Rural Perspectives of Online Lifestyle Medicine Intervention Delivery,Digital Data Collection,and Health Behavior Changes: A Qualitative Study

Abstract

Purpose: Chronic diseases contribute toward increased rates of disability, morbidity, and mortality around the world. People living in rural areas are disproportionately more likely to have chronic diseases and greater chronic disease risk from modifiable lifestyle risk factors. The purpose of this study was to explore the perspectives of rural participants of an online lifestyle medicine intervention study regarding online health program delivery format, digital data collection, and making health behavior modifications. Design: The study had a descriptive qualitative design using individual semi-structured interviews via Zoom to collect information from a subset of intervention group participants. The interviews (n = 26) were transcribed within the Zoom application and checked for accuracy. Grounded theory guided the thematic analysis of qualitative data using an iterative process to discover patterns, concepts, and central themes. Results: Four categorical themes emerged: Online and Digital Format, Health Behavior Outcomes, Health Behavior Change Barriers, and Health Behavior Change Facilitators. The findings highlighted rural perspectives about participating in online and digital intervention study modalities and making health behavior changes, including barriers and facilitators. Conclusion: The results emphasize that people living in rural areas can actively participate in online interventions, digitally complete study activities, and make healthier lifestyle choices.

Keywords

chronic illness lifestyle medicine rural online digital

“Educational content and discussions within the program sessions promoted understanding of linkages between physical inactivity and chronic disease development and exacerbation.”

Background

Chronic diseases present a major public health problem by requiring ongoing medical care, limiting daily activities, and contributing toward the deaths of more than 43 million people globally.^1,2 Among people living in the United States (U.S.), chronic diseases, including cardiovascular disease, diabetes, and cancer, are the leading causes of death and disability that affect more than half of the population and accrue healthcare costs exceeding $4.5 trillion dollars annually.^2,3 Alarmingly, national chronic disease rates are expected to continue rising despite medical advancements and progressive treatment options, especially as average life expectancy rates increase.^2–5 The chronic disease burden is especially apparent among rural populations, particularly in the southeastern US, where there are higher premature death rates and poorer overall health.^6,7 In fact, rural and urban differences in health outcomes have widened markedly over the past three decades and, similar to national chronic disease rates, gaps are projected to continue broadening.⁸ Compared to urban groups, rural populations have fewer public health resources and greater chronic disease risk from modifiable risk factors, including being overweight and physically inactive.^6,7,9,10

Unhealthy individual health behaviors contribute to more than half of all preventable disease deaths.^2,3 However, investment in prevention is often minimal.⁴ Lifestyle medicine interventions offer potentially cost effective means for mitigating this challenge by promoting healthier behaviors with subsequently reduced disease development and exacerbation.^2,5,11–14 The lifestyle medicine paradigm focuses on underlying causes of chronic diseases and fosters healthier behaviors based on 6 main pillars delineated by the American College of Lifestyle Medicine (ACLM) as predominantly plant-based dietary recommendations, regular physical activity, healthy sleep, stress management, avoidance of risky substances, and positive social connections.^15–18 Previous research guided by the ACLM framework showed that a group-based lifestyle medicine program delivered online among rural adults had positive effects on health behavior determinants and expanded program reach to family and social networks through ripple effects and modeling of healthier dietary and physical activity behaviors.^19,20

Web-based approaches can be effective means for delivering multi-domain lifestyle programs among community-dwelling adults.²¹ The use of online health technologies accelerated during and in the aftermath of the COVID-19 pandemic to facilitate both healthcare and personal communication functions.²² Presently, digital health intervention and data collection methodologies hold promise for bridging public health resource accessibility gaps and improving health behavior outcomes, especially in underserved areas.²³ Although rurality is not significantly associated with recruiting and engaging rural participants in digital health interventions,²⁴ more information is needed about rural groups regarding the effects of digital interventions on health outcomes and their views about online formats for community-based prevention programs and data collection methods.^25,26 This study helps to address this gap by exploring the experiences perceived by rural participants of an online lifestyle medicine intervention. The purpose of the study was to discover information about the unique viewpoints of rural people about online methods for health program implementation and digital data collection and gain insights about ways lifestyle change recommendations were applied in actuality, including perceived facilitators and barriers.

Qualitative Research Question

What were the perspectives of rural people regarding their experiences with online health intervention delivery format, digital data collection processes, and making health behavior modifications?

Methods

A descriptive qualitative design having a grounded theory approach was used to understand the unique perspectives of rural people about participating in an online lifestyle medicine intervention study, completing data collection digitally, and making health behavior changes. These experiences were further explored to discover perceived facilitators and barriers. This qualitative research component followed a primary study that involved a randomized controlled trial (RCT) to test the effects of an online group-based lifestyle medicine intervention among rural participants (n = 80) randomized to either an intervention (n = 40) or waitlisted control (n = 40) group.¹⁹ The intervention group received a group-based interactive and educational program guided by the ACLM¹⁵ 6 pillars and delivered via an online Zoom format along with digital materials sent electronically to each participant to reinforce the curriculum between sessions. Details about the intervention, RCT methods, and overall study sample have been previously reported.¹⁹ Quantitative survey data were collected digitally through the Research Electronic Data Capture (Recap) online application.²⁷ After all questions about the study were satisfactorily answered, each participant was sent an individualized weblink to digitally complete informed consent forms and all study surveys independently by entering answers to survey questions directly into REDCap. The study procedures received institutional review board (IRB) approval from Florida State University before any study activities were initiated. The reporting of this qualitative research phase was guided by the Standards for Reporting Qualitative Research: A Synthesis of Recommendations (SRQR).²⁸

Sample

Purposive sampling methods were used for this qualitative study to recruit a subsample of participants randomized within the primary study to the intervention group. Recruitment procedures for the qualitative component began after participants had completed the online intervention sessions and digital data collection of survey information at baseline and three post-intervention timepoints.¹⁹ They were at least 18 years old, proficient in English, and living with at least one chronic disease risk factor or diagnosis, such as being overweight, managing hypertension or diabetes, family history of chronic disease, etc.¹⁹ Participants had access to a computer with internet service or smartphone with cellular data and resided in a rural area as designated by the Rural-Urban Continuum Codes (RUCC). RUCC codes are updated every 10 years and differentiate counties as urban or rural by information about the population size, extent of urbanization, and proximity to a metropolitan area.²⁷

Data Collection

The data about the socio-demographic characteristics of participants were digitally collected online at the baseline data collection timepoint using self-reported survey answers entered by each individual participant in the online REDCap application. Qualitative information was collected using online individual semi-structured interviews conducted by three study team members during scheduled appointments with intervention group participants who agreed to participate in the interviews. To prepare for the scheduled interview time, participants were asked to find a quiet place in their homes where they could access the Zoom application free from distractions and influences from other family members in the home. It was anticipated that the number of participants needed for interviews depended upon reaching data saturation.

At the appointed time, the interview session was initiated by exploring overall perceptions about the program sessions followed by focused questions using a semi-structured interview guide. The interview guide included formative evaluation questions about the online Zoom intervention session format, digital data collection methods using REDCap, and behavior change outcomes, and exploratory questions were asked about facilitators and barriers. An example of a question in the interview guide about online intervention session formatting was “What did you think of the program sessions being delivered by Zoom? Did you find it easy or difficult to participate in the sessions? Why?” For perceptions about digital data collection using REDCap, a question was “Did you feel that the method you used was an effective means of collecting information? Why or why not?”.

Each individual qualitative semi-structured interview lasted approximately an hour. The interviews were closed captioned (CC) and recorded within the online Zoom application, and CC-captured text transcripts generated in Zoom served as the baseline transcript. For all interviews, audio/video review was performed by trained project personnel to ensure accuracy and finalize and clean verbatim transcripts. Researchers excluded or generalized any potentially identifying information captured on the recordings in the written transcripts, such as individuals’ names or specific geographic locations. Participants received a $50 gift card to a superstore for their participation.

Analytic Strategy

A grounded theory approach was used in this analysis because of its usefulness in enhancing understanding about unique lived experiences of rural people and eliciting themes for practical applications in future public health program development.²⁹ Analysis was assisted with analytical software for qualitative analysis (NVivo 20 and Taguette) to facilitate coding and categorizing deidentified data. Thematic analysis of qualitative data involved an iterative process of open, axial, and selective coding to discover patterns, concepts and central themes using methods to ensure trustworthiness and credibility.³⁰ A codebook was developed that included parent codes, subcodes, descriptions, and inclusion details (Table 1). Inter-rater reliability involved periodic meetings between researchers to manage discrepancies and reach consensus about descriptive codes and coding processes. Reaching data saturation in qualitative research involves collecting data until no new information or insights are noted, and for grounded theory research designs, the recommended sample size is typically between 20 and 30 participants.³¹ For this study, the data analysis process was concluded after code saturation and a full understanding of participant perspectives was reached for meaning saturation at 26 participants, and no other themes, insights, or nuances, or insights were noted.³²

Table 1.

Program Assessment, Application, and Outcomes Codebook.

Parent Code	Subcode 1	Subcode 2	Description	Inclusion details
Online and digital format			Experiences with the online methods in implementing intervention sessions and survey data collection
	Online program delivery	Overall assessment	Participant reported general positive assessment of the online program	Generally positive comments of program
	Curriculum	Barriers	Participant reported participation barriers related to program curriculum/content	Content (e.g., redundant content, remedial content, content that is not personally relevant)
	Curriculum	Facilitators	Participation facilitators related to program curriculum/content	Detailed information, scenarios
	Format, procedures and operations	Barriers	Participation facilitators related to program format, procedures and operations	Sessions (e.g., session length); Follow-up (e.g., too much time elapsed before follow-up)
	Format, procedures and operations	Facilitators	Participation facilitators related to program format, procedures and/or operations	Format (varied teaching techniques; varied data collection techniques; providing incentives to participants); Participants: Participant feedback, group discussion, Q & A); Materials and resources (e.g., PDFs of content and supplemental materials; recordings of sessions; providing slides; visual aids); Activities (taking notes for reference)
	Communication and interaction	Barriers	Participant reported participation barriers stemming from communication or interaction issues	Participants’ communication and interaction (e.g., lack of communication/non-interaction, fatigue/loss of attention; participants who dominate discussion/interactions; participant introversion); Interventionist’s communication and interaction (e.g., presentation style)
		Facilitators	Participant reported participation facilitators stemming from communication or interaction during or after the program	Participants communication and interaction (participant feedback, group discussion, and Q & A with interventionist); Interventionist’s communication and interaction (presentation style; ability to contact interventionist and researchers with questions or concerns)
		Benefits	Participant reported participation benefits stemming from communication or interaction during or after the program	Increased participant comfort; social support; deeper understanding of content
	Digital data collection	Overall assessment		Generally positive comments of digital data collection
		Barriers	Participant reported barriers to taking/completing the online surveys	Technical issues; survey characteristics (appearance, format, questions, frequency, repetition or duplication of questions}; Participants’ negative emotional or psychological response to surveys (e.g., feels “tricked” by questions; social desirability response bias); Participant error (e.g., inadvertently missing questions)
		Facilitators	Participant reported facilitators to taking/completing the online surveys	Participants (positive experience taking surveys; providing honest answers); Curriculum (relevance of training topics); Completing surveys (reminders emails); Learning environment (e.g., time, reduce/no distractions); Survey procedures and characteristics (e.g., ability to pause and return; can take as long as needed to complete)
		Benefits	Participant reported benefits of taking/completing the online surveys	Self-examination of health behaviors
	Zoom	Barriers	Participant reported barriers to Zoom online platform for program implementation	Technical issues (e.g., Wi-Fi in rural areas; microphone failures; participating by phone); Participant characteristics (e.g., introversion, shyness); Lack of experience or expertise using Zoom platform; Physical fatigue (eye fatigue); Mental fatigue (loss of attention); Learning environment (e.g., distractions)
		Facilitators	Participant reported facilitators to Zoom online platform for program implementation	No or minimal technical issues; Zoom capabilities (e.g., off camera option, share documents option; Learning environment (e.g., being alone during Zoom sessions); Participant characteristics (e.g., experience or expertise with information technology and/or Zoom)
		Benefits	Participant reported benefits of using online/zoom format for program implementation	Efficiency and convenience (e.g., can perform other tasks simultaneously; can participate from anywhere); privacy; protection from infectious/communicable disease
	Interventionists	Facilitators	Participant reported participation facilitators related to the interventionist	Commitment to participant learning, made curriculum simple, subject matter expertise
	Participants	Facilitators	Participant reported participation facilitators related to self and/or other participants	Commitment to participation
	Suggested program improvements	Format, procedures and operations	Participant suggestions for improvements to program format, procedures and/or operations	Communication and interaction (increase interaction among participants; explain study/research objectives in more detail to increase participant understanding and engagement; review/ask questions about previous session to start current session; provide optional time for unstructured participant interaction); Pre-intervention (pre-intervention assessment of participant knowledge level; prework for participants); Post-intervention (more in depth follow-up; longer-term follow-up; follow-up to assess participant progress); Materials and resources (Provide handouts of all program materials)
		Surveys	Participants’ suggestions for improving survey content or procedures	Allow paper surveys (complete on paper and return by mail or electronic image); provide more varied question formats; simplify questions
		Curriculum	Participants’ suggestions for improving the curriculum	More detailed information; Additional components (e.g., healthy cooking classes, medication information); additional information (e.g., more information on exercise); provide varied curricula for participants’ different competency levels or learning styles
Health behavior outcomes			The health behavior outcomes that participants described after program participation.
	Diet and nutrition		Health behavior outcomes related to diet and nutrition	Food shopping; healthier snacks; home garden; increased water intake; portion control; reduced fast food intake; reduced fat and cholesterol intake reduced salt intake; reduced sugar intake; Increased intake of fruits and/or vegetables; increased intake of healthy fats; intermittent fasting; using food labels; using spices; avoid restaurants
	Physical activity		Health behavior outcomes related to physical activity	Increased physical activity, higher intensity workouts
	Substance use		Health behavior outcomes related to substance use or abuse	Decreased tobacco/nicotine use; decreased alcohol consumption; decreased drug use
	Medical and clinical		Health behavior outcomes related to medical or clinical behaviors	Improved clinical indicators (e.g., reduced blood pressure), increased health screening and/or monitoring; learning more about local emergency care; changing health providers
	Sleep		Health behavior outcomes related to sleep	Increased or improved sleep
	Chronic disease management		Health behavior outcomes related to chronic disease management	Medication adherence,
	Pain		Health behavior outcomes related to pain	Reduced joint pain
Health behavior change barriers	Participants		Participant reported barriers to enacting health behavior changes	Knowledge retention; psychology and emotions (e.g., emotional eating); getting accustomed to new behaviors; health-related barriers (e.g., injuries, surgeries); accessing resources
	Health information		Health literacy, conflicting information, changing information; lack of time with healthcare providers to receive detailed health information
	Society		Costs of being healthy (e.g., healthy food more expensive); U.S. lifestyle (e.g., busy, fast paced); COVID impacts; vulnerable populations (e.g., low income, older adults)
Health behavior change facilitators	Participants		Participant reported facilitators to enacting health behavior changes
	Psychological or emotional		Participant reported facilitators to enacting health behavior changes associated with psychology or emotions	Having goals, making incremental changes, self-motivation
	Social support		Participant reported facilitators to enacting health behavior changes associated with social support	Social support, familia support, having a partner
	Medical and clinical outcomes		Participant reported facilitators to enacting health behavior changes associated with medical and clinical outcomes	Tracking clinical outcomes; not wanting to be on medication
	Disease awareness and knowledge		Participant reported facilitators to enacting health behavior changes associated with disease awareness and knowledge	Awareness of disease impacts, experience with chronic disease, recognizing symptoms and warning signs, understanding risk factors

Results

The sample (n = 26) for this qualitative study (Table 2) were mostly female (n = 22, 84.6%) and self-identified as being either White (n = 15, 57.7%) or African American (n = 9, 34.6%). The average age of participants was 50.38 (±14.99), and most were employed either full-time (n = 11, 42.3%) or part-time (n = 8, 30.8%), college graduates (n = 12, 46.2%) or attended some college (n = 10, 38.5%), and married (n = 13, 50%). Slightly more than half (n = 14, 53.9%) identified having 5 or more personal risk factors for chronic disease from the list provided in the survey (overweight, poor nutrition, etc.), and a majority (n = 20, 76.9%) were previously diagnosed with 1–2 chronic diseases (hypertension, diabetes, etc.).

Table 2.

Socio-demographic Characteristics.

	Participants (n = 26)
	n	%	M	SD
Age (years)			50.38	14.99
Gender
Male	4	15.4
Female	22	84.6
Employment
Full-time	11	42.3
Part-time	8	30.8
Not working and looking for a job	1	3.8
Not working and not looking for a job	1	3.8
Retired	3	11.5
Full-time homemaker	2	7.7
Marital status
Married	13	50.0
Not married/Have a significant other	4	15.4
Widowed	2	7.7
Divorced/Separated	7	26.9
Education
GED/High school diploma	4	15.4
Attended Some college	10	38.5
College graduate	12	46.2
Race
White	15	57.7
African American	9	34.6
Other	2	7.6
Number of people in household
1–2	15	57.7
3–4	8	30.8
5 or more	3	11.5
Income
Under $30,000	10	38.5
$30,000–$49,999	5	19.2
$50,000–$74,999	3	11.5
$75,000–$100,000	3	11.5
Over $100,000	5	19.2
Risk factors for chronic diseases (n)
1–2	6	23.1
3–4	6	23.1
5 or more	14	53.9
Personal history of chronic diseases (n)
1–2	20	76.9
3–4	5	19.2
5–6	1	3.8

The findings of the analysis included four categories (Table 3). The Online and Digital Format category contained experiences of participants regarding online methods for implementing intervention sessions and digital data collection. The Health Behavior Outcomes category encompassed the health behavior modifications that participants made after participating in the program. The Health Behavior Change Barriers and Facilitators categories included factors perceived as barriers and facilitators of making those described health behavior changes.

Table 3.

Categories, Concepts, and Codes.

Parent Code	Subcode	Concepts	Quotation Examples
Online and digital format	Online program delivery	Overall assessment	“ Doing it with Zoom, it worked best for me because I was able to attend weekly, and I…I do Zoom with my job…So, Zoom, it was very helpful.” (3) “I hate going to meetings. Even in my corporate life…But Zoom! I love it.” (13) “An excellent solution because even though there’s going to be limiting factors when it comes to technology, transportation is also a limiting factor. So, when I found out that… not only that, my mom was here and she’s going through her medical situations and our concerns and we had to consider whether we could even get out to participate. So having it on Zoom, she could be here, we could listen and that was fine. It was perfect
	Online program delivery	No tech issues	“No, I don’t think we had any problems at all” (26) “No, it was fine.” (1) “I’m a high-tech redneck. I kind of know what I’m doing.” (17) “I had to go to a place to make sure that I had internet. That’s another thing that’s not always available where I live but, you know, if I know of a meeting time, I can get to an area where I have good connectivity. So, I’m able to do that.” (59)
	Online program facilitators	Online visual aids	“I enjoyed interacting with the host and having the handouts. They were a big help!” (8) “The drawings y’all had showing how the arteries, how it works.” (36) “I really like the PowerPoints. It helped it to stick, as opposed to just having someone just talk at you.” (19) “In my situation I retained information better by seeing it and reading it. So, the handouts are very important in my case.” (8)
		Interactions	“It was so interactive. She would ask questions, you know, we were able to answer so I was able to stay involved with it, you know, and it was face-to-face.” (28)
		Online videos	“There were the videos, the replays, we always got the replays that was very helpful.” (39) “If there was anything that did come up, I think one time I had a follow-up with my cardiologist, so I had to miss that… that they were recorded it and that they sent us the link to watch it.” (19)
	Online program barriers	Lack of interaction	“We didn’t really interact with anybody else. I think there were like 6 other people.” (25) “Unfortunately, the facilitator had to kind of drag the answers out of everyone.” (13) “A lot of people just turn the monitor off and they turned the video off, and just listened… didn’t ask any questions.” (17)
		Sessions Too Long	“Sometimes they were a little long” (17) “That’d be the only thing, just kind of speed it up a little bit.” (17)
		Lack of retention	“I didn’t really like soak in the information as far as when it’s talking about the cancer” (56) “If I had had high blood pressure or diabetes, I would have paid more focus to it.” (4) “I don’t remember anything about that. I was so focused on the problems I had.” (4)
	Digital data collection	Overall assessment	“That was very effective.” (17) “I think allowing you to do it in your own time…I think like doing it online is awesome.” (19) “Kind of used to that being the way that everybody gets information nowadays.” (11)
	Digital data collection facilitators	Convenience	“I was able to just click on it. I mean, it’s easy to answer the question.” (26) “You can take your time so if somebody needed more time to, you know, they needed to take an hour, you know what I mean, to answer the survey, they weren’t rushed.” (25)
	Digital data collection barriers	Too long	“The surveys seemed to take a long time. There’s a lot of questions, and it’s just for me it was just like a lot at once.” (26)
		Missed questions	“I thought I completed the surveys, but the lady had to call me back to… to address questions I think I missed, or something.” (4)
		Survey appearance	“The only thing I would say to change on that is (the colors)-because I think that every time I would miss a question, the colors on it, because it’d be like a blue and grey, maybe have some type of more contrasting colors to see, but other than that it was fine.” (1)
Health behavior outcomes	Dietary changes	Reducing portion sizes	“I bought these containers so it’s just automatic. You just put the food in. It’s one cup. Then the 2 cups, so that way, if I, if you give me a plate, that’s not a good idea. So that’s a mental thing where I can just put it in the…and it cuts down on the food.” (1) “I understand the food now, I just… Now that I understand portion size, I really need to get down to the portion size.” (4)
		Using food labels	“We went over dietary things, what good foods to eat, things not to eat, how to read food labels again which is always a good refresher. I think that was something… a lot of people I can tell… that was the first time somebody ever showed them how to read a label.” (17) “Looking at labels and the session on fat, saturated fat. We just didn’t do that, you know. We looked at it, but didn’t pay attention…that’s been the quickest, most direct thing” (48) “One of the things that I thought was really good was going over was how to look at the back of the nutrition labels and to count, you know, what you need and how much you should have. Because it’s just not really something that we’re taught just in regular everyday life.” (19)
		Increasing produce and good dietary fats	“I’m eating more fruits and vegetables.” (1) “We’ve tried to eat healthier…paying more attention to more leafy greens” (32) “I wasn’t eating enough fruit. I eat more fresh fruit now than I ever have. I, you know, that’s what it made me eat more fresh fruit or fresh vegetables.” (72) “I’ll eat good fat. I eat avocados, and I eat… we only use olive oil.” (46)
		Reducing, sodium, sugar, and unhealthy dietary fats	“If we do buy canned (vegetables), we try to get, you know, no salt added, that way we could season it ourselves and kind of control sodium intake.” (25) “During this whole process we had to learn how to buy things that were sodium-free” (56) “I threw away all the sugar, and I haven’t been using even honey” (1) “With the butter and the grease, I haven’t eliminated it, but I went down on it.” (28) “We are big butter eaters, and we stopped buying butter…we would buy four pounds of butter…we don’t do that now.” (48) “Canned vegetables are not always the best thing, but if you can rinse them, that’s still…less salt than what you were previously taking in.” (49) “I think about it, you know, when I pick up that saltshaker.” (28)
		Avoiding restaurants	“We have stopped going to restaurants…” (56) “What we’ve started doing is the money, you know, that we were spending eating out…. We just take that money, and we buy the healthy stuff that we need.” (56) “Tried not to eat out with fast food as much” (25)
		Having healthier snacks and recipes	“I actually printed out those worksheets and created a new recipe book. I bought some heart-healthy recipe books…I’ve also been going through certain, you know, recipes I like… and then I made sure I put those tips… including like how to shop and choose different things so that way you’re doing less fat, less sugar, less salt, less cholesterol. So, I made sure to put those in my binder so that way, when I’m looking at some of these recipes I can flip back…I can make this substitution to make this a healthier recipe.” (36)
		Increase water intake	“I just try to drink more water now.” (8)
	Physical activity changes	Increasing physical activity	“Most of my positions have been sedentary…I thought if I was walking down the hall to give the secretary something…that I was active. Not really, so it made me…do more targeted movements…I make myself do things that I know will halt those illnesses.” (13) “With the physical activity, trying to do at least thirty minutes a day.” (8) “I’m more active. I am more active now than I ever have.” (72)
	Harmful substance changes	Reducing alcohol and tobacco use	“I probably used to drink, probably about 3 or 4 times a week. I’ve cut that down. I don’t do that like I used to.” (28) “Trying to reduce smoking. I smoke a tobacco pipe and even though it’s not like smoking a cigar or cigarette, it’s still bad for you.” (17)
	Sleep and stress changes	Improving sleep and stress	“I don’t sleep well, so sleep stood out to me, and I’m really working on that, trying to get to bed at a certain time, and I’m working on taking… Actually, I’m reading this book, Meditation and Mindfulness, to try to get more relaxed. I have a lot of stress and anxiety, and my body has taken it on. So, I’m working with that.” (46) “I turn off like all the electronics about an hour, hour and a half hour… an hour… hour and a half before I go to sleep so I can let my mind slow down.” (4)
	Clinical awareness changes	Monitoring health indicators	“My husband has high blood pressure, and he checks… He has a cuff, and so I’ve tried to at least check my blood pressure once a week, you know, to keep an eye on that.” (18)
	Clinical awareness changes	Help-seeking	“Since we started this (program), I changed doctors to a very comprehensive doctor in [town]…really the best thing I’ve ever done.” (48) “I was able to find another doctor. I’ve had my first appointment. That is one thing that I’ve done that’s helped me. I’m getting the medical care that I think I really need.” (48)
Health behavior change Barriers	Economic and financial	Income constraints	“I want to do right but, you know, between the gas and everything else, it’s like, ugh!” (1) “If you’re limited on your income, you can’t get a treadmill or exercise equipment.” (1)
	Economic and financial	Healthy food costs	“How do they sell fresh fruits and vegetables for double the price that they would for a bag of chips. Like it’s… it’s crazy!” (56) “Salads cost more than a hamburger.” (1)
	Physical activity	Injuries	“If I hadn’t had a broken foot, I would be further in an exercise program better than I am right now… The broken foot is making a difference.” (4) “I used to love exercising, but it was actually a knee injury, I fell at work, and then steroids and then that kind of ripple effect, so then I gained so much weight.” (1)
	Dietary change	Conflicting information	Hear…different things like, “Don’t eat this. Don’t eat eggs. Then go ahead, eat eggs.” (1)
	Dietary change	Altered diet and emotions	“Some people may not want to stick with it, but for me, I’ve got to.” (1) “When you’re kind of sad, you eat stuff (1) “It has been a challenge with my tastebuds going from the sodium you know all that salt, to not.” (1)
Health behavior change Facilitators	Social and behavioral Support	Family and social networks	“Sharing with others my participation in the program, not just my doctor or my therapist, but my children as well…coworkers was another… and I got a lot of support. In fact, it was one of my coworkers, another teacher, she actually joined the program as well.” (59) “…has always been big on vegetables, not so much me, but we’ve modified and we’re sharing more those things. She’s enjoying salmon, and I’m enjoying her vegetables.” (48)
	Shopping options	Shopping around and online	“…just checking your resources like [store name] is where I got the seasonings.” (1) “If I go to the store I may just I would spend more, and then, if you go hungry. But if you have, yeah, if you just have that list and you do it online, you spend less money.” (1) “Going online now, Walmart, online, and you can compare, and I think for me the easiest thing…I go online, and I order online, and then all have to do is go to the store and pick it up. it helps you kind of shop slower, more carefully, or whatever.” (1)
	Experience with health problems	Individual and family health issues	“My father had the heart attack, I started realizing you know, this hit home…I’m going to be eating right. And I actually, I have. I was like, I don’t want to go through this.” (49) “What has helped me, it’s just that I don’t want to take medicine. I don’t want to be on medicine, so I want to be as healthy as I can that way.” (46) “The sessions and then that happened. And I was like, you know what, it’s hitting home and I’m seeing the benefits of this.” (49)
	Beliefs	Self-efficacy	“I was like if I went that long, I could just keep going.” (3) “…you just pull back. I pull back myself. So, it’s up to me to check myself.” (13) “That’s the only way I can improve it is to do it myself, to do my homework.” (59)

Online and Digital Format

Participants had positive overall perceptions of the online Zoom format for intervention session delivery, expressed no technology problems, and were familiar with its use in the COVID-19 pandemic era. The online format was a deciding factor that promoted program participation because it allowed circumvention of personal transportation and family care issues. A few participants with unreliable connectivity problem-solved by going to places with better internet availability, such as the homes of family and friends.

It was easier to me, I don’t know if we've just all gotten used to Zoom after pandemic, … it was easier for me personally again (19)

Online format facilitators mentioned by participants included the visual aids shown during the sessions and the digital materials sent weekly via email between sessions that facilitated learning and enhanced retention. Other facilitators included interactive discussions during sessions that kept participants engaged and session video-recordings sent to absentees via emailed online links that enabled participants to view missed sessions.

They were bringing out things just like you were talking about people in rural areas. They had the same concerns. (56)

The online format barriers were that participants perceived the sessions as too long, and they sometimes had difficulty retaining information if the content was not personally relevant for them. Another barrier mentioned was the lack of interaction by some participants during discussions. For example, a few felt that others should be more vocal in expressing viewpoints and asking and answering questions during the sessions. However, other participants liked the fact that they were not required to participate in discussions and could just listen without talking to others.

Think for me, it’s not just about Zoom. I’m usually a wallflower kind of person, you know, so I can’t… (59).

Participants had positive overall perceptions of the digital data collection method for completing surveys by entering data directly into the REDCap application, and they voiced being able to complete them independently on their smartphones or computers without difficulty. Facilitators included the electronic online formatting that allowed participants to complete the surveys at any time and afforded the convenience of digital data collection compared with traditional paper surveys that needed to be mailed in or physically collected.

It's just instant and done, you know, you didn't have to mail me something where I had to return it and lose it, you know, so you actually got it back that way. (59)

A barrier of digital data collection included perceptions about the surveys being too long or too repetitive. Also, participants sometimes missed questions, and a few stated that the colors on the online surveys made the questions slightly more difficult to clearly see.

Health Behavior Outcomes

The participants reported that dietary changes were among the health behavior modifications they made after participating in the online lifestyle medicine intervention sessions. They conveyed that they reduced portion sizes at meals, used more scrutiny when selecting foods to purchase from grocery stores, and were reading food labels more frequently and thoroughly.

Now, when I go into the grocery store, I’m actually counting. I’m looking on the back of each item. I’m looking at the saturated fat., I’m actually counting calories and looking at the sodium… I mean it takes me a little longer in a grocery store, but it’s worth it. (3)

Participants also expressed that they had increased their daily servings of fruits and vegetables and reduced intake of sodium, sugar, and unhealthy fats while increasing consumption of healthier dietary fat options. They expressed using recommended strategies for reducing dietary sodium such as being more conscientious of the saltshaker on the table, rinsing canned vegetables, and using salt substitutes. They also stated that learning about the health effects of excess dietary sugar and saturated fat were motivational in making changes.

What I was really alarmed about was the fat and the plaque that can build up. I went back and checked my blood work, and I noticed that my good cholesterol was a little low, so it made me really make some lifestyle changes with watching the saturated fat. (46)

Other comments about dietary changes included avoiding food from fast food and other restaurants and purchasing recipe books to cook healthier dishes at home. Participants also reportedly began choosing healthier snacks and drinking more water.

Since taking the class, I have tried to make my snacks for when I’m at work, and you know, having these snacks, I tried to do healthier choices….(11)

Other health behavior outcomes included changes in physical activity, harmful substances, sleep, and stress as well as enhanced clinical awareness. Participants mentioned that their physical activity levels increased and use of alcohol and tobacco products decreased. They also reported efforts to improve sleep and reduce stress by implementing healthier strategies discussed in the intervention sessions. Other health behavior changes included improvements in clinical awareness and help-seeking, including blood pressure self-monitoring and seeking a “more comprehensive” primary care physician. Concerns were expressed regarding the level of detailed health information being received from current healthcare providers.

In this program, we are talking about all these details. I'm not getting those details at my current doctor. I’m not getting that stuff. (48)

Health Behavior Change Barriers

The Health Behavior Change category included perceptions about barriers and facilitators to making health behavior changes. Participants discussed perceived barriers to health behavior and lifestyle changes that included societal barriers. For example, participants expressed perceptions about the increasingly fast pace of society that often hindered making recommended behavior changes. Another barrier was described by participants with statements about being unable to afford a healthy lifestyle.

“People that’s on fixed incomes and barely have any money at all, like what do they do to eat healthy?” (56).

Reportedly, having low or fixed incomes serves as economic and financial constraints affecting ability to purchase equipment for physical activity and healthier foods considered costlier. Other barriers of engaging in healthier dietary patterns mentioned by participants were difficulties with adjusting to altered diets and confusion from conflicting information or changing dietary guidelines. Emotional eating was also discussed as hindering dietary health behavior changes.

When you’re kind of sad, you eat stuff. (1)

Health Behavior Change Facilitators

Facilitators that aided participants in making health behavior change included social and behavioral support received from family and other social networks. Encouragement and involvement from family, friends, and colleagues facilitated health behavior modification efforts, and assistance with responsibilities promoted healthy lifestyle change practices. Participants also reported that progress and sustainment of changed health behaviors were assisted by having social network members join them in making lifestyle modifications together.

That was the biggest thing, because at first, I was like, I’m not going to be able to do this here. But then my husband, he was so supportive he was like, “You done started it, you just keep going.” So, once I started… So, it’s just the whole house now. (3)

Another facilitator to modifying one’s health behaviors was having experience with individual or family health conditions or diseases. For example, experiences such as having a family member suffer a heart attack influenced health behavior changes as preventive measures to avoid such conditions or diseases. Such personal experiences affecting either the participant or a loved one seemed to expose life realities and facilitate preventive health behaviors. Participants also recognized self-efficacy to make desired health behavior modifications as a facilitator that promoted internal motivation to make the changes in actuality.

Knowing that I can help kind of reduce where my chronic diseases are currently, I can’t fully get rid of them, but I can help bring it back a little bit by making some smarter choices. (11)

Discussion

Little is known about how rural groups perceive online methodologies for health program delivery and digital data collection, and few studies have assessed health behavior outcomes, barriers, and facilitators experienced by rural participants of lifestyle medicine interventions. Addressing lifestyle factors of rural health aligns with national goals of improving health and attaining longer lives free of preventable disease,³³ but unfortunately, investment in prevention among underserved groups is often minimal.⁴ Previous studies evaluating lifestyle medicine programs have mainly concentrated on dietary and physical activity outcomes among primarily urban populations.^26,34–36 More research is needed to explore the impact of digital health interventions among rural groups.²⁴ This study addresses this gap and answers a call for research to explore and report the impact of increasingly employed online and group-based health approaches to improve lifestyle factors in the post-pandemic era.^25,37 Exploring the perspectives and experiences of rural participants of an online lifestyle medicine intervention study provided insight into rural perceptions about online intervention delivery and digital data collection methods, health behavior outcomes, and health behavior change barriers and facilitators. The findings can help guide intervention development and implementation and advance the lifestyle medicine mission of pursuing optimal health for all people in an increasingly digitalized era.

The results of Online and Digital Format thematic category provide a glimpse of rural fortitude and suggest that online intervention delivery and digital data collection methods were perceived as feasible, desirable, and convenient. Most participants portrayed online communication platforms, such as Zoom, as popular means to connect with friends and family during the COVID-19 pandemic and afterward, and the increasingly common use of online methodologies for public, work, and familial gatherings facilitated capability awareness and enhanced acceptance. Participants indicated that the online health education format and digital data collection methods used in this study were relatively easy to use, and they had minimal to no internet connectivity issues. Overall, research shows that digital methodologies can improve health outcomes among rural populations,²³ and rurality has not been significantly linked as a barrier to recruiting and engaging rural participants in digital health interventions.²⁴ Use of telehealth and digital technologies among rural populations can potentially effect a paradigm shift in delivery of healthcare services and public health programs in remote areas,³⁸ particularly as increasingly tech-savvy generations begin aging, develop risky health behaviors, and are diagnosed with chronic disease conditions and contributors, such as diabetes. However, connectivity issues and being unfamiliar with digital tools can serve as barriers that should be addressed to assure rural groups have equitable access to digital health technologies.²³

The findings of this study are consistent with current research regarding online, telehealth, and web-based formats as acceptable modalities among rural populations that increase satisfaction and reduce transportation costs.^2,21,25,39 Many participants of this study mentioned they would not have been able to participate in-person program sessions related to travel time, transportation access and costs, and responsibilities related to family and work. Although web connectivity can be variable in rural areas, research shows that, on average, only a small percentage, less than 19%, of rural dwellers report poor connections.⁴⁰ Another study suggested that geographical differences in online usage may be due to individual preference rather than lack of infrastructure.⁴¹ The online group-based format of this intervention was perceived positively by most participants although a few expressed viewpoints that other participants should have been more engaged in session discussions. Group-based lifestyle medicine interventions have positively impacted health outcomes and fostered empowerment through belongingness and shared experiences, but challenges include discomfort with sharing in a group context.⁴² In this study, there were different cohorts scheduled on different days and times, and some were more interactive and readily asked and answered questions than others. Participants were not required to speak during sessions if they did not choose to. Although some considered lack of participant interaction a barrier, it was a facilitator for more introverted individuals who expressed reluctance to comment when others voiced opinions that aligned with theirs.

The participants expressed that learning was facilitated by the inclusion of visual aids in presentation materials, digital health brochures sent via email after each intervention session to reinforce educational content, and digital links to Zoom session video-recordings sent to participants absent from a session to allow them to remain on track in the intervention. Digital data collection and completing study surveys asynchronously served as study facilitators, and all parent study participants (n = 80), except one, digitally completed them independently. Previous research suggests that digital surveys are more likely to appeal to people with higher incomes (>$25,000 annually) and more rural, or remote, households.⁴³ Comparatively, less than half (n = 10; 38.5%) of rural participants in this study reported an annual income of $30,000 or less while the rest had higher incomes (Table 2). Data collection barriers included common study participant perceptions that surveys were too long, and questions seemed redundant. Other barriers mentioned were answers not saving correctly in the digital application and survey color schemes possibly causing survey questions to be inadvertently skipped. In circumstances involving missing data, a research assistant telephoned each participant to facilitate data completion. Although digital challenges exist, people living in rural areas are adaptable, resourceful, and can accommodate to maximize contextual needs and resources that include traveling to areas, such as homes of family and friends and even county public libraries, where connectivity is more accessible.⁴⁴

The findings for the Health Behavior Outcomes thematic category indicated that participating in the online intervention influenced healthier lifestyle behaviors consistent with recommendations delineated by the 6 ACLM pillars.¹⁵ For example, participants described making several dietary modifications, such as increasing daily servings of vegetables and fruit and choosing healthier snacks. Other changes involved reducing portion sizes by resolutely measuring food when preparing and serving meals, drinking more water rather than sugar-sweetened beverages, and limiting intake of unhealthy dietary fat, sodium, and sugar. Further, participants began choosing healthier food options by reading food labels when grocery shopping, avoiding fast food restaurants, and cooking more meals at home using heart-healthy recipes with wholesome ingredients. Importantly, however, some participants regarded the program content about food labels as a refresher that strengthened and clarified previously learned knowledge, but for other participants, the online intervention empowered them with newly acquired skills that facilitated health behavior changes. This finding underscores the importance of covering rudimentary skills in public health interventions without having preconceived assumptions about baseline knowledge, skills, and abilities of participants, especially when working with underserved populations.

The online lifestyle medicine intervention positively impacted other health behaviors in addition to dietary outcomes. Educational content and discussions within the program sessions promoted understanding of linkages between physical inactivity and chronic disease development and exacerbation. For example, enhanced awareness of physical inactivity as a chronic disease risk factor motivated purposeful action toward making responsive health behavior changes as participants increased daily physical activity efforts and became less sedentary. The intervention also included educational information and useful strategies for improving sleep and managing stress, such as meditation and mindfulness, that participants used to improve well-being and reduce overall chronic disease risk. In comparison, previous research showed that lifestyle medicine interventions can effectively improve sleep quality and mental health outcomes, including depressive symptoms, stress, and overall mental health.^45,46 Participants also made concerted efforts to reduce use of tobacco and alcohol and improve self-monitoring of existing health conditions, such as hypertension. The intervention seemingly enhanced clinical awareness that motivated other less obvious health behaviors, such as seeking rural healthcare resources, establishing a primary care physician, and exploring rural emergency care services. Overall, the health behavior outcomes noted in this qualitative study support other evidence that health behavior changes can be facilitated by addressing modifiable chronic disease risk factors through lifestyle medicine interventions.⁴⁷ However, the findings also contribute information regarding the usefulness of implementing online interventions among rural groups to promote healthier lifestyle behaviors and potentially reduce chronic disease risk over diverse rural life trajectories.

The Health Behavior Change Barriers thematic category included barriers perceived by participants about making recommended health behavior modifications. Barriers mentioned were the financial constraints and the perceived costs of purchasing healthy foods compared with unhealthy options, especially in remote areas. Previous research conclusions support that transportation to access healthier foods can be challenging and incur additional costs for rural people.⁴⁸ Another perceived barrier that hampered dietary change modifications involved the impact of emotions on eating behaviors as participants described using food for emotional regulation during upsetting life events. Conflicting health information from healthcare providers, news and media outlets, and online resources created uncertainty for participants when making health behavior decisions. Barriers of increasing physical activity included limitations in mobility related to injuries and surgery.

The Health Behavior Change Facilitators thematic category included perceptions regarding factors that facilitated making recommended health behavior changes. Facilitators included positive relationships and connections involving family, friends, and other social networks that encouraged health discussions and making healthier lifestyle changes together, which extended program benefits beyond the participant-level.²⁰ This finding is supported by previous research that highlights the importance of social support for people involved in health programs.⁴⁹ An interesting facilitator involved perceptions that having individual and family health problems made the program content more personally relevant and meaningful. Sessions considered the most useful included prevalent chronic diseases in rural areas, especially heart disease, diabetes, and stroke, and contributing factors that participants or their family members had experienced. Another facilitator was the availability of online shopping for desired items that allowed participants to save time and money when shopping, and perceptions included having greater self-control when making choices when online shopping compared with shopping in a store. Self-efficacy was mentioned as a facilitator for intrinsic motivation that involved being personally accountable, taking responsibility for personal choices and their consequences, and making health behavior choices accordingly.

This study had strengths and limitations. One of the main strengths included the qualitative design to capture the depth and meaning of rural perspectives regarding participant experiences with digital data collection, participating in the online lifestyle medicine program, and making health behavior changes. Conducting individual interviews to avoid influence from others also contributed to the strength of the study. A study limitation was that the participants were primarily females residing in a rural southern region which may have led to premature data saturation. Future research could explore perceptions of online lifestyle medicine interventions among other rural groups, especially males because they are typically underrepresented in health research.⁵⁰ Additional research is needed that advances holistic care and explores lifestyle medicine intervention effects on mental health and other outcomes.⁵¹ Since rural residents have higher chronic disease rates and greater difficulty affording healthcare compared with urban groups, policy interventions tailored with consideration of chronic conditions and rurality are needed to address medical debt.¹⁰

Conclusions

The four themed categories highlighted rural perspectives about participating in an online intervention delivery format, completing study surveys digitally, making health behavior changes, and identifying perceived barriers and facilitators. The lifestyle medicine intervention promoted healthier behaviors among rural participants, and the online methods enabled circumvention of common external geographic barriers of health program participation, including transportation costs, travel distances, and family caretaking responsibilities. These findings have important implications for health professionals involved in public health program planning and implementation, especially in rural areas where chronic diseases and modifiable chronic disease risk factors are disproportionately prevalent. Lifestyle medicine programs hold promise for promoting beneficial health changes throughout the life course, and rurally tailored interventions using online and digital modalities can be feasible and acceptable implementation processes among rural groups.

Informed Consent

Participants provided informed consent prior to any study activities.

Footnotes

ORCID iD

Laurie S. Abbott

Ethical Approval

This research received approval from the Institutional Review Board (IRB) at Florida State University: (Study 00003258; 13 July 2022).

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Florida State University Translational Health Research Seed Grant, funded by the FSU Office of Research: 046517.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.*

Clinical Trial Registration

This study is registered at the registrations site under Name: Identification Number: Rural Chronic Disease Risk Reduction, NCT05611580.

Parent Trial registry name and URL

ClinicalTrials.gov:

Registration Name and Number

Rural Chronic Disease Risk Reduction, NCT05611580

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