Overall, the mean age (range) of the participants was 49.4 (24–74) years (Table 1). Sixty percent of the participants were female, 51.1% lived with a spouse/partner and 46.7% lived in the Midwest region of the US. A good representation of race was achieved across the full sample and clinical subgroups: African American/Black: 31.1%; White, 28.9%; Asian: 22.2%; other races: 17.8%. A majority (71.1%) were non-Hispanic, although some representation of Hispanic participants was obtained across the three clinical subgroups (Group A: 25.0%; Group B: 33.3%; Group C: 30.0%; Table 1). Of the total sample, 60.0% worked outside their home > 4/5 days a week, and the majority (68.9%) worked fixed/consistent hours. Most of the participants (88.9%) were omnivores. At the time of the study, 66.7% did not follow a specific diet plan or program. The average BMI (range) was 32.7 (21.5–55.6) kg/m2 for Group A, 41.2 (30.3–55.2) kg/m2 for Group B and 28.5 (26.5–29.8) kg/m2 for Group C. Participants across all subgroups most frequently reported hypertension and dyslipidemia as weight-related comorbidities (60.0% and 40.0%, respectively; Table 1).

Participant experiences of hunger: Most participants (43/45; 95.6%) reported hunger as a factor influencing their food choices (Fig. 2). Many described their perceptions of physical or emotional experiences of hunger (35/45 each; 77.8%), for which they used terms such as “growling stomach” or “emptiness in the stomach;” others described feeling a physical need to eat, feeling irritable or angry with hunger, i.e., “hangry,” or eating when stressed (Table 2). Five of 21 participants (23.8%) who completed the app-based RTDC task noted that hunger had influenced their meal choice on the task day, opting for convenient/quick options or leftovers when hungry (Table S1). Fifteen of the RTDC app-task participants (71.4%) mentioned that hunger influenced their decisions while grocery shopping, such as buying more food or making less healthy choices when hungry (Table S1).

Participant experience of hunger, cravings and satiety. N number of participants. Note: each concept is stratified by the number of participants who discussed the concept either spontaneously or when probed by the interviewer

Participant experiences of satiety: Most participants (44/45; 97.8%) considered that satiety influenced their food choices and experienced satiety as a physical sensation (Fig. 1, Table 2). Nearly half (21/44; 47.7%) of the participants described satiety as “not being able to eat any more” (Table 2). Of the 29 participants who were asked, 19 (65.5%) described satiety as an emotional experience and mentioned “feeling upset” from being “too full.” Seven out of 12 participants who responded (58.3%) in the RTDC subset mentioned feeling full after eating (Table S1). When asked to rate their hunger on the NRS from 0 to 10 after finishing a meal on the task day, 19 participants (90.5%) rated their hunger as low (between 0 and 3) from having eaten enough food or feeling satisfied or full.

Participant experiences of cravings: Of the 44 participants who were asked about cravings, 43 (97.7%) perceived them to influence their food choices, with nearly two-thirds (28/43; 65.1%) describing cravings as a strong desire for a specific food (Table 2). Sweet foods, salty foods or specific meals or snacks most frequently induced cravings (Table 2), and participants listed not having eaten the food for some time or exposure via media as some of the reasons for their cravings. Two-thirds of the participants in the RTDC subset (14/21; 67.0%) reported having a craving that day, specifically for unhealthy, high carbohydrate or fatty foods, such as chocolate, potato chips and sweets (Table S1).

Participants reported a total of 22 drivers/triggers of food choices in the interviews, both spontaneously and when probed (Fig. 3). Nearly all participants (43/45; 95.6%) considered health to be a key driver for their food choices (Table 3). Participants discussed the influence of medical diagnoses (such as obesity or T2D) on food choices, in addition to other health considerations such as food intolerances or allergies, current age and cholesterol levels. Most participants (42/45; 93.3%) discussed the influence of culture and heritage on food choices; many (34/42; 81.0%) noted that food provided a connection to their culture or occupied a central role in their family lives (Table 3). On the other hand, a few participants (6/42; 14.3%) did not consider food to be important to their identity or culture. Most (41/45; 91.1%) perceived that their location (such as being at a restaurant, work or home) influenced their food choices and mentioned eating less healthy food while visiting other people’s houses or while traveling (Table 3).

Drivers/triggers of food choice. N number of participants. Note: each driver/trigger is stratified by the number of participants who discussed the concept either spontaneously or when probed by the interviewer

Of 45 participants, 40 (88.9%) noted that stress from work, family life or being busy influenced their food choices and the amount of food they ate (Table 3). Stress tended to increase participants’ cravings and the likelihood of eating unhealthy foods that might be fried, sweet, salty or carbohydrate rich while reducing motivation to make healthier food choices. Among the 21 participants in the RTDC subset, 3 (14.3%) reported severe or moderate stress and consequently selected convenient foods or ate larger servings than usual. Mood was perceived to influence food choice, appetite and motivation by 37 participants (82.2%; Table 3). Both negative (feeling depressed, bored or anxious) and positive (being in a good mood) moods led participants to make less healthy food choices. In the app-based RTDC task, one participant noted that feeling relaxed or happy on the task day helped them make healthier food choices, while another opted for comfort food because of stress.

Most of the participants (36/45; 80.0%) perceived that social environment, such as being around family members, friends, partners, co-workers or being alone, influenced their food choices (Table 3). Participants noted that being with health-conscious friends or family members motivated them to eat healthy foods. Many of the participants who were asked (33/43; 76.7%) mentioned that work influenced their food choices; some participants opted for quick and convenient foods when they had limited time to prepare or eat food when working (Table 3). Similarly, the overall convenience or ease of availability of food influenced food choices for 33 participants (73.3%), with some preferring to eat unhealthy food if it was easy or quick to prepare. Of the 43 participants who were asked, 32 participants (76.7%) perceived that engaging in physical activities influenced their food choices; exercise motivated them to eat healthier or made them feel more hungry afterwards (Table 3). Similar findings were highlighted in the app-based RTDC task, with many participants (9/21, 42.9%) noting that physical activity increased their appetite or promoted healthier eating. More than half of the participants (25/45; 56.0%) believed poor quality of sleep influenced their food choices, often leading them to choose quick or convenient foods (Table 3). Nineteen participants (43.2%) perceived that their medication either reduced (e.g., diabetes medication) or increased (e.g., birth control) their appetite (Table 3). Participants reported additional drivers or triggers that influenced their food choices, including holidays and special occasions (19/45, 42.2%), enjoyment (i.e., foods they enjoyed eating [12/45, 26.7%]), seasons (11/45, 24.4%), financial reasons (10/45, 22.2%) and routine (4/45, 8.9%).

Some differences were observed between the clinical subgroups. A total of 14 participants in Group A (70.0%), 7 in Group B (46.7%) and 1 in Group C (10%) considered that their obesity and/or T2D had influenced their food choices, such as eating healthier foods or avoiding foods high in sugar or carbohydrates (Table 3). Furthermore, more participants in Group A (14/20, 70.0%) and Group B (11/15, 73.3%) reported convenience or availability as a driver/trigger of food choice relative to Group C (2/10, 20.0%).

For the total interview sample (N = 45), all eating behavior concepts and most of the drivers/triggers emerged in the first two sets of interviews (13/15; 86.7%), with the majority emerging in the first set of interviews (12/15; 80.0%; Table S2). Furthermore, most concepts and drivers/triggers were reported spontaneously in all four saturation sets (11/15; 73.3%), except medication, culture/heritage, sleep and mood. Medication was reported less frequently than some of the other drivers/triggers and was first reported spontaneously in the third set of interviews by one participant only. Additionally, culture/heritage was probed with a direct question at the start of the interview and therefore did not have any spontaneous counts across the sample. However, probed counts for this driver/trigger appeared in all sets of interviews, suggesting that this experience was fully explored (Table S2). The findings were similar at the clinical subgroup level. The results of this saturation analysis provide confidence that the eating behavior concepts and drivers/triggers of food choices were fully explored, and saturation was achieved within the total sample.

Based on the findings of the concept elicitation interviews, a conceptual model of eating behaviors and related drivers/triggers in obesity and T2D was developed (Fig. 4). The model presents the relationships between core eating behaviors and the drivers/triggers of eating as described by participants. The concept elicitation interviews identified seven core eating behavior concepts reflecting two levels of eating behaviors (Fig. 4). The first level contains underlying concepts which can prompt eating (i.e., appetite, hunger, cravings and satiety) as well as motivation/determination, which participants discussed in relation to making healthier food choices or following a meal plan. The second level relates to direct outcomes of food choices, including dietary intake (i.e., what food was chosen for a meal or snack) and amount of food eaten.

Conceptual model of eating behaviors and related drivers/triggers in obesity and T2D. n number of participants, N total number of participants, T2D type 2 diabetes. Drivers/triggers endorsed by five or more participants are presented in the conceptual model. Each driver/trigger is presented with the proportion of participants (n/N, %) who reported it to influence eating behaviors. Descriptors of a driver/trigger are provided with the number of participants who reported each during the interviews. Superscript numbers indicate participant-reported relationships/associations between drivers/triggers and eating behavior concepts

The 22 drivers/triggers perceived by participants to impact these eating behaviors were organized into health-related, environmental or situational, and emotional categories within the model (Fig. 4). Overall, the drivers/triggers most frequently reported by individuals with T2D and obesity were health considerations, location and stress. Probed discussions around culture/heritage during the interviews also identified this as an important driver/trigger for food choices and the role that food plays in forming a sense of identity.

To supplement and provide additional context to the conceptual model, the number of participants reporting relationships between individual drivers/triggers and specific eating behavior concepts was examined (Table S3). The most prominent driver/trigger and eating behavior associations included those between health conditions and impact on diet composition and quality (n = 26), stress and the amount of food eaten (n = 22) and the impact of stress (n = 21) and social environment (n = 21) on diet composition and quality.