Multivariate Probit Regression Model Research Articles

English

The study was carried out with the specific objective of analyzing the socio-economic factors affecting adoption of dairy cattle milk production technologies by smallholder dairy farmers in Mosop Sub County, Nandi County, Kenya. The study was guided by Innovation Diffusion Theory and descriptive research design was used. Cluster sampling and simple random sampling techniques were used to collect data from a sample of 198 smallholder dairy farmers, 70 large scale dairy farmers and 30 extension staff. To estimate the survey data, multivariate probit regression model was used. Descriptive statistics results revealed that 90% of smallholder dairy farmers were male-headed with 16.8 years of farming experience. Multivariate probit regression results showed that an increase in education level of the household head increased the marginal effect of adopting milking equipment by 7.5 percentage points. Results further revealed that a unit increase in the years of experience in dairy farming by the dairy farmers’ household head resulted in a decrease in the marginal effect of adopting the vaccination regime by 24 percentage points, whereas gender of the household head increased the marginal probability of adopting milk equipment technologies by 56 percentage points. Male gender of the household head also increased the marginal effect probability of adopting dairy cattle vaccination regime technologies by 103 percentage points. Therefore, farmer to farmer exchange visits needs to be strengthened, introduction of farmers’ mentorship programmes and revamping of extension service are paramount for technology adoption. Consequently, the county and national governments and their agencies should come up with strategies that would enhance the capacities of the dairy farmers so that they can continue appreciating new dairy cattle milk production technologies. Key words: Dairy cattle milk production technologies, smallholder dairy farmers, multivariate probit regression.

Factors Influencing the Adoption of Climate-Smart Agricultural Technologies Among Rice Farmers in Northern Ghana

In recent years, the effects of climate change on agriculture in northern Ghana have attracted the attention of researcher and policy makers. Stakeholders including research institutions have developed several climate-smart agricultural technologies aimed at reducing the negative effects of climate change on farmers. This study examined the factors influencing rice farmers’ adoption of these technologies using Multivariate Probit and Poisson regression models. Primary data were collected from 543 rice farmers using a semi-structured questionnaire. The results revealed that the intensity of farmers’ adoption of climate-smart agricultural technologies is positively influenced by farmers’ experience in rice cultivation, access to mass media, training, and perceived decrease in the amount of rainfall. On the other hand, farm size, the distance between farmers’ residence and farm sites, location and the observed increase in temperatures negatively influenced farmers’ intensity of adoption of the technologies. This study highlights the essential role of government regarding training of farmers and awareness creation for the adoption of the climate-smart agricultural technologies.

Household Attitudes towards Sustainable Management of Urban Green Spaces and Parks in Lagos State, Nigeria

The attitude of urban dwellers is essential to the sustainable management of green spaces and parks in their environment. The study was carried out to examine various ways of raising fund, preferred mode of contribution and determinants of mode of contribution of the respondents to sustainable management of urban green spaces and parks. A total of 120 respondents were purposively selected based on the existence of green spaces and parks in six local government areas of Lagos state, Nigeria, Frequency counts, percentages and multivariate Probit regression model were used to analyze the data. The result shows that voluntary donations and Tax were rated by 40.8% of the respondents respectively as the most viable way of generating funds for sustainable management and maintenance of urban green spaces and park in Lagos state. Also, 46.67% of the respondents were willing to donate or pay cash as their means of contributing to sustainable management of green spaces and parks, while 6.67% were not willing to donate or render any assistance for sustainable management of green spaces and parks. The study affirmed that the Sex, Marital status, and average monthly income of the respondents had positive and significant influence on the respondents’ contribution to sustainable management of urban green space and parks, while educational level had a negative influence on the mode respondents’ contribution to sustainable management of green spaces and parks.

Prediction and Inference With Missing Data in Patient Alert Systems

We describe the Bedside Patient Rescue (BPR) project, the goal of which is risk prediction of adverse events for non-intensive care unit patients using ∼100 variables (vitals, lab results, assessments, etc.). There are several missing predictor values for most patients, which in the health sciences is the norm, rather than the exception. A Bayesian approach is presented that addresses many of the shortcomings to standard approaches to missing predictors: (i) treatment of the uncertainty due to imputation is straight-forward in the Bayesian paradigm, (ii) the predictor distribution is flexibly modeled as an infinite normal mixture with latent variables to explicitly account for discrete predictors (i.e., as in multivariate probit regression models), and (iii) certain missing not at random situations can be handled effectively by allowing the indicator of missingness into the predictor distribution only to inform the distribution of the missing variables. The proposed approach also has the benefit of providing a distribution for the prediction, including the uncertainty inherent in the imputation. Therefore, we can ask questions such as: is it possible this individual is at high risk but we are missing too much information to know for sure? How much would we reduce the uncertainty in our risk prediction by obtaining a particular missing value? This approach is applied to the BPR problem resulting in excellent predictive capability to identify deteriorating patients. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Paid Leave, Welfare, and Material Hardship After a Birth

ObjectiveTo examine the relationships between state‐sponsored paid leave, Temporary Assistance for Needy Families (TANF) generosity and participation, and material hardship among low‐income single women following a birth.BackgroundPast research has examined the relationship between public assistance and paid leave after a birth, finding reductions in program enrollment. This research has not accounted for variation in program benefits across states and has largely overlooked implications for family well‐being.MethodWe use a sample (N = 1,174) of low‐income single women who gave birth between 1997 and 2001 from the Survey of Income and Public Program Participation and include measures of TANF generosity across states and over time that were constructed from the Welfare Rules database. A series of multivariate probit regression models are used to estimate the relationship between TANF generosity, paid leave availability, welfare participation, and material hardship while controlling for relevant individual and state‐level characteristics.ResultsPaid leave was associated with less TANF participation, but these reduction are related to the program's generosity. Paid leave, states' welfare work exemptions for mothers of infants, and TANF earnings eligibility limits were associated with a lower likelihood of experiencing some forms of material hardship.ConclusionSome forms of paid leave and TANF program generosity are related to reductions in TANF participation and material hardship after a birth for low‐income single women.ImplicationsThis study demonstrates that researchers should account for variation in TANF programs when considering changes in program enrollment associated with paid leave. Results suggest paid leave may help alleviate some forms of economic stress after a birth, which has implications for maternal, infant, and family well‐being.

Fiscal Consolidations in Polish Local Governments in the Period 2008–2016: Course and Causes

The article presents strategies of fiscal consolidations conducted in Poland in cities with powiat rights, and a study of causes behind the decision to conduct such fiscal consolidations. Local governments showing an improvement of their public finances have been distinguished; and based on that, a description of various methods of reduction of expenditures, deficit or debt in Polish local governments has been presented. An analysis of data shows the dominance of consolidations on the revenue side. The study has identified few cases of expenditure cuts, and they mostly included investments, public transport and housing expenditures. Besides the description of data concerning fiscal consolidations, the article also presents a multivariate probit regression model and logistic regression model estimated based on panel data aimed at studying the determinants of conducting financial consolidations in a given local government. The hypotheses that macroeconomic variables and the election cycle have a statistically significant effect on the decision to conduct consolidation have been positively verified; whereas the hypothesis that other political factors significantly affect the probability of improvement of the financial situation of a local government have been verified negatively.

UNDERSTANDING THE MULTIPLE SOURCES DRIVERS OF AGRICULTURAL INCOME AMONGST SMALLHOLDER FARMERS IN SOUTHERN MALI

Multiple sources of income are important strategies for reducing smallholder farmer liquidity constraints and over dependency on single income source. However, farmers in Southern Mali, especially Malian high agricultural potential region are still faced with liquidity constraints resulting from low income from cash crop (cotton) production. Therefore, this study was carried out to understand the factors that motivate farmers’ decision to engage in several income-generating activities. Cross-sectional data were collected from 134 randomly sampled smallholder farmers from three villages in different agro-ecological zones in Southern Mali. Multivariate probit (MVP) regression model was used to estimate the effect of socioeconomic and institutional factors on farmer participation in different sources of farm income. Correlation analysis showed that there is a significant correlation between the different income sources. Results from the econometric model revealed that the age of the family head determines the probability of farmers' participating in multiple sources of incomes, family size, dependency ratio, land tenure, education level, access to agricultural credit and extension services, cash crop income, off-farm income, input prices, agricultural output prices, and rural infrastructure. These results imply that policymakers and agricultural development programs should target strengthening of institutions as well as enhancement of farmers’ access to productive resources.

Adoption of climate change adaptation strategies by maize-dependent smallholders in Ethiopia

Climate change is an environmental process that is among the most limiting factors for increasing or even maintaining food production by small-farmer communities in Sub Saharan Africa (SSA). Adoption of climate change adaptation strategies that increase agricultural productivity and at the same time building farmers’ resilience capacity has become a top policy priority in SSA. In this study, we investigate how maize-dependent smallholders in Ethiopia adapt to climate change. Both household and plot-level data were collected, and subsequently analysed by a multivariate probit regression model. Results show that most climate change adaptation strategies implemented by maize-dependent smallholders, are complementary. Combining conservation tillage, mixed maize-legume cropping and terracing along with the use of drought-resistant maize varieties allows farmers to increase productivity while building resilience to climate change more than a subset of these strategies. Findings indicate that the likelihood of adopting soil and water conservation practices, drought-resistant maize varieties and chemical fertilizers significantly increase among young and male-headed households as well as farmers having confidence in extension agents and membership in local organisations. Hence, policies should aim at further building agricultural extension agents’ capacity by providing effective and continuous education and training on climate change impacts and responses. Promoting family ties and household memberships in local organisations through facilitating mutual cooperation and communication among farming communities would help to foster adoption of climate change adaptation strategies.

Determinants of adoption of alternative response to foot and mouth disease: micro-level evidence of smallholder pastoralist in north East District, Botswana.

This paper examines factors influencing the adoption of alternative response to Foot and Mouth Disease (FMD) among smallholder beef producers in the dry lands of Africa, specifically, North East district in Botswana. Principal component analysis was used to categorise FMD responses. Thereafter, a multivariate probit regression model was used to examine the effect of socioeconomic and institutional factors on the adoption of alternative responses to FMD. The study found that household size, opportunity cost incurred, frequency of contact with extension officers, training received on FMD, distance to the nearest market, as well as distance to grazing and water areas had a positive effect on the adoption of alternative responses to the outbreak. We conclude that although producers are aware of the detriments of FMD to their livelihoods, some still choose not to adopt the responses and socioeconomic and institutional characteristics play a role.

Financial Capability: Clinicians' Assessment of Beneficiaries With Dual Diagnoses

Objective: Adults with mental health disorders whose ability to work is sufficiently impeded are entitled to financial supports from the Social Security Administration. Beneficiaries determined to be incapable of managing these funds are supposed to be assigned a representative payee to assist beneficiaries in meeting their needs. However, patterns of payee assignment suggest that payee assignment is impacted by factors other than those the Social Security Administration instructs clinicians to consider. In this study, we tested the association between clinicians' judgments of their clients' financial capability and hypothesized predictors (demographic characteristics, psychiatric diagnosis, recent alcohol and other substance use, self-rated money mismanagement, recent homelessness, and provider characteristics). We posited that predictors might act indirectly on capability judgment via their impact on beneficiaries' money management. Methods: Altogether, 261 people receiving intensive mental health care who did not have payees or fiduciaries were enrolled after providing written informed consent. These beneficiaries completed in-person assessment interviews, reporting demographic characteristics, treatment history, substance use, and homelessness. Mental health clinicians identified by the beneficiaries were enrolled in the study and asked to judge their clients' financial capability with standard Social Security instructions for determining capability. Bivariate associations between hypothesized predictors and clinicians' determinations of incapability were tested. In multivariate probit regression models, incapability determination was modeled as a function of all beneficiary and clinician characteristics that had significant bivariate associations with the outcome. Results: Providers identified 24% of their clients as financially incapable. Determinations of financial incapability were unrelated to any beneficiary or provider demographic characteristics but were positively associated with money mismanagement, homelessness, and having a psychotic disorder. Alcohol use and other substance use were only significantly associated with capability determinations indirectly through their effects on money mismanagement. Conclusions: Providers' judgments of beneficiaries' capability to manage their funds were associated with factors that were consistent with Social Security Administration guidelines and were, importantly, not associated with personal characteristics. This finding suggests that guidelines can be fairly applied by clinicians and that reported inconsistencies in payee assignment are accounted for by other factors. The Social Security Administration is currently considering other approaches to standardize capability determinations.

Farm Gate Dairy Milk Marketing Channel Choice in Kericho County, Kenya

This study examined the factors that determined dairy farmer households’ choice of a commercial milk marketing channel in Kericho County, Kenya. Multistage cluster sampling technique was employed in collecting data from 432 dairy farmers and survey data was analyzed using multivariate probit regression model. Marginal effect results revealed that a unit change in household’s pasture farm size and partnership in lobbying for better milk price increased the probability of selling milk only to commercial milk buyer by one and 19 percentage points respectively. The number of cows milked per day and milk storage/cooling raised the probability of selling raw milk to commercial buyers by 2.3 and 16.1 percentage points respectively. Commercial milk buyers valued security in raw milk supply which came from trusted relationships and from contracts with the dairy milk seller households. To increase the choices of commercial dairy milk marketing channels and hence the switching power of the dairy farmer households in Kericho County and by extension, Kenya as a whole, this study recommends strengthening the capacity of dairy farmer households by up scaling their technical knowhow and by enlarging their herd sizes. Further, the study recommends group formation, partnership development and increased financial investments in livestock milk markets by national and county governments.

Willingness of smallholder rubber farmers to participate in ecosystem protection: Effects of household wealth and environmental awareness

The rapid expansion of natural rubber farming in southern China has led to negative environmental consequences, such as soil erosion and biodiversity loss. Therefore, local governments have made the restoration and protection of ecosystems a major policy issue. However, such efforts will only be successful if local communities participate. Using cross-sectional data on 612 smallholder rubber farmers in Xishuangbanna, this study investigates the willingness of smallholder rubber farmers to participate in ecosystem protection. We employ a multivariate probit regression model to estimate three ways of participating in environmental protection: (i) through monetary contributions of rubber farmers, (ii) by reducing rubber areas, and (iii) through the provision of free labor. The results show that most rubber farmers are willing to participate in local ecosystem protection. While wealthier households tend to participate by contributing money and providing free labor, poorer households prefer to reduce their rubber planting areas. Approximately 10% of the farmers believe that rubber cultivation has positive environmental effects and therefore abstain from participating in ecosystem protection measures. Our findings have important implications for policymakers who want to implement programs to restore and protect ecosystems in Xishuangbanna and other rubber planting regions in southern China.

English

This study aimed at identifying factors affecting farm gate milk price heterogeneity in dairy farmer households in Kericho County, Kenya. Multistage cluster sampling technique was used to collect data from 432 dairy farmer households. To estimate survey data, multivariate probit and selectivity biased mixed-effects linear regression models were used. Results showed that increased daily milk output sold and number of commercial milk buyers resulted in increased probability of farm gate milk price variability by 3.8 and 12%, respectively. However, number of milking cows and trust levels on commercial milk buyer by seller decreased farm gate milk price heterogeneity by 89 and 87%, respectively. While selling through commercial, milk buyers had significant positive effect on farm gate milk price, majority of dairy farmer households were hesitant to engage with them since milk buyers valued supply security which came from trusted relationships and contracts. Therefore, critical strategies to improve farm gate milk prices are needed. These include strengthening of dairy farmer groups and partnership development, bolstering milk cooperative societies and increased financial investments in livestock milk markets by national and county governments.   Key words: Farm gate milk price, price heterogeneity, mixed-effects linear regression, dairy farmer households, Kericho County, Kenya. &nbsp

Care-Seeking Patterns and Direct Economic Burden of Injuries in Bangladesh.

This study provides a comprehensive review of the care-seeking patterns and direct economic burden of injuries from the victims’ perspective in rural Bangladesh using a 2013 household survey covering 1.17 million people. Descriptive statistics and bivariate analyses were used to derive rates and test the association between variables. An analytic model was used to estimate total injury out-of-pocket (OOP) payments and a multivariate probit regression model assessed the relationship between financial distress and injury type. Results show non-fatal injuries occur to 1 in 5 people in our sample per year. With average household size of 4.5 in Bangladesh--every household has an injury every year. Most non-fatally injured patients sought healthcare from drug sellers. Less than half of fatal injuries sought healthcare and half of those with care were hospitalized. Average OOP payments varied significantly (range: $8–$830) by injury type and outcome (fatal vs. non-fatal). Total injury OOP expenditure was $355,795 and $5000 for non-fatal and fatal injuries, respectively, per 100,000 people. The majority of household heads with injuries reported financial distress. This study can inform injury prevention advocates on disparities in healthcare usage, OOP costs and financial distress. Reallocation of resources to the most at risk populations can accelerate reduction of preventable injuries and prevent injury related catastrophic payments and impoverishment.

Risk Model of Bacterial Coinfection in Children with Severe Viral Bronchiolitis.

Background Among children with respiratory failure from viral lower respiratory tract infection (LRTI), up to 39% will develop pulmonary bacterial coinfection, yet nearly all will receive antibiotics. We sought to identify patients with viral LRTI requiring mechanical ventilation at low risk of bacterial coinfection through the use of a risk prediction model. Methods We performed a retrospective cohort study identifying all patients admitted to the intensive care unit with laboratory-confirmed viral LRTI requiring invasive mechanical ventilation over a 2-year period and partitioned data in experimental and validation datasets. A multivariate probit regression model was constructed including variables associated with bacterial coinfection in the experimental dataset. Model was validated and recalibrated using the validation dataset. Model discrimination was assessed using receiver operating characteristic curve analysis. Results There were 126 patients included in the analysis. Variables associated with bacterial coinfection included tracheostomy in situ, Gram-stained smear white blood cells, and bacteria. The final recalibrated model discriminating between no coinfection and coinfection had an area under the curve of 0.8696. Conclusion Our prediction model identifies patients with viral LRTI requiring mechanical ventilation at very low risk of bacterial coinfection and has the potential to decrease antibiotic utilization without negatively impacting clinical outcome.

Adaptation and resilience to climate change and variability in north-east Ghana

North-east Ghana is characterised by frequent droughts and floods which adversely affect farming, the primary source of livelihood for majority of households in the region. Given the rapidly changing climate, these extreme events are expected to become more pervasive. This paper assesses the capacity of farm households to deal with climate-related risks. Using survey data from 409 farm households in three districts in north-east Ghana, this study specifically examines households' resilience to climate change and variability, and the determinants of the number and choice of adaptation measures adopted by households. Results from an indicator-based climate resilience assessment indicate that female-headed households and households located in Bongo district are less resilient to climate change and variability. The results also suggest that interventions aimed at building households' climate resilience should be mostly directed at raising household income, improving food security, and asset building. To enhance resilience to climate change and variability, households have mostly adopted a combination of autonomous adaptation measures, such as altering the timing of planting, use of drought tolerant and early maturing crop varieties, and switching to crops that are less sensitive to climate stress. Employing Poisson and multivariate probit regression models, it was found that increasing farmers' knowledge of climate change as well as building the capacity of extension agents to deliver information on climate change and appropriate adaptation measures are key to successful adaptation in the study region.

Factors affecting farmers’ coping and adaptation strategies to perceived trends of declining rainfall and crop productivity in the central Rift valley of Ethiopia

Farmers apply several and often different farmer-specific strategies to cope with and adapt to the perceived trend of declining rainfall and crop productivity. A better understanding of the factors affecting farmers’ coping and adaptation strategies to counteract both trends is crucial for policies and programs that aim at promoting successful rainfed agriculture in Ethiopia. The objective of this study was to identify the major factors that affect farmers’ coping and adaption strategies to rainfall variability and reduction in crop yield in the central Rift valley (CRV) of Ethiopia. A survey was conducted among 240 randomly selected farmers within six kebeles in the CRV using structured and pretested questionnaires. Multivariate probit (MVP) regression model was used to identify these key factors that affect farmers’ coping and adaptation strategies to the declining trends of rainfall and crop productivity. Generally, this study identified several factors that affect farmers’ choices of certain strategies, which can be grouped in four major factors: (1) livestock and landholdings, (2) availability of labour and knowledge, (3) access to information, and (4) social and cultural factors. Farmers with better resources, labour, knowledge, access to information and social capital had better coping and adaptation strategies to the declining rainfall and crop productivity. To conclude, improving farmers’ asset accumulation, access to information and knowledge are needed. Moreover, strengthening social capital and labour sharing institutions in the CRV is crucial to increase farmers’ capacities to cope with and adapt to environmental changes such as rainfall and crop yield variability.

USE OF UNSAFE COOKING FUELS AND BOILING PRACTICE AMONG INDONESIAN HOUSEHOLDS: EMPIRICAL EVIDENCE FROM THE 2012 DEMOGRAPHIC AND HEALTH SURVEY

Improved drinking-water sources need not be microbiologically safe. Hence, households usually boil their water prior to drinking. However, this practice can potentially harm health when households rely on unsafe cooking fuels. In Indonesia, little is known about the association of use of unsafe fuels with boiling practice. Hence, an analysis was carried out to elicit information regarding boiling practice using unsafe fuels. Such information would be useful in determining appropriate household water treatments. Data from the 2012 Indonesia Demographic and Health Survey (IDHS) were analysed to examine the relationship between the use of unsafe cooking fuel and choosing boiling as household water treatment. Bivariate and multivariate probit regression models (PRM) were fitted and compared using average marginal effects (AME) and its respective 95 per cent confidence interval (95% CI) as measures of association. The results suggest that using kerosene as cooking fuel is positively significantly associated with higher probability of practicing boiling (p = 0.006; AME: 0.019; 95% CI: 0.0056, 0.0333). This is also true for use of solid fuel (p< 0.001; AME: 0.3115; 95% CI: 0.3026, 0.3203). These association holds, albeit attenuated (Kerosene, p< 0.001; AME: 0.02706; 95% CI: 0.0186, 0.0355; Solid fuel, p< 0.001; AME: 0.0373; 95% CI: 0.02839, 0.0463), after the control variables are included. The authors suggest that stakeholders should promote the use of other household water treatment technologies to reduce the boiling practice using unsafe cooking fuels as to minimize the risk of smoke related infections. Moreover, universal access and equity to safe drinking water and sanitation facility in Indonesia should be realised to reduce demand of boiling water using unsafe cooking fuels.

Shared environmental responses drive co‐occurrence patterns in river bird communities

Positive or negative patterns of co‐occurrence might imply an influence of biotic interactions on community structure. However, species may co‐occur simply because of shared environmental responses. Here, we apply two complementary modelling methodologies – a probabilistic model of significant pairwise associations and a hierarchical multivariate probit regression model – to 1) attribute co‐occurrence patterns in 100 river bird communities to either shared environmental responses or to other ecological mechanisms such as interaction with heterospecifics, and 2) examine the strength of evidence for four alternative models of community structure. Species co‐occurred more often than would be expected by random community assembly and the species composition of bird communities was highly structured. Co‐occurrence patterns were primarily explained by shared environmental responses; species’ responses to the environmental variables were highly divergent, with both strong positive and negative environmental correlations occurring. We found limited evidence for behaviour‐driven assemblage patterns in bird communities at a large spatial scale, although statistically significant positive associations amongst some species suggested the operation of facilitative mechanisms such as heterospecific attraction. This lends support to an environmental filtering model of community assembly as being the principle mechanism shaping river bird community structure. Consequently, species interactions may be reduced to an ancillary role in some avifaunal communities, meaning if shared environmental responses are not quantified studies of co‐occurrence may overestimate the role of species interactions in shaping community structure.

Risk Score Algorithm for Treatment of Persistent Apical Periodontitis

Persistent apical periodontitis related to a nonvital tooth that does not resolve following root canal treatment may be compatible with health and may not require further intervention. This research aimed to develop a Deterioration Risk Score (DRS) to differentiate lesions requiring further intervention from lesions likely to be compatible with health. In this cross-sectional study, patient records (2003-2008) were screened for root-filled teeth with periapical radiolucency visible on periapical radiographs taken at treatment and at recruitment at least 4 yr later. The final sample consisted of 228 lesions in 182 patients. Potential demographic and treatment risk factors were screened against 3 categorical outcomes (improved/unchanged/deteriorated), and a multivariate independent multinomial probit regression model was built. A 5-level DRS was constructed by summing values of adjusted regression coefficients in the model, based on predicted probabilities of deterioration. Most lesions (127, 55.7%) had improved over time, while 32 (14.0%) remained unchanged, and 69 (30.3%) had deteriorated. Significant predictors of deterioration were as follows: time since treatment (relative risk [RR]: 1.11, 95% confidence interval [CI]: 1.01-1.22, p = .030, rounded beta value = 1, for every year increase after 4 yr), current pain (RR: 3.79, 95% CI: 1.48-9.70, p = .005, rounded beta value = 13), sinus tract present (RR: 4.13, 95% CI: 1.11-15.29, p = .034, rounded beta value = 14), and lesion size (RR: 7.20, 95% CI: 3.70-14.02, p < .001, rounded beta value = 20). Persistent apical periodontitis with DRS <15 represented very low risk; 15-20, low risk; 21-30, moderate risk; 31-40, high risk; and >40, very high risk. DRS could help the clinician identify persistent apical periodontitis at low risk for deterioration, and it would not require intervention. When validated, this tool could reduce the risk of overtreatment and contribute toward targeted care and better efficiency in the timely management of disease.