ORIGINAL RESEARCH ARTICLE

Observed Benefits of a Rehome Web Application For Harder-To-Adopt Pet Populations

John Cornelison^1*, Sue Neal² and Kevin Horecka¹

¹Department of Research, Austin Pets Alive!, Austin, TX, USA; ²Department of Political Science, Arkansas State University, Jonesboro, AR 72401, USA

Abstract

Introduction: Owner-to-owner rehoming platforms such as Home-Home.org, Getyourpet.com, and Rehome.adoptapet.com (hereafter, Rehome) were launched in 2016 and 2017 as alternatives to traditional shelter intake. Previous research identified characteristics that predict an animal’s likelihood of successful diversion from shelter intake via person-to-person rehoming platforms. These findings suggested that certain populations – specifically senior animals and large dogs – have lower odds of diversion. This study builds on this by evaluating whether harder-to-adopt animals can benefit from being listed on Rehome.

Methods: Using data from Rehome and 23 shelters participating in the Human Animal Support Services (HASS) initiative, this study used Cox regression, chi-square tests, and two outcome metrics: median length of stay (LOS) and adoption rate. Analyses focused on harder-to-adopt animals – defined as senior cats, senior dogs, and large dogs – and compared adoption rates between animals listed on Rehome and those surrendered to shelters.

Results: Animals on Rehome had longer LOS than animals in the shelter. Cox regression results further indicated that animals on Rehome had lower probabilities of adoption at any given time compared to those in shelters. Overall, adoption rates were higher in shelters, although considerable variability existed among shelters; whereas Rehome’s performance remained relatively stable. In some regions, Rehome had higher adoption rates than the corresponding local shelter.

Conclusion: The results imply that harder-to-adopt animals have a better chance of finding a new home in shelters than through an online rehoming website. However, harder-to-adopt animals still find success on Rehome. Considering that Rehome results in efficiency gains for shelter systems and a reduced-stress environment for animals, if properly expanded and utilized by shelter communities, Rehome could serve as a useful complementary tool for shelters. It may also help reduce shelter intakes, especially of animals traditionally classified as harder-to-adopt.

Keywords: online rehoming, peer-to-peer rehoming, senior cats, senior dogs, large dogs, animal shelter, animal adoption, animal length of stay, animal welfare

 

 

Although stray animals constitute the majority of shelter intakes, owner-relinquished animals account for approximately 25–35%^1–3 of admissions. Understanding the reasons for relinquishment can highlight intervention opportunities to prevent shelter intake. Owner-related factors, such as health issues or housing restrictions, are common reasons for animal surrender;^4–6 however, these decisions often involve complex, multifaceted considerations.^7,8 Weiss and colleagues⁹ found that 37% of rehomed animals were placed with friends or family, while 36% were surrendered to shelters, indicating shelters often serve as a last resort rather than a preferred option. Identifying and providing alternative avenues for rehoming animals before shelter surrender could reduce intake and shelter-related stressors for both animals and organizations.

Animals in shelters are subject to various adverse effects during their stay. Dogs that experience prolonged length of stay (LOS) exhibit elevated chronic stress levels compared to dogs living in home environments.¹⁰ Shelter cats similarly face negative welfare impacts, including deterioration in coat condition and unhealthy weight loss.¹¹ Additionally, extended shelter stays incur financial costs.¹² Identifying pathways for owners to rehome animals without shelter intervention could mitigate both the economic burden on shelters and the welfare challenges faced by animals. Although shelters receive a diverse range of animals, some categories require more time to rehome. Existing literature identifies senior animals,^13–15 guard-type dogs,¹⁵ and dogs perceived as pit bulls¹⁶ as having notably longer LOS. Furthermore, senior animals and large dogs often experience decreased adoption probabilities^17–19 and lower live release rates^20–22 – a metric utilized to quantify the percentage of animals exiting shelters alive. Consequently, peer-to-peer rehoming platforms warrant examination for their potential effectiveness in addressing these barriers. Evaluating such platforms may offer critical insights into their viability as complementary tools for shelters, particularly in supporting these animal populations that are disadvantaged within traditional shelter settings.

Extended LOS and decreased likelihood of adoption in animal shelters may suggest a reduced demand for certain animal groups; however, conclusions should not be drawn solely from shelter data. Demand is dynamic and can be influenced through strategic interventions such as targeted marketing campaigns.^18,23–25 For instance, community-engagement initiatives, like foster-to-adopt programs, have effectively increased adoption rates.²⁶ Examining alternative rehoming methods is essential to identify existing community demand and potential avenues to enhance it. By providing rehoming opportunities outside the shelter environment, these alternatives mitigate adverse effects associated with prolonged shelter stays. Evaluating these alternative rehoming pathways can reveal latent demand within communities and highlight opportunities to increase adoptions through innovative programs, such as temporary fostering for dogs.²⁷ Ultimately, such efforts may enhance placement opportunities for traditionally harder-to-adopt animals, emphasizing that perceived low demand can be effectively counteracted with proactive measures.

Ly and Protopopova²⁸ analyzed data from Rehome.adoptapet.com (hereafter, Rehome), an online platform that facilitates owner-to-owner adoptions, to identify characteristics associated with successful diversion from shelter intake. Their findings indicated that young, purebred cats and dogs without behavioral or medical issues had higher odds of successful diversion. Additionally, animals with longer rehoming deadlines set by owners were more likely to be adopted. Conversely, older animals and large dogs were less likely to be diverted from shelter intake. While their analysis focused on identifying predictors of diversion, the present study extends this work by evaluating whether placing animals with lower odds of diversion – such as senior and large dogs – remains a viable strategy. Investigating outcomes for these harder-to-adopt groups on online platforms is essential for understanding their potential as a complementary tool to traditional sheltering strategies and for identifying ways to reduce shelter intake while supporting adoptions.

In this study, we define ‘harder-to-adopt’ animals as senior cats and dogs and large dogs. This definition is not intended to encompass all categories of animals that may be more difficult to place, such as those with medical or behavioral challenges. Rather, these groups were selected because their characteristics were clearly identifiable within the available data. We hypothesize that harder-to-adopt animals listed on Rehome will have higher adoption success rates compared to their counterparts surrendered to animal shelters. Additionally, we examine differences in LOS between animals on Rehome and those in shelters, with the expectation that harder-to-adopt animals on Rehome will experience longer LOS than other animals on the platform. This analysis aims to assess the viability of online rehoming platforms for harder-to-adopt animals and to provide owners with more realistic expectations regarding adoption timelines when choosing these platforms as a rehoming strategy.

Methods and materials

Rehome data

The primary dataset used in this study was obtained from Rehome, an online platform that allows private individuals – rather than animal shelters or rescue organizations – to list animals for adoption. The dataset comprises 202,163 animal profiles listed between January 2, 2017, and June 26, 2021. Each record represents a unique animal posted for rehoming and includes characteristics such as species, age, size, temperament, number of profile views, and the recorded outcome of the listing.

Rehome includes 10 possible outcome categories. For this study, outcomes were consolidated into two classifications: adoption or negative. Outcomes that did not fit into either of these categories were removed. The adoption category consisted of three outcomes – adopted through the Rehome platform (adopted-p2p), placed with a friend or family member (adopted-friend), or rehomed through other means (adopted-other). Negative outcomes included animals surrendered to a shelter (relinquished shelter) or rescue (relinquished rescue). Several outcome types were excluded from analysis. These included ‘keep-pet’ and ‘kept-pet’, where owners chose to retain their animals, though the duration of retention was unknown. Outcomes labeled ‘pending-adoption’ or ‘high-demand’ were also excluded, as they do not signify a final resolution. Listings with the outcome ‘other’ were removed due to ambiguity.

While Rehome prompts owners to close listings when an application is received, it is possible that some profiles were not updated. Nonetheless, removing ambiguous or non-final outcomes ensured a more reliable classification. The final dataset consisted of 102,151 records, each categorized into either the adoption or negative outcome group. Additional details on data cleaning procedures are provided in the supplementary materials.

Shelter data

In addition to the Rehome dataset, this study utilized intake and outcome data from 23 animal shelters collected through the Human Animal Support Services (HASS) initiative. HASS, led by American Pets Alive!, provides training, tools, and guidance for shelters to implement community-based strategies^29–31 that better serve both animals and the public.

To ensure comparability with the Rehome dataset, the shelter data was limited to the period between January 2, 2017, and June 26, 2021. Within this timeframe, the participating shelters reported 977,551 animal intakes and 901,932 outcomes. Each intake represents the admission of an animal to a brick-and-mortar shelter, and each outcome denotes the animal’s exit pathway.

This integration of shelter and Rehome data enabled a comparative analysis of adoption and outcome patterns across rehoming systems, offering insight into the relative performance and utility of each model in supporting successful animal placements, particularly for harder-to-adopt animal populations.

Following initial review, data from several shelters were excluded due to insufficient quality or completeness for the planned analyses. Only owner-surrendered animals were retained, with owner-requested euthanasia excluded. Further details regarding the data cleaning process can be found in Supplementary Tables 1–5. The number of qualifying owner-surrendered animals varied substantially across shelters. After cleaning to ensure that each row represented a unique animal, the shelter with the largest sample had 13,081 records, while the smallest had only 35. When restricting the dataset to animals with complete age and size data and outcomes classified as either adoption or negative, substantial reductions in data volume occurred for some shelters. In certain cases, all records were removed based on these criteria. After applying these filters, data from 19 shelters remained for analysis.

To facilitate comparison across organizations, outcome categories were standardized. The adoption category included only outcomes explicitly labeled as ‘adopted’, while the negative outcome category included ‘euthanasia’, ‘died’, and ‘missing’. Semantically similar outcomes with variant spellings were consolidated to ensure consistency. A comprehensive list of all outcome types and their corresponding classifications is provided in Supplementary Table 6. Outcomes such as ‘transferred’ or ‘in foster’ were excluded, as they do not represent final outcomes. Data on animals without a definitive resolution or those not intended for rehoming were also removed. The final dataset included 49,959 animals from 19 of the 23 shelters.

Metrics and analysis

LOS – the duration an animal remains within a shelter – is commonly used to support operational planning and improve animal flow.^32,33 Although LOS has not traditionally been applied to online rehoming platforms, this study proposes that LOS may serve a similarly informative function in the context of owner-to-owner rehoming. Specifically, LOS can reflect the relative difficulty of placing certain animals into adoptive homes. For animals listed on Rehome, LOS was calculated from the date the animal’s profile was created to the date the profile was updated to the adoption outcome. In contrast, LOS for shelter animals was calculated from intake date to recorded outcome date. While owners may occasionally fail to update listings following an adoption, Rehome mitigates this risk by notifying owners when applications post adoption are received, prompting them to close the listing. Understanding LOS can help prospective relinquishers set realistic expectations about how long rehoming may take. To evaluate differences in LOS, we conducted Cox proportional hazards regression and constructed Kaplan-Meier survival curves. The Cox regression produced hazard ratios (HR), quantifying the relative likelihood of adoption at any given point in time. Animals recorded with zero LOS were adjusted to a duration of 0.1 days, and analyses were restricted to animals with an LOS of 365 days or fewer. Additionally, infant animals were excluded from the analysis to prevent inflated LOS due to waiting periods before adoption eligibility. Assessment of the proportional hazards assumption revealed statistically significant results; however, given the large sample size, this significance likely arose from statistical sensitivity, as indicated by minimal rho values ranging from −0.06 to 0.004. Confirmatory analysis using subsampled data yielded non-significant p-values, further supporting the proportional hazards assumption. Additionally, graphical examination using the Nelson-Aalen cumulative hazard plot against Cox-Snell residuals affirmed proportional hazards, except for longer-duration events.

To assess whether online rehoming platforms can support successful placement of harder-to-adopt animals, this study employed adoption rate as a primary evaluative metric, similar in function to the live release rate commonly used in shelters. Adoption rate was chosen with the understanding that if these platforms do not yield successful outcomes for harder-to-adopt animals, their promotion as an alternative to shelter surrender may not be warranted. Traditionally, adoption rate is calculated as the number of adoptions divided by total outcomes; however, in this study, outcome filtering was applied to ensure conceptual consistency across the Rehome and shelter datasets. To enhance the robustness of our analysis, animals with a LOS of less than 1 day were excluded, as the majority were euthanized shortly after intake, likely at the request of the owner.

We calculated aggregate adoption rates for Rehome and the 19 included shelters, along with the range and standard deviation of adoption rates across shelters. To further examine outcome differences, we constructed 2 × 2 contingency tables and conducted chi-square tests for each shelter. Rows represented harder-to-adopt animals from Rehome and shelters, while columns captured adoption and negative outcomes. Rehome animals were matched to shelters geographically to improve comparability. Only shelters and corresponding Rehome areas with a minimum of five adoption and five negative outcome cases were included, yielding a final sample of 11 shelters for this analysis. As with the adoption rate calculations, animals with a LOS of less than 1 day were excluded from this test.

Together, these metrics and tests provide insights into how both systems perform in rehoming harder-to-adopt animals. While not exhaustive, they offer an empirical foundation for evaluating the potential of online rehoming platforms as a complementary strategy within the broader sheltering ecosystem.

Results

The Kaplan-Meier survival curve (Fig. 1) illustrates notable differences in adoption timing by platform and adoptability. Cats classified as easier to adopt within shelters experienced the fastest adoption timelines, with over half adopted within a short timeframe and a 44% higher probability of being adopted at any given time relative to harder-to-adopt shelter cats (HR: 1.44; 95% confidence interval [CI]: 1.38–1.50; Median LOS: 9). Harder-to-adopt shelter cats followed closely and were adopted more quickly than their counterparts on rehome platforms. Easy-to-adopt cats listed through Rehome had longer LOS and a 42% lower probability of adoption at any given time (HR: 0.58; 95% CI: 0.56–0.61; Median LOS: 21), while hard-to-adopt rehome cats had the lowest probability of adoption throughout the study period (HR: 0.49; 95% CI: 0.45–0.52; Median LOS: 23). These results suggest that shelters may be more effective at rehoming cats in a timely manner, particularly those considered easier to adopt, whereas online rehoming platforms may face more challenges, especially with harder-to-place animals.

Fig. 1. Time to adoption for cats by platform and adoptability: Kaplan-Meier Survival Curves.

The Kaplan-Meier survival analysis for dogs (Fig. 2) reveals a similar pattern to that observed in cats. Dogs listed through shelters, particularly those considered easier to adopt, experienced significantly shorter LOS compared to dogs listed on online rehoming platforms, with a 55% higher probability of adoption at any given time relative to harder-to-adopt shelter dogs (HR: 1.55; 95% CI: 1.50–1.60; Median LOS: 6).

Fig. 2. Time to adoption for dogs by platform and adoptability: Kaplan-Meier Survival Curves.

Easy shelter dogs showed the steepest decline in survival probability, indicating more rapid adoption. Harder-to-adopt shelter dogs came next. Both rehome groups – especially the hard-to-adopt dogs – were associated with lower probabilities of adoption over time, with 43 and 29% lower likelihoods of adoption at any given time for harder-to-adopt (HR: 0.57; 95% CI: 0.56–0.59; Median LOS: 21) and easier-to-adopt dogs (HR: 0.71; 95% CI: 0.69–0.73; Median LOS: 15) on Rehome, respectively, as survival probabilities remained higher for longer durations.

Shelters generally demonstrated higher adoption proportions compared to the Rehome platform (Fig. 3). Specifically, shelters achieved adoption rates of 88% for cats and 76% for dogs, whereas Rehome placements resulted in lower adoption rates of 76% for cats and 73% for dogs. However, it is important to note that adoption outcomes varied substantially across individual shelters, indicating considerable heterogeneity in shelter performance. The Chi-Square test compares the proportion of harder-to-adopt animals successfully placed through shelters versus Rehome within the same geographic regions. For statistically significant comparisons, shelters reported a higher proportion of adoptions in areas 1, 3, and 11. Conversely, Rehome outperformed shelters in areas 8 and 9. The strength of association, as measured by Cramér’s V, ranged from weak to moderate (0.16–0.40), suggesting some regional variability in adoption outcomes across platforms but generally consistent with the pattern of faster and more frequent adoptions occurring through shelters.

Fig. 3. Adoption rate for 11 shelters and their corresponding area on Rehome for harder-to-adopt animals with their Chi-Square p-values.

Discussion

Animal shelters continue to evolve by integrating novel tools and community-based strategies, such as encouraging the use of online rehoming platforms prior to animal surrender.^34–37 Online rehoming websites complement traditional shelter services by reducing financial and operational burdens, enabling owners to directly participate in rehoming their animals from home. While shelters commonly facilitate strategies like short- and long-term fostering,³⁸ online rehoming uniquely offers owners an active role in the rehoming process, mitigating stress experienced by animals within shelter environments.

As described in the introduction, Ly and Protopopova analyzed data from Rehome to determine characteristics influencing an animal’s odds of diversion from shelters. Their findings indicated that younger and purebred animals had higher diversion odds, whereas older animals and large dogs exhibited lower odds. Our results extend this research by providing estimates of the expected duration animals spend on Rehome and comparing adoption rates for harder-to-adopt animals listed on Rehome with those surrendered to shelters in corresponding geographic regions. This extension aims to assess Rehome’s utility as a complementary tool for shelters supporting harder-to-adopt animal populations.

In general, when owners use online rehoming websites to place their animals, those classified as harder-to-adopt experience lower probabilities of adoption at any given time, resulting in increased LOS. This pattern is consistent with prior research and is supported by Cox regression results, which show HRs below 1 for harder-to-adopt and easier-to-adopt animals on rehoming platforms compared to harder-to-adopt animals in shelters. For both cats and dogs, harder-to-adopt animals exhibit a median LOS approximately 1 week longer than their counterparts. Additionally, a substantial proportion of LOS data points were outliers, indicating variability. As animal shelters continue to engage with their communities, it is crucial that they assist owners in setting realistic expectations regarding the anticipated duration required to rehome harder-to-adopt animals. One practical recommendation derived from these findings is to encourage owners to list their animals on rehoming platforms as early as possible.

While the data indicate that harder-to-adopt animals surrendered to shelters have higher adoption rates compared to those listed on Rehome – contrary to our initial hypothesis – Rehome facilitated successful placements for many animals in this category. Additionally, the study highlighted significant variability in shelter adoption rates, with standard deviations of 19% for cats and 31% for dogs, possibly due to disparities in shelter resources, community demographics, or organizational policies. Notably, in certain regions, Rehome exhibited higher adoption rates than local shelters. Given the relative consistency of Rehome’s adoption rate for harder-to-adopt animals across areas, these differences are more likely attributable to variability among shelter outcomes rather than a combined effect of both systems.

Because fundamental differences exist between Rehome and traditional animal shelters, it would be inappropriate to conclude, based solely on the comparisons made in this study, that one is inherently superior to the other. Instead, these comparisons primarily serve to evaluate the potential utility of Rehome as a supplementary tool for animal shelters. Moreover, LOS and adoption rates should not be misconstrued as direct or absolute indicators of animal demand, as demand can be influenced by interventions such as targeted marketing campaigns,^18,23–25 as previously discussed. Consequently, decision-makers should leverage these insights to proactively enhance adoption efforts, preferably intervening before animals enter the shelter system. Shelters could recommend the use of online rehoming websites via social media or their website, especially during high intake months. Utilizing platforms like Rehome provides an alternative pathway for animal placement. Although animals classified as harder-to-adopt generally require longer to place, there is nonetheless evidence of success on rehoming websites for these animals.

Limitations and future work

Several limitations should be noted when interpreting the results of this study. The conditions experienced by animals listed on Rehome differ substantially from those in brick-and-mortar shelters. For instance, a negative outcome on Rehome typically indicates the animal was surrendered to a shelter or otherwise removed from the application process. In contrast, a negative outcome for a shelter animal may include outcomes such as euthanasia or death. These discrepancies in outcome definitions create a limitation in direct comparison and may result in potential double counts of animals appearing in both datasets.

The Rehome dataset is unevenly distributed across time, with lower utilization during its early implementation. For example, 73,382 animals were listed in 2020, compared to only 5,826 in 2017. This temporal skew overlaps with the COVID-19 pandemic, which may have influenced rehoming behaviors.

Simplifying outcome categories into binary classifications, namely, adoption and negative outcome, was necessary to enable cross-system comparison. However, this may oversimplify outcome complexity, especially given the diversity across shelters. Standardizing outcome labels across platforms and shelters would greatly improve future comparability. Approximately 43% of Rehome outcomes – particularly those labeled ‘keep-pet’ or ‘high-demand’ – were excluded due to ambiguity. Future studies may consider methods to interpret or track these ambiguous outcomes more accurately.

Several limitations to model accuracy were noted, including potential misclassification of certain cats as easier-to-adopt despite possessing behavioral or medical issues that warrant classification as harder-to-adopt. Furthermore, regional variability in shelter practices and adoption environments may also introduce geographical effects impacting the generalizability of the model. Regional variation in adoption rates underscores the need to investigate local factors influencing demand and explore experimental studies on rehoming platforms for harder-to-adopt animals.

Conclusion

This study evaluated the performance of Rehome, a peer-to-peer online rehoming platform, in facilitating adoptions for harder-to-adopt animals – specifically senior cats, senior dogs, and large dogs – compared to outcomes for similar animals surrendered to traditional animal shelters. While adoption rates for harder-to-adopt animals were generally higher in shelters, Rehome demonstrated consistent success in placing a substantial number of these animals across various regions. Furthermore, shelters exhibited considerable variability in adoption rates, whereas Rehome’s performance remained more stable. These findings suggest that online rehoming platforms like Rehome may offer a valuable complement to shelter services, particularly when used proactively to prevent shelter intake and minimize animal stress associated with the shelter environment.

Although harder-to-adopt animals typically experienced longer lengths of stay on Rehome than other animals, these durations are important for setting realistic expectations with owners. The ability to rehome directly from a home environment may not only reduce shelter crowding and operational costs but also preserve animal welfare by avoiding negative health outcomes and stress associated with shelter stays. Accordingly, shelters should consider integrating online rehoming platforms into their diversion strategies, particularly for owners seeking alternatives to surrendering their pets to shelters. Continued research is necessary to refine the metrics used to compare shelter and online outcomes, and to evaluate the long-term effectiveness of such platforms in supporting both animal welfare and community-based sheltering models.

Acknowledgments

First, the authors would like to thank HASS for funding this project. The authors would also like to thank April Huntsman and the team at Adopt-a-Pet who gave us access to their data and helped answer questions about the data. Finally, the authors would like to thank Andrew Rowan for his help with ideas for analyzing the rehome data and invaluable feedback.

Authors’ contributions

John Cornelison performed analysis, visualization, writing – original draft. Sue Neal contributed to conceptualization, analysis, writing – review and editing. Kevin Horecka was involved in conceptualization, analysis, writing – review and editing.

Statement of ethics

This work did not involve the use of animals nor human subjects and therefore ethical approval was not required for publication.

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