Limitations of Existing Dialysis Diet Apps in Promoting User Engagement and Patient Self-Management: Quantitative Content Analysis Study

Jun-Hao Lim, Cordelia-Kheng-May Lim, Imliya Ibrahim, Jazlina Syahrul, Mohd Hazli Mohamed Zabil, Nor Fadhlina Zakaria, Zulfitri Azuan Mat Daud, Jun-Hao Lim, Cordelia-Kheng-May Lim, Imliya Ibrahim, Jazlina Syahrul, Mohd Hazli Mohamed Zabil, Nor Fadhlina Zakaria, Zulfitri Azuan Mat Daud

Abstract

Background: With the unprecedented growth of mobile technology, a plethora of dialysis diet apps have been developed to promote patient dietary self-management. Nevertheless, the utility of such apps remains questionable.

Objective: This study aimed to evaluate the content, features, and quality of commercial dialysis diet apps for adult dialysis patients.

Methods: This study consisted of a quantitative content analysis of commercial dialysis diet apps downloaded from Google Play and the Apple App Store available in the Asian marketplace, searched for using the following keywords in English: dialysis diet and diet for kidney disease. Free and paid apps available in English that provide nutrition information for adult dialysis patients were included. Apps that were not relevant to the dialysis diet, not meant for patient self-management, or redundant were excluded. Apps were evaluated for language medium (subscore=1), credibility (subscore=1), food database (subscore=1), valuable features (subscore=12), health-behavior theory constructs (subscore=60), and technical quality (subscore=25). The relationships among the variables of interest were determined by Pearson correlation. Stepwise multiple linear regression analysis was performed to identify the features that contribute to greater technical quality of dialysis diet apps. Statistical significance was defined as P<.05.

Results: A total of 22 out of 253 apps (8.7%) were eligible for evaluation. Based on a 100-point scale, the mean overall score of the apps was 31.30 (SD 14.28). Only 5% (1/22) of the apps offered relevant language options, and 46% (10/22) contained food databases. In addition, 54% (12/22) of the apps were not credible. The mean score for valuable features was 3.45 (SD 1.63) out of 12, in which general education (16/22, 73%), free download (15/22, 68%), and usability (13/22, 59%) were the three most popular features. However, the apps scored a mean of 13.41 (SD 11.56) out of 60 for health-behavior theory constructs. The overall app technical quality was considered poor, with a mean score of 2.70 (SD 0.41) out of 5. The scores of valuable features (r=.65, P=.001) and health-behavior theory constructs (r=.55, P=.009) were positively correlated with the overall technical quality of the commercial dialysis diet apps. Features such as free download (β=.43, P=.03) and usability (β=.41, P=.03) could significantly determine the functional quality of the apps. Health-behavior theory constructs such as self-monitoring could significantly predict both the subjective quality (β=.55, P=.008) and the engagement quality (β=.66, P=.001) of the apps, whereas the information quality domain could be determined by plan or orders (β=.48, P=.007) and knowledge (β=.45, P=.01).

Conclusions: Although most of the available commercial dialysis diet apps are free and easy to use, they are subject to theory deficiency, limited language options, and a lack of food databases, credibility, tailored education, and overall technical quality.

Keywords: dialysis; mHealth; nutrition; renal apps; self-management.

Conflict of interest statement

Conflicts of Interest: None declared.

©Jun-Hao Lim, Cordelia-Kheng-May Lim, Imliya Ibrahim, Jazlina Syahrul, Mohd Hazli Mohamed Zabil, Nor Fadhlina Zakaria, Zulfitri Azuan Mat Daud. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 01.06.2020.

Figures

Figure 1
Figure 1
Flow diagram of the selection process and filtering results for the content analysis of existing dialysis-specific diet apps.
Figure 2
Figure 2
Radar chart for the evaluation results of existing dialysis-specific diet apps.

References

    1. Kemp S. DataReportal. 2019. Jan 31, [2019-09-17]. Digital 2019: Malaysia .
    1. Jahns RG. Research 2 Guidance. 2016. [2019-09-17]. The mHealth apps market is getting crowded
    1. Krebs P, Duncan DT. Health app use among US mobile phone owners: A national survey. JMIR Mhealth Uhealth. 2015 Nov 04;3(4):e101. doi: 10.2196/mhealth.4924.
    1. Fakih El Khoury C, Karavetian M, Halfens RJG, Crutzen R, Khoja L, Schols JMGA. The effects of dietary mobile apps on nutritional outcomes in adults with chronic diseases: A systematic review and meta-analysis. J Acad Nutr Diet. 2019 Apr;119(4):626–651. doi: 10.1016/j.jand.2018.11.010.
    1. Lambert K, Mullan J, Mansfield K. An integrative review of the methodology and findings regarding dietary adherence in end stage kidney disease. BMC Nephrol. 2017 Oct 23;18(1):318. doi: 10.1186/s12882-017-0734-z.
    1. Wizemann V, Wabel P, Chamney P, Zaluska W, Moissl U, Rode C, Malecka-Masalska T, Marcelli D. The mortality risk of overhydration in haemodialysis patients. Nephrol Dial Transplant. 2009 May;24(5):1574–1579. doi: 10.1093/ndt/gfn707.
    1. Karamanidou C, Clatworthy J, Weinman J, Horne R. A systematic review of the prevalence and determinants of nonadherence to phosphate binding medication in patients with end-stage renal disease. BMC Nephrol. 2008 Jan 31;9:2. doi: 10.1186/1471-2369-9-2.
    1. Kim Y, Evangelista LS. Relationship between illness perceptions, treatment adherence, and clinical outcomes in patients on maintenance hemodialysis. Nephrol Nurs J. 2010;37(3):271–280; quiz 281.
    1. Lin M, Liu MF, Hsu L, Tsai P. Effects of self-management on chronic kidney disease: A meta-analysis. Int J Nurs Stud. 2017 Sep;74:128–137. doi: 10.1016/j.ijnurstu.2017.06.008.
    1. Klein J. Utilization of mobile nutrition applications by patients with chronic kidney disease. J Ren Nutr. 2019 Jan;29(1):e5–e7. doi: 10.1053/j.jrn.2018.02.007.
    1. Kosa SD, Monize J, D'Souza M, Joshi A, Philip K, Reza S, Samra S, Serrago B, Thabane L, Gafni A, Lok CE. Nutritional mobile applications for CKD patients: Systematic review. Kidney Int Rep. 2019 Mar;4(3):399–407. doi: 10.1016/j.ekir.2018.11.016.
    1. Campbell J, Porter J. Dietary mobile apps and their effect on nutritional indicators in chronic renal disease: A systematic review. Nephrology (Carlton) 2015 Oct;20(10):744–751. doi: 10.1111/nep.12500.
    1. Jusoh S. A survey on trend, opportunities and challenges of mHealth apps. Int J Interact Mob Technol. 2017 Nov 27;11(6):73–85. doi: 10.3991/ijim.v11i6.7265.
    1. Lambert K, Mullan J, Mansfield K, Owen P. Should we recommend renal diet-related apps to our patients? An evaluation of the quality and health literacy demand of renal diet-related mobile applications. J Ren Nutr. 2017 Nov;27(6):430–438. doi: 10.1053/j.jrn.2017.06.007.
    1. West JH, Hall PC, Arredondo V, Berrett B, Guerra B, Farrell J. Health behavior theories in diet apps. J Consum Health Internet. 2013 Jan;17(1):10–24. doi: 10.1080/15398285.2013.756343.
    1. Mendiola MF, Kalnicki M, Lindenauer S. Valuable features in mobile health apps for patients and consumers: Content analysis of apps and user ratings. JMIR Mhealth Uhealth. 2015 May 13;3(2):e40. doi: 10.2196/mhealth.4283.
    1. Hoffman L, Benedetto E, Huang H, Grossman E, Kaluma D, Mann Z, Torous J. Augmenting mental health in primary care: A 1-year study of deploying smartphone apps in a multi-site primary care/behavioral health integration program. Front Psychiatry. 2019;10:94. doi: 10.3389/fpsyt.2019.00094. doi: 10.3389/fpsyt.2019.00094.
    1. Schumer H, Amadi C, Joshi A. Evaluating the dietary and nutritional apps in the Google Play store. Healthc Inform Res. 2018 Jan;24(1):38–45. doi: 10.4258/hir.2018.24.1.38.
    1. Stoyanov SR, Hides L, Kavanagh DJ, Zelenko O, Tjondronegoro D, Mani M. Mobile app rating scale: A new tool for assessing the quality of health mobile apps. JMIR Mhealth Uhealth. 2015 Mar 11;3(1):e27. doi: 10.2196/mhealth.3422.
    1. Davis SF, Ellsworth MA, Payne HE, Hall SM, West JH, Nordhagen AL. Health behavior theory in popular calorie counting apps: A content analysis. JMIR Mhealth Uhealth. 2016 Mar 02;4(1):e19. doi: 10.2196/mhealth.4177.
    1. Ash S, Campbell K, MacLaughlin H, McCoy E, Chan M, Anderson K, Corke K, Dumont R, Lloyd L, Meade A, Montgomery-Johnson R, Tasker T, Thrift P, Trotter B. Evidence based practice guidelines for the nutritional management of chronic kidney disease. Nutr Diet. 2006 Sep;63(s2):S33–S45. doi: 10.1111/j.1747-0080.2006.00100.x.
    1. Wiggins KL, Harvey KS. A review of guidelines for nutrition care of renal patients. J Ren Nutr. 2002 Jul;12(3):190–196. doi: 10.1053/jren.2002.34252.
    1. Kopple JD. National Kidney Foundation K/DOQI clinical practice guidelines for nutrition in chronic renal failure. Am J Kidney Dis. 2001 Jan;37(1 Suppl 2):S66–S70. doi: 10.1053/ajkd.2001.20748.
    1. James G, Jackson H. European guidelines for the nutritional care of adult renal patients. J Ren Care. 2012 Jul 30;29(1):23–43. doi: 10.1111/j.1755-6686.2003.tb00270.x.
    1. National Kidney Foundation K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis. 2002 Feb;39(2 Suppl 1):S1–S266.
    1. Chan M, Johnson D. Modification of Lifestyle and Nutrition Interventions for Management of Early Chronic Kidney Disease. Westmead, Australia: Kidney Health Australia – Caring for Australasians with Renal Impairment (KHA-CARI); 2012. Jul, [2019-02-17]. .
    1. Medical Nutrition Therapy Guidelines for Chronic Kidney Disease Working Group Committee . Medical Nutrition Therapy Guidelines for Chronic Kidney Disease. Bukit Jalil, Kuala Lumpur: Malaysian Dietitians' Association; 2005. [2019-02-17]. .
    1. Morel S, Portolese O, Chertouk Y, Leahy J, Bertout L, Laverdière C, Krajinovic M, Sinnett D, Levy E, Marcil V. Development and relative validation of a food frequency questionnaire for French-Canadian adolescent and young adult survivors of acute lymphoblastic leukemia. Nutr J. 2018 Apr 21;17(1):45. doi: 10.1186/s12937-018-0355-9.
    1. Noor Hafizah Y, Ang LC, Yap F, Nurul Najwa W, Cheah WL, Ruzita AT, Jumuddin FA, Koh D, Lee JA, Essau CA, Reeves S, Summerbell C, Leigh Gibson E, Poh BK. Validity and reliability of a food frequency questionnaire (FFQ) to assess dietary intake of preschool children. Int J Environ Res Public Health. 2019 Nov 27;16(23):4722. doi: 10.3390/ijerph16234722.
    1. Fatihah F, Ng BK, Hazwanie H, Norimah AK, Shanita SN, Ruzita AT, Poh BK. Development and validation of a food frequency questionnaire for dietary intake assessment among multi-ethnic primary school-aged children. Singapore Med J. 2015 Dec;56(12):687–694. doi: 10.11622/smedj.2015190.
    1. Nutritionist Pro. Woodinville, WA: Axxya Systems; [2019-01-01].
    1. Keeney M, Yeh M, Landman R, May Leung M, Gaba A, Navder K. Exploring the use of an iPhone app: A novel approach to dietary assessment. J Am Acad Nutr. 2016 Feb 1;1(4):22–30. doi: 10.14302/issn.2379-7835.ijn-14-566.
    1. Koo HC, Poh BK, Ruzita AT. Intervention on whole grain with healthy balanced diet to manage childhood obesity (GReat-Child™trial): Study protocol for a quasi-experimental trial. Springerplus. 2016;5(1):840. doi: 10.1186/s40064-016-2431-y.
    1. Abdul Majid H, Ramli L, Ying SP, Su TT, Jalaludin MY, Abdul Mohsein NA. Dietary intake among adolescents in a middle-income country: An outcome from the Malaysian Health and Adolescents Longitudinal Research Team Study (the MyHeARTs Study) PLoS One. 2016;11(5):e0155447. doi: 10.1371/journal.pone.0155447.
    1. Tomayko EJ, Kistler BM, Fitschen PJ, Wilund KR. Intradialytic protein supplementation reduces inflammation and improves physical function in maintenance hemodialysis patients. J Ren Nutr. 2015 May;25(3):276–283. doi: 10.1053/j.jrn.2014.10.005.
    1. Sahathevan S, Se CH, Ng SH, Chinna K, Harvinder GS, Chee WS, Goh BL, Gafor HA, Bavanandan S, Ahmad G, Karupaiah T. Assessing protein energy wasting in a Malaysian haemodialysis population using self-reported appetite rating: A cross-sectional study. BMC Nephrol. 2015 Jul 07;16:99. doi: 10.1186/s12882-015-0073-x.
    1. Khor B, Chinna K, Abdul Gafor AH, Morad Z, Ahmad G, Bavanandam S, Visvanathan R, Yahya R, Goh B, Bee B, Karupaiah T. The state of nutrition care in outpatient hemodialysis settings in Malaysia: A nationwide survey. BMC Health Serv Res. 2018 Dec 04;18(1):939. doi: 10.1186/s12913-018-3702-9.
    1. Perreault M, Xu VY, Hamilton S, Wright D, Foster W, Atkinson SA. Validation of a food frequency questionnaire for bone nutrients in pregnant women. Can J Diet Pract Res. 2016 Sep;77(3):133–139. doi: 10.3148/cjdpr-2016-002.
    1. Moghames P, Hammami N, Hwalla N, Yazbeck N, Shoaib H, Nasreddine L, Naja F. Validity and reliability of a food frequency questionnaire to estimate dietary intake among Lebanese children. Nutr J. 2016 Jan 12;15:4. doi: 10.1186/s12937-015-0121-1.
    1. Jin XW, Slomka J, Blixen CE. Cultural and clinical issues in the care of Asian patients. Cleve Clin J Med. 2002 Jan;69(1):50, 53–54, 56. doi: 10.3949/ccjm.69.1.50.
    1. McGillicuddy JW, Weiland AK, Frenzel RM, Mueller M, Brunner-Jackson BM, Taber DJ, Baliga PK, Treiber FA. Patient attitudes toward mobile phone-based health monitoring: Questionnaire study among kidney transplant recipients. J Med Internet Res. 2013 Jan 08;15(1):e6. doi: 10.2196/jmir.2284.
    1. Lee Y, Cui Y, Chang P. A content analysis of mobile apps for chronic kidney disease patient care: Searching in English and Chinese. Stud Health Technol Inform. 2017;245:1232.
    1. Kreps GL. The relevance of health literacy to mHealth. Stud Health Technol Inform. 2017;240:347–355.
    1. Ramirez V, Johnson E, Gonzalez C, Ramirez V, Rubino B, Rossetti G. Assessing the use of mobile health technology by patients: An observational study in primary care clinics. JMIR Mhealth Uhealth. 2016 Apr 19;4(2):e41. doi: 10.2196/mhealth.4928.
    1. Dennison L, Morrison L, Conway G, Yardley L. Opportunities and challenges for smartphone applications in supporting health behavior change: Qualitative study. J Med Internet Res. 2013 Apr 18;15(4):e86. doi: 10.2196/jmir.2583.
    1. Chen J, Lieffers J, Bauman A, Hanning R, Allman-Farinelli M. Designing health apps to support dietetic professional practice and their patients: Qualitative results from an international survey. JMIR Mhealth Uhealth. 2017 Mar 31;5(3):e40. doi: 10.2196/mhealth.6945.
    1. Nielsen J, Mack RL, editors. Usability Inspection Methods. New York, NY: John Wiley & Sons; 1994. pp. 1–471.
    1. Byrnes N. MIT Technology Review. 2014. Jul 21, [2019-01-14]. Mobile health’s growing pains
    1. Kankanhalli A, Taher M, Cavusoglu H, Hyun KS. Gamification: A new paradigm for online user engagement. Proceedings of the 33rd International Conference on Information Systems; The 33rd International Conference on Information Systems; December 16-19, 2012; Orlando, FL. 2012. Dec 16, pp. 16–19.
    1. Lee K, Kwon H, Lee B, Lee G, Lee JH, Park YR, Shin S. Effect of self-monitoring on long-term patient engagement with mobile health applications. PLoS One. 2018;13(7):e0201166. doi: 10.1371/journal.pone.0201166.
    1. Dunford E, Trevena H, Goodsell C, Ng KH, Webster J, Millis A, Goldstein S, Hugueniot O, Neal B. FoodSwitch: A mobile phone app to enable consumers to make healthier food choices and crowdsourcing of national food composition data. JMIR Mhealth Uhealth. 2014 Aug 21;2(3):e37. doi: 10.2196/mhealth.3230.
    1. Holzmann S, Pröll K, Hauner H, Holzapfel C. Nutrition apps: Quality and limitations. An explorative investigation on the basis of selected apps. Ernaehrungs Umschau. 2017;64(5):80–89. doi: 10.4455/eu.2017.018.
    1. Yazid MA, Jantan AH. User experience design (UXD) of mobile application: An implementation of a case study. J Telecomm Electron Comput Eng. 2017;9(3-3):197–200.
    1. Ling J, van Schaik P. The effect of text and background colour on visual search of web pages. Displays. 2002 Nov;23(5):223–230. doi: 10.1016/s0141-9382(02)00041-0.
    1. Fjeldsoe BS, Miller YD, Marshall AL. MobileMums: A randomized controlled trial of an SMS-based physical activity intervention. Ann Behav Med. 2010 May;39(2):101–111. doi: 10.1007/s12160-010-9170-z.
    1. Riley WT, Rivera DE, Atienza AA, Nilsen W, Allison SM, Mermelstein R. Health behavior models in the age of mobile interventions: Are our theories up to the task? Transl Behav Med. 2011 Mar;1(1):53–71. doi: 10.1007/s13142-011-0021-7.
    1. Bardus M, van Beurden SB, Smith JR, Abraham C. A review and content analysis of engagement, functionality, aesthetics, information quality, and change techniques in the most popular commercial apps for weight management. Int J Behav Nutr Phys Act. 2016 Mar 10;13:35. doi: 10.1186/s12966-016-0359-9.
    1. Welch JL, Astroth KS, Perkins SM, Johnson CS, Connelly K, Siek KA, Jones J, Scott LL. Using a mobile application to self-monitor diet and fluid intake among adults receiving hemodialysis. Res Nurs Health. 2013 Jun;36(3):284–298. doi: 10.1002/nur.21539.
    1. Molaison EF. Stages of change in clinical nutrition practice. Nutr Clin Care. 2002;5(5):251–257. doi: 10.1046/j.1523-5408.2002.05507.x.
    1. Forster H, Walsh MC, Gibney MJ, Brennan L, Gibney ER. Personalised nutrition: The role of new dietary assessment methods. Proc Nutr Soc. 2016 Feb;75(1):96–105. doi: 10.1017/S0029665115002086.
    1. Lee Y, Cui Y, Tu M, Chen Y, Chang P. Mobile health to maintain continuity of patient-centered care for chronic kidney disease: Content analysis of apps. JMIR Mhealth Uhealth. 2018 Apr 20;6(4):e10173. doi: 10.2196/10173.

Source: PubMed

Sponsorit ja yhteistyökumppanit

Sairaudet

Huumeiden interventiot

3
Tilaa