Online patients: characteristics and behaviour on health social networks - feb 2014

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Information about Online patients: characteristics and behaviour on health social networks...
Health & Medicine

Published on February 25, 2014

Author: ric_lampreia



Health social networks are created to allow patients to interact online.
In this presentation i cover some of the topics related to online health social networks: patient characteristics, criteria for user segmentation, and actual behaviour. I present a series of results related to actual search behaviour, user characteristics, self-tracking and patient quantified-self status, emotional content vs data, behavioural modification status, and comparability of online patient populations and offline populations.
Presented in the context of activity.

Patients and online networks – characteristics, motivators, behaviour! Ricardo Sousa! Vitanect co-founder and General Manager ! February 2014! 1  

Synopsis! •  Goal: To share insights about patient online behaviour! •  Audience: all those interested in online patient networks! •  Date: Feb 2014!

Why do patients go online?! Seek  informa-on  (on   drugs,  diseases,   diagnosis)   Seek  treatment   (which  doctor,  which   hospital)   Seek  advice  (how  to   live  with,  family   issues,  psychological   support)  

Who is there to help?! Seek  informa-on   (on  drugs,  dWikipedia   iseases,   WebMD   diagnosis)   Pa-ent  groups   Pharma   Disease  portals   Seek  treatment   (which  doctor,   sites   Hospital  and  clinic   which  hospital)   Health  systems  sites   Review  sites   Seek  advice  (how  to   live  with,  family   Facebook??   issues,  psychological   Pa-ent  support)   Forums   Groups  

Patient-to-patient support: A gap in online information! •  There are no reference websites worldwide! •  Facebook is not a great alternative due to privacy concerns! •  Missing vertical social network… but: confidentiality ≠ virality?!

Perceived risks (by patients)! •  Privacy! –  Employers and colleagues! –  Insurers, Banks! –  Friends, family and neighbours! –  Exposing their children! •  Fake doctors! •  Bad advice! •  Business people making money out of them!

Caveat: what do we mean when we say “ online patients”?!

N x N population! •  There is no “patients”: thousands of diseases and multiple stages by disease. People are different! –  A Parkinson’s disease caregiver has little in common with a schizophrenia caregiver! –  An early stage diabetes patient has little in common with an insulin-dependent diabetes patient!

No global village! •  There is no “global village” for most patients! –  NHS is in England. Germany uses another word and another system. Language, processes, patient experiences are different! –  Specialist referral paths are different by country! –  Drugs have different names…! –  … and sometimes different indications!! –  Clinical practice is often very different! –  Language is a barrier even inside the same country!

Disease type and stage strongly influence online behaviour! Acute disease! Searching diagnosis and treatment, occasional! Chronic degenerative disease! Continuous online presence! Accident/Impairment! Event-based online presence, sometimes continuous!

Disease stage and patient concerns/information needs! Pre-care: Prevention/ Wellness! §  Wellness solutions! §  Selfdiagnosis / disease information! Point-of care: Diagnosis/ Consultation/ Procedure! §  Provider search / matching! §  Telemedicine! §  eDiagnosis! §  Remote care / patient-doctor link! Post-care: Medication! Post-care: Management/ Optimization! §  Rx fulfillment! §  Comprehensiv §  Adherence! e disease §  Vigilance! mgmt! §  Follow-up / §  Treatment Monitor! optimization! §  Alerts! §  Follow-up / Monitor! Further reading: IMS, Pa-ent  Apps  for  Improved  Healthcare,  October  2013 and Swan, Emerging PatientDriven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking, Int J Environ Res Public Health. 2009 February; 6(2): 492–525. !

Online behaviour depends on the patient type (attitudinal segmentation is needed)! Self-­‐managers   •  Core  quan-fied   self-­‐users   •  App  users   •  Data-­‐tracking   pioneers   •  Con-nuous   engagement   Find-­‐me-­‐a-­‐ solu-on   •  Hospital  /   Doctor  seeking   •  Rx  advice   seeking   •  Temporary   engagement     Give-­‐me-­‐the-­‐ good-­‐news   •  Occasional   ac-vity   •  Low   engagement   Source: Vitanect research, 2013. For an alternative view on online patient segmentation, see mHealth in an mWorld - How mobile technology is transforming health care, Deloitte 2012 (link - page 6). “Segment ‘Online and Onboard’ corresponds to % of total population)!

Empirical observation – online patient behaviour in social networks!

Search behaviour: What are common searches today?! 4%  2%   %  of  searches   16%   Disease  informa-on   Symptoms   Treatments   55%   23%   Source: Vitanect internal data, Jan-Feb 2014! Medica-on  informa-on   Other  

Motivations of patients seeking health information online via social health networks! Online survey, N=605 online social health site users. Cluster analysis:! Cluster:  main  mo3va3on   User  characteris3cs   Acquiring  informa-on   and  support   over  age  55  years,  women,  those  with  lower  income,   chronic  pain,  obesity  and  depression   Communica-ng   men,  those  20–34  years  old,  those  with  less  educa-on,   or  an  ea-ng  disorder   Networking   mul-ple  sclerosis  or  depression   Browsing   mul-ple  sclerosis   Source: Magnezi R1, Grosberg D, Novikov I, Ziv A, Shani M, Freedman LS Characteristics of patients seeking health information online via social health networks versus general Internet sites: a comparative study, Inform Health Soc Care. 2014 Jan 29.! !

Patient self-tracking: how much is taking place?! •  70% of doctors report that at least one patient is sharing health-measurement data with them! •  Most common methods:! –  Hand writing the data! –  Printout of the information! •  ¾ of physicians agree that self-tracking leads to better outcomes! Source: Manhattan Research’s Taking the Pulse, US 2013, N=2950!

Are patients interested in self-tracking?! •  Depends. A majority is not – they are interested in living a normal life. Patient segments:! –  Self-managers: they carefully follow their disease, medication, progress. Interested in self-tracking. Minority! –  Help-me-if-you-can: they want solutions and seek them. But diagnosis and treatment is the job of the health professionals. Big group! –  Give me the good news: they intend to live normally and avoid actions that reminds them they are sick. Disengage. Big group.! •  Test – which group do you belong?:! –  Do you read the results of your blood tests carefully or do you hand it over to your doctor? ! –  Do you forget taking your pills after 3 days?! –  A doctor is someone you visited once in your life, or less! Further reading: See some additional data here by @susannahfox !

Empirical results: health-information seeking behaviour and social networking use! Online survey, N=1,745 online health information users. Results:! Factor   Used  online  health  rankings/reviews  or  health  social  networks   Has  chronic  disease?   Twice  as  likely    [OR  2.09,  P<.001).   Formal  educa-on   Lower  odds  for  less  formal  educa-on  (OR  0.49,  P<.001)   Male  /  Female   Lower  odds  for  male  (OR  0.71,  P<.001)   Income   1.5x  as  likely  when  higher  incomes  (OR  1.49,  P=.05)   Age   Older  respondents  were  less  likely  to  use  SNS  (OR  0.96,  P<.001   Regular  health  care   provider   1.9x  odds  for  users  with  a  regular  provider  (OR  1.89,  P<.001)   Source: Thackeray R1, Crookston BT, West JH. Correlates of health-related social media use among adults. IJ Med Internet Res. 2013 Jan 30 !

Are online patient populations comparable with populations in the clinical practice?! •  Comparison between patientslikeme MS population (N=10,255) and MS center (N=4,039)! –  Online population is younger (45 vs 48) ! –  Higher % of females (80% vs 75%)! –  Higher % of high education (26% completed college vs 12%)! –  Good correlations between patient-reported MSRS composite and physician-derived measures! Source: Bove R, Secor E, Healy BC, Musallam A, Vaughan T, et al. (2013) Evaluation of an Online Platform for Multiple Sclerosis Research: Patient Description, Validation of Severity Scale, and Exploration of BMI Effects on Disease Course. PLoS ONE 8(3): e59707. doi:10.1371/journal.pone.0059707!

Emotion and data! •  Disease is emotional. It is not a game, a contest, a cool new “space”: Emotional message is important! •  The average patient is not a 25 year-old hispter! •  Medicine and healthcare are often scientific areas with precise language!

Some empirical evidence on emotion and online behaviour – emotions matter! Online survey, N=525 posts by 116 participants in a cancer social network. Results:! Message  content   Result   Higher  word  count   More  likely  to  receive  a  reply  (OR  1.3  P=0.001)     Fewer  2nd  person  pronouns   (you,  your,  etc)   More  likely  to  receive  a  reply  (OR  0.92  P=0.04)     High  level  of  posi-ve   emo-on   Less  likely  to  receive  a  reply  (OR  0.94,  P=0.03)     Topics  with  higher  likelihood   Self-­‐disclosure  (p < 0.001)   of  a  reply   Medical  experiences  (p = 0.01)   Rela-onship  issues  (p = 0.05)   Introductory  posts  (p < 0.01).     Source: Lewallen AC1, Owen JE, Bantum EO, Stanton AL.. (2014) How language affects peer responsiveness in an online cancer support group: implications for treatment design and facilitation. !

Some empirical evidence on emotion and online behaviour – emotions matter, and can have detrimental impact for some patients! Online survey, N=18,064 posts by 236 patients in a breast cancer social network. Results:! Type  of  pa3ent   Impact  of  giving  and  receiving  emo3onal  support  in   CMSS  groups   With  higher  emo-onal   communica-on   competence   Posi-ve  effects  on  emo-onal  well-­‐being   With  lower  emo-onal   communica-on   competence   Detrimental  impacts  on  emo-onal  well-­‐being   Source: Yoo W1, Namkoong K, Choi M, Shah DV, Tsang S, Hong Y, Aguilar M, Gustafson DH.. (2014) Giving and Receiving Emotional Support Online: Communication Competence as a Moderator of Psychosocial Benefits for Women with Breast Cancer, omput Human Behav. 2014 Jan;30:13-22. !

Behaviour modification – are we close to affecting outcomes with online/mobile applications?! •  Systematic review of 2,040 studies (2014) assessing the current level of evidence regarding the effectiveness of online social network health behaviour interventions.! –  10 studies met inclusion criteria! –  9 out of 10 reported significant improvements in some aspect of health behaviour change! –  Effect sizes for behaviour change in general were small in magnitude and statistically non-significant! Source: Maher CA1, Lewis LK, Ferrar K, Marshall S, De Bourdeaudhuij I, Vandelanotte C. (2014) Are Health Behavior Change Interventions That Use Online Social Networks Effective? A Systematic Review. J Med Internet Res. 2014 Feb 14;16(2):e40.!

Takeaways! •  Don’t treat patients as a single entity – there is wide variability! –  Geography! –  Disease, disease type and stage! –  Patient behavioural segment! •  Takeaways on current behaviour! –  –  –  –  Information and support seeking is main motivation. Gap is real.! Women more than men, younger, better educated! Self-tracking is still done by a minority! Online populations are comparable to offline, slight bias to young, more educated! –  Emotional content matters, but impact differs by user! –  Early stage, little evidence on behaviour modification claims!

Questions?!! ! About Vitanect! ! Vitanect is an online social network for patients and caregivers, focusing on healthcare research! ! Visit us at !

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