When Janna Stephens wrote about technology-incorporating obesity interventions, it was clear that the meta-study she consulted had the same problems as many other such conglomerations of knowledge from many sources. Researchers who do this sort of work need to think carefully about the parameters they designate for which documents are to be considered and which will be put aside in the particular instance.
For her purposes it was, in general, hard to compare results because the proposed intervention strategies varied widely from one study to the next in the areas of “interfaces, mode of delivery of message, types of messages, dosage of intervention, and goals.”
Another important factor to consider is the strength of the evidence reported from these studies. Was each paper generated by a reputable person or group, at a reputable institution? Also, some of the intervention studies had other factors built in, aside from the technology — like calls or mailings from a healthcare provider, and even in-person visits. Stephens wrote,
Not all of the studies were randomized controlled trials; introducing potential biases, including sample selection biases and instrumentation biases. Those that were randomized controlled trials also had limitations that should be noted when examining the reported results.
Generalizability and the facility to synthesize results are subject to limitations. Since some of the studies under consideration were conducted outside the U.S., certain factors did not match up. If there was a focus on cultural elements, or the measurement tools used were culture-specific, not everything could be extrapolated to other countries.
Stephens notes that even within the U.S., when the cardiovascular risk factors having to do with physical inactivity and weight loss are involved, certain factors come into play. If the patient needs to have a smartphone, or even a less versatile mobile phone with text-messaging capability, that can present an obstacle because obviously, not everyone can afford to own such instruments.
Of course, in research of this kind and especially in studies of studies, it often seems that every answered query generates a new batch of questions. Stephens gives typical examples:
How can smartphone and text messaging interventions benefit children and adolescents? Will text messaging and smartphone applications be effective interventions in the elderly?
Is a text messaging intervention more or less beneficial than a smartphone application in reduction of weight and increasing physical activity? Would the combination of a smartphone and text-messaging be more beneficial than either intervention alone?
Are smartphone interventions effective in low socioeconomic status subgroups? What are the long-term outcomes of smartphone and text messaging interventions?
How can successful interventions be translated to populations? What is the cost-effectiveness of this type of intervention?
Your responses and feedback are welcome!
Source: “Smartphone Technology and Text Messaging to Promote Weight Loss in Young Adults,” JHU.edu, July 2015
Image by Edna Winti/CC BY 2.0