Abstract
Objectives:
To identify endometrial cancer survivors’ (ECS) barriers and facilitators for participation in lifestyle interventions to improve their dietary and exercise behaviors. Our secondary objective is to determine baseline information: physical activity level, quality of life (QoL), and impact of COVID-19 on exercise, diet, and mental health.
Methods:
Obese, early-stage ECS participated in 2-part mixed-methods data collection; Part 1: survey gathering sample characteristics, QoL, exercise, and basic endometrial cancer- related knowledge. Part 2: virtual focus group or individual interviews using a brainwriting premortem protocol. Statistical analysis was performed using SAS (version 8.3). Qualitative data were analyzed using deductive thematic coding guided by the RE-AIM framework.
Results:
Twenty percent (70/358) of ECS from a survivorship database and clinic recruitment completed the survey; 16 ECS provided qualitative feedback. Common barriers to intervention participation included time and resource costs, meeting frequency, and pessimism about weight loss maintenance. Facilitators included an opportunity to connect with other survivors and a focus on health rather than weight loss. Most ECS could not identify exercise guidelines (60%) and 83% were not meeting these guidelines. Higher BMI was correlated with a lower confidence in completing in moderate physical activity (p-value= 0.0206). Post-COVID-19 pandemic, physical activity, nutritional decisions, and/or mental health worsened for 67% of ECS.
Conclusion:
ECS are a disparate population, with worsening behaviors and mental health following the pandemic. The identified ECS-specific barriers and facilitators to behavioral intervention participation are being used to simultaneously improve the reach of and adherence to a lifestyle intervention aimed at improving their health and QoL.
Keywords: endometrial cancer survivor, survivorship, physical activity, nutrition, physical activity intervention, mental health, behavioral intervention, patient reported outcomes
INTRODUCTION
Endometrial cancer is the most common gynecologic cancer in the United States and its incidence is directly related to excess adiposity (1–3). After diagnosis and treatment, over 70% of endometrial cancer survivors (ECS) remain overweight or obese resulting in poorer clinical outcomes and increased mortality compared to survivors with a normal body weight (1, 4). Additionally, ECS with obesity experience multidimensional quality of life issues (i.e., physical, social, functional, and emotional well-being) spurred by social anxiety and concerns about appearance, fatigue, feelings of isolation, and sexual dysfunction (5–7). Therefore, a multifaceted approach is needed to address these issues and enhance the survivorship of ECS.
A growing body of literature supports the broad benefits of physical activity and a healthy diet for cancer survivors, as highlighted in the recently updated American Cancer Society’s Nutrition and Physical Activity Guidelines for Cancer Survivors (8). Despite the known benefits of a healthy lifestyle, ECS do not spontaneously make changes to meet national physical activity or nutrition guidelines, which has prompted the development of behavioral interventions with varying success and limited uptake (7, 9). A recent Cochrane review including 12 weight loss interventions for ECS failed to show quality of life or weight loss benefits (10). Failure of small behavioral interventions to make widespread impact is not unique to ECS, given in part to their linear development (11). A widely held assumption is that pre-packaged interventions or programs, once they have shown effectiveness, have enough evidence to be widely disseminated and offered to new populations (11). However, barriers to successful delivery and implementation of programming in the “real-world” exist that are not apparent during the initial development and testing of these programs. Complicating this issue further is the fact that many interventions (and interventionists) focus on the packaged program, rather than identifying the adaptable core elements that might be tailored for a specific population or outcome of interest. These factors lead to a significant time lag (of over 15 years on average) from program development to implementation and dissemination (12).
One way to speed the development of a physical activity and nutrition intervention for ECS is to start with “the end in mind” (13). To do this, we engaged survivors in the development of a lifestyle intervention for them. By engaging the ECS in program development, we hope to address the significant loss-to-follow up (28% withdrawal and 58% missing data) noted in the recent Cochrane review (10). Thus, a mixed methods approach was utilized to identify barriers and facilitators of delivering a lifestyle modification program, as well as to understand the context of survivor’s knowledge and physical and mental state. We aim to use this information to speed the selection, adaptation, delivery, and integration of lifestyle interventions tailored for ECS.
Methods
Overview of the Approach
Our work follows the ORBIT (Obesity-Related Behavioral Intervention Trials) translational model, which was initially created to speed the development of evidence-based behavioral therapies addressing chronic diseases, such as obesity (14). Here, we report the results from Phase Ia, the “define” phase of ORBIT. To identify our target population and behavioral treatment, we used a mixed-methods approach including 1) quantitative data collection via a cross-sectional survey to investigate the characteristics of ECS as well as their preferences for a weight loss intervention; and 2) qualitative data collection via focus groups (see “Brainwriting Premortem Focus Group”) and individual interviews to enrich survey data on intervention participation barriers and facilitators as well as the delivery requirements needed prior to the launch.
Cross-sectional Investigation
Participants.
ECS were eligible if they: received care at Carilion Clinic between 1/1/2010 and 2/1/2020, were diagnosed with stage I-II endometrial cancer with endometrioid or mixed histology, were at least 6 months post-treatment, were at least 18 years old, and had a BMI greater than 30 kg/m2 at diagnosis. Survivors with recurrent cancer, or who were non-English speaking, were excluded. Questionnaire variables included:
Clinicodemographic characteristics including level of education, household income, height, weight, etc.
Health behaviors including the personal practice of physical activity [multi-select options for types of physical activities performed before diagnosis; report of weekly minutes, intensity, and frequency], their confidence in completing physical activity [5-point Likert scale, “not at all” to “completely” ], health compared to peers [4-point Likert scale, “extremely healthy” to “very unhealthy”], knowledge of association of obesity and endometrial cancer risk [multiple choice question with answers showing no relationship, some relationship, strong relationship, or “unknown”], and physical activity guidelines for cancer survivors [multiple choice question including 3 variations of minutes of activity and frequency per week or “unsure”].
Quality of life using the 43-item Functional Assessment of Cancer Therapy-Endometrial (FACT-En) evaluating physical, social/family, emotional, and functional well-being. Higher scores indicate greater quality of life (15).
COVID-19 impact including questions on pandemic associated mental health, physical activity, and nutrition choices.
Intervention participation barriers and facilitators including questions about components of a lifestyle intervention program, including the frequency and length of sessions, mode of delivery (e.g., in-person, virtual), and other specific characteristics (e.g., group exercise, cooking demonstrations).
Recruitment
An existing ECS database was used to identify eligible participants. In October of 2020, surveys were distributed via email. Additionally, two virtual outreach events were hosted to spark interest in the survivorship program. Events consisted of a 30 minute “slow flow” yoga session followed by an introduction to research opportunities with the research team, including a gynecologic oncologist.
After six months of recruitment via email and virtual events, survey response rate and focus group recruitment remained low, prompting the addition of in-clinic recruitment during surveillance visits. This allowed participation from survivors who were either in our database and did not respond to the emails or with a diagnosis since the creation of our database. Following survey completion, survivors could indicate interest in focus group participation. This work was approved by the Carilion Clinic Institutional Review Board (IRB-20–956).
Brainwriting Premortem Focus Group
All sessions were delivered virtually using a HIPPA-certified Webex platform and were facilitated by two research team members. The focus group methodology was adapted from the brainwriting premortem, described by Gilmartin et al. (16). Following this protocol, participants are introduced to a failed lifestyle intervention and asked to discuss the potential reasons the program failed. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework guided these discussions and is one of the most widely used frameworks in the field of implementation science (17, 18) and is based on the 5 dimensions included in its title (19, 20). During each focus group, a question related to a RE-AIM dimension was posed to the survivors(21). Individual responses were collected prior to interactive, group-level discussion.
Individual Interviews
Due to slow recruitment and scheduling challenges, individual interviews were undertaken until data saturation was reached. Participants were recruited at clinic visits, as described above. Interviews were delivered via telephone using a standardized script with questions corresponding to each RE-AIM dimension as well as data collected from focus groups.
Qualitative Data Management
All data from focus groups and individual interviews were recorded and transcribed verbatim following the sessions and guided by the Rapid and Rigorous Qualitative Data Analysis, “RADaR,” technique (22). Using the RE-AIM framework, the premortem text data was deductively analyzed into each dimension as well as categorized for any emergent themes that do not align with the framework. Two members of the research team independently coded all responses. The results from each coder were compared and differences were resolved by a third research team member. Comments that were similar were consolidated into an overall theme (e.g., transportation limitations, lack of access to internet, etc.) and total numbers of unique themes were counted for each dimension.
Data saturation was reached following the “10+3” rule, which states that the initial analysis should include comments from 10 individuals. If there are no new codes generated after interviewing three more individuals, then this can be the defined point of data saturation (23). Guest et al. (2006) found that approximately 73% of codes are identified in the first six of their interview transcripts, and they achieved data saturation by the 12th interview (92% of codes) (24).
Analysis
Our mixed-methods approach followed an explanatory sequential design by first obtaining quantitative data and using qualitative data to provide a richer picture of the patient experience and expectations of a lifestyle intervention (25). Most clinicodemographic data were assessed through descriptive statistics. Fisher’s exact test was used for categorical variables and Wilcoxon rank sum test for the numeric variables. For our analysis, patient BMI was used to create two groups: 1) obese = BMI 30–39.9 kg/m2 (obesity classes I and II) and 2) morbidly obese= BMI ≥40 kg/m2 (obesity class III). SAS Analytic software (SAS Institute Inc. 2020. SAS® Enterprise Guide® 8.3: User’s Guide. Cary, NC: SAS Institute Inc.) was used for the statistical analysis.
The qualitative analysis followed an established protocol and was guided by the dimensions of the RE-AIM framework. The premortem text data was analyzed deductively (by each dimension of RE-AIM) and then inductively for emergent themes that did not align with RE-AIM (26). Two coders cross-checked their results, and any differences were addressed through discussion or, if needed, resolved by a third research team member. Comments that were similar were consolidated into an overall theme (e.g., transportation limitations, lack of access to internet, etc.) and total numbers of unique themes were counted for each dimension. Open-ended responses in the follow-up survey and individual interviews were also analyzed using this approach.
Results
Survey respondents and focus group recruitment:
Within the database, 329 survivors had an email address and were eligible to participate. Fifty-five survivors (17%) completed the survey following email prompts. From the clinic, 15 of 65 survivors (23%) completed the survey. The overall response rate was 20%. See Figures 1 and 2 for recruitment rates from our database and clinic, respectively. Five virtual focus groups and three individual interviews were conducted with a total of 16 participants. Eight survivors attended the virtual outreach events, 75% of whom had already participated in a focus group.
Figure 1: CONSORT diagram from database recruitment:
Survey, focus groups/individual interviews completion.
Figure 2: CONSORT diagram from clinic recruitment:
Survey, focus groups/individual interviews completion.
Table 1 shows clinicodemographic characteristics of all eligible participants (n=358) from the database (n=329) and those identified in the clinic that were not part of the original database list (n=29) compared to those who completed the initial survey (n=70). Most survivors were non-Hispanic, White, with an average age of 60 years (IQR 10 years) and average BMI of 40.7 kg/m2 (IQR 7.2 kg/m2). No differences were identified between the BMI groups.
Table 1:
Demographic information and treatment: eligible target population vs initial survey responders.
| Eligible Participants | Survey Responders | ||
|---|---|---|---|
| N = 358 | N = 70 | p-value | |
| Time since Diagnosis (months) – Median (IQR) | 37 (37) | ||
| Age at SURVEY (years), – Median (IQR) | 63 (14) | ||
| Age at Diagnosis (years) – Median (IQR) | 60 (10) | 60 (16) | 0.560 |
| BMI at Diagnosis – Median (IQR) | 40.7 (7.2) | 39.2 (8.4) | 0.829 |
| BMI Class (BMI, kg/m2), n (%) | 0.895 | ||
| Class I and II (BMI 30.0 – 39.9) | 200 (55.9) | 38 (54.3) | |
| Class III (40.0+) | 158 (44.1) | 32 (45.7) | |
| Marital Status, n (%) | 0.349 | ||
| Married | 222 (62.0) | 40 (57.1) | |
| Single | 49 (13.7) | 14 (20.0) | |
| Divorced | 43 (12.0) | 10 (14.3) | |
| Widowed | 38 (10.6) | 4 (5.7) | |
| Separated | 6 (1.6) | 2 (2.9) | |
| Race, n (%) | 0.817 | ||
| White or Caucasian | 335 (93.6) | 68 (97.1) | |
| Black or African American | 18 (5.0) | 2 (2.9) | |
| Unknown/ Other | 4 (1.2) | 0 (0) | |
| Ethnicity, n (%) | 1.000 | ||
| Non-Hispanic | 352 (98.3) | 70 (100) | |
| Hispanic | 1 (0.3) | 0 (0) | |
| Unknown or Blank | 5 (1.4) | 0 (0) | |
| Disease Stage, n (%) | 0.254 | ||
| Stage IA | 237 (66.2) | 55 (78.6) | |
| Stage IB | 57 (15.9) | 8 (11.4) | |
| Stage I (Not further classified) | 38 (10.6) | 5 (7.1) | |
| Stage II | 26 (7.3) | 2 (2.9) | |
| Treatment, n (%) | 0.870 | ||
| Surgery | 279 (77.9) | 59 (84.3) | |
| Surgery + radiotherapy | 55 (15.4) | 8 (11.4) | |
| Surgery + chemoradiation | 10 (2.8) | 1 (1.4) | |
| Surgery + chemotherapy | 9 (2.5) | 1 (1.4) | |
| Hormone therapy | 5 (1.4) | 1 (1.4) |
CROSS-SECTIONAL INVESTIGATION:
Current Knowledge, Self-Efficacy, and Quality of Life
Survivors’ knowledge of the relationship between obesity and endometrial cancer was poor with most responders (46%) unsure of the relationship, some (41%) were unclear of the strength of the relationship, and one reported no existing relationship. When asked to compare their health to that of their peers, two-thirds of respondents rated their health as “somewhat healthy,” with only 6% of respondents feeling “extremely healthy.” The majority (60%) of respondents were “unsure” of the national physical activity guidelines for survivors. After being prompted with the physical activity guidelines, 78% of survivors were “moderately/somewhat/not at all” confident in their ability to achieve the guidelines. When stratifying responses based on BMI, those with class I or II obesity were more likely to be “completely” or “very confident” in their ability to complete moderate level physical activity compared to those with class III obesity (35% versus 10%, respectively; p= 0.021). Median quality of life scores was 136.7 (range, 0–172). Complete quality of life data with subscales can be found in Table 2.
Table 2:
FACT-En total score ranges from 0 to 172. Higher scores represent better quality of life.
| FACT-En (n=70) | Median Score (range) |
|---|---|
| Physical Well-Being: | 24.5 (0–28) |
| Social/Family Well-Being: | 18.5 (0–28) |
| Emotional Well-Being: | 18.5 (0–24) |
| Functional Well-Being: | 18.7 (0–28) |
| QOL Issues Specific to endometrial cancer: | 55.5 (0–64) |
| Total Score: | 136.7 (0–172) |
COVID-19 Impact on Physical Activity, Nutrition, and Mental Health
When comparing pre-COVID to post-COVID health, survivors reported negative impacts, with 47/70 (67.1%) of ECS reporting worsening of some aspect of their life during the pandemic. Specifically, 56% of survivors noted decreased physical activity levels, 33% made poorer nutrition decisions, and 48% experienced worse mental health. BMI category did not impact these results (p>0.05). Prior to the pandemic, 33% of survivors reported meeting physical activity guidelines and this percentage decreased, but not significantly, during the pandemic to 17% (p=0.0501). No significant difference was identified in proportion of survivors meeting guidelines when stratified by BMI category (p> 0.05).
Preferred Exercise Post-Treatment
Post-treatment exercise preferences were collected from 45 survivors; note multiple selections were allowed: walking (n=31), swimming (n=11), structured class at a gym (n=8), structured class at home (n=6), and “other” (responses n≤2) including biking, bowling, golfing, farm work, water aerobics, and weightlifting. Four participants indicated that they did not participate in physical activity following cancer treatment.
Preferred Intervention Components
Survivors preferred information delivered electronically [online (56%) or via email (41%)] versus in person (30%) or via text (21%). Preferences for physical activity location included exercising at home (46%) or online with a coach (33%) versus with a group fitness class (18%) or at the gym (17%). Combining a health promotion program with exercise was appealing to most participants (37%), while others were not interested (27%) or unsure (31%). Responses were similar between patients meeting and not meeting physical activity guidelines (p>0.05). The most preferred lifestyle intervention components included: tracking progress (56%), health recipes (56%), one-on-one counseling (46%), tips for cheap and healthy eating (41%), exercising alone (41%), and online sessions (39%). Table 3 outlines the proportion of respondents that indicated their preference for each aspect of an intervention.
Table 3:
Frequency of responses related to intervention characteristics.
| Health promotion intervention characteristics | Survey response frequency n (%) |
|---|---|
| Frequency of a health promotion class | |
| Would not attend | 33 (47.1%) |
| Monthly | 19 (27.1%) |
| Weekly | 18 (25.7%) |
| 3 times a week | 3 (4.3%) |
| Duration of a health promotion class | |
| Would not attend | 32 (45.7%) |
| 60 minutes | 26 (37.1%) |
| 30 minutes | 18 (25.7%) |
| 90 minutes | 3 (4.3%) |
| Method of information delivery * | |
| Online | 39 (55.7%) |
| Via email | 29 (41.4%) |
| In person | 21 (30.0%) |
| Via DVD/Video | 19 (27.1%) |
| Via text message | 17 (24.3%) |
| Would not participate | 10 (14.3%) |
| Attendance if a health promotion program including exercise during the session | |
| Yes | 26 (37.1%) |
| No | 19 (27.1%) |
| Unsure | 22 (31.4%) |
| No response | 3 (4.3%) |
| Location of physical activity * | |
| At home | 32 (45.7%) |
| With an online coach | 23 (32.9%) |
| Would not attend | 22 (31.4%) |
| In a group fitness class | 13 (18.6%) |
| In a gym | 12 (17.1%) |
| Location of health promotion class * | |
| Online (virtual meeting) | 31 (44.3%) |
| Would not attend | 25 (35.7%) |
| Community room | 19 (27.1%) |
| In a gym | 18 (25.7%) |
| At a hospital | 16 (22.9%) |
| In an office | 13 (18.6%) |
| Other – class in my area which is about 50 miles from the clinic | 1 (1.4%) |
| Necessity of incentives for participation | |
| Disagree/ Strongly Disagree | 37 (52.9%) |
| Neither agree nor disagree | 19 (27.1%) |
| Strongly Agree/ Agree | 11 (15.7%) |
| Program characteristics * | |
| Tracking my progress | 39 (55.7%) |
| Healthy recipes | 39 (55.7%) |
| One-on-one counselling with a health professional | 32 (45.7%) |
| Exercising alone | 29 (41.4%) |
| Tips for cheap, healthy eating | 29 (41.4%) |
| Online sessions | 27 (38.6%) |
| Medication for weight loss | 25 (35.7%) |
| Cooking demonstrations | 25 (35.7%) |
| Opportunities to interact with others in the group | 24 (34.3%) |
| Developing goals | 24 (34.3%) |
| A credible exercise instructor | 23 (32.9%) |
| Exercise diary | 21 (30.0%) |
| Opportunities to discuss barriers to success with a health professional | 20 (28.6%) |
| Assistance with portion control | 19 (27.1%) |
| Food diary | 19 (27.1%) |
| Opportunities to discuss barriers to success with others trying to lose weight | 18 (25.7%) |
| Feedback on my goals | 18 (25.7%) |
| A peer exercise instructor (similar age, same sex) | 16 (22.9%) |
| Grocery store demonstration (e.g., tour for healthy shopping) | 8 (11.4%) |
| In-person sessions | 13 (18.6%) |
| Exercising in a group | 12 (17.1%) |
Note multiple selections could have been made. % is based on selection out of n=70 participants.
PART 2: FOCUS GROUPS AND INDIVIDUAL INTERVIEWS
Seven themes were used for analysis including the five components of the RE-AIM framework and two emergent themes: program component and cancer treatment/survivorship (see Table 4). Additionally, 18 subthemes, 34 categories, and 54 individual codes were identified. The theme with the largest proportion of total meaning units (MU) was program components (185 MU) while cancer treatment/survivorship had the smallest proportion (20 MU). Several of the individual comments had more than one code attached. If a comment had two meanings, it was separated into meaning units that aligned with their respective themes.
Table 4:
Barriers, facilitators, and characteristics of interventions preferred by endometrial cancer survivors based on focus groups and individual interviews (n=16).
| Theme | Subtheme | Category | Code | Example Comment |
|---|---|---|---|---|
| REACH (n=91) “Why would this program not work for you or other survivors?” |
Cost to participants (n=67) | Time and resource cost (n=67) | Time commitment – overall, of each meeting (n=24) | “This would not work for me because I work 2 jobs” |
| Transportation (n=14) | ||||
| Interference with daily activities (n=10) | ||||
| Barrier: potential cost to participants (n=19) | ||||
| Access (n=11) | Rural populations (n=11) | How to make intervention accessible for rural populations (n=11) | ||
| Participant characteristics (n=13) | Age (n=1) | Older patients may be less confident that they can participate in physical activity (n=1) | ||
| Physical conditions (n=10) | Less able-bodied individuals may not want to participate in certain activities (n=10) | |||
| Weight and BMI (n=2) | Obesity as a barrier to participate due to embarrassment about weight (n=2) | |||
| EFFECTIVENESS (n=91) “Why would this program not achieve its desired outcomes?” |
What happens if the intervention doesn’t work? (n=17) | Fear/Concern (n=13) | Concern about failure/weight gain (n=9) | “Unintended negative consequences are feeling bad about yourself because you didn’t follow through and lose the weight” |
| Concern about cancer recurrence (n=4) | ||||
| Expectation of success (n=4) | Comparisons to other participant success – what happens if I am the only one who doesn’t lose weight? (n=4) | |||
| Mental health impact (n=19) | Negative consequence (n=6) | Added stress (n=6) | ||
| Positive impact (n=13) | Emotional support (n=13) | |||
| Empowerment (n=18) | Education (n=12) | Access to knowledge/education (n=12) | ||
| Empowerment (n=6) | Empowerment – to make changes, seek knowledge, embrace failure/fear (n=6) | |||
| Being healthy vs losing weight (n=37) | Scope (n=28) | Scope (weight loss vs feeling healthier), making lifestyle changes (n=28) | ||
| Tangible (n=9) | Tangible results (n=9) | |||
| ADOPTION (n=115) Who do you want delivering this intervention? |
Facilitator (n=85) | Facilitator characteristics (n=51) | Facilitator personality – outgoing, funny (n=14) | “Somebody funny who knows their stuff. I’d go back for the laughs that help me absorb the information” |
| Facilitator expertise/medical knowledge (n=24) | ||||
| Facilitator empathy/compassion (n=13) | ||||
| Facilitator life experiences (n=13) | Facilitatory experience with weight loss (n=7) | |||
| Facilitator experience with endometrial cancer (n=6) | ||||
| Facilitator diversity (n=21) | Speaker/teacher diversity – guest speakers (n=15) | |||
| Facilitator consistency – same facilitator most of the time (n=6) | ||||
| Facilitator-participant dynamics (n=30) | Evaluation (n=18) | Maintain interest/ check ins on group progress/evaluations (n=18) | ||
| Mentor (n=8) | Mentorship – during program and continuing after (n=8) | |||
| Validation (n=4) | Participant validation – of successes, challenges, fears (n=4) | |||
| IMPLEMENTATION (n= 112) “What are the costs or resources needed? How long should this program be?” |
Logistics (n=90) | Session logistics/structure (n=90) | Session length (n=17) | “I think an hour is a good time frame. Thirty minutes of information, thirty minutes of discussion” |
| Session frequency (n=34) | ||||
| Structured activities (n=19) | ||||
| Timing of session – what day/time of day (n=7) | ||||
| Timing after surgery/treatment (n=8) | ||||
| Variety in activities (n=5) | ||||
| Costs to program (n=22) | Financial (n=22) | Equipment/ food/ presenter cost (n=22) | ||
| MAINTENANCE (n=49) “Why would this program not help you or other survivors maintain weight loss?” |
Sustainability/continued intrinsic + extrinsic motivation (n=40) | Sustainability (n=12) | Sustainability/resilience to life events – continue to lose weight/ maintain changes (n=12) | “Because it’s hard to maintain any weight loss over the long term, when the stresses of life come up” |
| Continued contact (n=22) | Newsletters (n=8) | |||
| Follow ups after program completion/accountability (n=14) | ||||
| Motivation (n=6) | Motivation to continue lifestyle changes (n=6) | |||
| What happens if intervention doesn’t work long-term? (n=9) | Expectation of failure (n=9) | Pessimism about weight loss maintenance (n=9) | ||
| PROGRAM COMPONENT (n=185) | Stakeholders’ buy in (n=81) | Novel/newness (n=19) | Different from past interventions/Excitement about program (n=19) | “Again, a weight loss program is not a selling point because most of us have probably done that route before” |
| Personalization (n=17) | Adaption for different bodies/ capabilities/survivorship, ownership over process (n=17) | |||
| Interest (n=16) | Incentives/participant buy in (n=16) | |||
| Engagement (n=29) | Active participation/interaction (n=29) | |||
| Group dynamics (n=66) | Closeness/social (n=66) | Planned “mingling” time (n=3) | ||
| Group connectedness/community building (n=42) | ||||
| Opportunity to share with others who have similar experiences (n=21) | ||||
| Virtual delivery (n=29) | Virtual delivery as a barrier (n=14) | Zoom fatigue/technology issues (n=3) | ||
| In person delivery strongly preferred (n=11) | ||||
| Virtual delivery as a facilitator (n=17) | Virtual delivery preferred – for convenience, because of COVID, etc. (n=17) | |||
| Other delivery options (n=9) | Phone calls as mode of delivery or follow up (n=9) | Phone calls too impersonal (n=9) | ||
| CANCER TREATMENT/SURVIVORSHIP (n=20) | Cancer treatment issues (n=20) | Frustration (n=20) | Frustration with perceived lack of transparency about surgeries/ side effects of treatments (n=8) | “I was only 49 and going through menopause so suddenly was devastating” |
| Frustration with not knowing enough about endometrial cancer diagnosis (n=2) | ||||
| Frustration with lack of follow up after diagnosis (n=4) | ||||
| Not knowing where to find accurate information about cancer or surgery (n=6) |
During the deductive analysis process, there were 92 total disagreements between the two independent coders. Of these, 76 were classified as minor disagreements, which were defined to be different subthemes, categories, or codes but within the same overall theme. The remaining 16 were classified as major disagreements, where the individual comments were not coded within the same theme. All disagreements were resolved between the two coders without need of the predetermined third party.
For this study, data saturation was achieved after the first individual interview, which did not result in any new codes from the focus groups. Two more interviews were conducted, which also reiterated many of the same ideas formed by the focus groups and did not result in new codes. Thus, data saturation was achieved with a total of 16 survivors across the focus groups and individual interviews. Our codebook is included in Table 4.
Discussion
Our ECS with obesity report worsening mental health and are less likely to choose healthy behaviors such as physical activity and healthy eating following the COVID-19 outbreak. Most ECS preferred walking as their primary mode of exercise. However, they lack strong self-efficacy in their ability to complete any activity at a moderate to vigorous level. This provides one explanation for why 83% of ECS are not meeting national physical activity guidelines. To improve inactivity and health, approximately one-third of ECS were willing to attend a health promotion course with an exercise component, while another one-third of ECS were unwilling to commit to attendance. For those who did indicate interest, appealing intervention components included: 1) an intervention with a “health” (not weight loss) focus; 2) remote delivery; 3) social/community support 4) guidance from trained and knowledgeable facilitators and 5) focus on low impact physical activity.
Globally, the COVID-19 pandemic has negatively impacted physical activity and nutrition choices, with greater and more negative impacts seen with increasing BMI (27). Within gynecologic oncology, the literatures notes changes in surgical outcomes and identifies risks and disparities in care of survivors but does not comment on changes in weight-related behaviors and mental health (28). In a group that is already disparate, our ECS have poor quality of life, which is lower than the pre-pandemic quality of life levels, as well as worsening health-related behaviors (29).
To address these disparities, interventions created with the “end in mind” and incorporating end-user feedback are essential (13). Survivor preferences likely vary across cancer types and thus cannot be globally applied. A recent systematic review reported the facilitators of physical activity participation for all cancer survivors (ECS comprising 1% of data). Facilitators included symptom (i.e., fatigue) management tools, health-care providers social support, and perceived health benefits (30). While these facilitators generally align with our findings, the details differ. Our respondents prefer an intervention with a health focus, rather than an emphasis on weight loss. This approach will help them feel better but does not need to be targeted at specific symptoms. Additionally, social support is also crucial, but ECS desire connections with other survivors, not necessarily healthcare providers. Barriers for intervention participation are the time commitment needed, transportation, access for rural communities, and concerns about maintaining new habits after the program has concluded. These barriers parallel those reported by survivors seeking weight loss that include negative self-perceptions and difficulty with follow-through (31). Also relevant to our population of primarily rural, underserved communities, lower income was associated with difficulty accessing available interventions (31, 32). Taken together, the facilitators and barriers to intervention participation provide unique insights into ECS preferences, while also aligning with themes demonstrated in related populations.
Another significant barrier to program success was a general unwillingness to participate in an intervention. Depending on the question, 33–48% of ECS indicated they would not participate in a physical activity intervention. This reluctance could be related to their low self-efficacy for exercise, misunderstanding of what physical activity is (e.g., high impact or strength training, versus walking), or apprehension about the “fit of an intervention” into their life. Additionally, our data support the importance of an intervention focus on health as opposed to weight loss. Thus, projected participation rates in a “weight loss” intervention may be significantly less than if it was framed as a “health promotion/ quality of life enhancing” intervention. Finally, it is possible that survivors would feel more invested in attending a program that they or other ECS helped to create. Future work will focus on delineating reasons for lack of participation.
Our survivors prefer a low-impact or walking focus, which aligns with reports from other ECS (33). Walking is an easily accessible form of physical activity that can be used to improve self-efficacy. For obese survivors, self-efficacy is correlated with exercise intention, which is thought to be the immediate predecessor to a behavior (34). Introduction of other low impact movements, such as yoga, could also be a way to build a foundation for physical activity efficacy, as a step before moderate activity.
When endometrial cancer-specific issues are excluded, ECS quality of life (FACT-G mean= 80.2) is similar to that of the normative data from the non-cancer population (FACT-G mean= 80.1) (35) However, a diagnosis of endometrial cancer impacts many facets of an ECS quality life, which resulted in the addition of 16-items specifically designed for ECS that were added to the general quality of life assessment (FACT-General+ ECS questions= FACT-En). Being mindful and in tune with these unique is one of the reasons ECS value connection with other ECS via a program designed for them.
Strengths of this study are the inclusion of an understudied and disparate group of ECS, many of whom live in rural Appalachia, and with data collection adapted to the COVID-19 pandemic restrictions via use of a virtual format. By intentionally including community-building efforts during this process, relationships were formed and continue to be fostered with our target patient population, leading to continued engagement in ongoing survivorship research projects.
One limitation of our work is our response rate of 20%, which is lower than that of other cross-sectional studies including ECS report response rates of approximately 40% (36, 37). It is possible that our emails did not reach our intended survivors, as verification email accuracy prior to distribution was not possible. Additionally, many of our survivors are not familiar with research, which could have been a barrier to participation. To address these issues moving forward, our office staff are now verifying email addresses at each visit. Additionally, research fliers for investigator- initiated trials are displayed in exam rooms and are discussed with survivors to help normalize research and address barriers to participation. We have also formed a Community Advisory Board including ECS to collect information about barriers and recommendations to increase ECS participation in research.
Although our focus groups were representative of our larger patient population, we were limited in our diversity of patients, primarily older white women. Thus, our findings may not be generalizable to ECS with obesity in other geographical areas or communities. There was difficulty with patient recruitment that required expansion of the pool of potential respondents with in-clinic recruitment and eventually transition from focus groups to in-person interviews. Additionally, many patients who indicated interest when approached in clinic ultimately did not complete the initial survey when it was sent to them electronically. Other factors such as socioeconomic status, degree of rurality, and distance required for cancer treatment could have impacted our findings but were not assessed.
This work provides a foundation for developing behavioral interventions with and for ECS. Future work will build upon the results of this study, following the ORBIT model, with the goal of creating a scalable and sustainable health promotion program created for ECS.
HIGHLIGHTS:
Appealing intervention components include a health focus, remote delivery, social support, and low impact exercise.
Following the COVID-19 outbreak, endometrial cancer survivors’ physical activity, nutrition, and mental health worsened.
Self-efficacy for moderate-vigorous exercise was lower for survivors with class III obesity compared to class I and II.
FUNDING:
Shannon Armbruster is an iTHRIV Scholar. The iTHRIV Scholars Program is supported in part by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Numbers UL1TR003015 and KL2TR003016.
Footnotes
CONFLICT OF INTEREST: Authors report no conflicts of interest.
CRediT author statement: Shannon D. Armbruster: Conceptualization, methodology, data curation, writing- original draft, funding acquisition. Katie Brow: Investigation, data curation, visualization, writing-review & editing. Tonja Locklear: Formal analysis, data curation, visualization, writing-review & editing. Mary Frazier: Writing-review & editing. Samantha Harden: Conceptualization, methodology, resources, writing-review & editing, supervision.
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