Category: 3. Business

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By Joseph Adinolfi

The largest companies have seen their weighting in the S&P 500 rise more quickly than their share of total earnings

One stock-market bull says recent developments are making her more concerned that an AI-driven bubble might be forming in the U.S. stock market.

Lori Calvasina, head of U.S. equity strategy at RBC Capital Markets, has repeatedly rebutted claims that the U.S. equity market has entered an AI-driven bubble. But in a report recently shared with MarketWatch, she included one chart that is making her a bit more nervous.

The chart in question, shown below, compares the weighting of the 10 most valuable stocks in the S&P 500 index SPX with the companies’ share of total net income. As Calvasina points out, the weighting of these stocks in the index recently touched a new peak north of 44% – the highest level going back to at least 1990, according to the data used by RBC. Yet the share of total profit of all index members that is being produced by these firms hasn’t quite kept up.

“While we’ve generally not agreed with the view that the stock market is in the midst of an AI bubble, similar to the TIMT bubble, due to a better earnings foundation, we do think this risk has grown,” Calvasina said in the report. TIMT in this context refers to Technology, Internet, Media and Telecommunications. The acronym is frequently used in reference to the stock-market bubble that crested in early 2000.

Among the 10 largest companies in the S&P 500, the AI theme is heavily represented. Names like Nvidia Corp. (NVDA), Meta Platforms Inc. (META), Broadcom Inc. (AVGO), Microsoft Corp. (MSFT), Amazon.com Inc. (AMZN), Alphabet Inc. – which is counted twice by RBC due to its dual share classes, Class A (GOOGL) and Class C (GOOG) – Apple Inc. (AAPL) and Tesla Inc. (TSLA). The only company in the group that doesn’t have direct and significant exposure to the AI theme is Berkshire Hathaway (BRK.B).

See: The ‘Magnificent Seven’ have never been this important to the stock market – and a big test lies ahead

To be sure, this isn’t exactly a new trend. The biggest companies in the S&P 500 have been seeing their overall weighting in the index climb more quickly than their share of earnings since at least 2021, Calvasina said.

This is largely because investors have been willing to pay a premium on the expectation of stronger long-term earnings growth, especially since the launch of ChatGPT kicked off the AI investment frenzy in late 2022.

However, over the past few months, the pace at which this gap has been widening has intensified. As of the end of October, the 10 largest companies in the S&P 500 accounted for 34.3% of total net income for all of the companies included in the index, according to the latest available data. That pushed the gap between the weighting of these companies in the S&P 500 and their share of profits to 9.9 percentage points. That isn’t far off from the 10.3 percentage-point gap seen in March 2000.

Worries about an AI bubble have resurfaced as many of the biggest players in the space – the so-called “hyperscalers” – have reported earnings over the past couple of weeks. Although some on Wall Street have been warning about frothy valuations practically since the trend first found its legs during the first half of 2023.

Meta shares dived last week, erasing more than $200 billion in value. Two Wall Street analysts downgraded the stock after panning the company’s plans for more aggressive AI-related spending, MarketWatch reported at the time. The stock was down again Monday, further trimming its yearly gain to about 8.9%.

Gains for other members of the big AI-plays, most notably Amazon, helped to compensate as U.S. stocks finished higher for a third straight week on Friday.

News on Monday that Amazon had inked a deal with OpenAI to provide cloud-computing power to the privately held AI company has helped to keep the stock-market rally going as November trading got under way, one portfolio manager told MarketWatch.

U.S. stocks mostly climbed on Monday, with the S&P 500 and Nasdaq Composite COMP finishing higher. Meanwhile, the Dow Jones Industrial Average DJIA and the small-cap Russell 2000 RUT ended modestly lower.

-Joseph Adinolfi

This content was created by MarketWatch, which is operated by Dow Jones & Co. MarketWatch is published independently from Dow Jones Newswires and The Wall Street Journal.

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Introduction

Research funding in digital health interventions (DHIs) has increased over the last 2 decades, given their potential for widespread health promotion and disease prevention [-]. With expanded access to mobile phones and the internet, even among low-income populations, DHIs can broaden the reach of prevention and treatment programs and overcome barriers presented by traditional, in-person interventions []. While traditional face-to-face interventions have been used for HIV prevention, the advent of DHIs as a platform for promoting health behavior change opens new avenues for developing effective strategies to combat HIV transmission. Incorporating DHIs into existing HIV prevention services is promising, yet few DHIs for HIV prevention have been implemented at scale beyond research studies, and little is known about scaling up their effectiveness in real-world settings [,]. Scaling up their effectiveness in real-world settings requires an assessment of how to recruit and retain participants.

For nearly 40 years, community-based organizations (CBOs) have been funded by the Centers for Disease Control and Prevention (CDC) to deliver HIV prevention interventions in affected communities primarily through face-to-face individual and small group interventions. Given the years of experience of CBOs, combined with their accessibility to the community, knowledge of the community, and credibility in the community, they are well-positioned to implement HIV DHIs. However, how CBOs implement HIV DHIs remains underdocumented. The primary barriers to successful implementation include limited organizational resources and a lack of adaptation guides [,]. Among the most significant challenges faced by CBOs in scaling HIV DHIs are recruitment and retention []. Numerous barriers prevent individuals from participating in HIV DHIs, including time constraints, technological challenges, and dissatisfaction with the perceived impersonal nature of technology [,].

To address these challenges, implementation science has increasingly called for enhanced dissemination strategies to improve recruitment and retention in HIV DHIs [,]. These strategies include diversifying how DHIs are marketed to consumers and incorporating co-design approaches to involve consumers in promoting DHIs []. Efforts to document and scale enrollment strategies have also intensified. These strategies include using text message reminders, encouraging consumers to create online accounts on platforms, or offering personalized assistance from health professionals or administrators []. While these dissemination and engagement methods require further evaluation, particularly within CBOs, financial incentives have consistently been a cornerstone strategy across studies and CBOs to facilitate recruitment, retention, and response rates [-]. Research in both HIV and other disciplines has demonstrated the effectiveness of financial incentives in improving these outcomes []. However, less is understood about how CBOs manage financial incentives. This includes how decisions are made to cap or increase financial incentives and how they are paired with other forms of incentives. Further research is needed to document these practices to better support the scale-up of HIV DHIs in real-world settings.

Pragmatic trials, such as the Keep It Up! (KIU!) trial, are intended to test the effectiveness of an intervention and its implementation under typical, real-world conditions. Pragmatic trials “emphasize a balance between internal and external validity” []. In other words, such trials emphasize a balance between the scientific rigor, generalizability, and implementation of an intervention in a way that reflects the real circumstances in which it would otherwise be implemented outside a trial (eg, staff or organizational capacity to make adaptations when needed []). As such, the results are more readily and realistically applicable to addressing health and health care issues as well as providing implementers with recommendations for future policy and practice [-]. This paper describes the various approaches CBOs used to recruit and retain KIU! participants and describes the lessons learned to inform future implementations of DHIs in CBO settings.

Methods

Study Data

The data for this study were obtained from a type III hybrid effectiveness-implementation trial [], KIU!, which compared 2 delivery approaches: direct-to-consumer and CBO-based implementation. The study protocol has been discussed elsewhere []. This manuscript focuses on the CBO-based implementation approach to recruitment and retention.

Intervention: KIU!

KIU! is a CDC-designated best-evidence HIV risk reduction DHI. Previous iterations of KIU! have been discussed elsewhere [-]. KIU! was designed with and for young cisgender men who have sex with men (YMSM) aged 18‐29 years, who recently tested HIV-negative. KIU! supports risk reduction and promotes protection practices to maintain a negative HIV status. KIU! includes 3 modules focused on different prevention and risk negotiation content informed by the information-motivation-behavioral (IMB) skills model of HIV risk behavior change [-]. These modules are followed by 2 “booster” sessions 3 and 6 weeks after completion of the main intervention sessions. Booster sessions include additional encouragement of regular HIV testing, condom use, and pre-exposure prophylaxis (PrEP) uptake, and information on negotiating condom use with long-term partners.

As the effectiveness of KIU! has been previously demonstrated on behavioral outcomes (eg, condom use and casual anal sex) and biomedical outcomes (eg, sexually transmitted infection [STI] incidence [,]), the main aim of KIU! 3.0 was to (1) compare the 2 implementation delivery strategies, (2) examine the effect of strategies and determinants on variability in implementation outcomes using a mixed-methods research approach, and (3) explore the sustainment of KIU! at the completion of the study. This study (KIU! 3.0) was implemented in 22 CBOs located in counties with high HIV rates and large populations of YMSM.

Participants

Twenty-two CBOs were selected through a request for proposal process similar to that used by HIV-prevention funders. Thirteen CBOs launched implementation in the fall of 2019, 7 in the summer of 2020, and 2 in the fall of 2020. KIU! 3.0 staff provided virtual training to CBOs on the intervention, provided capacity building support on how best to integrate it into routine HIV testing, and made monthly technical assistance calls. As part of the training, CBO staff completed the KIU! intervention to best describe it to clients during recruitment. CBO staff also received information about project logistics (ie, an online administrative dashboard to track recruitment and retention and manage project reporting via REDCap) and had time to ask any questions related to implementation within their organizations. While all CBOs recruited participants for the same intervention, how participants were recruited and retained varied across CBOs, as no set recruitment or retention plan was provided to them. CBOs were able to decide how to spend their implementation funding, how many staff members to include in the implementation, and whether to provide incentives to YMSM participants.

Data Collection

This paper provides a comprehensive discussion and outline of the diverse range of activities that CBOs undertook while implementing KIU!. Furthermore, the manuscript details insights and lessons learned to enhance future implementation. Data for this paper were collected in several ways from CBOs: applications in response to a request for proposals, monthly standing calls, interviews, and the KIU! 3.0 application dashboard (). Data collection and analyses are reported in line with the Standards for Reporting Qualitative Research (SRQR; ) []. While this manuscript uses quantitative data, the entire analysis is qualitative (ie, categorical) and descriptive.

Request for Proposals and Monthly Standing Calls

Data were extracted from responses to the request for proposals submitted between March and September 2019 and meeting notes from standing monthly calls between December 2020 and April 2022, with a range of staff involved in implementation from each CBO. Notes from standing monthly calls were collected by a research assistant using a note template capturing recruitment and retention successes, challenges, and plans for improvement. The data extracted from the request for proposals and monthly meeting notes were entered into an Excel spreadsheet (Microsoft Corp) and separated according to recruitment-related activities (eg, offering KIU! during HIV testing) and retention-related activities (eg, frequency of communication with participants). To validate the data extracted from the request for proposals and monthly meeting notes, member checking was performed with CBO staff in the middle of implementation.

Interviews

KIU! research staff trained in qualitative methods (including AZ and ER) aimed to conduct semistructured, in-depth interviews with 2 staff from each CBO who were designated by the CBO as implementers of KIU! in the middle of implementation. A total of 36 staff members were involved in the implementation of KIU! across the 22 CBOs (range=1‐3 per CBO). CBOs were each asked to select 2 staff members to participate in the interviews. Interviews in the middle of implementation were conducted between March 2021 and February 2022. Only 1 staff member participated in interviews from 9 CBOs, and 5 CBOs did not participate, resulting in a total of 25 interviews (response rate=56.8%). In the 5 CBOs that did not participate, the implementation staff did not consent to an interview. CBOs with only 1 staff member participating had a second staff member who did not consent to participate. Implementer roles varied across CBOs, with some staff holding managerial positions, others holding HIV testing positions, and others holding communications positions.

Interviews were based on the Consolidated Framework for Implementation Research (CFIR) []. Interviews occurred over Zoom (Zoom Communications), a videoconferencing software, and lasted an average of 1 hour and 15 minutes (range: 54 minutes to 2 hours). The interviews were recorded and automatically transcribed by Zoom. Research staff and senior investigators edited transcriptions to ensure consistency with the audio recordings, deidentified transcripts, and uploaded transcripts to MaxQDA (VERBI Software) for qualitative coding. Two of the authors with expertise in qualitative research conducted a descriptive thematic analysis of CBO staff responses using a constant comparison method []. For this study, we focused on staff responses to the question, “Based on your experiences delivering KIU!, if you could do things differently to improve any aspects of the implementation, what would they be?” This analysis focused only on responses related to probes regarding recruitment and retention. These data have been used to highlight CBO recommendations for future implementations of KIU! and other DHIs.

Administrative Dashboard

The KIU! application dashboard was developed to allow CBO staff to register participants, track their progress through the KIU! intervention, record and track participant contacts, and export usage data related to the participants. The KIU! dashboard also provided CBO staff with task lists to allow the easy identification of participants who needed additional reminders to complete the KIU! content. The KIU! study team tracked the number of logins into the dashboard per CBO during KIU! implementation (January 2020-April 2022) to assess the extent to which CBOs used the dashboard to monitor participant retention and intervention completion.

Analysis

Client volume was divided (ie, annual HIV testing volume) roughly into thirds. CBOs having an annual HIV testing volume of YMSM between 20 and 139 were categorized as low volume. Those with a YMSM HIV testing volume of 140‐339 were categorized as medium volume, and those with a YMSM HIV testing volume of 340 or more were categorized as high volume. Regarding years of HIV service provision, we divided CBOs into 3 categories based on decades of experience. Those with 3‐9 years of experience were categorized as low (n=3), those with 10‐19 years of experience as medium (n=5), and those with 20 or more years of experience as high (n=14). CBO characteristics were compared by client volume and years of HIV service provision.

The analysis plan was not prespecified as the study was not intended to include a statistical analysis detailing whether one recruitment and retention approach was superior or more effective than another. Instead, the aim was to document these various approaches and detail the lessons learned, as CBO recruitment and retention for DHIs are relatively new concepts. This manuscript thus provides a contextual description of CBO approaches to reach YMSM for an HIV-prevention DHI, as a means to disseminate this information for future CBOs implementing KIU! or other DHIs. A report involving complete statistical analysis of the effectiveness and implementation of KIU! is currently under review [], and the research team has recently published a latent class analysis examining the differences in implementation outcomes across classes of substance abuse [].

Positionality

The research study team included 1 research study assistant, 2 investigators with master’s-level experience, and 4 investigators with doctoral-level experience. One investigator had over 10 years of experience working in a local health department (NB), and 2 were experts in qualitative research methods (AZ and JPZ). The research study team predominantly included white individuals and women.

Ethical Considerations

The study protocol was approved by the institutional review board (IRB) at Northwestern University (IRB reference number: STU00207476) []. YMSM and CBO staff participants were informed of the aims of the study as well as data protection. All participants provided consent to participate in our trial. No compensation was provided to CBO staff for participating in interviews. Identifiable information about participating organizations has been removed.

Results

CBO Characteristics

The 22 participating CBOs were located within the South, West, Midwest, and Northeast regions of the United States, with 1 outside the continental United States. All CBOs provided HIV testing services and either directly offered or referred individuals to PrEP services. Among the YMSM who accessed HIV and STI services from these CBOs between 2016 and 2019, 43.0% (3336/7759) were white, 22.0% (1707/7759) Black, 10.0% (776/7759) Asian, 9.0% (698/7759) multiracial, and 8.0% (620/7759) American Indian/Alaskan Native. Moreover, 68.0% (5276/7759) of clients were non-Hispanic/Latino, and 32.0% (2483/7759) were Hispanic/Latino. CBOs tested an average of 352.68 YMSM in 2018 (median 241; range 20‐1025).

Of the 22 CBOs, 13 (59%) had prior experience implementing evidence-based interventions (EBIs) such as VOICES/VOCES [], CLEAR [], and MPowerment []. Moreover, 14 (64%) CBOs had served YMSM for more than 20 years, 5 (23%) had served YMSM for 11‐20 years, and 3 (14%) had served YMSM for 10 or fewer years. While not required to do so, all CBOs offered some form of incentive to participants (eg, cash incentives or free HIV/STI testing). Incentive timing varied by CBO, with 16 (73%) offering incentives at baseline, 18 (82%) offering incentives after all 3 main episodes, and 20 (91%) offering incentives after booster episodes (). CBOs, on average, provided a greater proportion of the total intervention incentive after boosters (48.3% of total incentives offered to participants; US $35.91 out of US $72.27), compared with 15.3% (US $11.36 out of US $72.27) at baseline and 33.6% (US $25.00 out of US $72.27) after completion of main episodes. Two CBOs provided incentives for participant referrals. Over half of CBOs (13/22, 59%) had their project managers directly involved in the implementation of KIU!. Project managers were mid- and high-level leaders, including deputy directors, program directors, and project coordinators.

Client Volume

Medium-volume CBOs had slightly more staff involved in KIU! delivery than high- and low-volume CBOs (2.29 vs 2.13 and 1.43, respectively) (). Medium-volume CBOs also reported higher rates of project manager involvement in KIU! than high- and low-volume CBOs (5/7, 71% vs 4/8, 50% and 4/7, 57%, respectively). Low-volume CBOs had never been directly funded by the CDC for HIV prevention, while nearly 40% of medium- and high-volume CBOs had been funded (3/7, 43% and 3/8, 38%, respectively). Medium- and high-volume CBOs also had more experience implementing CDC-designated EBIs (5/7, 71% and 7/8, 88%, respectively).

Years of HIV Service Provision

CBOs with more years of experience providing HIV services tested more YMSM for HIV on average per year, with high-experience CBOs testing an average of 402.2 YMSM per year for HIV compared to 338.4 YMSM in medium-experience CBOs and 145.3 YMSM in low-experience CBOs. High-experience CBOs also had slightly more staff involved in KIU! delivery than medium- and low-experience CBOs (2.21 vs 1.40 and 1.67, respectively). High- and low-experience CBOs’ project managers were more frequently engaged in KIU! (9/14, 64% and 2/3, 67%, respectively) than medium-experience CBOs (2/5, 40%). Medium-experience CBOs less frequently reported funding from the CDC for HIV prevention than high- and low-experience CBOs (1/5, 20% vs 4/14, 29% and 1/3, 33%, respectively). Finally, high- and medium-experience CBOs more frequently reported prior experience implementing CDC-designated EBIs (9/14, 64% and 3/5, 60%, respectively) than low-experience CBOs (1/3, 33%).

Prior Experience Implementing CDC-Designated EBIs

CBOs with prior experience implementing CDC-designated EBIs reported, on average, a higher number of YMSM receiving HIV tests per year (490.5 YMSM) than CBOs without prior experience (153.7 YMSM). CBOs with prior experience implementing EBIs reported a slightly higher average of staff involved in KIU! than CBOs without prior experience (2 and 1.8, respectively). However, CBOs with prior experience implementing EBIs reported more often than those without prior experience that project managers were directly involved in implementation (8/13, 62% and 4/9, 44%, respectively).

Recruitment Activities

To recruit for KIU!, CBOs used four recruitment methods: (1) online recruitment (eg, on their website or on social media); (2) recruitment on hook-up and dating apps (eg, Grindr, Scruff, and Jack’d); (3) recruitment through participant referrals; and (4) recruitment through outreach and community partnerships. The most frequent mode of recruitment was through outreach and community partnerships (21/22, 95%), and the least frequent recruitment occurred via hook-up apps and participant referrals (6/22, 27% and 5/22, 23%, respectively; ). Nearly 70% (15/22, 68%) of CBOs additionally created their own promotional materials to recruit participants in addition to materials provided by the research team. We compared the frequency of engagement in these activities by client volume of the CBOs, years of HIV service provision, and prior experience implementing CDC-designated EBIs (). We discuss these differences in approaches to recruitment below.

Client Volume

Regardless of client volume, nearly all CBOs (21/22, 95%) used outreach and community partnerships to recruit participants for KIU! (). Low-volume CBOs used online recruitment slightly more frequently than medium- and high-volume CBOs (4/7, 57% vs 3/7, 43% and 2/8, 25%, respectively). Medium-volume CBOs most frequently used hook-up apps as a medium of recruitment (5/7, 71%), with no high-volume CBOs using hook-up apps for recruitment. Fewer than a third of the CBOs in each category of client volume used participant referrals for recruitment, with only 1 medium-volume CBO doing so. High- and low-volume CBOs more frequently developed their own promotional recruitment materials (6/8, 75% and 5/7, 71%, respectively) than medium-volume CBOs (4/7, 57%).

Years of HIV Service Provision

Across years providing HIV services, nearly all CBOs used outreach and community partnerships to recruit participants for KIU! (). Low- and medium-experience CBOs providing HIV services more frequently used online recruitment (eg, social media and websites; 2/3, 67% and 4/5, 80%, respectively) than high-experience CBOs (3/14, 21%). Medium-experience CBOs reported using hook-up apps for recruitment more frequently than high- and low-experience CBOs (3/5, 60% vs 3/14, 21% and 0/3, 0%, respectively). Few CBOs (5/22, 23%) used participant referrals as a method of recruitment, with no low-experience CBOs doing so.

Prior Experience Implementing CDC-Designated EBIs

CBOs with prior experience more frequently reported using online recruitment than CBOs without prior experience (8/13, 62% vs 3/9, 33%). However, slightly more CBOs without prior experience than those with prior experience reported recruiting through outreach and community partnerships (7/9, 78% vs 9/13, 69%). CBOs without prior experience implementing EBIs more frequently reported developing their own promotional recruitment materials than CBOs with prior experience (7/9, 78% vs 9/13, 69%). Regardless of prior experience, only 14% (3/22) to 32% (7/22) of CBOs recruited through participant referrals or hook-up apps.

Retention Activities

To retain participants, CBOs used four communication methods: (1) phone calls; (2) text messages; (3) emails; and (4) social media. Communication methods were primarily used to send reminders to participants to complete KIU! modules. Communication frequency varied across CBOs from no set schedule to infrequent (ie, monthly or less) and frequent (ie, weekly or biweekly). Phone calls and text messages (14/22, 64% for both) were the most common methods of communication, while social media was less common (2/22, 9%). Moreover, 36% (8/22) of CBOs chose to offer in-house accommodation to complete KIU! modules (eg, space and technology). In addition to CBOs’ individual approaches to retention, they were also able to use an online dashboard developed by our research team to track participant completion of KIU! modules. On average, all CBOs logged into the KIU! dashboard 10.5 times per month. We have compared modes of retention and dashboard utilization by client volume, years of HIV service provision, and prior experience implementing CDC-designated EBIs (). We discuss these differences in approaches to retention below.

Client Volume

Low-volume CBOs used phone calls more frequently than high- and medium-volume CBOs (6/7, 86% vs 5/8, 63% and 4/7, 57%, respectively). Low-volume CBOs also used emails more frequently than high- and medium-volume CBOs (6/7, 86% vs 4/8, 50% and 3/7, 43%, respectively), while high- and medium-volume CBOs used text messages more frequently (6/8, 75% and 5/7, 71%, respectively) than low-volume CBOs (4/7, 57%). One medium-volume and 1 low-volume CBO used social media, while no high-volume CBOs did.

Furthermore, 27% (6/22) of all CBOs, regardless of client volume, had no reminder schedule. Medium-volume CBOs most frequently had an infrequent reminder schedule (4/7, 57%), while high- and low-volume CBOs most frequently had a frequent reminder schedule (4/8, 50% and 3/7, 43%, respectively). High-volume CBOs most frequently offered accommodation to participants (5/8, 63%), while only 1 low-volume CBO did so. Low-volume CBOs logged into the KIU! dashboard, on average, more frequently than high- and medium-volume CBOs (13.0 vs 11.1 and 7.4 times, respectively).

Years of HIV Service Provision

All medium-experience CBOs used phone calls, text messages, and emails to contact participants. Low-experience CBOs used emails the least frequently (1/3, 33%), but were the only CBOs to use social media (2/3, 67%). A third (1/3, 33%) of low-experience CBOs had either no reminder schedule or an infrequent or frequent one. Medium-experience CBOs most frequently had an infrequent schedule (3/5, 60%), while high-experience CBOs most frequently had a frequent reminder schedule (7/14, 50%). Only 1 low-experience CBO offered accommodation to participants, while 43% (6/14) of high-experience CBOs and 40% (2/5) of medium-experience CBOs did. Finally, low-experience CBOs logged into the KIU! dashboard, on average, slightly more times than medium- and high-experience CBOs (12.0 vs 11.4 and 9.9 times, respectively).

Prior Experience Implementing CDC-Designated EBIs

There was little difference in the number of CBOs with and without prior experience implementing EBIs that reported communicating reminders via phone calls (7/13, 54% and 5/9, 56%, respectively) and emails (5/13, 38% and 3/9, 33%, respectively). CBOs with prior experience more often reported using text messages (7/13, 54%) and social media (3/9, 33%) than those without prior experience. CBOs without prior experience more often reported a frequent reminder schedule (4/9, 44% vs 3/13, 23%) and no reminder schedule (4/9, 44% vs 2/13, 15%). CBOs with prior experience implementing EBIs more often reported an infrequent reminder schedule (6/13, 46% vs 1/9, 11%). Moreover, CBOs with prior experience more often reported providing accommodation to complete KIU! (3/13, 23% vs 1/9, 11%). CBOs without prior experience logged into the KIU! dashboard, on average, more times per month than CBOs with prior experience (14.3 vs 7.2 times).

Lessons Learned

We previously described differences in recruitment and retention activities by CBO client volume, years of HIV service provision, and direct project manager involvement in implementation. In recruiting and retaining participants, CBOs highlighted numerous lessons learned regarding what they felt helped with recruitment and retention and what hampered recruitment and retention. We now describe these lessons learned. In , lessons learned are compared by years of HIV service provision and project manager involvement. No discernible differences in lessons learned by client volume were found, and thus, these categorizations are not included within the table.

Recruitment

In interviews, CBOs highlighted the need to change how they pitched KIU! to their clients. CBOs described the need to point out the benefits of the intervention to participants and their communities rather than simply describing what KIU! is. Additionally, CBOs noted the importance of reaffirming that clients were not being offered KIU! because staff perceived them to be lacking in efforts to prevent HIV and framing the KIU! pitch to reinforce what clients were already doing to protect their health (eg, HIV testing). Further, using personalized, recipient-centered language rather than technical jargon and including the pitch within a larger discussion of holistic health prevention seemed to increase client registration. The timing of the pitch also mattered, with 1 CBO noting that it was difficult to recruit clients to participate when the offer came before HIV test results were delivered. In such cases, clients were too focused on whether their HIV tests would be reactive for the offer to be effective. One CBO also tried to pitch KIU! outside the testing room while clients waited for their test. However, this did not prove effective. A staff member explained:

We initially had me kind of sitting out in the lobby with a table and talking to the clients as they were leaving their appointments—that wasn’t very well received by clients, because the lobby was a public area. People could overhear them about their LGBT status, and [clients worried about] if there’s going to be a negative response, so we were able to work with our provider to figure out a flow to integrate me into the actual clinic room.

Two other CBOs had not originally planned to incorporate recruitment into their testing and PrEP programming, but during the implementation, they began to incorporate it and identified this as a source of increased recruitment.

CBOs also made changes to their intake forms to boost recruitment. These changes included ensuring that KIU! was listed on forms to be offered to participants, as well as ensuring that intake forms identified whether clients were eligible to participate. Once intake forms were completed, 1 CBO had a staff member review the form and place a sticker on the form to let counseling staff know whether the client was eligible for recruitment:

We have tablets here, [but] it wasn’t giving us, it wouldn’t give us their age. So that’s one of the main reasons why we started putting stickers on their intake forms, because, yeah, you will see the birthday, but I feel like it was almost like bypassed for some reason. [Now], it was already pre-filled, already calculated for you.

Staffing was also of concern to CBO staff in terms of the capacity to recruit. Staff turnover resulted in 3 CBOs having to retrain and reorient new individuals to implementing KIU! and also resulted in a limited number of staff (often 1) focused on recruitment amidst other ongoing work. One interviewee explained:

We had like a pause because on recruitment because the previous person that had my title, he left like in June [or] July, so there was like six months that there wasn’t recruitment.

Another CBO had been distributing flyers to promote KIU!; however, the staff member tasked with implementation left, resulting in a temporary end to promotion. The interviewee noted:

The person that was previously working on the KIU! program, they’re not an employee anymore, so they [the fliers] kind of went away as far as like the promotion material.

Interviewees also highlighted the need for more than one person to be tasked with recruitment, regardless of turnover. For example, 1 CBO trained all testing staff and volunteers on how to pitch KIU! to boost reach. However, staff in lower-level positions found it difficult to ask or tell colleagues to do so, stating that this request should come from upper management. Additionally, staff needed resources to support recruitment. One CBO found it helpful to provide each staff member with a cellphone and a laptop to keep track of client eligibility and to promote KIU!.

CBO staff diverged in their reflections on whether online recruitment aided their efforts. Three interviewees found their use of social media and hook-up apps to provide fruitful results. Interestingly, 1 CBO described LinkedIn as an effective social media site for recruitment:

On social media, the (CBO) has Facebook, Instagram and LinkedIn. But they have posted like just a few, like maybe three times, and LinkedIn proved to be pretty effective.

Another CBO compared their recruitment on 2 hook-up apps (Grindr and Scruff) with word-of-mouth recruitment and found better results online. However, they found it difficult to post on Facebook for recruitment due to Facebook’s restriction on sexually explicit content, which was described as having a potentially homophobic bias. They explained:

Facebook’s ad policy has been on all of my ads for being too sexually suggestive or being sexually explicit. It’s gotten, to the point where they’ll say like your clothes to skin ratio is off and it’s just like….And then I look at the photo and it’s just like two men hugging and it’s the arms and face and then this much or chest is showing [makes gesture with hand to signify a small amount].

Three other CBOs, though, highlighted a lack of results from online recruitment. One CBO felt that the lack of results may be due to the types of pages individuals seek out on social media. The interviewee elaborated:

I don’t know that it’s incredibly successful. I don’t think a lot of people will follow health care program.

Others highlighted difficulties with online recruitment due to fraudulent attempts to participate in KIU! from individuals or fake accounts that were not eligible to participate. One interviewee said:

Once you put something like that out on the internet, and you say that you’re offering money, there are a lot of bots and scammers out there that are going to be reaching out. So we kind of pulled back a little bit on that. And we didn’t get a lot of traction from it outside of you know, bots and scammers. So we’ve moved away from that.

There were no notable differences between CBOs that found online recruitment to yield results and those that did not. Both groups of respondents included staff from CBOs with a high, medium, or low number of years providing HIV services; with a high, medium, or low client volume; and with or without direct project manager involvement.

Finally, nearly one-third of interviewees (8/22, 36%; representing 5/22, 23% of all CBOs) highlighted difficulties with recruitment due to the COVID-19 pandemic. The first cohort of CBOs implementing KIU! launched implementation right before the pandemic began. For these and subsequent cohorts, implementation occurred alongside stay-at-home requirements, self-distancing, mask requirements, and pandemic-related layoffs that made recruitment a challenge to simultaneously manage. One interviewee commented:

Originally, we were planning to have an in-person photo shoot. We were going to go to some of the LGBTQ businesses, like the bars and restaurants, and do in-person promotion and because of COVID-19, that hasn’t happened, because everything got shut down right? So that had to be pending, and then things are starting to open up here in [city] again and we’re just starting to think of that. We can finally plan things.

Retention

Few interviewees offered reflections on retention (n=4). Among these interviewees, lessons and concerns they pointed to included discussion of in-person events for enrolled participants, calling participants for retention purposes, and general difficulties with retention.

In addition to having events for recruitment (eg, trivia nights where they encouraged participation in KIU!), 1 CBO also held in-person events for enrolled participants. At these events, staff and participants would play games and discuss participant questions about KIU! modules, and raffle prizes would be given to those who continued to complete KIU! modules. While this was seen as successful by the CBO, some challenges with this approach to retention were highlighted, as 2 participants were uncomfortable with in-person events and were upset that they were invited to something that was not entirely virtual. The CBO also began organizing virtual events on Zoom (Zoom Communications):

[Colleague] organizes an event on Zoom once a month centered around some sort of theme. It’s usually sexual health related, but I think last month was sexual health plus nutrition, and we put together a gift basket for the client. If you attend, you have a chance of winning a gift basket and [there are] drawings where we give people $25 gift cards.

Two interviewees also reflected on the use of phone calls for retention. One interviewee noted the difficulty in contacting participants this way, saying:

They don’t really respond to our contact messages or calls.

The interviewee, along with another interviewee at a separate CBO, felt unsure of how to retain participants despite trying various modes of contact. Another CBO, though, developed a “retention plan” to track participants. The retention plan included a spreadsheet of participants, when they had last been active, when they had been contacted, and who had contacted them. The interviewee implemented this to “lighten the load for myself and kind of do a cross check.”

Of note, only 1 high-experience CBO staff member reflected on retention successes and difficulties. The other 4 interviewees were from medium- and low-experience CBOs. Interviewees who reflected on retention were fairly evenly split between those with direct project manager involvement and those without (see ).

Discussion

Principal Findings

Despite the interest in and uptake of DHIs, little is known about how local organizations, such as CBOs, engage in recruitment and retention in real-world settings. We analyzed phone or Zoom call transcripts and interview data to capture CBO recruitment and retention approaches to KIU! implementation. We also used qualitative analyses to identify lessons learned by CBOs related to recruitment and retention. In future analyses, the research team plans to use coincidence analysis to identify configurations of recruitment and retention activities that promote greater recruitment.

Throughout the implementation of KIU!, CBOs used 4 approaches to recruit participants: outreach and community partnerships, online recruitment (eg, on their website or on social media), hook-up and dating apps, and participant referrals. Overall, CBOs most often used outreach through community partnerships and online recruitment. Most CBOs also developed their own promotional recruitment materials, especially CBOs with prior experience implementing CDC EBIs. During interviews, CBOs acknowledged that their recruitment efforts should have focused on communicating the benefits of KIU!, using recipient-centered language (ie, removing jargon), and emphasizing that KIU! was for anyone and not targeted for individuals deemed at higher risk. CBOs also noted how the recruitment location introduced barriers to discussions with participants (in a waiting room compared to a private room). CBO staff were able to recognize that individual values and preferences were barriers to recruitment efforts. As a result, CBOs had to adjust their approaches by creating customized information about KIU! to communicate the benefits and find safe locations for participants to honestly answer personal questions about themselves in order to enroll in the intervention. CBO recruitment reflections echo the importance of tailoring content for the target audience and considering the perspectives of clients in intervention delivery [-]. These findings stress the importance of researchers working closely with their participant audience to anticipate recruitment barriers and collaboratively create facilitators.

For retention, CBOs used a variety of approaches. CBOs called, sent text messages, and emailed participants to remind them about KIU!. Additionally, 1 CBO hosted in-person events with prizes to promote continued engagement; however, these were met with mixed reviews from participants who expected events to be hosted virtually since KIU! is a digital intervention. Overall, CBOs noted that all retention methods had limited success. While reminders represented the most common approach, CBOs may need to consider using other research retention methods such as providing incentives, reducing barriers (providing alternative data collection methods), tracing, and emphasizing participation benefits [,]. Further, CBOs may want to work closely with participants to understand which retention strategies are the most meaningful to them [].

Scaling Up DHIs (Challenges and Potential)

DHIs have the potential to enhance the quality of care and reduce health care costs. Despite evidence that DHIs are effective for improving HIV prevention outcomes [,,], the requirements to effectively scale these programs and bring them to practice are not well-established. The pre-established infrastructure, workflow, and experience of CBOs can create challenges for the scaling up of DHIs. Previous research indicates that the main obstacles to the adoption and scaling of DHIs include a lack of technical support, resistance to change, and financial constraints. Many CBOs lack technical proficiency and experience with implementing EBIs. These barriers make training a necessary component of implementation but can be a burden for CBO staff. CBOs also experience high turnover rates of staff who are involved in the recruitment and retention of participants, which can result in delays and deprioritization of recruitment for interventions that require additional training and cause gaps in retention as new staff undergo the training process. Workflows and strategies for recruiting and retaining participants for testing or in-person intervention modalities differ greatly from the implementation of DHIs, which could promote CBOs’ resistance to change or adapt already existing processes. Some CBOs also lack experience in retaining participants for an extended period of time, which is necessary for completing the learning objectives of online HIV prevention programs (eg, KIU! requires a minimum participant retention period of 3 months). All these challenges can be overcome with a better understanding of the optimal approaches of retention and recruitment activities to achieve DHI implementation success.

Although CBOs have been working with YMSM for many years and have experience implementing other CDC-designated EBIs, there is no consensus on successful recruitment and retention strategies for this population. This suggests that there is a critical need for implementation researchers to identify the best practices to improve the reach and benefits of future EBI implementation.

Limitations

This study described the approaches real-world CBOs use to recruit and retain participants in a DHI for HIV prevention among YMSM. Although lessons learned are reported through interviews with CBO staff about intervention success, this manuscript does not report recruitment or retention rates, as the evaluation in this study was not part of a prespecified data analysis and was not meant to be a statistical analysis. Instead, a descriptive evaluation of the different recruitment and retention approaches CBOs used to implement a novel DHI for HIV prevention is provided. The results represent staff perceptions of success with different methods and are not associated with participant engagement or retention outcomes. The recruitment and retention methods listed here may not be representative of CBOs that did not choose to be enrolled in this study. CBOs self-selected to offer KIU!, and they may have had more resources and interest to engage in research activities. While the research team aimed to interview 2 staff members at each CBO implementing KIU!, CBO staff were not required in their funding contracts to participate in these interviews, and the research team was not willing to coerce participation. This resulted in 9 CBOs only having 1 staff member who consented to participate and 5 CBOs not having any staff member who consented to participate. Further, the staff who engaged in interviews varied greatly in their position titles across CBOs, which may have resulted in varied perspectives on implementation. This limitation was reduced by requiring those participating in interviews to be directly involved with the implementation of KIU!. Additionally, the retention findings were limited by few interviewee reflections on the approaches in the sample. This study took place during the COVID-19 pandemic. As a result, some of the reflections from CBO staff included challenges unique to that time period and may not be as relevant to recruitment and retention practices during stable economic and epidemiologic periods.

Conclusion

Limited research has described the recruitment and retention practices of CBOs, especially for HIV prevention DHIs. CBOs providing HIV prevention services often have more experience recruiting clients than retaining them, given the nature of point-in-time services such as HIV testing and condom distribution. While some CBOs have experience with behavioral interventions for HIV prevention, DHIs like KIU! rely on CBO staff to ensure ongoing participant engagement and retention, even though the intervention takes place outside the CBO’s physical premises. In this trial of 22 CBOs implementing a DHI for HIV prevention, only a few CBOs had prior experience with DHIs, highlighting the need for dedicated staff and resources to successfully implement such interventions. These resources should include insights and strategies for effective recruitment and retention, as presented in this manuscript.

By Claudia Assis

Advertising side gets hurt in part because of Google AI Overviews

Barry Diller, IAC’s chairman. The bulk of IAC’s revenue comes from the media division, People Inc., that saw revenue shrink 2% year over year.

Media and internet holding company IAC Inc., led by digital-media mogul Barry Diller, late Monday reported revenue below Wall Street’s expectations and pointed to a growing concern among others in the same business.

That’s the heightened presence of Google AI Overviews, a relatively new feature of Alphabet Inc.’s (GOOGL) (GOOG) Google Search that appears at the very top of query results.

Shares of IAC (IAC) dropped more than 9% in the extended session Monday, after ending the regular trading day up 1.1%.

AI Overviews uses generative AI to provide users with an overview of a topic, but may bury sites where people would ordinarily seek information about an issue.

IAC’s media brands include instantly recognizable print and digital names such as People, Food & Wine and Better Homes & Gardens, to name a few. The company reported third-quarter revenue of $590 million, or $10 million less than the FactSet consensus for the quarter.

The bulk of its sales come from the media division, People Inc. That saw revenue shrink 2% year over year to $430 million.

That reflects a 3% drop in advertising revenue, part of a downward pressure mostly due to “the impact of the increasing prominence of Google AI Overviews on Google search sessions,” IAC said. Higher advertising rates and higher premium advertising softened that, the company said.

Alphabet said last week its Google Search business has remained strong. On a post-earnings call, Chief Executive Sundar Pichai said that overall queries and commercial queries have continued to increase thanks to AI Overviews and Google’s AI Mode. Google Search revenue rose more than 14% year on year to $56.57 billion in the third quarter.

IAC, for its turn, also reported a wider-than-expected quarterly loss: It lost 27 cents a share in the third quarter, whereas analysts polled by FactSet had expected a loss of 24 cents a share.

People Inc. is the “heart of our future” alongside IAC’s investment in casino operator MGM Resorts (MGM), CEO Diller said. Diller doesn’t seem afraid of AI: He also praised People Inc.’s licensing deal with Microsoft AI.

People Inc. has signed a deal with Microsoft Corp. (MSFT) to be one of the publishers building Microsoft’s Publisher Content Marketplace, a two-sided content marketplace that would compensate publishers for use of their content by AI. Microsoft’s AI Copilot assistant would be the first buyer, the company has said.

-Claudia Assis

This content was created by MarketWatch, which is operated by Dow Jones & Co. MarketWatch is published independently from Dow Jones Newswires and The Wall Street Journal.

  (END) Dow Jones Newswires

  11-03-25 1718ET
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Ariana Salvatore: Welcome to Thoughts on the Market. I’m Ariana Salvatore, Morgan Stanley’s U.S. Public Policy Strategist.

 

Erin Wright: And I’m Erin Wright, U.S. Healthcare Services Analyst.

 

Ariana Salvatore: Today we’ll talk about what the U.S. government shutdown means for healthcare.

 

It’s Thursday, October 30th at 12pm in New York.

 

Thus far, it seems like markets haven’t really been paying too much attention to the government shutdown.

 

Obviously, we’re aware of the cumulative economic impact that builds every week that it lasts. But we haven’t seen any movement from the political front either this week or last, which signals that it could be going on for a while longer. That being said, the end of this month is an important catalyst for a few reasons.

 

First of all, you have the potential rollover of SNAP benefits. You have another potential missed military paycheck. And most importantly, the open enrollment period for healthcare plans. Polling is still showing neither side coming out on top with a clear advantage.

 

Absent that changing, you probably need to see one of two things happen to have any movement forward on this front. Either more direct involvement from President Trump as he wraps up the APEC meeting or some sort of exogenous economic event, like a strike from air traffic controllers.

 

Those types of events obviously are difficult to predict this far in advance. But up until now we know that President Trump has not really been involved in the debate. And the FAA seems to be operating a little bit with delays, but as usual.

 

So, Erin, let’s pivot to what’s topical in here. From a healthcare policy perspective, what are investors that you speak with paying the most attention to?

 

Erin Wright: You bring up some important points Ariana. But from a policy perspective, it’s very much an always top of mind for healthcare investors here. Right now, it is a key negotiating factor when it comes to the government shutdown.

 

So, the shutdown debate is predominantly centered around the Affordable Care Act or the healthcare exchanges. This was a part of Obamacare. It was a program where individuals can purchase standalone health insurance through an exchange marketplace.

 

The program has been wildly popular; in recent years with 24 million members. Growing 30 per cent last year, particularly with enhanced subsidies that are being offered today. So those subsidies are expected to expire at the end of this year, and those exchange members could be left with some real sticker shock – especially when we’re going to see premium increases that could, on average, increase about 25 to 30 percent, in some states even more.

 

So, folks are really starting to see that now. November 1st will be a key date here as open enrollment period begins ends.

 

Ariana Salvatore: Right. So, as you mentioned, this is pretty key to the entire shutdown debate. Republicans are in favor of letting the expanded subsidies roll off. Democrats want to restore them to that COVID level enhancement. Of course, there’s probably some middle path here, and we have seen some background reporting indicating that lawmakers are talking about a potential middle path or concession. ,

 

So, talk me through what’s on the table in terms of negotiating a potential compromise or extension of these subsidies.

 

Erin Wright: So, we could see a permutation of outcomes here. Maybe we don’t get a full extension, but we could see something partial come through. We could see something in terms of income caps, which restrict kind of the level of participants in the AC exchanges. You could see out-of-pocket minimums, which would eliminate some of those shadow members that we’ve been seeing and have been problematic across the space. And then you could also grandfather in some existing members that get subsidies today.

 

So, all of those could offer some degrees of positive and some degrees of relief when it comes to broader healthcare services, when it comes to insurance companies, when it comes to others that are participating in this program, as well as the individuals in themselves. So, it’s really a patient dynamic that’s getting real here.

 

A lot is on the table, but a lot is at stake with the potential for the sunsetting of these subsidies to drive 4 million in uninsured lives. So, it is meaningful, and I think that that’s something we have to kind of put into perspective here.

So, would love to know Ariana though, beyond healthcare, what are some of those key debates in terms of the negotiations around the shutdown?

 

Ariana Salvatore: Healthcare really is central to this debate. So aside from just the ACA subsidies that we talked about, some Democrats have also been pushing for a repeal or rollback of some of the pieces of the One Big Beautiful Bill Act that passed earlier this year. That was the fiscal bill of Republicans – passed through reconciliation process – that included some cuts to Medicaid down the line. So, there’s been talk around that front.

 

I think more of a clear path on the subsidies front, because that seems to be something that Republicans are treating as an absolute no-go. Some of the other really key debates are around just kind of how to keep the ball rolling while we’re still in the shutdown.

 

So, I mentioned SNAP at first, the potential release of some contingency funds there. Again, the military paychecks are really critical. And, of course, what this all means for incoming data, which is really important – not just for investors but also for the Fed, as it kind of calibrate[s] their next move. In particular, as we head into the December meeting, I think we got a little bit of a hawkish surprise in yesterday’s meeting, and that’s something that investors were not expecting.

 

So, obviously the longer that this goes on, the more those risks just continue to grow, and this deadline that we’re talking about is a really critical one. It’s coming up soon, so we should have a sense of how our prognosis pans out in the coming days.

 

Thanks for the conversation, Erin.

 

Erin Wright: Great talking to you, Ariana.

 

Ariana Salvatore: And to our audience, thanks for listening. Let us know what you think by leaving us a review wherever you listen. And if you like Thoughts on the Market, tell a friend or colleague about the podcast today.

 

 

A randomized controlled trial conducted in 18 public hospitals in Kenya finds that the the addition of glucocorticoids to standard care for severe community-acquired pneumonia (CAP) reduced the risk of death by 16%.

For the pragmatic, open-label trial, published last week in the New England Journal of Medicine, a team led by researchers at the Kenya Medical Research Institute assigned adult CAP patients without a clear indication for glucocorticoids to receive either standard care or standard care plus oral low-dose glucocorticoids for 10 days.

Of the 2,180 patients, none required intensive care, 1,089 were assigned to glucocorticoids within 48 hours after hospital admission, and 1,091 were assigned to standard care. The median patient age was 53 years.

“Adjunctive glucocorticoids may reduce mortality among patients with severe community-acquired pneumonia (CAP) in well-resourced settings,” the authors wrote. “Whether these drugs are beneficial in low-resource settings with limited diagnostic and treatment facilities is unclear.”

Balancing benefits with risk of metabolic complications

By 30 days, 22.6% of glucocorticoid recipients and 26.0% in the standard-care group had died (hazard ratio, 0.84). Rates of adverse and serious adverse events (SAEs) were similar in the two groups.

Although hyperglycemia is mostly controllable, blood glucose monitoring is difficult in overburdened sub-Saharan hospitals.

The trial’s pragmatic nature means that the results are likely to be more relevant to patients in sub-Saharan Africa than to those in high-resource settings, the researchers said. “On the basis of our findings, adjunctive glucocorticoids could represent a low cost intervention to reduce the high case fatality associated with CAP in sub-Saharan Africa,” they wrote.

In an editorial in the same journal, Arthur Kwizera, MD, of Makerere University College of Health Sciences in Uganda, and Martin Dunser, MD, of Johannes Kepler University in Austria, noted that hyperglycemia (high blood glucose) occurred in 16.6% of glucocorticoid recipients.

“Although hyperglycemia is mostly controllable, blood glucose monitoring is difficult in overburdened sub-Saharan hospitals,” they wrote. “As the prevalence of diabetes is increasing across Africa, introducing glucocorticoid therapy without strengthened laboratory and nursing capacity may put patients at risk and requires a nuanced balance of the survival benefits and metabolic complications.”