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Mining Online Social Network Data for Biomedical Research: A Comparison of Clinicians’ and Patients’ Percept ions About Amyotrophic Lateral Sclerosis Treatments

June 28, 2012 Comments off

Mining Online Social Network Data for Biomedical Research: A Comparison of Clinicians’ and Patients’ Perceptions About Amyotrophic Lateral Sclerosis Treatments

Source: Journal of Medical Internet Research

Background:

While only one drug is known to slow the progress of amyotrophic lateral sclerosis (ALS), numerous drugs can be used to treat its symptoms. However, very few randomized controlled trials have assessed the efficacy, safety, and side effects of these drugs. Due to this lack of randomized controlled trials, consensus among clinicians on how to treat the wide range of ALS symptoms and the efficacy of these treatments is low. Given the lack of clinical trials data, the wide range of reported symptoms, and the low consensus among clinicians on how to treat those symptoms, data on the prevalence and efficacy of treatments from a patient’s perspective could help advance the understanding of the symptomatic treatment of ALS.

Objective:

To compare clinicians’ and patients’ perspectives on the symptomatic treatment of ALS by comparing data from a traditional survey study of clinicians with data from a patient social network.

Methods:

We used a survey of clinicians’ perceptions by Forshew and Bromberg as our primary data source and adjusted the data from PatientsLikeMe to allow for comparisons. We first extracted the 14 symptoms and associated top four treatments listed by Forshew and Bromberg. We then searched the PatientsLikeMe database for the same symptom–treatment pairs. The PatientsLikeMe data are structured and thus no preprocessing of the data was required.

Results: After we eliminated pairs with a small sample, 15 symptom–treatment pairs remained. All treatments identified as useful were prescription drugs. We found similarities and discrepancies between clinicians’ and patients’ perceptions of treatment prevalence and efficacy. In 7 of the 15 pairs, the differences between the two groups were above 10%. In 3 pairs the differences were above 20%. Lorazepam to treat anxiety and quinine to treat muscle cramps were among the symptom–treatment pairs with high concordance between clinicians’ and patients’ perceptions. Conversely, amitriptyline to treat labile emotional effect and oxybutynin to treat urinary urgency displayed low agreement between clinicians and patients.

Conclusions:

Assessing and comparing the efficacy of the symptomatic treatment of a complex and rare disease such as ALS is not easy and needs to take both clinicians’ and patients’ perspectives into consideration. Drawing a reliable profile of treatment efficacy requires taking into consideration many interacting aspects (eg, disease stage and severity of symptoms) that were not covered in the present study. Nevertheless, pilot studies such as this one can pave the way for more robust studies by helping researchers anticipate and compensate for limitations in their data sources and study design.

Categories: diseases and conditions, health and health care, Journal of Medical Internet Research, social media

There’s an App for That: Content Analysis of Paid Health and Fitness Apps

June 4, 2012 Comments off
Source:  Journal of Medical Internet Research
Background:
The introduction of Apple’s iPhone provided a platform for developers to design third-party apps, which greatly expanded the functionality and utility of mobile devices for public health.
Objective:
This study provides an overview of the developers’ written descriptions of health and fitness apps and appraises each app’s potential for influencing behavior change.
Methods:
Data for this study came from a content analysis of health and fitness app descriptions available on iTunes during February 2011. The Health Education Curriculum Analysis Tool (HECAT) and the Precede-Proceed Model (PPM) were used as frameworks to guide the coding of 3336 paid apps.
Results:
Compared to apps with a cost less than US $0.99, apps exceeding US $0.99 were more likely to be scored as intending to promote health or prevent disease (92.55%, 1925/3336 vs 83.59%, 1411/3336; P<.001), to be credible or trustworthy (91.11%, 1895/3336 vs 86.14%, 1454/3349; P<.001), and more likely to be used personally or recommended to a health care client (72.93%, 1517/2644 vs 66.77%, 1127/2644; P<.001). Apps related to healthy eating, physical activity, and personal health and wellness were more common than apps for substance abuse, mental and emotional health, violence prevention and safety, and sexual and reproductive health. Reinforcing apps were less common than predisposing and enabling apps. Only 1.86% (62/3336) of apps included all 3 factors (ie, predisposing, enabling, and reinforcing).
Conclusions:
Development efforts could target public health behaviors for which few apps currently exist. Furthermore, practitioners should be cautious when promoting the use of apps as it appears most provide health-related information (predisposing) or make attempts at enabling behavior, with almost none including all theoretical factors recommended for behavior change.
Categories: health and health care, Journal of Medical Internet Research, technology and internet
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