Exploring Everyday Health Routines of a Low Socioeconomic Population Through Multimedia Elicitations
Summary: Low socioeconomic status (SES) populations are prone to acquiring chronic diseases. Among the major causes are individuals’ everyday health-related decisions that affect their long-term health. Many technological interventions exist to help with monitoring health, however they are not designed with low SES populations in mind. This paper presents the last of a three-part needs assessment study to develop guidelines for designing health intervention technologies for underserved populations. To this end, the authors conducted a multimedia-elicitation interview (MEI) study where participants captured pictures and videos of their everyday health routines. Sociotechnical interventions were found to be most beneficial if they assisted people with their dietary intake periodically throughout the week. Finally, the authors identify opportunities for MEI use by the participatory medicine community and potential sociotechnological interventions.
Keywords: Diet, low socioeconomic populations, culture, capturing behaviors, mobile health.
Citation: Khan DU, Ananthanarayan S, Siek KA. Exploring everyday health routines of a low socioeconomic population through multimedia elicitations. J Participat Med. 2011 Aug 29; 3:e39.
Published: August 29, 2011.
Competing Interests: The authors have declared that no competing interests exist.
Individuals must be empowered to better understand how their everyday activities affect their personal health, given the increasing rates of obesity and chronic illness in our world. Currently, there are many multimedia mechanisms that provide easily accessible information about health, eg, smallsteps.gov commercials, print ads, and websites. The fortunate and affluent can use GPS-enabled smartphones to log exercise; dietary intake with text-based interfaces or photos; or sleep patterns. Once this information is collected, individuals can reflect on their habits and integrate improved health practices into their everyday lives. Moreover, people can share their experiences with their health care providers, friends, and family through their own personal health records (PHRs) or social networking applications (eg, runkeeper.com or Nikeplus.com).
Low socioeconomic status (SES) individuals stand to benefit the most by monitoring, sharing, and reflecting on their health practices because of their increased risk for morbidity and mortality. Unfortunately, their ability to effectively participate is limited by a lack of health literacy and health care access. Outside of the work done by Pempek and colleagues, Grimes and colleagues, and the authors, few technology researchers have focused on the scope of technology to help low SES populations improve their health. Researchers have shown that low SES is directly correlated with lower health literacy levels and poor health outcomes. Based on these facts, the authors were motivated to explore the target low SES population’s health routines to identify opportunities for socio-technological interventions that would improve their health habits. The authors conducted a 4-week Multimedia-Elicitation Interview (MEI) study where participants used mobile phones to capture videos and pictures of their everyday health routines. Specific to this population, two “gateways” to family health were identified: The mother, who was the primary caregiver, and the eldest daughter, who was the secondary caregiver. Four primary caregivers and four secondary caregivers were selected to participate in the study with the goal of understanding their everyday health habits and investigating how technology can assist in gradually improving their entire family’s health.
The authors were specifically interested in technological interventions for families because numerous studies have examined the positive influence that family has on an individual’s health. Although other researchers have explored how technology can leverage the family context to improve individuals’ health,  this study focused on low SES families. The authors were also interested in understanding how multiculturalism in the target population would play a role in the design of the technological intervention. Many studies  have highlighted the importance of culturally sensitive designs for effective socio-technical health interventions.
The findings of this study were: (1) Low SES caregivers’ definition of health was predominantly based on diet. Their diet followed a feedback loop where their existing dietary knowledge informed their eating practices, upon which they reflected and updated their knowledge; (2) culture was deeply ingrained in the dietary Knowledge-Practice-Reflection (KPR) cycle; and (3) the primary caregivers had control of their schedules, while the secondary caregivers had limited control. Based on these findings, the authors propose that any technological intervention needs to accommodate multicultural issues. The technological intervention should be designed to induce a gradual positive change in low SES families’ health and highlight examples of good health to educate the community.
This paper advances participatory medicine because it discusses conceptual design considerations necessary for developing a health intervention that empowers low SES populations to improve their dietary habits. It also showcases how medical informaticians can successfully employ a participant-centered methodology, MEI, to discover useful insights for designing consumer health technologies.
This study is a part of a broader needs assessment study, aimed at exploring the health routines of a low SES population. In one study, the authors interviewed 17 primary caregivers about diet and exercise, and found that individuals were generally aware of which foods were healthy, but they struggled to convert this knowledge into an everyday healthy diet. The authors also conducted two design workshops which demonstrated that caregivers wanted reminder-based systems that could assist them with managing family health. Whereas the previous studies examined the target population’s perceptions about health and what kind of technological solutions they desired, this study examined their actual everyday health habits.
The Bridge Project
The Bridge Project (Bridge) is a community outreach project that serves over 500 families in four Denver city public housing neighborhoods. Most of these families live below the poverty line and belong to minority groups. The project offers educational programs for neighborhood children aged 3-18 to help prepare them for K-12 curriculums. The authors have volunteered for more than 80 hours to tutor children at the Bridge and, in so doing, build a trusting relationship with Bridge families. The Bridge also offers nutrition and cooking classes to the primary caregivers to promote healthy dietary habits in the community. This specific population was chosen because an earlier study showed that 87% of children in the Bridge neighborhoods were exposed to at least one modifiable cardiovascular disease (CVD) risk factor with poor diet being the leading factor.
Participant Recruitment and Retention
After obtaining approval from the Institutional Review Board, the authors recruited participants using flyers, information sessions, and face-to-face briefings. While volunteering at Bridge, the authors learned that teens often cooked dinner for their families. In this population, there is a primary caregiver and secondary caregiver where the caregivers are most likely the mother and oldest daughter. Initially, eight primary caregivers and five secondary caregivers were recruited for the study, however four primary caregivers could not complete the study; one mother moved, another mother had to care for her hospitalized family member, and two others could not spare time from their schedules. One teen lost the phone and could not participate. All the participants were from different families.
Since a mechanism was needed to explore the participants’ daily health routines, the authors were interested in utilizing multimedia diary methods. Initially, a photo-elicitation interview (PEI) methodology was considered because researchers in social sciences successfully use this method to learn about various aspects of individuals’ daily lives. PEIs are a type of diary study  where participants are asked to take pictures of their daily lives; researchers meet with the participants to discuss these pictures. The benefit of using PEIs is that it is participant-driven, provides contextual information, and presents participants with an opportunity to informally explain various aspects of their lives to researchers.
Carter and colleagues contended that although the PEI method was useful, it required a mechanism for participants to annotate their pictures so that researchers could effectively review and categorize the pictures. Thus, for annotation purposes, we decided to use a video-elicitation interview (VEI) where the participants could video-record their everyday health routines and could annotate in the audio of the video recording. Since some participants did not feel comfortable making videos, they took un-annotated pictures. This study ultimately used a mix of VEI and PEI, or a Multimedia-Elicitation Interview (MEI). The MEI method has also been used by O’Brien and fellow researchers to explore everyday health experiences of individuals living in Kyrgyzstan and Brazil.
Informed consent was first obtained from the participants in the study. A researcher attempted to meet with the participants every week to conduct the MEIs during the 4-week study. Due to the participants’ schedules, some weekly meetings were merged and conducted after a gap of more than 1 week. This resulted in an average of 3.5 meetings per parent and 4.25 meetings per teenager. One teenager could not participate in the final meeting due to travel. Each meeting lasted between 20 minutes to 1 hour depending on whether meetings were merged. Apart from the first meeting (where participants were provided the mobile phone) every meeting was video-recorded with participants’ consent for later analysis. Participants were provided a total stipend of $30 in the form of supermarket or retail gift cards prorated at $5.00 each for the first two weeks and $10.00 each for the last two weeks.
Meeting 1: The authors provided participants a mobile phone (Nokia N95 8GB) with its charger and demonstrated: (1) How to make videos using the mobile phone; (2) how to charge the mobile phone; and (3) how to turn on the phone. The participants were asked to make videos and take pictures of anything that reminded them of health and provided examples of eating, exercising, and grocery shopping. Printed instructions were also provided to the participants describing how to use the mobile phone. The remaining meetings started with transferring videos and pictures from the participants’ phone to the authors’ laptop (Lenovo ThinkPad X60). Semi-structured interviews were conducted during meetings where participants could answer questions and discuss the multimedia they captured. The remaining time was utilized as follows:
Meeting 2: Discussion of the participants’ everyday routines.
Meeting 3: Predefined targeted questions were used to understand the participants’ health behavior.
Meeting 4: Discussion of the participants’ perceptions about their own health.
Meeting 5: Discussion of the participants’ perceptions about their family’s health.
After collecting the videos and pictures, the authors performed qualitative analysis using grounded theory with the NVivo 8 qualitative data analysis software. As the multimedia content was analyzed, new codes and concepts were identified based on the activity captured in the multimedia. After coding the multimedia, the three authors discussed the concepts thoroughly to identify the main categories that resulted in the dietary KPR cycle.
Eight participants were recruited: four primary caregivers (mothers) and four secondary caregivers (teenagers). The average age of the mothers was 32.8 years (sd= 5.4 years). Two mothers were Hispanic, one African American, and one white. None of the mothers were employed and all were single. Two mothers had four children each, while the remaining two had three children each. Although all the mothers had access to a computer, only two had a computer at their home and used it frequently. All mothers owned a mobile phone and were proficient in mobile phone tasks such as making/receiving calls, sending/receiving texts, and taking pictures. In terms of childrearing assistance, two mothers mentioned that the children’s father helped them, while the remaining two did not provide this information.
The average age of the four teenagers was 16.3 years (sd = 1 year). Two teenagers were African American and two were recently immigrated Somalians. All the teenagers were single and two of them worked part-time at the Bridge computer laboratory. Two teenagers had eight siblings each, one had six siblings, and one had four siblings. All the teenagers had access to a computer and all, except one, regularly used it for email, word processing, music, videos, and pictures. Three teenagers had a mobile phone and comfortably used the basic mobile phone features. Teenagers were helped by their family members in watching over their younger siblings.
The authors collected a total of 119 multimedia objects (videos and pictures) and computed separate usage statistics for mothers and teenagers. The videos and pictures were then analyzed to identify major themes and examined how they affected the understanding of diet in the caregivers’ lives.
The majority of the content of their activities, as shown in Figure 1, consisted of meals and cooking. While there were a few pictures and videos of exercise, caregivers primarily equated health with diet. Most of the meals captured were dinners. The mothers captured more cooking related activities compared to the teenagers, confirming their role as primary caregivers. The food items in Figure 1b represent multimedia objects that consisted of food stored in the home.
Figure 1: Multimedia objects breakdown.
As seen in Figure 1, there were few instances where participants made videos of exercising. These videos were discussed during the MEIs, and it was found that most of the mothers only reported walking. The African American teenagers exercised regularly and participated in directed sports including basketball and track. The Somalian teenagers documented walking and occasional jogging. In the rest of the findings, the authors focus on diet because 86% of mothers’ and 96% of teenagers’ videos/pictures were about their diet.
Overview of Cycle
Since participants did not have control of external factors such as income, environment, and lack of transportation, we focused more on the tractable dietary issues. The dietary routines of the caregivers followed a knowledge-practice-reflection cycle (Figure 2). The dietary knowledge was based on their cultural upbringing and family experiences; the application and management of this knowledge was illustrated by their cooking and eating practices; and reflection was the resulting thoughts about their practices. In this cycle, reflection informs the participant’s health to create an active feedback loop.
Figure 2: The Dietary Knowledge-Practice-Reflection (KPR) Cycle
The videos and pictures revealed that the participants had a general knowledge of healthy and unhealthy foods. For example, some mothers were aware that vegetables were healthy and used them in their diet, but did not know their nutritional value. P4 discussed how salad was healthy: “A really good healthy salad you should eat just as it is or with parsley, a little bit of salt and pepper or vinegar because a lot of the ranches and buttermilk are really high in fat.” (PV).[a] P3 mentioned that she attended cooking workshops held at the Bridge, “… they are teaching how to eat more healthier.. like not using too much grease and oil in our food and trying to use less seasonings…” (M3).[b] P3 further stated how she made sure to have vegetables in her meals, “I cook a lot of healthy stuff…I cook vegetables and stuff … it is just a habit to make sure that we have some kind of vegetables going through our body….” (M3). The teenagers also expressed a similar general knowledge of diet. T4 said, “My mom tries to have fish a lot, but my brother doesn’t like it, he eats beef, meat. My mom likes fish a lot because it is healthier.” (M2).
Despite the general dietary knowledge, the participants had little knowledge of nutrition (eg, the role of carbohydrates and proteins). This is illustrated by P2 in the following quote: “Because I don’t know too much about carbohydrates…if I had more knowledge on what carbohydrates and all that was…I would be like he ate this many carbs.” (M3). This was confirmed by another caregiver who added that this lack of knowledge can sometimes be a frustrating obstacle in understanding health.
During the MEIs, the authors observed that the participants’ family health experiences affected their dietary knowledge. T1’s family minimized their sugar intake because her extended family had diabetes. In contrast, T2 did not mention any adverse family health experiences and preferred sprinkling sugar over her fruits: “I put sugar on everything. So yeah, every fruit has to have sugar on it. It has to be sweet. I shave my bananas up and then I put sugar on them and then when I eat apples I have like a little sugar salt-shaker and when I bite the apples I put a little sugar on it.” (M2).
A somewhat odd case was that some teenagers could not always visually identify the foods they ate at school. An example of this from T4’s school cafeteria is shown in Figure 3. In both cases, when prodded, she said: “I have no idea.” (M2). If they are not able to identify what they are eating, how can they decide whether it is good or bad for their health?
Figure 3: T4’s School Lunch.
Despite the lack of knowledge, there was one family who had healthy dietary habits. This particular Somalian family was of Muslim faith and, therefore, only ate halal food. Consequently, they did not eat at fast food restaurants readily available in their neighborhood.
Cooking and meal planning were the two predominant dietary practices captured in the findings. Two mothers planned their meals at the start of each day, one mother was not interested in planning her meals because she received food from the church where she volunteered, and the remaining mother thought she was not a planner type.
The mothers who planned meals daily usually planned in the morning. Meal planning in this case was based on their children’s taste and not nutrition. The primary motivation behind this approach was to avoid food wastage. In answering the question as to how she decided what to cook, P2 said: “What the kids like. Because you know I can cook this big meal, go all out and they won’t even want to eat it. So I’d rather cook something that they like versus to cook something that they will…barely eat… it all goes to waste.”(M2). Mothers also reused leftovers to reduce the waste, as shown in P1’s video: “This is my lunch … It is the enchiladas from leftovers…I try to eat all the leftovers so that I don’t waste any food because food is not cheap.” (PV).
Teenagers, on the other hand, did not plan meals; they primarily prepared them based on their own likes and dislikes. Answering the question as to whether she planned her meal, T1 said: “No, I just look in my refrigerator and I cook…I think about what I wanna eat and they [family members] will eat that too. So that’s how it works.” (M2). We found that some practices were unique to a particular family. For example, although some of the teenagers cooked what they liked, T3 had to seek her mother’s approval before cooking. T3 said “I was going to make something but then my mom said, ‘No.’ ” (M2).
Figure 4: Effect of surrounding culture on recently immigrated Somalian families’ diet: (a) T3’s refrigerator with prepackaged food (b) T4’s refrigerator with home-cooked food.
The authors also observed that the surrounding culture induced a change in a recently immigrated Somalian family. Figure 4a shows T3’s refrigerator full of pre-packaged foods (pizzas and chicken nuggets), which is not native to her culture. Another Somali family, however kept a healthy diet and mostly used home-cooked food (Figure 4b).
The mothers had some control over their schedule. They usually did not eat lunch, snacked the entire day, and cooked only for dinner because the children ate breakfast and lunch at school. The teenage caregivers, on the other hand, had little control over their schedule. They snacked immediately after school and headed over to the Bridge Project. Upon returning, they cooked and had their dinner. One teenager remarked that she only saw her family on the weekends because the adults returned home from work late at night.
Reflection played an important role the participants’ diet because it allowed them to become aware of their bad dietary habits. For instance, P1 snacked after her children went to bed because she did not want to pass her bad habits to her children: “They [children] were in the bed at that time. Because I don’t want them to eat at night before they go to bed. So I don’t want to pass on bad habits.” (M2). Similarly, P2 mentioned about soda when discussing about grocery items: “That’s for the grownups, not for the kids.” (M2). This indicates that the mothers reflected on their bad dietary choices and attempted to pass on positive habits to their children. This is emphasized by P1: “… I have to bring down the bad habits [of children]. But for them to change, I have to change.” (M3).
In teenagers, we observed cases of misinformed reflections. For example, T3 said her family generally ate fresh food, but her refrigerator, shown in Figure 4a, was full of pre-packaged foods. Similarly, in cooking chicken, T1 remarked how healthy chicken was, but deep-fried it in oil. While chicken is healthy, the preparation practice used by T1 was not necessarily healthy. It is a reflection based on partial dietary knowledge.
The authors also observed instances of family-based reflection on health that helped reaffirm good dietary habits in children. For example, in a cooking commentary video, P3’s child was cooking the food and when P3 asked her, “Are onions and bell peppers healthy?” (PV), the child responded affirmatively. This video also illustrated cooking practices being passed down from mother to daughter. When the child questioned her mother about seasonings, the mother responded, “We will put seasonings when we add water and bring it to boil.” (PV).
The authors successfully employed a participant driven method, the MEI, to explore everyday health routines of a low SES population. The benefit of using MEIs over other needs analysis methods is that it shifts the balance of power from the interviewer to the interviewee; since the participants are the authors of the content, they feel a sense of ownership that makes them comfortable while discussing their everyday health habits. Moreover, while discussing the videos and pictures, the participants get an opportunity to reflect on their lifestyle, providing more contextual information and thereby allowing for a deeper analysis of the data. Unlike shadowing, where participants are conscious of researchers observing them and that is likely to affect their actions, MEIs protect participants’ privacy where they only record information that they want to share. The community of participatory medicine can benefit from the MEI method because it provides deeper insight into participants’ motivations and the rationale behind their everyday choices.
The usage pattern statistics for this study suggest that the participants will use a mobile phone-based health routines-capturing application with no feedback 2 to 3 times a week. During the study, the participants confirmed that they would use their own mobile phones for managing their health because they already used it in their daily lives. Since most of the meals captured were dinners, evening hours may be the best time of day for a dietary sociotechnological intervention.
A nascent theme was how participants reflected on what they saw in the videos, either while recording something that reminded them of health or when reviewing the videos with the authors during interviews. They noticed the impact of actions, eg, watching their children put too much seasoning in a dish or realizing how hard they were breathing while walking. This reflection, identified in the KPR cycle, is a key aspect of inducing positive change and in turn informs their everyday health, knowledge, and practice. Any successful dietary technological intervention needs to utilize this positive feedback loop for effective health outcomes.
Diet and Technology
When discussing health related activities with low SES populations, diet was the dominant topic. Thus, the authors believe that, in order to improve the target populations’ health, effective socio-technological dietary interventions need to be designed. Although there are many dietary and nutrition applications available from the commercial (eg, calorieking.com and mealsnap.com), government (eg, mypyramidtracker.gov), and academic  sectors, they do not take into account the needs of low SES populations: specifically, limited resources, culturally influenced diets, lack of nutritional knowledge, and access to healthy foods. For example, providing specific nutritional knowledge might not be as helpful in motivating change. In discussing a potential nutritional application, P1 commented, “That is how I am. If I don’t understand it, I will get frustrated and I won’t use it.” (M3). Therefore, any technology needs to educate or abstract nutritional information so that it is easy to understand. For example, star icons can provide a weighted representation of nutritional values.
The Role of Culture
While acknowledging different ethnic backgrounds, it is also necessary to consider the confluence of different cultures. The local geographic culture tends to dominate native culture over time in children who are born into one culture but grow up in another. Immigrants increasingly supplement their cultural diet with non-native processed foods. One immigrant Somalian family was using more local foods in their diet (see Figure 4). Based on this, the authors propose to retain the best practices of a culture’s traditional diet while adopting healthy foods from the host country. For example, one Somalian family had a healthy diet compared to other families, despite their current economic situation and environment. The health practices of the healthy familycan be modeled and introduced to other Somalian families so that they can include these everyday habits to improve their health. Since cultures are ethnocentric by nature, a healthy family’s habits can be used as an example to motivate positive dietary change for a particular culture. In this case, the authors can create a mobile phone application that displays picture storyboards or videos of the healthy family discussing healthy dietary tips particular to each culture. This method is also useful for families that suffer from chronic illnesses.
The results showed that participants’ cooking and eating choices were based on their taste. To improve their dietary habits, their food preferences should be considered. Instead of making suggestions, such as, “Eat this, not that!” — which promotes nutrition over taste — the technology can be used to recommend gradual reduction of unhealthy food items. One way of visualizing this gradual change can be adopted from Pollak and colleagues, where an individual’s intake impacted a virtual pet’s emotional state. More research is needed to optimize this solution for taste. In the authors’ prior study in the same community, the participants discussed more physical activities. In this study however, in spite of logging exercising, they still perceived themselves as “big.” Based on the diets logged in this study, the authors hypothesize that their limited physical activity is not enough to burn the calories consumed. Because the authors advocate a gradual change in their diet, the participants will not witness rapid positive results of their new lifestyle. This can lead to a lack of motivation toward their exercise goals. Technologies are needed that help visualize results until the body “catches up” to make participants aware of these imperceptible physical changes.
The findings also suggest a need for technologies that provide timely feedback to support long-term dietary change. This is evidenced by P1’s self-reported addiction to food, where she snacked after her children went to bed. Despite knowing that it is bad for her health, she was not aware how this repeated instance negatively contributed to her long-term health. Conversely, P2 walks her children to school, but does not consider it as exercise. The authors wish to design technology that shows how every action, whether positive or negative, affects everyday health. An interesting avenue of research that has the potential to fill this gap is wearable technology (eg, pedometers). Most mobile phones today contain sensors (eg, accelerometers) that can be used as a wearable device to monitor and share timely information at the right time and place to encourage opportunistic activities. As opposed to structured exercise, a person incorporates activities into their everyday lives (eg, taking the stairs instead of the elevator) in an effort to increase overall activity. Research has shown that this can often lead to structured exercise.
During the MEI, the participants were seen to snack a great deal and had a broad definition of snacks that included pizza and burritos. Rather than designing technology to improve the diet as a whole, their diet might be improved gradually, by designing a technological intervention to improve a subset of their diet such as snacking.
The authors aim to improve the target population’s snacking habits to foster gradual dietary change. To this end, the authors are designing multiple mobile phone-based applications that visualize the target population’s snacking habits to provide participants timely feedback on their dietary choices. The applications are based on established behavioral change theories to motivate and engage users. The authors will conduct a usability evaluation study with the same population to determine the optimal interface and interaction with the application.
The authors acknowledge that the study had a small number of participants — four mothers and four teenagers. This highlights the challenge of working with a low SES population whose tight schedules and mobile lifestyles present difficulties in recruitment and retention. Another limitation is that although the MEI method provides deep insights into the target population’s everyday health routines, the multimedia data captured was limited by whatever participants wanted to share.
We thank the Bridge Project based in Denver’s public housing neighborhoods. Funding for this research was provided by National Science Foundation Award No IIS-0846024. The phones were donated by Nokia Research.
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Copyright: © 2011 Danish U. Khan, Swamy Ananthanarayan, and Katie A. Siek. Published here under license by The Journal of Participatory Medicine. Copyright for this article is retained by the authors, with first publication rights granted to the Journal of Participatory Medicine. All journal content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License. By virtue of their appearance in this open-access journal, articles are free to use, with proper attribution, in educational and other non-commercial settings.
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