Dividing the Diabetic population into Personas

I recently wrote a BLOG entry about personas and their usefulness in User Centric Design. [LINK] Personas are fictitious characters that represent segments of the target population. A persona has the following characteristics: (per usability.gov [LINK])

• a name and picture
• demographics (age, education, ethnicity, family status)
• job title and major responsibilities
• goals and tasks in relation to your site
• environment (physical, social, technological)
• a quote that sums up what matters most to the persona with relevance for your site

Defining diabetic personas is information driven

Research and information drive the segmentation of populations into discrete user groups whose characteristics will affect the design of our solution. I am particularly interested in designing software for self-management and health engagement of diabetes.

Choose which characteristics to segment population with.

Choose characteristics that will affect the design of your solution. Research and information will help determine these characteristics. I did some general reading / discovery and found research that evidenced certain characteristics affecting diabetic rates.

• Age
• Obesity
• Educational Level
• Socioeconomic status (income level)

I then found research from Forrester Research that segments the population at large according to their adoption & acceptance of technology – important for my focus (self-engagement). Forrester calls this Technographic Segmentation, meaning they segment populations based on their attitude towards and adoption of technology. They define 10 specific groups of individuals.

The table below characterizes all potential users of technology into 10 groups based on their attitudes, income characteristics and family status.

From IP Business (refers to the 2007 North American Technolographics Benchmarks Survey):

Segment the population using research:

First I find research that divides the diabetic population into discrete groups / segments. This CDC Document segments the population by age:

Choose a specific group and further refine the segmentation

I am specifically interested in the 40-59 year age group representing 10.8% of the population.

According to the National Bureau of Economic Research, diabetic rates vary according to socioeconomic and educational levels. I’ve summarized their general findings in the two trending charts below, essentially lower income and less education equates to higher diabetic rates.

Education level affects diabetes

Comparing prevalence by education group, the author finds that high school dropouts are roughly sixty percent more likely to have diagnosed diabetes and twice as likely to have actual diabetes as men who have attended college. The improvement in diabetes detection over the past twenty-five years has been larger for college-educated men (from 50 percent of cases undiagnosed to 16 percent) than for high school dropouts (from 49 percent to 31 percent).

 

Socioeconomics / Income affect diabetes

Further research from BMC Health Services Research concludes: 

Low income is associated with a higher prevalence of diabetes and a higher population rate of referral.

The Rand institute reported similar findings [ LINK ]

Obesity increases with lower income / socioeconomic status

Perhaps this isn’t surprising as there are numerous studies that find inverse relationships between income and obesity:

WorldFoodPrize.org : 52% of food insecure (lower income) people become overweight.

This paper by Dr Marguerite Bryan (Xavier University) states: The disease of obesity disproportionately impacts subpopulations of African-Americans/Hispanics, people of lower socioeconomic status and women.

DocShop.com puts it succinctly: Statistics show that low-income individuals are significantly more likely to be overweight or obese than those who are financially well-to-do.

CDC also states: Body weight is the result of genes, metabolism, behavior, environment, culture, and socioeconomic status. 

 

Type II Diabetes rates increase with obesity rates.

Science daily: Obesity is probably the most important factor in the development of insulin resistance

Obesity.org: Carrying extra body weight and body fat go hand and hand with the development of type 2 diabetes

Thus I’m making the inference:

Build Personas from your segmented population:

Forresters Technographic segmentation of the population resonates with me. So I’m going to try and map the diabetic population into Forrester Research’s 10 technographic segments. Further more, I’ll do a bit of hand waving and try to quantify how much of the population is in each segment.

1) I’m focusing on the 40 – 59 year old diabetic population.

2) I’m going to cut that population into Forrester’s High and Low Income earners, of which the low income earners with have a higher diabetic population and higher obesity population (given research above)

3) I’ll then use Forrester’s values to create personas.

Referring back to Forrester’s Technographic table (I’ll provide 2 here, from 2 sources):

Ref: IP Business

1. Techno Optimist : High Income Career
2. Techno Optimist : High Income Family
3. Techno Optimist : High Income Entertainment
4. Techno Optimist : Low Income Career
5. Techno Optimist : Low Income Family
6. Techno Optimist : Low Income Entertainment
7. Techno Pessimist: High Income Career
8. Techno Pessimist: High Income Family
9. Techno Pessimist: High Income Entertainment
10. Techno Pessimist: Low Income Sidelined Citizens

Now I’m going to focus in on a select few of these. I’m going to toss 7 & 8 and address them using a persona geared for the 10th segment. Why? B/c 7 & 8 are difficult to address with technology (as is 10) and they are less likely to have diabetes, so by having a 10 persona I can provide tools that 7&8 can use without putting much effort into them. That leaves us with:

1. Techno Optimist : High Income Career
2. Techno Optimist : High Income Family
3. Techno Optimist : High Income Entertainment
4. Techno Optimist : Low Income Career
5. Techno Optimist : Low Income Family
6. Techno Optimist : Low Income Entertainment
7. Techno Pessimist: High Income Entertainment
8. Techno Pessimist: Low Income Sidelined Citizens

 

Personas:

a name and picture

demographics (age, education, ethnicity, family status)

job title and major responsibilities

goals and tasks in relation to your site

environment (physical, social, technological)

a quote that sums up what matters most to the persona with relevance for your site

 

1. Jack (Techno Optimist : High Income Career)

• Age: 40-50’s
• College degree (+)
• Single – no kids
• White Collar worker (manager – executive)
• Wants to manage his diabetes given a very busy schedule.
• Has Time for exercise, eats out often.

My career and work activities dominate my life, I need a tool to help me manage my diabetes and help me stay on track.

Likely Technologies:

• PC
• SmartPhone [ IPhone or Blackberry ]

 

2. Sue (Techno Optimist : High Income Family)

• Age: 45-55
• College degree (+)
• Married w/ kids
• White Collar worker (manager – executive) and parent
• Wants to manage her diabetes given a very busy schedule in a family friendly way
• She has video on demand, net book, a smart phone
• Little time for exercise, has control over meals cooked at home & bought out

My personal time is spent on family matters and my work life is demanding as well, I need a convenient tool to help me manage my diabetes that works around my family and my work.

Likely Technologies:

• PC
• SmartPhone [Blackberry/IPhone] or Cell [SMS]

 

3. Curtis (Techno Optimist : High Income Entertainment)

• Age: 40-55
• College degree (+)
• Married w/ older kids
• White Collar worker (manager – executive) and parent
• Wants to manage his diabetes in the most convenient way
• Little time for exercise, no control over meals cooked at home and eats out regularly

I enjoy using interactive technology in convenient ways, namely on my PC.

Likely Technologies:

• PC

 

4. Katie (Techno Optimist: Low Income Career)

• Age: 40 - 50
• Highschool or College degree (+)
• Single no kids
• Low level wage earner – retail, help desk, fringe white collar worker
• Wants to manage her diabetes using new / hot technologies
• Does not exercise often, financial constraints limit control over meals cooked at home and eats out at less expensive restaurants (fast food)

I try to adopt new technologies and want to manage my diabetes using the newest applications.

Likely Technologies:

• PC
• IPhone

 

5. Suzie (Techno Optimist: Low Income Family)

• Age: 40 - 50
• Highschool or College degree (+)
• Family with kids
• Low level wage earner – retail, help desk, fringe white collar worker
• Wants to manage her diabetes using technologies her family uses
• Does not exercise often, financial constraints limit control over meals cooked at home and rarely eats out.

Our family has a few basic technologies that I can use to control my disease

Likely Technologies:

• Low cost PC
• Gaming console
• SMS
• IVR

 

6. Drew (Techno Optimist: Low Income Entertainment)

• Age: 40 - 50
• Highschool
• Single
• Low level wage earner – retail, help desk, fringe white collar worker
• Wants to manage his diabetes using entertainment based technology
• Does not exercise often, eats out at low cost restaurants (e.g. fast food)

I use technology for entertainment and want to track my diabetes in the same way.

Likely Technologies:

• IPod
• Gaming Consoles

 

6. Drew (Techno Pessimist: High Income Entertainment)

• Age: 48-59
• College +
• Married
• High wage earner, manager or executive
• Wants to manage his diabetes but generally dislikes technology except for entertainment.
• Does not exercise often, eats out often at nice restaurants and can afford nutritious food when cooking at home (him or his wife)

I use technology for entertainment but otherwise want to stay away from technology. If it isn’t easy, I won’t use it.

Likely Technologies:

• SMS
• PC (though unlikely)

 

6. Don (Techno Pessimist: Low Income Sidelined Citizens )

• Age: 40-59
• Highschool
• married or single
• Low wage, blue collar worker
• Wants to manage his diabetes but does not use new technologies
• Does not exercise often, eats at home but financially constrained as to what food he can purchase or at low cost (e.g. fast food) restaurants

I don’t use technology. I have a cell phone and a TV. I don’t use the internet often outside of maybe email.

Likely Technologies:

• SMS