Integrated collaborative care intervention for depression and obesity in primary care: translation from research to practice

Abstract

The objective of this study was to present lessons learned about engagement, delivery modality and pandemic impact while delivering a collaborative care intervention with a socioeconomically, racially and ethnically diverse sample. Participants completed a post-intervention survey (n = 41) on experiences and preferred intervention delivery modality, coronavirus 2019 (COVID-19) Impact Survey (n = 50) and provided open-ended feedback about the intervention (n = 27). Intervention process data included attendance, modality, and withdrawals. Data were analyzed using descriptive statistics and inductive content analyses. Of 71 intervention participants, 6 (8%) withdrew before session 1. Completers adhered to intervention timeline better than withdrawals. Participants liked the in-person interaction, efficient coach support, accountability of in-person and Zoom vs. phone sessions and the flexibility and convenience of phone and Zoom vs. in-person sessions. A majority of participants reported experiencing pandemic impacts such as heightened emotional distress, decreased activity engagement, poorer eating behaviors and being unable to meet basic needs. Participants deviating from intervention timelines may be re-engaged by targeted outreach attempts. Videoconference has the potential for providing as-needed coaching. Future interventions may be optimized to account for and address areas impacted by the pandemic. Findings revealed specific strategies that can be implemented in future interventions to improve emotional and physical health among diverse populations.

Introduction

Depression affected 20.6% of US adults at some point in their lifetime [1], while obesity prevalence was 42% [2] before the coronavirus 2019 (COVID-19) pandemic. These conditions are often comorbid, are complex to treat and have worsened during the COVID-19 pandemic due to unprecedented, persistent disruptions in all aspects of life. In fact, several national studies have reported poorer mental well-being, elevated levels of stress, higher physical health complaints and weight gain as a result of COVID-19 [3–8].

The need for efficacious behavioral interventions that can improve both emotional well-being and weight is paramount and has become even more pronounced during the pandemic, particularly among Black, Indigineous and other People of Color and people living in poverty who have been disproportionately impacted. However, few interventions have been shown to be effective at simultaneously improving mental health and weight outcomes, posing a significant challenge for practitioners and researchers in attempting to translate interventions to practice.

The Integrated Coaching for Better Mood and Weight (I-CARE) intervention is the first of its kind integrated collaborative care intervention for comorbid depression and obesity [9]. The I-CARE intervention integrated problem-solving therapy (PST) plus as-needed antidepressant medication for depression care management with behavioral weight loss treatment, which promoted calorie-reduced healthy eating and increased moderate-intensity physical activity. The effectiveness of this intervention was demonstrated in a rigorous randomized clinical trial (RCT) with 409 primary care patients with depression and obesity [10]. The I-CARE intervention was subsequently updated (I-CARE2) to include motivational interviewing (MI) strategies to enhance intervention adherence. The I-CARE2 intervention was evaluated in a pilot RCT with an independent, socioeconomically and racially/ethnically diverse patient sample [11]. The main goal of this pilot RCT, which was completed during the COVID-19 pandemic, was to examine neurobiological mechanisms underlying the I-CARE2 intervention. The results showed robust intervention effects on improved depression and anxiety symptoms, despite coinciding with the COVID-19 pandemic, which has been found to exacerbate mental distress; however, the pandemic may have contributed to a diluted intervention effect for weight loss [12]. The objectives of this study are focused on trial participants randomized to the I-CARE2 intervention group to present the process evaluation data and participant feedback on the intervention delivery in a diverse sample, including changes due to the COVID-19 pandemic. Closely examining intervention delivery can provide lessons and key insights to researchers and practitioners and help inform future implementation of similar interventions in real settings.

Methods

The full protocol for the pilot RCT was previously published [11]. The protocol was approved by the institutional review board of the University of Illinois at Chicago, and all participants provided written informed consent. Below we describe the methodologic information pertinent to this study.

Study participants

Participants were recruited from the University of Illinois Hospital & Health Sciences System (UI Health) Internal Medicine Outpatient Care Clinics in Chicago between March 2019 and March 2020. Eligible adults met inclusion criteria, including body mass index (BMI) ≥ 30 kg/m² (≥27 if Asian) and clinically significant depressive symptomology (score ≥ 10) assessed via Patient Health Questionnaire-9 (PHQ-9) [13], and no exclusion criteria, such as serious medical or psychiatric comorbidities. A total of 106 participants were randomly assigned in a 2:1 ratio to the I-CARE2 intervention (n = 71) or the usual care control group (n = 35). This study included only participants in the intervention group.

I-CARE2 intervention

As in the I-CARE intervention, I-CARE2 combines PST involving the seven-step problem-solving and behavioral activation strategies as first-line, plus antidepressant medications as needed for depression [14, 15] and the Group Lifestyle Balance (GLB) program [16] for weight loss. In PST, the coach guided patients to identify a problem, set a goal, brainstorm solutions, choose a solution and develop, implement and evaluate an action plan. The intervention was composed of 9 total, hour-long one-on-one in-person sessions with a health coach certified in GLB and PST. There were 6 one-on-one in-person PST sessions in the first 2 months and 3 additional PST sessions and 11 home-viewed GLB videos over the next 4 months. Participants were asked to self-monitor their weight and diet and synchronize their activity tracker data via the Fitbit application throughout the intervention. Participant engagement and progress were tracked throughout the intervention and reviewed at sessions 4 and 7, respectively. I-CARE2 included the following updates: (i) the health coach prescribed self-monitoring of weight and wearing Fitbit activity tracker starting with session 1, (ii) the health coach conducted focused problem-solving or MI-enhanced sessions with participants displaying poor engagement (at session 4) and/or progress (at session 7) in order to attempt to re-engage them with the intervention (Appendix A), (iii) the health coach sent motivation-reinforcing messages to participants (by email) between sessions 4 and 9 and (iv) for participants whom the study psychiatrist recommended use of medication, the preferred antidepressant choice was escitalopram (instead of fluoxetine). Participants were expected to self-monitor their weight, diet and physical activity and synchronize their steps on the Fitbit platform and were provided with weight scales and Fitbit activity trackers for doing so.

The intervention began in May 2019. Due to COVID-19, all in-person sessions with the health coach were suspended on 16 March 2020 until the last participant complette the intervention in September 2020. The intervention format changed to phone or videoconference (i.e. Zoom) based on participants’ preference, which had been used as an alternative to in-person for make-up sessions prior to the COVID-19 lockdown.

Study measures

Mixed methods [17] integrating quantitative and qualitative approaches were used to obtain a complete understanding of the intervention delivery. This was achieved through the use of quantitative data from close-ended survey questions and the intervention delivery process and qualitative data from the open-ended survey question. Specifically, quantitative data included intervention delivery process data, answers to Likert-scale questions on the post-intervention survey and yes/no questions on the COVID-19 Impact Survey. Process data included participants’ session attendance, date, modality (in person, phone and Zoom) and withdrawal over the 6-month intervention. The post-intervention survey included 5-point Likert scales on how much each modality was liked/disliked and multiple-choice questions on what participants liked about each intervention delivery modality. The post-intervention survey was sent to 65 of 71 intervention participants who completed at least one I-CARE2 session and was self-administered online by 41 participants (Fig. 1). The COVID-19 Impact Survey was adapted from the Epidemic–Pandemic Impacts Inventory (EPII) [18, 19] and sent to intervention participants (excluding one participant who withdrew) on 7 May 2020 for self-completion. Participants who had not completed the survey (by June) were contacted by research staff (until the end of August) and offered the survey by phone. We used 54 items from the EPII to assess pandemic-related impacts on work and employment (6 items), education and training (1 item), home life (7 items), social activities (7 items), economic (4 items), emotional health and well-being (6 items), physical health problems (6 items), physical distancing and quarantine combined with infection history (5 items) and positive changes (12 items). Participants indicated if each item was true in their life (yes/no). Qualitative data included open-ended (free-text) feedback provided at the end of the post-intervention survey, where participants had an option to include any final comments regarding their intervention participation.

Fig. 1.

Flow diagram.

Statistical analyses

Quantitative data on the intervention delivery process and post-intervention and COVID-19 Impact Survey responses were summarized with descriptive statistics (means and standard deviations [SDs] or counts and percentages) using SAS software (version 9.2; SAS Institute Inc.). The number of days between session 1 and subsequent sessions was summarized for completers and withdrawals separately. Qualitative feedback was analyzed using inductive content analysis [20] to synthesize the open-ended responses. A researcher (N.L.) developed an initial set of codes, which two other researchers (S.D. and R.S.) tested on a small subset of the responses and compared their coding results to reach consensus on a final list of codes and their definitions and higher-order categorical groups of codes. Using this final list of codes, S.D. and R.S. independently coded all open-ended feedback. Finally, using the coded data, the researchers identified themes and analyzed them for independence, coherence and consistency [21, 22]. The quantitative and qualitative findings were then integrated [23] to answer our research questions about I-CARE2 engagement, delivery modality and pandemic impact. The authors thank Rohit Shresta for his assistance with coding participant feedback for this study.

Results

Intervention participants

The 71 intervention participants were primarily middle aged (mean 46.7 [SD 11.7] years), female (77%) and African American (58%) and had at least some college education (90%) and an annual family income <$55 000 (54%) (Table I). They had moderately severe obesity (BMI, mean 37.0 [SD 6.0]) and moderate depression (PHQ-9, 12.9 [2.9]; Depression Symptom Checklist 20-item, 1.2 [0.7]) (Table I). Post-evaluation survey responders (n = 41) had significantly higher education than non-responders (n = 30); they did not differ significantly in other baseline characteristics.

Table I.

Baseline characteristics by post-evaluation survey completion group

Characteristic	All intervention (n = 71)	Post-evaluation survey responders (n = 41)	Post-evaluation survey non-respondersa (n = 30)	P value
Age, years, mean ± SD	46.7 ± 11.7	46.9 ± 12.5	46.6 ± 10.7	0.93
Female, n (%)	55 (77.5)	31 (75.6)	24 (80.0)	0.66
Race/ethnicity, n (%)				0.28
Non-Hispanic White	13 (18.3)	5 (12.2)	8 (26.7)
African American	41 (57.8)	23 (56.1)	18 (60.0)
Asian/Pacific Islander	2 (2.8)	1 (2.4)	1 (3.3)
Hispanic	10 (14.1)	8 (19.5)	2 (6.7)
Other (e.g. decline to state and multirace)	5 (7.0)	4 (9.8)	1 (3.3)
Education, n (%)				0.02
High school/GED or less	7 (9.9)	1 (2.4)	6 (20.0)
College—1 year to 3 years	31 (43.7)	17 (41.5)	14 (46.7)
College—4 years or more	19 (26.8)	11 (26.8)	8 (26.7)
Post-college	14 (19.7)	12 (29.3)	2 (6.7)
Income, n (%)				0.89
<$35 000	22 (31.0)	14 (34.2)	8 (26.7)
$35 000 to <$55 000	16 (22.5)	9 (22.0)	7 (23.3)
$55 000 to <$75 000	12 (16.9)	6 (14.6)	6 (20.0)
≥$75 000	21 (29.6)	12 (29.3)	9 (30.0)
BMI, kg/m2, mean ± SD	37.0 ± 6.0	36.7 ± 6.0	37.6 ± 5.9	0.53
Weight, kg, mean ± SD	101.9 ± 15.4	100.6 ± 15.5	103.8 ± 15.3	0.38
Waist circumference, cm, mean ± SD	111.9 ± 11.7	111.9 ± 11.7	111.8 ± 12.1	0.98
PHQ-9 score, mean ± SD	12.9 ± 2.9	12.6 ± 2.9	13.2 ± 3.1	0.38
SCL-20 score, mean ± SD	1.2 ± 0.7	1.1 ± 0.6	1.4 ± 0.8	0.10
GAD-7 score, mean ± SD	7.0 ± 5.0	6.1 ± 4.0	8.2 ± 6.0	0.12
Current use of ADM, n (%)	12 (16.9)	7 (17.1)	5 (16.7)	0.96

Abbreviations: ADM, antidepressant medication; GAD-7, 7-item Generalized Anxiety Disorder Scale; GED, general educational development; SCL-20, Depression Symptom Checklist-20.

^aIncludes participants who were ineligible to receive the post-intervention survey because they did not complete session 1 (n = 6) and those who were eligible but did not complete the surveys (n = 24).

Intervention engagement

Of all intervention participants (n = 71), 36 (51%) completed all 9 sessions and 47 (66%) completed at least 6 sessions (minimal effective ‘dose’ based on prior PST trials in primary care) [24]. Of all intervention participants, the cumulative withdrawals were 6 (8%) before session 1, 15 (21%) before session 4, 29 (41%) before session 7 and 35 (49%) before session 9. Of the participants who completed at least 1 session (n = 65), the mean (SD) number of sessions completed was 6.9 (2.6) with a median of 9 and an interquartile range of 4.

Figure 2 shows the number of days between session 1 and subsequent sessions (i.e. sessions 2–9) among completers and withdrawals. Overall, completers had fewer days between session 1 and subsequent sessions compared to withdrawals. Completers attended their sessions in a shorter time period than withdrawals; this difference became larger as the intervention proceeded. For example, the mean (SD) number of days since session 1 was 10 (10) among completers and 16 (24) among withdrawals for session 2, 24 (17) and 33 (21) for session 3, 38 (32) and 56 (42) for session 4 and 113 (46) and 160 (77) for session 7.

Fig. 2.

Distribution of number of days between session 1 and subsequent sessions among completers and withdrawals.

Note: The I-CARE2 intervention was comprised of nine one-on-one sessions. The recommended frequency was weekly for the first 4 sessions (sessions 1–4), biweekly for the next 2 ( sessions 5 and 6) biweekly and monthly for the last 3 (sessions 7–9). This figure shows the distribution of number of days between session 1 and subsequent sessions among participants who completed the intervention (‘Completers’ in blue) and those who withdrew (‘Withdrawals’ in red) separately. The n denotes the number of completers and withdrawals who completed each subsequent session (sessions 2–9). All withdrawals withdrew by session 7; therefore, no withdrawal completed sessions 8 and 9. Minimum and maximum are depicted by the bottom and top of the whiskers. The box signifies the lower to upper quartiles (Q1–Q3). The median is represented by a line within the box. The means are represented by О for completers and + for withdrawals.

Despite the differences in intervention engagement between completers and withdrawals, open-ended feedback (Table II) showed that participants would have preferred weekly contacts throughout the intervention. One participant said, ‘When I first started, the sessions were frequent (once a week), and I would prefer they continue at this frequency. I lost focus in the program when there were fewer visits with the coach.’ Another stated, ‘For people with weight loss goals, weekly support is needed, and connection to other support groups. Intervention will continue by meeting and surrounding myself with people of the same interest.’ Instead of weekly contacts, additional support via other resources (e.g. apps) might be helpful as well. One participant suggested, ‘I was seeing results, but then complications from COVID-19 caused weight to be regained. I think an additional app for emotional/mental record would assist in that aspect of the intervention with correlation with data from Fitbit. I also think material from Yale’s “The Science of Happiness”course could be implemented, including their companion app “ReWi” or something like it. These are just ideas on potential expansions for the program’.

Table II.

Selected qualitative feedback themes and quotes

Theme	Quote
Session Scheduling & Attendance	‘It was good - they were able to work around my schedule’.
	‘When I first started the sessions were frequent (once a week), and I would prefer they continue at this frequency’.
	‘The coaching and support system in place was well done. However, for people with weight loss goals, weekly support is needed’.
Intervention Delivery Modality	‘The commute to the office was not worth all the effort for something that could have happened over the phone or electronically. Like commuting there and trying to park in the UIC hospital garage and getting out of the garage to leave was longer than the time I spent with the coach’.
	‘Coming up with different ways of doing it would be helpful - obviously you have to come in person for some things, but in the future, it would be really nice to have the option of doing phone or Zoom, especially for people that can’t make it due to scheduling or transportation issues’.
	‘It was important to have the in-person sessions to establish the relationship with the coach, and that made the Zoom sessions a lot more productive because we had walked through the forms and the goals and we knew what we were doing. We had created the personal relationship in those first sessions and that made the Zoom sessions a lot more fruitful’.
	‘Would have really liked in-person sessions - Zoom was much better than phone because it felt like more of a personal connection. Harder to communicate toward the end, especially over the phone. It would have been helpful to talk to someone face-to-face to really understand what to do’.
COVID-19 Pandemic Impact	‘We had a good rhythm going, but it was just the disruption and everything due to COVID, so it was really out of everyone’s hands’.
	‘It was very difficult for me to complete (the intervention) due to the pandemic having other responsibilities with family and losing my job…’
	‘Because of the pandemic, I think the program should have paused until we can have the face-to-face interaction again’.
	‘I was seeing results, but then complications from COVID-19 caused weight to be regained’.
	‘COVID made it difficult to meet and be motivated to lose weight’.

Intervention delivery modality

As a result of intervention delivery shifting from in-person to phone and/or Zoom video conferencing on 16 March 2021, participants experienced various intervention delivery modalities. Of the 41 participants who completed the post-intervention survey, the majority used in-person only (11, 26.8%), phone only (5, 12.2%) or in-person and phone (20, 48.8%). Only five (12.2%) used Zoom and in-person and/or phone. In-person sessions remained the most preferred format (4.8/5), followed by Zoom (4.4/5) and phone (4.1/5) sessions (Table III). Of the participants who used phone sessions (n = 28) and Zoom sessions (n = 5), 100% liked the convenience, 85–100% liked the flexibility and 60–64% liked the user-friendly features of the telephone or Zoom software, compared to 41%, 63% and 34%, respectively, for in-person sessions. Participants comparatively liked in-person interaction, efficient coach support and in-person accountability for in-person sessions and Zoom, while phone sessions were less liked in these features.

Table III.

Post-evaluation survey results on session delivery formats (n = 41)

		What did you like about the session formats you used? (Check all that apply)
Session delivery formata	How much was the format liked? (1 = not at all to 5 = very much)	Convenience	In-person interaction	Flexibility	Ease of communication	Visual presentation of intervention content	No technology needed	Efficient coach support	No commute needed	In-person accountability	User friendly
In-Person (n = 32)	4.8	41%	100%	63%	78%	38%	38%	72%	3%	59%	34%
Phone (n = 28)	4.1	100%	11%	86%	68%	0%	14%	50%	64%	14%	64%
Zoom (n = 5)	4.4	100%	80%	100%	80%	40%	0%	80%	80%	60%	60%

^a20 (48.8%) used in-person and phone, 11 (26.8%) used in-person only, 5 (12.2%) used phone only, 1 (2.4%) used Zoom only, 1 (2.4%) used in-person and Zoom, 1 (2.4%) used phone and Zoom and 2 (4.9%) used in-person, phone and Zoom.

Open-ended feedback (Table II) supported preference for in-person interaction and accountability provided through in-person and Zoom sessions. One participant stated, ‘It was important to have the in-person sessions to establish the relationship with the coach, and that made the Zoom sessions a lot more productive because we had walked through the forms and the goals and we knew what we were doing. We had created the personal relationship in those first sessions and that made the Zoom sessions a lot more fruitful.’ Another participant similarly mentioned, ‘Would have really liked in-person sessions - Zoom was much better than phone because it felt like more of a personal connection. Harder to communicate toward the end, especially over the phone. It would have been helpful to talk to someone face-to-face to really understand what to do.’

Open-ended feedback also supported preferences for convenience and flexibility of phone and Zoom sessions. One participant stated, ‘The commute to the office was not worth all the effort for something that could have happened over the phone or electronically.’ Another also suggested, ‘Coming up with different ways of doing it would be helpful - obviously you have to come in person for some things, but in the future, it would be really nice to have the option of doing phone or Zoom, especially for people that can’t make it due to scheduling or transportation issues.’

Impact of COVID-19 pandemic

The COVID-19 pandemic impacted participants in general, as well as more specifically, relating to lifestyle factors addressed during the intervention (e.g. activity involvement, healthy eating, mental health and physical activity) (Table IV). Of those completing the COVID-19 Impact Survey (n = 50), 70% reported being physically/socially separated from family and close friends (including lack of ability/resources to talk while separated) and 80% said they were unable to do enjoyable activities/hobbies. Economic impacts were also prevalent, with 44% stating they were unable to meet basic needs (e.g. acquiring food/healthy food, medications and paying important bills like rent or utilities). Emotional health was negatively affected as well with 62% reporting an increase in mental health problems, use of alcohol/other substances or being unable to access mental health treatment. Lastly, 94% of respondents reported worse health behaviors, including less physical activity or exercise, overeating or eating more unhealthy foods, and spending more time sitting down, sedentary and more screen time. Interestingly, participants also reported several positive changes brought on by the pandemic such as more quality time and/or improved relationships with family/friends (62%), improved health behaviors/paying more attention to physical health (64%) and spending more time doing enjoyable activities (56%).

Table IV.

COVID Impact Survey results among intervention participants (n = 50)

	Intervention participants (n = 50)
Work and employment	YES	%
Lost work, including reduced work hours, furloughed, laid off from job or had to close own business.	14	28
Had to continue to work even though in close contact with people who might be infected (e.g. customers, patients and coworkers).	12	24
Changes in workload, work responsibilities or work location.	9	18
Hard time doing job well because of needing to take care of people in the home.	12	24
Home life
Changes in childcare responsibility, including childcare or babysitting unavailable, difficulty taking care of children in the home and take over teaching or instructing a child at home.	16	32
Had to move or relocate.	3	6
Increased verbal and/or physical conflict in the home.	12	24
Social activities
Physically and/or socially separated from family or close friends, including lack of ability or resources to talk while separated.	35	70
Family celebrations canceled or restricted.	44	88
Planned travel or vacations canceled.	41	82
Religious or spiritual activities canceled or restricted.	41	82
Unable to be with a close family member in critical condition.	17	34
Unable to do enjoyable activities or hobbies.	40	80
Economic
Unable to meet basic needs: food/healthy food, important bills like rent or utilities and medications.	22	44
Difficulty getting places due to less access to public transportation or concerns about safety.	20	40
Emotional health and well-being
Increase in mental health problems, use of alcohol or substances or unable to access mental health treatment.	31	62
Increase in sleep problems or poor sleep quality.	24	48
The coronavirus disease pandemic outbreak has impacted my psychological/mental health negatively.	24	48
Physical health problems
Increase in illness or health problems not related to the coronavirus disease pandemic.	20	40
Worse health behaviors: less physical activity or exercise, overeating or eating more unhealthy foods and more time sitting down or sedentary/screen time.	47	94
Got less medical care than usual, including routine or preventive care appointments and cancellation of medical procedures.	37	74
Physical distancing and quarantine
Isolated or quarantined from others due to possible symptoms or exposure to coronavirus (including living away from family due to high-risk job).	12	24
I have had coronavirus-like symptoms or been diagnosed with the coronavirus.	8	16
Positive change
More quality time and/or improved relationships with family or friends.	31	62
New connections made with supportive people, including volunteering time/resources to a cause related to this disease.	19	38
Improved health behaviors/paid more attention to personal health: more physical activity or exercise, ate healthier foods, less use of alcohol or substances and spent less time on screens or devices/sedentary.	32	64
More time doing enjoyable activities (reading books, puzzles, developing new hobbies and more time in nature or being outdoors).	28	56
More efficient or productive in work, employment or school.	17	34

Open-ended feedback (Table II) showed that intervention engagement and progress were affected by the COVID-19 pandemic, with one stating: ‘It was very difficult for me to complete (the intervention) due to the pandemic having other responsibilities with family and losing my job…’ One participant mentioned, ‘I was seeing results, but then complications from COVID-19 caused weight to be regained.’ Another participant similarly said, ‘COVID made it difficult to meet and be motivated to lose weight.’

Discussion

Summary of results

This study demonstrates that intervention engagement differed between completers and withdrawals, with completers having fewer days between session 1 and subsequent sessions than withdrawals. Furthermore, due to the intervention being underway at the time COVID-19 restrictions took effect, session delivery quickly pivoted from in-person to phone or Zoom videoconferencing. Participant feedback around intervention delivery modality revealed that participants liked the in-person interaction, efficient coach support and in-person accountability of in-person and Zoom sessions, while phone and Zoom sessions were liked better than in-person sessions due to their flexibility and convenience. Finally, the timing of the intervention delivery coinciding with COVID-19 presented a unique opportunity to learn more about how the pandemic may have affected participants’ intervention engagement and progress. It became evident that participants were affected in a number of ways, including heightened emotional distress; having lower levels of social, physical and pleasant activity engagement relative to their pre-pandemic lifestyles; engaging in poorer health behaviors such as inactivity/being sedentary; overeating; making less healthy food choices and being unable to meet basic needs such as acquiring food/healthy food or paying for shelter and utilities.

Practice implications

Lessons learned about intervention engagement

Differences were observed between participants who completed the intervention and those who did not. Participants with longer periods between sessions early on in the intervention were ultimately more likely to withdraw from the study, underscoring the importance of keeping participants on schedule from the beginning for persistent engagement over time. This may be accomplished by discussing participant challenges, concerns and ambivalence about the recommended schedule and continued participation, revisiting initial motivation to participate in the intervention along with the intervention’s personal relevance to participants, helping troubleshoot challenges to continued participation and reinforcing the importance of following intervention timelines. This is consistent with previous studies that have found a relationship between intervention session absenteeism and attrition [25]. Participants deviating from intervention timelines may be displaying early signs of disengagement and may benefit from targeted outreach attempts aimed at intervention re-engagement and motivational enhancement. For example, I-CARE2 was an enhanced version of the I-CARE intervention, and one of the enhancements implemented in I-CARE2 included adapting sessions 4 and 7 to incorporate MI techniques focusing on adherence (for session 4) or progress (for session 7) indicators. Currently, adherence indicators that trigger an MI-focused session 4 include attendance (e.g. missing any sessions) and no self-weighing and/or Fitbit use (in three of four sessions), while progress indicators that trigger an MI-focused session 7 include PHQ-9 ≤5 or ≤50% decrease since visit 1, <3% weight loss or weight gain, <5000 steps per day or <100 min of physical activity per week (Appendix A). In I-CARE2, all participants who attended the first seven sessions (60% of whom received an MI-enhanced session) went on to complete the intervention, perhaps highlighting the importance of the MI-enhanced sessions along the way. In future work, in addition to session attendance, prolonged periods between intervention sessions may be added as an additional indicator of poor adherence, as it is an early sign of disengagement.

Lessons learned about intervention delivery modality

Our findings build on existing reports describing the impact of the COVID-19 pandemic on remote intervention delivery. Transitioning behavioral interventions to phone or Zoom-based delivery was a common solution to enable ongoing trials to continue at the onset of COVID-19 [26]. In fact, a cross-sectional survey study with 250 health-related research participants found that most participants (76%) in behavioral intervention studies reported that the study in which they were enrolled had transitioned to remote delivery because of the pandemic [27]. Despite changing the modality of intervention delivery in this study, the I-CARE2 intervention was completed at a similar rate to that of the I-CARE intervention, which was completed in November 2017, and sessions were delivered in person except for discretionary use of phone or Zoom for make-up session [10].

Furthermore, the shift to utilizing phone and Zoom provided insights into preferences, acceptability and feasibility of engaging diverse populations in telehealth. The present study identified that participants valued both the convenience and flexibility of remote sessions and the camaraderie of in-person and Zoom sessions, suggesting the utility of videoconferencing technology as an alternative to improve access and provide benefits (e.g. accountability and interaction) of in-person sessions. This is consistent with previous studies showing that acceptability for videoconferencing interventions is generally high in health care of different chronic diseases including mental health care [28]. To build on this evidence, clinical staff may develop hybrid intervention models (e.g. in-person orientation followed by Zoom intervention sessions) that will increase flexibility in scheduling and efficiency in intervention delivery and decrease the use of physical space and the cost of intervention delivery. However, despite acceptance and potential benefits of telehealth in delivering health services, the future of ongoing reimbursement for telehealth delivered programs remains uncertain [29–33]. This study did not collect information about why most participants chose phone over Zoom sessions during the transition. The small sample size also precludes analysis of whether preference for modality differs based on race/ethnicity. Future studies may investigate particular barriers (e.g. technology literacy and access) to using videoconferencing technology, especially among populations with lower socioeconomic status, as well as examine whether intervention delivery modality preferences differ by race/ethnicity. If technology is a barrier, in-person orientation in a hybrid intervention model may efficiently tackle these barriers by providing technology access (e.g. Wi-Fi hotspots) and training if needed. This may be especially important among older adults and socioeconomically underserved populations. This is promising given that telehealth interventions are able to extend the reach beyond only those who can come into the clinic for in-person interventions. It is especially advantageous during and after the COVID-19 pandemic as effective and feasible interventions that provide as-needed remote coaching are in urgent need.

Lessons learned about impact of COVID-19 pandemic on lifestyle behavioral interventions

Additionally, participants in multiple behavioral intervention studies have reported that the COVID-19 pandemic created barriers to adhering to behavioral health recommendations within intervention trials [27]. Specifically, shutdowns associated with the pandemic impacted access to facilities and public spaces, modified and eliminated routines, canceled activities and caused increased fear, anxiety and stress that negatively impacted the ability to adhere to lifestyle recommendations [34–36]. In I-CARE2, participants reported similar lifestyle impacts associated with the pandemic that may have negatively impacted their adherence to the integrated collaborative care intervention. It is important to note that participants responded to the COVID-19 Impact Survey once, at the end of the study between May and August 2020, and were not assessed repeatedly and regularly during the pandemic. As social and personal contexts continue to evolve, along with changes in the control of the pandemic, different factors and barriers may affect the delivery of, and engagement in, behavioral interventions. Moving forward, in interventions, participants can be assessed (before and during the intervention) for the presence of real-time barriers that may impact their intervention participation. Health coaches may then follow up with participants experiencing significant barriers, engage them via MI techniques and guide them through problem-solving some of their encountered barriers. Intervention adaptations may also be warranted at this time, such as revisiting and resetting goals in light of the participant’s experiences. In addition, the areas impacted by the pandemic may be the potential areas for optimizing future interventions during the pandemic recovery phase, as restrictions lessen and become eliminated. For example, participants (including those diagnosed with COVID-19) can be assessed for sustained impacts of the pandemic (e.g. sustained emotional distress, worsened activity and poorer eating behaviors) before future interventions, so health coaches may particularly target these negative lifestyle consequences.

Limitations

The study has several potential limitations. First, the sample size was small (n = 71), limiting generalizability of the results. Second, there was a modest response rate on post-intervention survey (n = 41 [63% of those eligible to receive survey]). It is possible that participants who responded to the survey were more committed to or engaged with the intervention, limiting feedback from non-engaged participants. The health coach attempted to mitigate this potential confounder by encouraging all intervention participants to complete the survey and by conducting extensive outreach aimed at reminding participants to complete the survey. Furthermore, few participants had utilized Zoom during the pandemic, and participants were not explicitly asked why they chose the delivery modality they did (e.g. phone vs. Zoom). Therefore, additional information cannot be extracted around the preference for use of the telephone over Zoom (e.g. availability of device and no Internet access).

Conclusion

In summary, this study provides lessons learned about engagement in, and delivery of, an integrated collaborative care intervention for comorbid depression and obesity in a diverse patient population. The results indicate that longer time between sessions is associated with higher intervention attrition rates, serving as an early warning sign of disengagement. Furthermore, as in-person sessions were replaced by phone or Zoom (due to COVID-19 restrictions), participants indicated acceptability of these remote session delivery modalities and cited benefiting from their flexibility and convenience. Lastly, participants also discussed challenges and barriers brought on by COVID-19 (e.g. heightened emotional distress, lower levels of activity engagement and poorer eating behaviors), which may have affected their intervention participation and engagement. These results extended our published findings from the pilot RCT, suggesting that, compared with usual care, the I-CARE2 intervention improved depression and anxiety symptoms but had a minimum effect on weight loss, during the COVID-19 pandemic [12]. These results can guide the future development of effective and accessible interventions for patients with comorbid depression and obesity, which is a gap in the literature as noted in the recent systematic review [37]. As next steps, the lessons learned from this study should inform future research and practice aimed at optimizing interventions in similarly diverse and highly impacted patient populations.

Appendix A

Appendix A.

I-CARE2 intervention outline ^a

Week	Session	Time	Content
1	1	60 min	Introduction to I-CARE2 Mood and I-CARE2 Lifestyleb sequenced integration (5 min) Technology: Fitbitc—using, syncing and sending friend request to coach. Encouragement to wear/sync Fitbit and check uploads (10 min) Physical activity safety guidelines handout (GLB session 4, pages 3 and 4) Evaluation of bathroom scale ownership and provision of scale to participants requiring a scale Encourage participant to begin self-weighing and wearing Fitbit right away I-CARE2 Mood Session 1 (45 min)
2	2	60 min	I-CARE2 Mood Session 2 (60 min)
3	3	60 min	I-CARE2 Mood Session 3 (60 min)
4	4	60 min	I-CARE2 Mood Session 4 (50 min) Technology: Fitbit—explanation of logging physical activity minutes and weight, introduction to logging diet and importance of self-monitoring (10 min) Tailor session based on adherence behaviors (0 adherence issues, proceed with regular PST session; 1 adherence issue, proceed with PST session but focus on adherence issue as the problem for the session; 2 or more adherence issues, follow a different script for session, based on MI techniques, to re-engage participant)
6	5	60 min	I-CARE2 Mood Session 5 (45 min) I-CARE2 Lifestyle introduction and self-study guidelines (5 min) Technology: Fitbit—review of logging physical activity and weight, explanation of logging diet and importance of self-monitoring (10 min)
8c	6	60 min	I-CARE2 Lifestyle Progress Check (5 min) I-CARE2 Mood Session 6 (30 min) Technology: Fitbit check in (5 min) Goals confirmation: weight, physical activity and steps (5 min) Optional tools to reduce calorie intake: meal plans and packaged meals (5 min) I-CARE2 Lifestyle Session (GLB Sessions #1 and 2) (10 min)
12	7	60 min	I-CARE2 Lifestyle Progress Check (10 min) I-CARE2 Mood Session 7 (35 min) I-CARE2 Lifestyle Session (GLB Sessions #3, 4, 5 and 6) (15 min) Tailor session based on goal attainment (meeting all interim goals, proceed with regular PST session; not meeting 1 or more interim goals, follow a different script for session, based on MI techniques, to re-engage participant)
16	8	60 min	I-CARE2 Lifestyle Progress Check (10 min) I-CARE2 Mood Session 8 (35 min) I-CARE2 Lifestyle Session (GLB Sessions #8, 9 and 10) (15 min)
20	9	60 min	I-CARE2 Lifestyle Progress Check (10 min) I-CARE2 Mood Session 9 (35 min) I-CARE2 Lifestyle Session (GLB Sessions #1112) (10 min)

^aIntervention participants also receive: group-based orientation with MI informed strategies before baseline visit; between-session messaging (begins after Session 4); escitalopram as first-line antidepressant choice (if medication is recommended).

^bI-CARE2 Mood = PEARLS program.

I-CARE2 Lifestyle = GLB program.

^cParticipants receive Fitbit instructions via email prior to the first session.

Decision Tree for Session 4 Type

Decision Tree for Session 7 Type

Funding

National Institutes of Health Science of Behavior Change Common Fund Program through an award administered by the National Heart, Lung, and Blood Institute (grant numbers UH2HL132368 and UH3HL132368).

Conflict of interest statement

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute or the National Institutes of Health. No sponsor or funding source has a role in the design or conduct of the study; collection, management, analysis or interpretation of the data or preparation, review or approval of the manuscript.