to 2.878).10-.153 (-1.806 to 1.500).86
Low educationIntermediate education1.275 (-1.224 to 3.774).321.262 (-1.189 to 3.712).31
High education-1.992 (-4.302 to 0.318).09-2.512 (-4.791 to -0.232).03
No chronic diseaseDiabetes-.377 (-2.692 to 1.939).80.347 (-2.053 to 2.747).78
Asthma or COPDb-3.399 (-6.337 to -.416).02-3.630 (-6.545 to -0.715).02
Cardiovascular disease-.286 (-2.668 to 2.096).81.890 (-1.576 to 3.357).48

ab: unstandardized beta value.

bCODP: chronic obstructive pulmonary disease.

Determinants for Perceived Self-efficacy

Education level was a relevant determinant for self-efficacy in the univariable analysis with P<.10 (b=-3.521, 95% CI -6.469 to -.572; P=.02) (Table 5). Other determinants were not relevant; therefore, there was no need for a multivariable analysis.

Table 5. Determinants to perceived self-efficacy.
DeterminantUnivariable analysis
Reference groupDeterminantba (95% CI)P value
Age per yearAge-.035 (-.095 to 0.024).24
MaleGender-1.490 (-3.478 to 0.498).14
Low educationIntermediate education.159 (-3.031 to 3.348).92
High education-3.521 (-6.469 to -0.572).02
No chronic diseaseDiabetes-1.279 (-4.254 to 1.697).40
Asthma or COPDb-2.438 (-6.214 to 1.338).21
Cardiovascular disease2.205 (-.856 to 5.265).16

ab: unstandardized beta value.

bCODP: chronic obstructive pulmonary disease.

Principal Findings

This study aimed to evaluate the impact of patient characteristics on the perceived usability and self-efficacy of a patient portal. Higher education was associated with decreased usability and self-efficacy. Furthermore, usability was lower for older patients and for patients with asthma or COPD. The eHIQ is a validated questionnaire, and the results of this study with the eHIQ are in line with our previous study [6].

The finding that highly educated people have a significantly lower perceived usability and self-efficacy after using the portal is not in line with other research projects [21]. Mostly, people with high education tend to be more eHealth literate, showing more positive outcomes (motivation, self-efficacy, and better interaction with the doctor) after reading health information on the internet [21]. The use of qualitative interviews with the participants to explore the usability findings would be worthwhile. Nonetheless, other research projects on digital health information showed that tailoring—enabling users to self-tailor the preferred mode of information delivery via text and (audio)visuals—enhanced satisfaction with attractiveness and comprehensibility as compared with various versions of the nontailored digital information [22,23]. The patients were directly involved in the design phase of the studied results portal. However, the portal is not tailored for a specific group and might not be suitable for highly educated people. The continued development of the portal is an opportunity to take into account, especially by involving different education groups to give tailored advice through the portal.

This study also revealed that older participants scored lower on the usability of the portal. In other studies, the differences between age groups could be explained via the groups' digital skills. Van Deursen et al [24] and Broekhuizen et al [25] found that a higher age lowered operational and formal internet skills, such as operating an internet browser and maintaining a sense of orientation. However, in a study about the association of the usage of a public evidence-based health website and health care consultations, the use of digital information led to a decrease in regular doctors’ consultations for older people in the same way as for other age groups [26]. Nevertheless, the presentation and design of test results should be tailored for every age group [27] to obtain excellent usability and self-efficacy.

Furthermore, our research demonstrated that patients with asthma or COPD were more negative about usability. Other research projects reported that these patients are often insufficiently capable of understanding health information [28], which could be explained by anxiety, specific illness perception, age, and disease severity [29]. Other studies showed that the use of COPD self-management platforms is higher when the platform is an integrated part of health care [4]. Finally, some studies emphasized the importance of integrating skill-building activities into comprehensive education programs that enable patients with severe cases of asthma or COPD to identify high-quality sources of web-based health information [30]. Our study revealed that asthma or COPD patients are more negative about the results portal. Even more important for this group is tailoring the portal and integrating it into usual care [4]. Therefore, considerations for redesigning the online portal are at issue, together with COPD patients.

Strength and Limitations

A strength of our study was the high sample size and that the patients completed the questionnaire immediately after they viewed their results, thereby limiting recall bias and giving an accurate picture of the patients’ attitudes toward the portal. Nevertheless, those who completed the study questionnaire were a small portion of the total group that used the patient portal. The low response rate precludes generalizing whether the patient portal display and explanation of the results are acceptable and informative for all of the patients. In future research, it is interesting to compare patients that use the portal to those who do not. Moreover, we were not exhaustive with the possible patient characteristics as determinants. We cannot determine other factors that contribute to the patients' perceived usability and self-efficacy after seeing their lab results online. Possible other determinants that may impact usability and self-efficacy are the quality of the portal, the motivation to use the internet for health improvement [31], and the way patients use their knowledge in relation to the doctor [32,33]. Regarding the patient portal itself, lab results need to be easily understandable [34], and technology needs to be easy to use [8,35]. Previous research shows that the related lab results are easily understandable and that the patient portal is easy to use [3]. Therefore, it is interesting to explore which other factors influence a patient's attitude toward the patient portal.


Highly educated users of a test results portal scored lower on usability and self-efficacy. The usability was also lower for older people and for patients with asthma or COPD. Result portals must adapt the language and communication used, according to the different target groups of age, education, and chronic illness. Only then can users take full advantage of the online information provision. Further research is necessary to determine promoting factors that users themselves consider important in a results portal, in order to tailor it for different groups. Further research is also needed on ways in which a portal can be optimally implemented and integrated within the daily practice of a doctor.


The authors would like to thank the patients that were involved in several phases of the development of the portal and this study. The authors also thank the professionals and employees of Saltro who contributed to the development of the portal and this study.

Conflicts of Interest

RT and AG are employees of Saltro, where the portal has been developed and implemented. ET is a former employee of Saltro.

Multimedia Appendix 1

Mean (SD) score subscales “information and presentation” and “motivation and confidence to act” from the eHealth impact questionnaire (eHIQ).

DOCX File , 15 KB

  1. Hibbard JH, Mahoney ER, Stock R, Tusler M. Do increases in patient activation result in improved self-management behaviors? Health Serv Res 2007 Aug;42(4):1443-1463 [FREE Full text] [CrossRef] [Medline]
  2. Snyder H, Engström J. The antecedents, forms and consequences of patient involvement: A narrative review of the literature. Int J Nurs Stud 2016 Jan;53:351-378. [CrossRef] [Medline]
  3. Struikman B, Bol N, Goedhart A, van Weert JCM, Talboom-Kamp E, van Delft S, et al. Features of a Patient Portal for Blood Test Results and Patient Health Engagement: Web-Based Pre-Post Experiment. J Med Internet Res 2020 Jul 20;22(7):e15798 [FREE Full text] [CrossRef] [Medline]
  4. Talboom-Kamp EP, Verdijk NA, Kasteleyn MJ, Harmans LM, Talboom IJ, Numans ME, et al. High Level of Integration in Integrated Disease Management Leads to Higher Usage in the e-Vita Study: Self-Management of Chronic Obstructive Pulmonary Disease With Web-Based Platforms in a Parallel Cohort Design. J Med Internet Res 2017 May 31;19(5):e185 [FREE Full text] [CrossRef] [Medline]
  5. McDonald KM, Bryce CL, Graber ML. The patient is in: patient involvement strategies for diagnostic error mitigation. BMJ Qual Saf 2013 Oct;22 Suppl 2:ii33-ii39 [FREE Full text] [CrossRef] [Medline]
  6. Talboom-Kamp E, Tossaint-Schoenmakers R, Goedhart A, Versluis A, Kasteleyn M. Patients’ Attitudes Toward an Online Patient Portal for Communicating Laboratory Test Results: Real-World Study Using the eHealth Impact Questionnaire. JMIR Form Res 2020 Mar 4;4(3):e17060. [CrossRef]
  7. Kelly L, Jenkinson C, Ziebland S. Measuring the effects of online health information for patients: item generation for an e-health impact questionnaire. Patient Educ Couns 2013 Dec;93(3):433-438 [FREE Full text] [CrossRef] [Medline]
  8. Hoogenbosch B, Postma J, de Man-van Ginkel JM, Tiemessen NA, van Delden JJ, van Os-Medendorp H. Use and the Users of a Patient Portal: Cross-Sectional Study. J Med Internet Res 2018 Sep 17;20(9):e262 [FREE Full text] [CrossRef] [Medline]
  9. Irizarry T, DeVito Dabbs A, Curran CR. Patient Portals and Patient Engagement: A State of the Science Review. J Med Internet Res 2015 Jun 23;17(6):e148 [FREE Full text] [CrossRef] [Medline]
  10. Rains SA. Perceptions of Traditional Information Sources and Use of the World Wide Web to Seek Health Information: Findings From the Health Information National Trends Survey. Journal of Health Communication 2007 Oct 11;12(7):667-680. [CrossRef] [Medline]
  11. Taalprofielen. Amersfoort: SLO; 2021 Jun 02.   URL: [accessed 2021-11-30]
  12. Kelly L, Ziebland S, Jenkinson C. Measuring the effects of online health information: Scale validation for the e-Health Impact Questionnaire. Patient Educ Couns 2015 Nov;98(11):1418-1424 [FREE Full text] [CrossRef] [Medline]
  13. Neijenhuijs KI, van der Hout A, Veldhuijzen E, Scholten-Peeters GGM, van Uden-Kraan CF, Cuijpers P, et al. Translation of the eHealth Impact Questionnaire for a Population of Dutch Electronic Health Users: Validation Study. J Med Internet Res 2019 Aug 26;21(8):e13408 [FREE Full text] [CrossRef] [Medline]
  14. Grossman LV, Masterson Creber RM, Benda NC, Wright D, Vawdrey DK, Ancker JS. Interventions to increase patient portal use in vulnerable populations: a systematic review. J Am Med Inform Assoc 2019 Aug 01;26(8-9):855-870 [FREE Full text] [CrossRef] [Medline]
  15. van der Heide I, Wang J, Droomers M, Spreeuwenberg P, Rademakers J, Uiters E. The relationship between health, education, and health literacy: results from the Dutch Adult Literacy and Life Skills Survey. J Health Commun 2013;18 Suppl 1:172-184 [FREE Full text] [CrossRef] [Medline]
  16. RIVM: Chronische ziekten. RIVM. Bilthoven: RIVM; 2020.   URL: [accessed 2021-11-30]
  17. Factsheet Chronische aandoeningen bij 40-plussers. Vektis. 2019 Jun 04.   URL: [accessed 2021-11-30]
  18. Bevolking; hoogstbehaald onderwijsniveau en onderwijsrichting. CBS. 2011 Nov 16.   URL: [accessed 2021-11-30]
  19. Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med 2008 Dec 16;3:17 [FREE Full text] [CrossRef] [Medline]
  20. SPSS Statistics 24.0.0. IBM. 2016.   URL: [accessed 2021-11-30]
  21. Neter E, Brainin E. eHealth literacy: extending the digital divide to the realm of health information. J Med Internet Res 2012 Jan 27;14(1):e19 [FREE Full text] [CrossRef] [Medline]
  22. Nguyen MH, Bol N, Lustria MLA. Perceived Active Control over Online Health Information: Underlying Mechanisms of Mode Tailoring Effects on Website Attitude and Information Recall. J Health Commun 2020 Apr 02;25(4):271-282. [CrossRef] [Medline]
  23. Nguyen MH, Smets EMA, Bol N, Loos EF, Van Weert JCM. How Tailoring the Mode of Information Presentation Influences Younger and Older Adults' Satisfaction with Health Websites. J Health Commun 2018;23(2):170-180. [CrossRef] [Medline]
  24. van Deursen AJ, van Dijk JA. Using the Internet: Skill related problems in users’ online behavior. Interacting with Computers 2009 Dec;21(5-6):393-402. [CrossRef]
  25. Broekhuizen T, Emrich O, Gijsenberg M, Broekhuis M, Donkers B, Sloot L. Digital platform openness: Drivers, dimensions and outcomes. Journal of Business Research 2021 Jan;122:902-914. [CrossRef]
  26. Spoelman WA, Bonten TN, de Waal MWM, Drenthen T, Smeele IJM, Nielen MMJ, et al. Effect of an evidence-based website on healthcare usage: an interrupted time-series study. BMJ Open 2016 Nov 09;6(11):e013166 [FREE Full text] [CrossRef] [Medline]
  27. Tao D, Yuan J, Qu X. Presenting self-monitoring test results for consumers: the effects of graphical formats and age. J Am Med Inform Assoc 2018 Aug 01;25(8):1036-1046 [FREE Full text] [CrossRef] [Medline]
  28. Heins MJ, Spreeuwenberg P, Heijmans M. Leven met een longziekte in Nederland: cijfers en trends over de zorg- en leefsituatie van mensen met een longziekte. Nivel. 2016.   URL: https:/​/www.​​nl/​publicatie/​leven-met-een-longziekte-nederland-cijfers-en-trends-over-de-zorg-en-leefsituatie-van [accessed 2021-11-30]
  29. Korpershoek Y, Bos-Touwen ID, de Man-van Ginkel JM, Lammers J, Schuurmans MJ, Trappenburg J. Determinants of activation for self-management in patients with COPD. Int J Chron Obstruct Pulmon Dis 2016;11:1757-1766 [FREE Full text] [CrossRef] [Medline]
  30. Stellefson ML, Shuster JJ, Chaney BH, Paige SR, Alber JM, Chaney JD, et al. Web-based Health Information Seeking and eHealth Literacy among Patients Living with Chronic Obstructive Pulmonary Disease (COPD). Health Commun 2018 Dec;33(12):1410-1424 [FREE Full text] [CrossRef] [Medline]
  31. Otokiti A, Williams KS, Warsame L. Impact of Digital Divide on the Adoption of Online Patient Portals for Self-Motivated Patients. Healthc Inform Res 2020 Jul;26(3):220-228 [FREE Full text] [CrossRef] [Medline]
  32. Wildevuur SE, Simonse LW, Groenewegen P, Klink A. Information and communication technology enabling partnership in person-centred diabetes management: building a theoretical framework from an inductive case study in The Netherlands. BMJ Open 2019 Jun 16;9(6):e025930 [FREE Full text] [CrossRef] [Medline]
  33. Otte-Trojel T, Rundall TG, de Bont A, van de Klundert J, Reed ME. The organizational dynamics enabling patient portal impacts upon organizational performance and patient health: a qualitative study of Kaiser Permanente. BMC Health Serv Res 2015 Dec 16;15:559 [FREE Full text] [CrossRef] [Medline]
  34. Garrido T, Jamieson L, Zhou Y, Wiesenthal A, Liang L. Effect of electronic health records in ambulatory care: retrospective, serial, cross sectional study. BMJ 2005 Mar 12;330(7491):581 [FREE Full text] [CrossRef] [Medline]
  35. Ros WJ. MyUMC Patient Portal: patient and professional perspectives. Int J Integr Care 2012 Jun 13;12(4):None. [CrossRef]

COPD: chronic obstructive pulmonary disease
eHIQ: eHealth impact questionnaire
GP: general practitioner

Edited by G Eysenbach; submitted 04.11.20; peer-reviewed by J van Delden, F Lau, T Risling; comments to author 27.11.20; revised version received 20.01.21; accepted 27.09.21; published 17.12.21


©Rosian Tossaint-Schoenmakers, Marise Kasteleyn, Annelijn Goedhart, Anke Versluis, Esther Talboom-Kamp. Originally published in JMIR Formative Research (, 17.12.2021.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.