Self-Managed Energy Assistance

Our proposed intervention is an alternative way to deliver LIHEAP benefits which gives recipients control over when and how their benefits are applied. The intervention will be implemented through a text-based platform that enables recipient-controlled benefit allocation.

Treatment group participants receive access to a multilingual text-based platform enabling them to: (1) view their full LIHEAP benefit allocation, (2) choose how much benefit to apply to each utility bill throughout the year, and (3) receive reminders about upcoming bills and benefit usage.

2026-10-01

2027-08-15

Primary outcomes include utility disconnection rates, on-time bill payment rates, total energy consumption, total arrearages (accumulated utility debt), energy burden (percentage of income spent on energy).

Disconnection rates will be measured as any service interruption for non-payment during the study period. On-time payment rates will be calculated as the proportion of monthly bills paid by or before the due date. Arrearages represent the cumulative unpaid balance on utility accounts at study end. Energy burden will be calculated as: (total annual energy costs / annual household income) × 100.

Secondary outcomes include self-reported financial stress related to energy bills, bill management, ability to maintain comfortable in-home temperatures, need to reduce food or medicine purchases to pay energy costs, understanding of energy usage and costs, sense of control over energy decisions, and household thermal health indicators.

Financial stress will be measured using validated insecurity surveys, including questions about worry over paying bills, difficulty affording energy costs, and trade-offs between energy and other necessities.

Comfortable temperature maintenance is a binary indicator based on whether households report being able to keep their home at a comfortable temperature during the heating season without compromising health or safety.

Food/medicine trade-offs capture whether households report reducing or forgoing food purchases or skipping/reducing medication doses to pay energy bills in the past 3-6 months.

Energy usage understanding assesses comprehension of how energy use translates to costs, how to reduce energy costs, and self-reported understanding of why energy costs are what they are.

Sense of control measures perceived agency using items like "I feel in control of my energy costs" and "I worry about whether my home energy bill will become overdue before I can pay it." on 5-point agreement scales.

We will conduct a RCT with 1,000 LIHEAP-eligible households in Illinois to evaluate whether a self-managed delivery model improves energy security outcomes compared to traditional LIHEAP implementation. The treatment group will receive self-managed LIHEAP benefits with control over allocation timing. The control group will receive traditional LIHEAP delivery (one-time direct payment to utility).

Not available

The randomization will be implemented through the Illinois Association of Community Action Agencies and its member organizations at the time of application. Recruitment of research participants will occur when utility customers apply for LIHEAP benefits. After securing written consent and determining LIHEAP eligibility, participants will be randomly assigned to either the treatment or control group.

Households will be randomly assigned at the individual level using stratified randomization to ensure balance across key characteristics that may influence treatment effects: geographic location (urban/rural/suburban), household composition (presence of elderly, children, medically compromised, and disabled members), housing type (owner/renter), historical energy burden, and race/ethnicity (household representative that identifies as Black, White, Hispanic, or mixed race).

No

NA

1,000

We will employ a 1:1 allocation ratio with 500 households in the treatment and control groups.

Based on a small pilot study, we have calculated the required sample size to detect meaningful effects. The pilot showed a 60-percentage point difference in bill payment rates between treatment (95%) and control (35%) groups. Using a two-sided test with α=0.05 and 80% power, we would need approximately 11 participants per group to detect this effect size (Cohen's h=1.34), however, we anticipate smaller effect sizes at this scale due to the reduced intensity of support compared to the pilot. Comparable interventions in utility bill management suggest a potential reduction in disconnection rates from 15% to 7.5%. To detect this effect size, we would need 376 participants per group. Conservatively assuming a 20-percentage point difference in payment rates, we would need 97 participants per group. The pilot demonstrated a 20% reduction in electricity usage and 10% reduction in gas consumption. For a conservative 7% reduction in overall energy consumption, which aligns with findings from behavioral interventions in energy consumption, we would need approximately 283 participants per group to achieve 80% power. We would need approximately 156 participants per group to detect a 15-percentage point difference in arrearages. For a 10% relative reduction in energy burden, consistent with outcomes from other energy assistance interventions, we would need approximately 425 participants per group. Our planned sample of 500 participants per group exceeds all these requirements, providing sufficient power even with anticipated attrition of up to 15%. This sample size also enables us to detect relatively small effects (5-7 percentage point differences) in secondary outcomes, conduct meaningful subgroup analyses by demographic characteristics to identify heterogeneous treatment effects, and maintain adequate power for stratified analyses examining impacts by household composition, geographic location, and baseline energy burden. We will supplement these a priori power calculations with sensitivity analyses during the study to refine our estimates of minimum detectable effects based on observed variance in outcomes, correlation between baseline and follow-up measures, and actual attrition rates.