“CATCH-IT Reports” are Critically Appraised Topics in Communication, Health Informatics, and Technology, discussing recently published ehealth research. We hope these reports will draw attention to important work published in journals, provide a platform for discussion around results and methodological issues in eHealth research, and help to develop a framework for evidence-based eHealth. CATCH-IT Reports arise from “journal club” - like sessions founded in February 2003 by Gunther Eysenbach.

Tuesday, October 13, 2009

CATCH-IT DRAFT REPORT: Cellular phone and Internet-based individual intervention on blood pressure and obesity in obese patients with hypertension


Globally overweight and obesity, representing at least 300 million clinically obese persons, pose a major risk for chronic diseases, including type 2 diabetes, cardiovascular disease, hypertension and stroke (1). Increasingly, health care planners are looking for affordable strategies(2) inclusive of leveraging the use of information and communication technology (ICT) as a viable tool to support patients’ self-management of these diseases. This paper (3) is one of the most recent studies, which evaluates the use of both cellular phone and internet as an intervention in the relationship between measures of self-efficacy and managing obese hypertension.

One of the authors of this paper, Hee-Sung Kim, has experience with previous research studies using ICT for chronic disease management focusing on diabetes care in publications dated back to 2003. No further work in this area is established for the other authors.

The aim of the study is to evaluate whether an intervention using a short message service (SMS) by cellular phone and Internet would improve blood pressure (BP), weight control, and serum lipids of obese patients with hypertension during 8 weeks(3). The authors cite the rationale for this as “no study has been done to test the direct efficacy of the cellular phone or internet-based system” on improving of these measures for hypertension”. Logan etal, 2007 presented a paper on use of both inventions, which is referenced by authors making this not a novel research.

Methodological Issues

Firstly, the intervention is not clearly defined, “.. intervention group were requested to record their blood pressure and body weight in a weekly web based diary through the Internet or by cellular phones.” (3) No justification is given for the choice of SMS or descriptive given of how the patient would input information from the cellular phone. In addition given that the data is self-reported, there is no indication of any objective ways to confirm if any of the data reported on which the decision for the alerts were sent.

Secondly, omission of the actual population size of the data collected from which participants are drawn. Associated with this is the potential for selection bias, as it is unclear as to who selected the control group and what other factors might have been considered in addition to matching the age, sex, systolic BP, diastolic BP and body weight to the intervention group at the same department. This appears to pose the single most important threat to internal validity, as it is possible to pull patient records with no change in the clinical outcome variables, unless this was a blinded process.

Thirdly, usage data of the intervention is omitted. Review done on related articles presenting studies with the use of ICT intervention such as by Patrick etal 2009, Raab etal 2009, Cocosila etal 2009, Morak etal 2008, Logan etal, 2007, and Kwon etal 2004, report results in addition to the clinical outcome. Data expected are those such as mean number of logon times per patient per day, alerts sent from both SMS and internet, entries for clinical measures such as blood pressure, weight, drug entries and most frequent comments over the period.

Fourthly, given that the study incorporates the behavioral pattern of patients, the theoretical approach used for this study is not stated explicitly for self-efficacy(4).


This report is contributing to the body of literature on behavioural change through online intervention which is still a relatively new area of research. However, the results must be taken with caution base on the fundamentally flawed methodological issues that is associated with the research.

Hee-Seung Kim has authored one publication(5) and co-authored eleven publications. In one of the earlier researches co authored in 2004, “Establishment of Blood Glucose Monitoring System Using the Internet”(6), the ICT intervention is clearly defined with inclusion of images of the screen and reporting of the results as seen in related researches(7)(8)(9)(10).

It is quite noticeable that subsequent studies co-authored have been the usage of the same web-based diary intervention research from the same institution, which has been extended into variations of research papers on diabetes management in conjunction with SMS cellular phone. This paper under review has portions of the writing that are verbatim with blind application of parts of study with no evidence of results or relevance. How much of this is original work and could this have lead to the decrease in the quality of the reporting and exclusion of the pertinent information alluded to in the methodological issues?

The authors state amongst the limitations cited that some patients may not had access to a computer or able to use a cell phone, despite the inclusion criterion that they "should be able to input data into the website and have their own cellular phone" (3). Clearly, this is conflicting and poses additional difficulty on the validity of assessing “direct efficacy”.

Another critical element missing from this and past reports of similar study by the authors is the lack of information regarding the patients’ perspective on the ease of use, acceptance and effectives of the interventions. It would be valuable to know the extent to which patients find the ICT interventions to be helpful in disease self-management, increased self-efficacy, and treatment adherence, as the technology becomes an integral part of people's everyday life. This information would also help to inform future research and long-term planning.

Finally, the authors conclude, “the intervention using SMS of cellular phone and Internet improved blood pressure, body weight, waist circumference, and HDL-C at 8 weeks in obese hypertensive patients (3).” However, given the number of concerns regarding the internal validity, no method of accounting for alternative explanations opportunity for researchers to introduce bias in the interaction with patients and lack of generalization due to low sample size; these will limit greatly the level of confidence in all inferences that might be drawn from this study deeming the results not valid. Overall, the poor quality of reporting has detracted from the goal of the study.


Thank you to the professors and fellow graduate students of the 2009 CATCH-IT Journal Club at the University of Toronto, for their helpful and insightful discussion and comments that contributed to this report.

Questions to the Authors

1. What is the usage data of the cellular phone and internet intervention such as daily frequency response rate per patient per measure, number of alerts sent, and number of entries for clinical measures over the 8 weeks period?

2. What measurement is used to determine self-efficacy in the adherence to control of hypertension?

3. What is the rationale for exclusion of patients that changed medication during the period of the interventions and how many persons were excluded due to this in the intervention and control group?

4. What specific differences are identified using the paired t-test with Bonferroni correction and why use ANOVA rather than t-test when comparing the groups?

5. Why is the patient’s perspective not included on the usability and effectiveness of the intervention?


1. World Health Organization. Obesity and overweight. [Online].; 2003 [cited 2009 October 2. Available from: http://www.who.int/dietphysicalactivity/publications/facts/obesity/en/.

2. Prentice A. The emerging epidemic of obesity in developing countries. Int. J. Epidemiol. 2006; 35: p. 93–99.

3. Park M, Kim H, Kim K. Cellular phone and Internet-based individual intervention on blood pressure and obesity in obese patients with hypertension. Int J Med Inform. 2009 Oct; 78(10): p. 704-10.

4. Kim H. A randomized controlled trial of a nurse short-message service by cellular phone for people with diabetes. Int J Nurs Stud. 2007 July; 44(5): p. 687-692.

5. Kwon H, Cho J, Kim H, Song B, Ko S, Lee J, et al. Establishment of Blood Glucose Monitoring System Using the Internet. Diabetes Care. 2004 February; 27(2): p. 478-483.

6. Logan AG, McIsaac WJ, Tisler A, Irvine MJ, Saunders A, Dunai A, et al. Mobile Phone-Based Remote Patient Monitoring System for Management of Hypertension in Diabetic Patients. Am J Hypertens. 2007 September; 20(9): p. 942-948.

7. Morak J, Schindler K, Goerzer E, Kastner P, Toplak H, Ludvik B, et al. A pilot study of mobile phone-based therapy for obese patients. J Telemed Telecare. 2008; 14(3): p. 147-9.

8. Cocosila M, Archer N, Haynes RB, Yuan Y. Can wireless text messaging improve adherence to preventive activities? Results of a randomised controlled trial. Int J Med Inform. 2009 April; 78(4): p. 230-238.

9. Patrick K, Raab F, Adams M, Dillon L, Zabinski M, Rock C, et al. A Text Message–Based Intervention for Weight Loss: Randomized Controlled Trial. J Med Internet Res. 2009; 11(1 ): e1.

10. Anhoj J, Moldrup C. Feasibility of Collecting Diary Data From Asthma Patients Through Mobile Phones and SMS (Short Message Service): Response Rate Analysis and Focus Group Evaluation From a Pilot Study. J Med Internet Res. 2004 Oct–Dec; 6(4): p. e42.


  1. Hi Plumaletta,
    Your writing style flows very nicely but just wanted to clarify the comments on the methodology,
    Point 1: I am not entirely sure I understand your point. Why do you need an “objective way to confirm” self reported data?
    Point 2: Was it the “actual population size of data” that was omitted or possible issues on how the sample was selected?
    Point 3: Was it the “usage” data that is missing or just “data? What was the data collected on the intervention? And how did the researchers analyze this when not all patients had access to a computer of phone?
    Point 4: I did not know that self efficacy was the theoretical approach of study.
    By the way, not sure you need to list reference (3) for the article which you are critiquing.
    You have a nice way with words. Hope my points help.

  2. Hi Plumaletta,

    Your paper is a nice summary of the presentation you gave in-class. Thanks.

    One question that might be worthwhile to pose to the authors is whether or not the findings were of not just statistical significance, but of clinical significance.

    Just a thought, but what do you think about the choice of control group in this study? Other studies looking at SMS interventions (i.e. Patrick 2009, JMIR) chose to make their comparison between the regular intervention (i.e. print or non-personalized health ed materials) and the new eHealth intervention. In this case there isn't much description of the care of the control group. Would it make a difference in interpreting the results?

  3. Great report Plumaletta!

    For your last question to the author, you might also want to ask "How in your opinion including the patients' perspectives might have altered the results?"

    An additional question for the author(s)- Other than receiving health status recommendations, was there any other incentive offered to the participants? Some subjects did not record their blood presuure levels for more than 4 weeks. How significant was the impact of the motivational aspects of the study on the analyses? Hope this is applicable.

  4. Great feedback!! I will review the comments and revise draft accordingly. Thanks to all the persons who commented so far.

  5. Hey Plumaletta,

    Great start. I like how you mentioned the internal validity issues, specifically in the selection of participants. I wonder if you should mention something about the timeline of this intervention. Eight weeks seems quite small to conclude that the intervention was indeed effective. I also think that this affects their conclusions. In line with Gunther’s comments from class, have you considered commenting on their statistical analysis. Specifically, why did they use ANOVA instead of a t-test?