Two Research Papers Published on PatientsLikeMe

Two research papers were published this month on the Health 2.0 website, PatientsLikeMe. PatientsLikeMe is arguably the only “real” health social network online today, because it lets patients share actual data that matters with one another — their personal health data. (Other supposed health social networks seem more focused on the “social” than the “health,” allowing for little integrated data sharing.)

The two research papers provide some interesting data points and insights into both the disease process itself, and how e-patients are using Web-enabled tools such as PatientsLikeMe to improve their own care.

The first study looked at one of the diseases PatientsLikeMe covers, ALS. The researchers administered two surveys to basically look at people’s perceptions and knowledge — both patients and the patient’s self-report about what their physicians told them — about ALS. Here’s the abstract (Wicks et. al, 2008):

Once thought to impact only voluntary motor function, ALS/Motor neuron disease (MND) is now seen as a multi-system disorder in which a minority of patients experience mild cognitive dysfunction or frontotemporal dementia. Despite clinical guidelines advocating supplying complete information to patients, educational materials on ALS often state that the mind is unaffected. We sought to establish how much patients and caregivers understand about ALS, what they have been told to expect by their physician, and if they would have appreciated more complete information.

METHODS: A two-part survey was administered online. An ‘ALS quiz’ gauged participants’ knowledge of physical and psychological aspects of ALS. A second questionnaire assessed which symptoms patients had discussed with their clinician and explored patients’ desire to receive information on psychological effects.

RESULTS: A total of 247 ALS patients and 87 caregivers participated. Participants knew less about psychological symptoms than physical ones (72% correct responses versus 82%; paired t((333)) = -5.04, P < 0.001). Patients commonly reported being told by their doctor about physical symptoms such as problems walking (85%) or stiffness/cramps (74%) but not psychological issues like emotional lability (46%) or cognitive change (11%). The majority of patients (62%) and carers (71%) indicated a desire to be informed that cognitive change or dementia might occur. CONCLUSION: ALS is a multi-system disorder. However, despite a desire for more information from patients and their carers, healthcare professionals continue to primarily address only the physical consequences of the disease.

The obvious problem with this sort of survey research is that you’re relying on patient’s self-report about what a third-party told them about the disease, rather than what they actually said. Historically, such third-party self-reporting can vary in reliability and accuracy.

Nevertheless, one of the points of this study was to show the type of research that could be more readily conducted with a 247-patient ALS community at your fingertips online.

The second study (Frost et. al, 2008) was more of an exploratory and narrative paper that gives people a sense of the ALS community on PatientsLikeMe and how a hopefully-representative sample of that community uses the community. It was titled, Social Uses of Personal Health Information Within PatientsLikeMe, an Online Patient Community: What Can Happen When Patients Have Access to One Another’s Data.

This study only looked at 123 comments out of 17,059 posted to the community. (One of the interesting footnote findings to me that out of those 17,059 comments, only 7852 — about 46% — were composed from scratch. The rest just used one of the default comments you could send another user (such as “Thank you”).)

(Another interesting footnote was that in the course of 15 months, only 63% of the registered users posted a comment from scratch to the site. What are the 37% doing on the site, one wonders, given that messaging is a pretty integral part of any popular social networking website.)

Back to the study…

The thing that makes PatientsLikeMe unlike a regular health support group site like NeuroTalk is the addition of patients easily adding their personal health data to their online health profile. Like many other PHRs online, one must manually enter in one’s data and keep it updated regularly (for instance, when adding a new medication). In addition, you are encouraged to note changes in your condition — getting better or worsening, and track anything and everything that might be related to your condition — diet, treatments, changes in your life, work, supplements, exercise, you name it.

The results’ section of the study looked at three specific categories or types of comments: (1) targeted questions to others with relevant experience, (2) advice and recommendations, and (3) forming and solidifying relationships based on similarity.

Because this was a retrospective study, the only data relationships the researcher could draw were correlational and based upon the patients’ self-report. The first category, targeted questions, illustrated these possible relationships. Unfortunately, such relationships are only as good as the data upon which they’re based. The researchers gave no indication of the reliability or accuracy of the patients’ data in their records, which would seem to be a good foundational base upon which to build studies such as this. I am not certain what the researchers base their assumption that such records are reliable and accurate.

The second category is interesting, but not unique to PatientsLikeMe. Virtually all online patient support communities are full of positive advice and recommendations that members share with one another.

The third category describes how many people in a health support community find others online with share activities and hobbies. Interesting, but there were no data presented that suggest such communications actually show people “solidify” their relationships based upon these shared hobbies.

This is an introductory study, and as such, it does provide some interesting insights into how patients use an online social network in health:

Although small in number, the comments selected for this study represent an undetermined fraction of all uses of profile data. Nevertheless, they offer insight into the potential value of patients sharing health information.

This study represents a first examination of the use of shared medical information, which is still a novel model for personal health data.

I agree. I’d like to see more information about the PatientsLikeMe data itself — how many users enter in data regularly, how reliable their data entry is, and whether we can trust that data when it comes to analyzing it on a more global basis.

Update: After talking more with the lead researcher on the second study, I believe I may have misunderstood exactly the type of data the researchers examined. They were looking at profile comments that user’s left for one another on their profiles (not in the public discussion forums, or elsewhere on the site).

The researchers were interested to find that members were carefully looking at one another’s profiles, examining the data displayed there, and providing advice based upon that examination. Research of this nature has not been done previously because such data were not available — most health sites don’t have this feature available (much less have any researchers analyze it!).

So I apologize for my initial reading of the study was inaccurate.

PLM is a fantastic, research-oriented (both on the personal level — helping people track their own health progress for specific conditions, and on the aggregate level to look at broader research trends and such) social network that is, I believe, the gold standard amongst social networking health websites. I greatly look forward to reading future studies coming out from this passionate, dedicated and superb group of researchers.


Frost JH, Massagli MP. (2008). Social Uses of Personal Health Information Within PatientsLikeMe, an Online Patient Community: What Can Happen When Patients Have Access to One Another’s Data. J Med Internet Res, 10(3):e15.

Wicks, P. & Frost, J. (2008). ALS patients request more information about cognitive symptoms.
Eur J Neurol. 15(5):497-500.


Posted in: patient networks





10 Responses to “Two Research Papers Published on PatientsLikeMe”

  1. Susannah Fox says:

    Thanks, John, fascinating studies.

    The finding that “only 63% of the registered users posted a comment from scratch to the site” pinged my memory of the CHESS studies. My recollection is that, overall, a small group posted to the bulletin boards, but many benefited from those messages (and from the library of resources made available). So the 37% not posting messages on PatientsLikeMe may just be lurkers (and it’s amazing that the lurker group is in the minority since it’s usually the reverse).

    Another study to check out as a model is Meier et al’s ACOR study which “systematically sampled 9% of all archived messages for each group” yielding a nice, big sample of 2,775 messages.

    I keep hearing about how we need more randomized, controlled trials of internet interventions to prove (or disprove) their efficacy (and I’m collecting a list of these studies). Meantime, I think we can expect to see more studies coming out of orgs like PatientsLikeMe, ACOR, and others.

  2. John Grohol says:

    Indeed, I should’ve made clear a few points–

    1. Most survey research conducted on patient communities show that the majority of people post very rarely. My pointing out the 63% number was more that with the PLM website, I simply was expecting virtually all patients to be posting messages back and forth to one another because of what it is — a social networking website for health. To find a significant minority still not using the social aspects of the site in what I think is the “expected” manner is interesting to me.

    2. PLM was specifically set up, from listening to its founders talk about PLM, to encourage population-based data that could be analyzed and significant trends discovered. So indeed, not only are these not the last studies to come from PLM, they are really only the first of what will likely be dozens more in the future.

    3. People who are putting their data into the PLM engine know they are exposing themselves to such research, which may bias the sampling of PLM patients versus a truly randomized sample. This may have implications for future research done on PLM users (especially if one doesn’t look and quantify the differences between ‘active’ PLM users and ‘inactive’ users, but use both sets of data in one set).

    PLM has a lot of very smart and talented people working there, so I suspect they’ll figure most of these issues out. I look forward to reading future studies from them.

  3. John,
    I agree that PatientsLikeMe is currently the gold standard for collecting and organizing patients’ personal health data in a way that is useful for research studies. I used PLM as an example in my recent article on “infodemiology”, a relatively new term that refers to the usage of patient behavior and outcomes revealed via analysis of online data. And, although PLM leads the pack now, newcomers can learn from their example.

    In my view, infodemiology data will be of most value when used in conjuction with other research data, for example, to enhance and help test results from controlled clinical studies.

    The explosion of data that will be available from the increased digitization of medical records, healthcare transactions, and individual patient behavior (and genomics) is still in the early stages. There will be bumps in the road as we figure out how best to collect, organize, and incorporate new sources of data into medical research. Still, it’s exciting to consider how all these new data sources can be applied to transform medical research–and ultimately transform healthcare delivery.

  4. SusannahFox says:

    @ivanoransky Great question. @DocJohnG debated similar re self-reported data: (@accarmichael comment?)

  5. It’s a step up from survey research, but still not as robust as a randomized clinical trial, most of which go to great pains to ensure their samples are normative against the general population.

    As for whether this opens a new door for epidemiological research is still yet to be determined. I think it has great potential, but it still needs to be published in peer-reviewed journals for it to be accepted on the same level of prior scientific data.

    So while I think stuff like this from CureTogether is also great:

    A conference presentation + press release is still not the same thing as getting it through a peer-review process and published. I think it’s great to see the results disseminated more quickly than the traditional scientific process, but I still believe there’s value in going through that process.

    Unanswered by the CureTogether press release are questions like, “Are CureTogether users like the general population? If not, how do they differ? Are they “more sick” or “less sick” than traditional patients, e.g., do they report greater numbers of severity of symptoms than a traditional patient sample? Etc. etc.”

    It’s all a *very good* start, however, and I hope will produce more interesting and quicker data than traditional research.

  6. I agree, potential is exciting and, if used properly, patient-generated data can improve current state of RCT studies reported in medical journals.

    I emphasize “current state”, since the field of scholarly publishing is undergoing a transformation that is also driven by changes in information technology. (See my piece:

    Having access to a large pool of data on post-marketing outcomes could certainly help our understanding of a drug’s longer-term efficacy, don’t you think? But, as you point out, work has to be done to make sure the data are of high quality for research purposes.

  7. Daniel Reda says:

    Thanks for the question, John!

    Yes, our analysis is not as robust as a randomized clinical trial – ours was an observational study, and RCTs usually require some kind of intervention. We are exploring how to give patients the tools to self-randomize and conduct more robust, crowdsourced RCTs.

    Certainly, additional work needs to be done to determine how representative CureTogether members are of the general population. This can be done by comparing CureTogether data with previously published results from other scientific studies – something we are also working on.

    We are partnering with researchers who have extensive data expertise at several universities, and will soon be opening up the entire, de-identified CureTogether dataset for them (and other applicants) to analyze. Their findings would generally be published in peer-reviewed journals.

    As for how we disclose our own findings, we agree it is important for research to go through the peer review process. At the same time, we want to balance it with your excellent point of quickly disseminating data and opening up even preliminary results to spark new research questions.

    The major purpose of CureTogether is to generate hypotheses and new ideas, so our observations at this point in time are not meant to stand on their own as conclusive evidence.

    Much appreciated, please keep the comments coming!

  8. Thanks, Daniel, for the clarification. It does leave me a little confused, however. You say the site’s “major purpose” is to “generate hypotheses and new ideas,” yet the blog entry on CureTogether about this first finding from the site reads:

    Crowdsourced Health Confirms Infertility-Asthma Finding

    It’s not clear to me what the new idea or hypothesis was in this particular example. And maybe this was more of a “test case” in terms of seeing that your data indeed is confirming long-held research hypotheses about this link. If that’s the case, it’s a good datapoint, demonstrating similar findings as more traditional research holds.

    I can’t wait for the future efforts from sites like yours and PLM. This is an exciting time when the old meets the new, seeing the interaction (and synergies) between the two.

    I wonder if you couldn’t publish something on your site about your data findings, and yet still publish it in a journal as well in order to reach more traditional researchers and professionals? I imagine the new Journal of Participatory Medicine would be very interested in such studies, for instance.

  9. Daniel Reda says:

    Yes, our announcement in this case was that purely crowdsourced data had confirmed a link that previous, more traditional research approaches had observed.

    You can imagine that if our data consistently failed to reflect the existing scientific literature, it would raise questions about the general applicability of our findings to the real world.

    Conversely, if we ARE able to demonstrate multiple replications of prior findings – particularly otherwise unexpected associations – then any future genuinely novel findings from our data may be quite useful in generating new hypothesis that could be independently tested.

  10. Truckkas says:

    I’ll check this out again.

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