Series 13: Special Topics in Work Requirements Implementation
Opening Vignette: Maria’s Intention
Maria has the documents. She knows the deadline. She has every intention of submitting her work verification by the 15th.
She works Tuesday through Saturday at a hotel cleaning rooms. The hours vary, but she consistently hits 80-plus per month. Her employer provides pay stubs. She photographs them on her phone each payday. The submission portal is bookmarked. She has done this before.
But this month unfolds like so many others. Tuesday, her nine-year-old daughter comes home sick from school. Wednesday, Maria works a double shift when a colleague calls out. Thursday, her mother needs a ride to the doctor. Friday, she realizes the utility bill is past due and spends her lunch break on the phone with the electric company. Saturday, she works until 7 p.m. On Sunday, she does laundry, buys groceries, and helps her daughter with a school project.
Monday morning she remembers the verification deadline. She reaches for her phone, but the portal is asking her to reset her password. She cannot remember the security question. She will need to call, but she is running late for her Tuesday shift. She will call during lunch. But lunch becomes fifteen minutes scarfing down leftovers because the hotel is understaffed. By Tuesday evening, she has forgotten again.
On the 16th, she receives a notice that her verification was not submitted. She has thirty days to appeal. The notice arrives when she is at work. It sits on the counter until Friday. By then she has missed the ten-day response window for expedited review. Her coverage enters pending termination status.
Maria did not decide to be non-compliant. She did not weigh the benefits of keeping her healthcare against the costs of spending five minutes on a portal. She simply did not get to it. The system treated her intention as irrelevant. To the system, a missed deadline is a missed deadline. Whether she was negligent or overwhelmed, indifferent or struggling, makes no difference in the automated workflow that flags her for disenrollment.
Somewhere in an office, a policy analyst reviewing compliance statistics will note that Maria failed to verify her work hours. The statistic will join thousands of others suggesting that members do not take their obligations seriously. What the statistic will not capture is that Maria was working the whole time, that she had the documents the whole time, that she intended to comply the whole time. The gap between intention and action consumed her coverage.
This is not a motivation problem. Maria wanted to submit. This is a design problem. The system assumed that deadlines create action, that reminders create compliance, that clear instructions create behavior. Decades of behavioral science research demonstrate why these assumptions are wrong and what to do instead.
Section 1: The Intention-Action Gap#
The insight that transformed behavioral economics emerged from a simple observation: people consistently fail to do things they intend to do. This intention-action gap is not a character flaw or a motivation deficit. It reflects how human minds actually work.
Consider the foundational research. Peter Gollwitzer’s studies on implementation intentions demonstrate that people with strong goals fail to achieve them roughly half the time. The gap between wanting to exercise and actually exercising, between intending to save money and actually saving, between planning to complete a form and actually completing it, is not explained by weak motivation. People genuinely want these outcomes. They simply do not translate intention into action.
Several well-documented psychological mechanisms explain why.
Present bias describes our tendency to weight immediate demands more heavily than future consequences, even when we know the future consequences are more important. Maria knew that maintaining her health coverage mattered more than any single day’s immediate pressures. But immediate pressures are concrete, salient, and demanding. Future coverage loss is abstract and distant until suddenly it is not.
Cognitive load refers to the limited bandwidth we have for processing information and making decisions. Every bureaucratic task competes with every other demand for this finite resource. When Maria is navigating her daughter’s illness, her mother’s medical needs, her employer’s staffing crisis, and her utility bill, the verification portal becomes one more thing demanding mental space she does not have. The fact that it is objectively simple is irrelevant. Simple tasks still require attention, and attention is exhausted.
Decision fatigue compounds this problem. Each decision we make depletes our capacity for subsequent decisions. By the end of a day filled with hundreds of small decisions about work, family, and logistics, the decision to sit down and complete a government form feels insurmountable. This is not weakness. It is human neurobiology.
The planning fallacy causes us to systematically underestimate how long tasks will take and overestimate our future available time. Maria genuinely believed she would have time to submit her verification. She was not lying to herself. She was experiencing the same optimistic forecasting error that affects everyone. We plan for best-case scenarios and then encounter average-case reality.
Traditional program design ignores these mechanisms. It assumes that providing information creates understanding, that understanding creates intention, that intention creates action, and that action follows from rational calculation of costs and benefits. This model of human behavior has been empirically demolished. Yet work requirement systems are designed as if it remains valid.
The consequences are predictable. Arkansas’s work requirements produced 18,000 coverage losses in ten months. Subsequent research found that most people who lost coverage were actually working or qualified for exemptions. They failed to prove what they were doing, not failed to do it. The intention-action gap, built into a healthcare system, produced healthcare loss.
Section 2: Defaults and Pre-Population#
The most powerful tool in behavioral design is the default. When systems require affirmative action, participation rates collapse. When systems pre-select beneficial options and allow people to opt out, participation soars.
The evidence is overwhelming. Madrian and Shea’s landmark study found that automatic enrollment in retirement savings plans increased participation by 50 percentage points. The same people, with the same incomes and the same financial needs, saved dramatically more when saving was the default rather than a choice they had to make. This is not about changing preferences. It is about recognizing that the path of least resistance determines most behavior.
Current work requirement systems invert this principle. They require affirmative action at every step. Members must log in to portals, navigate interfaces, locate documents, upload files, and confirm submissions. Each step is an opportunity for dropout. Each step loses people who intended to comply but encountered friction they could not overcome.
Behavioral design flips this architecture. Instead of requiring members to prove compliance, systems should presume compliance unless evidence suggests otherwise. Instead of demanding documentation at every reporting period, systems should automatically verify through data matching and require member action only when automated verification fails.
Consider what states already know. Unemployment insurance wage records capture formal employment. SNAP ABAWD compliance records document work activities. Educational institution enrollment data confirms student status. Employer quarterly wage reports provide verification without member involvement. These data exist. States collect them. Most states simply do not use them to reduce member burden.
Pre-population extends this principle to required forms. When members must submit information, systems should pre-fill every field that can be populated from existing records. Name, address, employer of record, income, household composition, existing qualifying activities from prior periods, all can be entered automatically. The member reviews and confirms rather than entering from scratch. Review is less cognitively demanding than data entry. It preserves accuracy while reducing friction.
Auto-renewal represents the most powerful default. When a member has demonstrated six consecutive months of compliance, the behavioral evidence suggests they are compliant. Continuing their coverage automatically, with annual verification rather than monthly reporting, maintains the work requirement while eliminating the monthly intention-action gap that produces coverage loss among compliant people.
Georgia’s experience illustrates the alternative. Pathways to Coverage launched requiring monthly verification. By late 2024, only about 5,500 people had enrolled despite an estimated 240,000 eligible residents. The state’s extension proposal eliminates monthly reporting in favor of annual verification at enrollment and renewal. This is not abandoning work requirements. It is recognizing that monthly reporting creates a monthly opportunity for compliant people to lose coverage through administrative failure rather than work failure.
The objection to defaults and presumptive eligibility is typically program integrity. If we do not verify monthly, how do we know people are actually working? The answer is that monthly verification does not reliably establish that people are working. It establishes that people successfully navigated the verification system. As Arkansas demonstrated, these are different populations with different characteristics.
Section 3: Friction Mapping#
Every system contains friction points where users encounter difficulty completing desired actions. Behavioral design involves systematically identifying these points and reducing or eliminating them for desired behaviors while potentially adding them for undesired behaviors.
In work requirement systems, the desired behavior is continued coverage for compliant members. The friction points that prevent this include portal access requirements, password complexity, document format specifications, upload size limits, unclear instructions, confusing terminology, multi-step processes, inconsistent interfaces, timeout sessions, lack of mobile optimization, and absence of progress confirmation.
Portal access creates the first barrier. Many members lack consistent internet access. Those who have it may lack computers, relying on smartphones with smaller screens and touch interfaces poorly suited to document management. Library computers offer access but limited privacy and time constraints. The Georgia Pathways experience documents members encountering portal glitches across multiple devices, indicating system-level problems rather than user error.
Password requirements create persistent friction. Security best practices demand complex passwords that are difficult to remember. Members who access systems infrequently, as most work requirement participants do, predictably forget credentials between sessions. Password reset processes add steps, create delays, and introduce additional failure points.
Document specifications multiply problems. When systems require specific formats, file sizes, or naming conventions, every deviation produces rejection. Members who photograph pay stubs on their phones may create files that exceed size limits. Those who scan documents may inadvertently create formats the system cannot process. The technical sophistication required to diagnose and resolve these problems exceeds what we can reasonably expect from a population already burdened by economic stress.
Unclear instructions generate confusion that wastes time and causes errors. When systems use bureaucratic terminology like “verification of qualifying activities during the applicable reporting period,” members may not understand that this means “prove you worked this month.” When instructions reference form numbers, database codes, or regulatory citations, they assume familiarity that most people lack.
Mobile optimization has become essential. The populations subject to work requirements disproportionately rely on smartphones rather than computers for internet access. Systems designed for desktop interfaces, then adapted for mobile as an afterthought, create friction that falls most heavily on those least able to overcome it.
Friction mapping involves documenting every step a member must complete, identifying where members drop off, measuring time required at each stage, and testing whether typical users can complete the process without assistance. States that have conducted this analysis consistently find that their systems contain unnecessary barriers that lose compliant members.
Adding friction strategically also matters. If the goal is preventing inappropriate termination, systems should make termination harder rather than easier. Requiring supervisor review before disenrollment, mandating multiple contact attempts, and creating cooling-off periods between coverage suspension and termination all add friction in the right place. Currently, most systems make enrollment difficult and disenrollment automatic, inverting what behavioral design principles suggest.
Section 4: Timing, Triggers, and Reminders#
When we ask people to do something matters as much as how we ask. Behavioral research identifies optimal timing for behavior change and demonstrates that poorly timed reminders can be worse than no reminders at all.
Fresh start moments represent periods when people are naturally more receptive to taking action. The beginning of a new month, a new year, a new season, following a birthday, after a major life transition, these moments create psychological openings for new behaviors. Reminders and deadlines aligned with fresh starts produce higher response rates than arbitrary dates.
Work requirement systems typically use calendar-based deadlines that ignore fresh starts. The 15th of the month, the 20th of the month, dates chosen for administrative convenience rather than behavioral effectiveness. Shifting deadlines to align with psychologically meaningful moments requires minimal administrative change while potentially improving compliance rates.
Channel optimization involves reaching people through the medium they actually use. Research consistently shows that SMS text messages outperform email for populations that rely primarily on mobile phones. Email outperforms postal mail for populations that check email regularly. Postal mail remains essential for populations with limited digital access or unreliable phone numbers.
Current systems often rely on single channels. Mailed notices assume stable addresses and consistent mail retrieval. Portal notifications assume regular portal visits. Neither assumption holds for populations experiencing housing instability, frequent moves, or limited technology access. Multi-channel approaches that use SMS, email, phone calls, and postal mail together reach more people than any single channel.
Escalating contact sequences apply behavioral insights to outreach timing. The first reminder might be a simple SMS. If no response, a follow-up email. Then a phone call. Then a mailed notice. Then outreach through community organizations or in-person contacts. Each escalation signals increased urgency while providing additional opportunities for response.
Implementation intentions transform vague plans into specific commitments. The research of Gollwitzer and others demonstrates that asking people to specify when, where, and how they will complete a task doubles completion rates. “I will submit my verification” produces different results than “I will submit my verification on Saturday morning at 10 a.m. using my phone at the kitchen table.”
Work requirement systems can incorporate implementation intentions into their communications. Rather than simply stating deadlines, notices can prompt members to specify when they plan to act. “Your verification is due by July 15th. When will you submit it? Write down the day and time below.” This simple addition leverages decades of behavioral research at essentially zero cost.
Calendar integration and scheduling tools extend implementation intentions into technology. Systems that allow members to schedule their submission, add reminder events to their phone calendars, and receive automated prompts at their self-selected times convert intention into behavioral infrastructure. The technology is straightforward. Most systems simply do not incorporate it.
Section 5: Framing and Social Proof#
How we describe choices influences which choices people make. This framing effect operates outside conscious awareness, shaping decisions through language, emphasis, and context rather than argument or persuasion.
Loss aversion describes people’s tendency to weight potential losses more heavily than equivalent gains. Losing $100 feels worse than gaining $100 feels good. This asymmetry has profound implications for how systems communicate with members.
Current work requirement communications typically emphasize eligibility requirements. “To maintain your eligibility, you must verify your work hours by…” This framing presents compliance as achieving a bureaucratic goal. Behaviorally-informed framing emphasizes what members stand to lose. “Your healthcare coverage will end unless you submit verification by…” The same deadline, framed as loss prevention rather than goal achievement, produces higher response rates.
The specific language matters. “Keep your coverage” outperforms “maintain your eligibility.” “Protect your healthcare” outperforms “comply with requirements.” “Don’t lose your prescription benefits” outperforms “remain enrolled in Medicaid.” Testing different frames with actual populations identifies which messages produce action.
Social proof leverages our tendency to look to others’ behavior as guidance for our own. When we learn that most people like us have taken an action, we become more likely to take it ourselves. “Most people in your area complete their verification within five days of receiving this notice” provides a behavioral benchmark that suggests both that completion is normal and that the timeline is achievable.
Social proof must be deployed carefully. Telling people that 40% of members fail to verify on time might normalize non-compliance rather than prevent it. Effective social proof emphasizes positive behaviors and suggests that the recipient is similar to successful compliers rather than to those who struggle.
Progress indicators address the psychological need for feedback. When members cannot see how close they are to completion, each step feels like it might be followed by endless additional steps. Progress bars, completion checklists, and stage indicators provide feedback that sustains motivation through multi-step processes.
Immediate confirmation reduces the uncertainty that generates anxiety and follow-up contacts. When members submit verification, they need to know immediately whether their submission succeeded. Delayed confirmation leaves them wondering whether they need to resubmit, whether something went wrong, whether they will lose coverage despite their effort. Real-time confirmation eliminates this uncertainty while reducing call center volume from members checking their status.
Normalizing compliance means presenting work requirements as standard expectations that most people meet, rather than as punitive measures that assume members are trying to cheat. Communications that treat members as cooperative partners, providing reminders and assistance to help them succeed, produce better results than communications that treat members as suspected violators requiring surveillance. The former generates collaboration. The latter generates resistance.
Section 6: Commitment Devices and Accountability#
Some behavioral interventions help people constrain their future selves. These commitment devices recognize that our current intentions and our future actions often diverge, and that we can take steps now to bind ourselves to better outcomes later.
Self-designed reminders allow members to specify when and how they want to be contacted. A member who knows she is most likely to complete administrative tasks on Sunday evenings can request reminders for Sunday at 6 p.m. A member who responds to texts but ignores emails can specify his preferred channel. Self-designed reminders leverage members’ knowledge of their own behavioral patterns while increasing ownership of the compliance process.
Accountability partnerships extend social proof into personal relationships. Systems that allow members to designate someone who will receive notification if verification is not submitted create social accountability that reinforces individual intention. The designated person might be a family member, a navigator, a community organization contact, or a healthcare provider. The notification does not share private information about the member’s circumstances. It simply indicates that the member authorized this reminder and that verification is due.
Public commitments strengthen intention by making them socially visible. Community organizations working with members can facilitate commitment ceremonies where members publicly state their intention to maintain compliance. While this approach is not appropriate for formal government communications, it can be incorporated into navigation and assistance programs.
Scheduled future submissions allow members to complete verification in advance of deadlines. Rather than requiring submission during a specific window, systems can allow members to submit at any time during the month for the current or upcoming period. Members who know their schedules are unpredictable can submit early when they have time, reducing the risk that the deadline will arrive during a difficult period.
Commitment device limitations must be recognized. These techniques work best when people want to do something but anticipate difficulty doing it. They work poorly when people do not want to do something or when external barriers rather than internal conflicts prevent action. A member who lacks internet access does not benefit from self-designed reminders that she cannot receive. A member whose employer refuses to provide documentation is not helped by accountability partnerships that increase social pressure to produce documents he cannot obtain.
Return to Maria#
Consider Maria’s experience through a behaviorally-designed system.
When Maria applied for coverage, the system connected to unemployment insurance wage records and identified her employer. It pre-populated her application with income and work hours from state data. Rather than requiring her to provide pay stubs, it informed her that her work hours had been automatically verified through data matching. She confirmed the information was accurate and signed.
Six months later, the system still has access to quarterly wage data. Maria’s employer reports wages to the state unemployment system. The work requirement system queries this data and finds that Maria continues working more than 80 hours monthly. Her eligibility continues without any action on her part.
One quarter, the automated verification shows fewer hours than required. Perhaps her employer made a reporting error, or perhaps Maria reduced her hours. The system does not immediately terminate her coverage. Instead, it sends a text message. “Hi Maria, we noticed your work hours look different this quarter. If you’re still working 80+ hours, please upload a recent pay stub so we can update your records. You can do this anytime before [date 30 days out]. Reply HELP for assistance.”
Maria sees the text on a Tuesday. She is busy, but she knows she needs to respond. On Sunday morning, she takes a photo of her most recent pay stub and texts it back using the same number that contacted her. Within minutes, she receives confirmation. “Thanks Maria! Your work hours are verified. No additional action needed.”
No portal. No password. No multi-step process. No document format requirements. The system met Maria where she was rather than demanding she come to where the system lived.
In this scenario, Maria’s intention translated into action because the system removed the friction between them. She still had to do something. The work requirement still applied. But what she had to do matched what she was actually capable of doing given her actual life constraints.
The technology for this system exists. States already collect wage data. SMS verification is standard in many industries. Photo-based document submission is routine. The barrier is not technical capacity. It is design philosophy. Current systems assume that members should adapt to bureaucratic requirements. Behaviorally-informed systems assume that bureaucratic requirements should adapt to how members actually behave.
Conclusion: Design for Humans, Not Assumptions#
The behavioral economics of compliance reveals a fundamental mismatch between how work requirement systems are designed and how human beings actually function. Systems built on assumptions of rational, future-oriented, cognitively abundant actors fail populations that are stressed, present-focused, and cognitively depleted by the conditions that made them eligible for assistance in the first place.
This is not a counsel of despair. It is an invitation to design better systems using principles that have been validated across dozens of domains and thousands of studies. Defaults, friction reduction, timing optimization, appropriate framing, and commitment devices are tools available to any state willing to use them.
The choice before policymakers is not whether to impose work requirements. That decision has been made at the federal level. The choice is whether to implement work requirements through systems designed to catch people failing or systems designed to help people succeed. The behavioral science is clear on which approach produces better outcomes.
Systems that help people comply do not compromise program integrity. They strengthen it by ensuring that compliance statistics reflect actual work activity rather than administrative navigation ability. They reduce coverage churn that disrupts care continuity and increases costs. They maintain the dignity of members who are doing everything right but cannot prove it through systems designed without their lives in mind.
Maria is working. She was always working. The question is whether the system will see her work or only see her paperwork. That question is a design choice, and design choices can be changed.