Retention Strategies: Successes and Challenges
Routine weekly SAPPHIRE team meetings provided an outlet for field staff to discuss the successes and challenges of follow-up data collection with study management. With this information, study management could alter staff makeup, protocols, and the allocation of resources toward beneficial methods of follow-up. Key insights from these retention strategies are presented below.
Information Obtained from Locator Forms
Detailed and accurate locator forms were essential for successful completion of follow-up visits. In addition to participant name and birthdate, the most beneficial pieces of information included: primary phone number(s); participant physical description; email address; social media accounts; and phone numbers and addresses of stable contacts. Detailed physical descriptions of participants helped field team members in identifying participants during data collection. Contacting participants through primary phone numbers emerged as a low-cost method of communicating with a large portion of participants. However, the most hard-to-reach participants often cycled through phone numbers or relied on “pay as you go” cellphones that expire without payment.
Email and social media also served as critical no cost resources that improved the likelihood of locating a participant with minimal staff effort. These communication platforms are accessible on a variety of devices and allowed participants to engage with study staff whenever they could access their accounts. Participants with limited phone access, unreliable internet capability, and those with the propensity to change cell phones could and often did contact study staff using social media. Participants frequently visited fast food establishments with free Wi-Fi or hotels and libraries with computers to check their online accounts for messages. One of the greatest benefits of social media and email communication was that conversation histories were retained irrespective of duration since last contact or device used. Participants could see prior messages from study staff regardless of the time since the original contact attempts. This feature also allowed study staff to review prior conversations, setup subsequent interview sessions, and update locator information in REDCap based on past contact. Furthermore, social media photos supported pre-existing physical descriptions recorded on locator forms, which allowed study staff to more easily identify participants during data collection.
One challenge of using social media to locate participants was the occasional difficulty in locating accounts due to duplicate profiles or profiles created using a different name. Additionally, messages sent to study participants occasionally went to spam or junk folders and never reached participants. To minimize these issues, interviewers confirmed the correct account(s) during each study visit and sent a friend request with the participant’s permission. Once friend requests were accepted, messages went to the participant’s direct message folder and notified the participant.
When participants could not be reached directly, stable contacts provided information regarding participant whereabouts and updated phone numbers and addresses. Many participants listed parents, relatives, or romantic partners as stable contacts, some of which proved to be more useful than others. When making outreach calls or home visits, it was not uncommon to learn that the stable contact listed had not seen or communicated with the participant for an extended period of time. While unavoidable, study staff would document the finding in the participant’s REDCap file so that a new stable contact could be obtained during subsequent interactions. Once this issue became apparent, interviewers also encouraged participants to list other women enrolled in the study as stable contacts to create a network of women who were able to convey messages and locate each other for follow-up visits.
The one item on the locator form that was not useful for retention was the list of three locations frequented by participants. In practice, most participants listed the same convenience stores or prominent sex work areas within a recruitment zone. The likelihood of encountering a participant at one of these convenience stores was minimal, and staff were already spending time in these areas during van and tracking shifts.
Scheduling Participants
Study management implemented the use of a participant database in REDCap after the start of 6-month follow-up interviews that allowed all staff to access locator forms, determine participant eligibility, and view previous contact attempts. REDCap also improved communication between field staff and reduced the time spent calling or visiting non-viable contacts. REDCap allowed study staff to remove incorrect participant information efficiently. Having a central participant database also allowed study management to audit participants contact history to ensure all possible methods had been attempted.
Use of a Mobile Van
Branded with the study logo, the study RV was recognizable and quickly became well-known among our target population. CFSW with no viable contact information frequented the van for outreach materials, to inquire about follow-up visits, and to seek refuge from inclement weather. The van provided a safe and private space for staff to speak with participants, update locator information, and complete follow-up interviews. In addition to being recognizable, the study van could accommodate simultaneous interviews, affording staff the capacity to complete up to eight interviews during a typical four-hour data collection shift.
There were also several disadvantages to using the van as a follow-up resource. The van’s large size made it difficult for study staff to drive and park throughout the city when conducting home visits, thus rendering its use for participant tracking negligible. Van shifts also required significant staffing resources. Due to the interview capacity of the van, the unpredictability of the number of interviews per shift, and the need for staff to sometimes canvas areas on foot, three staff members were needed during all van shifts. For many shifts, staff costs were incurred even though no interviews were obtained. Additionally, due to our targeted sampling recruitment strategy, dozens of participants were simultaneously eligible for follow-up visits in varying zones. As a result, van shift times and locations constantly varied each week. The unpredictability of the van shift schedule made it difficult for participants to know when the van would be in their area.
Participant TrackingIndividualized participant tracking was employed to locate the study’s hardest-to-reach participants. The mobility of tracking teams and their focus on a select number of participants proved crucial to maintaining high retention. Tracking staff found participants during non-traditional hours and completed visits at convenient times for participants. Tracking teams frequently encountered potentially eligible women while conducting targeted outreach, who were approached and screened for study participation – enhancing the use of the extensive time spent on tracking. In general, tracking staff covered significantly more area than the study van and drastically increased the likelihood of random participant encounters. These staff members engaged with several peers, family members, and friends which helped establish rapport with the participant’s social network and ultimately, with the participant.
The primary drawback to participant tracking was the reliance on staff’s personal vehicles. In addition to placing an added burden on staff, the vehicles used were usually sedans or small vehicles and not physically designed for data collection. At times, this lack of space made interview administration difficult. Tracking interviews in personal vehicles also required participants to find private locations to collect vaginal swabs since there was no available restroom.
Maryland Judiciary Case Search
Case Search emerged as a retention strategy that complemented the use of locator forms and individualized retention methods such as participant tracking and outreach. Occasionally, addresses listed in the locator form were incorrect from data entry or participant errors (e.g., missing apartment number, incorrect house number). By using publicly-listed case information, study staff were able to verify participant information and update errors in REDCap. At times, additional addresses were listed that study staff could visit to inquire about a participant’s location. Case search was also beneficial as it provided participant incarceration status, pending court cases, and sentence duration. After verifying a participant’s incarceration status, staff avoided wasting resources by not having to conduct home visits or phone calls to reach participants or their stable contacts.
There were several drawbacks to using Case Search. Since participants were not required to provide identification to enroll in SAPPHIRE, staff were limited to searching Case Search with reported names; thus, case information listed under different names or differently spelled names could be missed. To help mitigate this issue, study staff searched using variations of participant’s first and last names and birthdate. Additionally, entry of information into case search was not always entered in real time, resulting in outdated information. Information regarding case status and dispositions are also abbreviated and lack detail, so a participant’s current incarceration status was not always apparent.
Incentives
The $45 USD and $70 USD prepaid VISA debit cards greatly incentivized participants to return for follow-up visits. However, feedback from study participants indicated that cash could not be withdrawn from the prepaid debit cards, reducing the overall value of the incentive. Ultimately, SAPPHIRE study management chose not provide cash incentives due to quality assurance and staff safety.
The use of non-monetary incentives was also extremely beneficial for retention. Participants frequently stopped by the van or approached tracking teams to obtain items, thus increasing the likelihood of random encounters. For participants between visits, this provided the opportunity to distribute items branded with the study logo and phone number; participants used these items to call study staff and inquire about eligibility. Non-monetary incentives also helped with rapport building by providing an additional reason to interact women other than to inquire about eligibility.
While the non-monetary incentives provided during data collection were beneficial to sex workers, our sample was also characterized by high rates of drug use. Although we did distribute naloxone, retention efforts could have been further supported by providing additional harm reduction supplies such as safe injection and smoking materials (e.g., cookers, cotton, sterile water, stems), while also improving participant wellbeing.
Staff Composition & Rapport Building
The cultural competency and diverse makeup of our staff was a tremendous asset to building rapport with our study population. Throughout the study, staff established and maintained relationships with participants through repeated positive encounters. It was common for participants to come to the study van or approach tracking teams and ask for staff members by name. Participants exemplified their comfort with our research team by providing unprompted information about peers that were also enrolled in the study (e.g., participant in treatment, jail, moved away), or giving study contact numbers to friends who had misplaced the information.
The greatest lesson learned regarding staff structure was the reliance on full-time staff versus the larger cadre of part-time staff and students. At the height of data collection, there were five distinct study visits occurring simultaneously, and it became evident that a full-time staff member specifically dedicated to retention was necessary. While casual staff and students served as low-cost data collectors, inconsistent availability and competing priorities restricted their ability to take ownership of participant retention. As a result, a full-time research assistant (RA) was hired to oversee study follow-up. This individual was tasked with assigning specific participants to field tracking teams and operating study phones and social media accounts. When participants became eligible, the full-time RA efficiently scheduled visits, deployed tracking teams, and audited outreach attempts to ensure exhaustion of contact methods before a participant’s eligibility window ended.
It is also possible that SAPPHIRE retention efforts could have benefited from the use of a peer navigator to assist with locating participants. Although a peer navigator was used with the SAPPHIRE study TFSW cohort not reported in this analysis, the use of peer navigators for the CFSW cohort would have required extensive effort and resources that were beyond our scope. Through participant interaction, it became apparent that familiarity among cisgender participants was primarily at the neighborhood level as opposed to citywide. Cisgender SAPPHIRE participants overwhelmingly stayed in the zones which they were recruited. For peer navigators to be beneficial, the study would have needed multiple people familiar with each respective recruitment zone. Additionally, prior to the start of data collection, study management lacked rapport with women in our recruitment zones. Given the vulnerabilities experienced by our population, study management decided against the use of a peer navigator for retention to avoid creating a problematic dynamic in which an individual received financial incentives for locating peers within their network.
Follow-up Rates
[Insert Figure 1. “SAPPHIRE Study Participant Retention Flow” here]
Of the original 250 individuals recruited, 178 (71%) completed the 3-month follow-up visit (Figure 1). Of the 72 participants that were not retained during this interval, study staff exhausted all means of contact for 41 participants. The other 31 participants were unable to be contacted due to circumstances which prevented them from being followed, including being deceased, in jail, moving away, enrolled in in-patient drug treatment, or refusing to participate in follow-up. These individuals were removed from the total denominator given the inability to follow them, resulting in an adjusted retention proportion of 81%.
From the 3-month to 6-month follow-up, one participant who had previously refused to participate decided to re-engage. Twenty-eight participants were unable to be contacted for follow-up, and study staff exhausted all means of follow-up for 57, resulting in an adjusted 6-month retention proportion of 74%. From the 6- to 9-month follow-up, 33 participants were unable to be contacted for follow-up, and staff exhausted all means for 53 participants, resulting in adjusted 9-month retention of 76%. Between the 9-month follow-up and the final survey at 12 months, 33 participants were unable to be contacted, one of whom was removed from the study due to her conduct with study staff resulting in her being unable to complete the 12-month survey (all other data from this individual was included in analysis). Staff exhausted all means of follow-up for 57 participants. The adjusted 12-month retention was 74%.
Table 1. Baseline characteristics of SAPPHIRE participants by number of completed visits, N (%).
|
|
Total
|
Baseline only
|
2 visits
|
3 visits
|
4 visits
|
5 visits
|
χ2
p-value
|
Characteristic
|
n=250
|
n=34
|
n=19
|
n=46
|
n=48
|
n=103
|
Age, mean (SD)
|
35.7 (9.0)
|
33.3 (7.8)
|
31.7 (8.0)
|
37.1 (10.1)
|
32.6 (8.2)
|
37.9 (8.7)
|
<0.001†
|
Race/ethnicity
|
|
|
|
|
|
|
0.133
|
White, non-Hispanic
|
166 (66.4)
|
24 (70.6)
|
13 (68.4)
|
26 (56.5)
|
27 (56.3)
|
76 (73.8)
|
|
Black, non-Hispanic
|
57 (22.8)
|
6 (17.6)
|
4 (21.1)
|
16 (34.8)
|
11 (22.9)
|
20 (19.4)
|
|
Hispanic or other
|
27 (10.8)
|
4 (11.8)
|
2 (10.5)
|
4 (8.7)
|
10 (20.8)
|
7 (6.8)
|
|
Relationship status
|
|
|
|
|
|
|
0.050
|
In a relationship/married
|
84 (33.6)
|
8 (23.5)
|
3 (15.8)
|
17 (37.0)
|
12 (25.0)
|
44 (42.7)
|
|
Single
|
165 (66.0)
|
26 (76.5)
|
15 (78.9)
|
29 (63.0)
|
36 (75.0)
|
59 (57.3)
|
|
≥ 1 financial dependents
|
95 (38.0)
|
10 (29.4)
|
10 (52.6)
|
16 (34.8)
|
24 (50.0)
|
35 (34.0)
|
0.157
|
Children <18 living with them
|
44 (17.6)
|
1 (2.9)
|
2 (10.5)
|
9 (19.6)
|
10 (20.8)
|
22 (21.4)
|
0.127
|
Less than high school/GED
|
131 (52.4)
|
18 (52.9)
|
13 (68.4)
|
20 (43.5)
|
24 (50.0)
|
56 (54.4)
|
0.448
|
Homeless, past 3 months
|
156 (62.4)
|
24 (70.6)
|
17 (89.5)
|
38 (82.6)
|
36 (75.0)
|
41 (39.8)
|
<0.001
|
Food insecurity, past 3 month
|
135 (54.0)
|
17 (50.0)
|
12 (63.2)
|
29 (63.0)
|
29 (60.4)
|
48 (46.6)
|
0.245
|
Arrested, past 12 months
|
116 (46.6)
|
18 (52.9)
|
9 (47.4)
|
25 (54.3)
|
25 (53.2)
|
39 (37.9)
|
0.227
|
Experienced childhood abuse
|
126 (52.5)
|
21 (63.6)
|
9 (50.0)
|
20 (45.5)
|
23 (48.9)
|
53 (54.1)
|
0.575
|
Daily sex work
|
165 (66.0)
|
26 (76.5)
|
11 (57.9)
|
33 (71.7)
|
35 (72.9)
|
60 (58.3)
|
0.154
|
30+ clients in past 3 months
|
111 (44.8)
|
11 (32.4)
|
9 (47.4)
|
21 (45.7)
|
17 (35.4)
|
53 (52.5)
|
0.177
|
Ever find clients indoors
|
120 (48.4)
|
16 (47.1)
|
9 (47.4)
|
21 (46.7)
|
24 (51.1)
|
50 (48.5)
|
0.994
|
Ever find clients online
|
69 (27.8)
|
14 (41.2)
|
7 (36.8)
|
14 (31.1)
|
15 (31.9)
|
19 (18.4)
|
0.063
|
Ever find clients from referrals
|
110 (44.4)
|
11 (32.4)
|
8 (42.1)
|
24 (53.3)
|
14 (29.8)
|
53 (51.5)
|
0.047
|
Time in street-based sex work
|
|
|
|
|
|
|
0.065
|
6+ years
|
129 (51.6)
|
16 (47.1)
|
5 (26.3)
|
21 (45.7)
|
25 (52.1)
|
62 (60.2)
|
|
≤5 years
|
121 (48.4)
|
18 (52.9)
|
14 (73.7)
|
25 (54.3)
|
23 (47.9)
|
41 (39.8)
|
|
Daily non-injection drug use*
|
186 (74.4)
|
28 (82.4)
|
10 (52.6)
|
36 (78.3)
|
35 (72.9)
|
77 (74.8)
|
0.179
|
Daily injection drug use
|
146 (58.4)
|
28 (82.4)
|
11 (57.9)
|
26 (56.5)
|
28 (58.3)
|
53 (51.5)
|
0.038
|
†F-test *excluding marijuana use
|
|
|
|
|
|
|
|
Of the original 250 CFSW recruited, 41.2% completed all time points, 19.2% completed four time points, 18.4% completed three, 7.6% completed two, and 13.6% only completed baseline (Table 1). In comparing the number of visits (1-5) completed, women significantly differed in age at enrollment, relationship status, homelessness in the past 3-months, finding clients via referrals, and daily injection drug use. Women who only completed baseline were more likely to inject drugs daily at baseline as compared to women who completed more than one visit, and women who completed all 5 study visits were significantly less likely to experience homelessness in the past 3-months at baseline. There were no differences in racial/ethnicity composition, educational attainment, arrest, childhood abuse, daily engagement in sex work, number of clients, or time in street-based sex work.