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American Journal of Public Health Research
DOI: 10.12691/ajphr-1-1-3

The Implementation of a Tele-Homecare System with Service Oriented Architecture and HL7 Message Transmission Standard
Ching-Sung Wang

American Journal of Medical and Biological Research
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The Influence of Ethanol on Pyruvate Kinases Activity in Vivo, in Vitro, in Silico
Lelevich Sergey Vladimirovich, Khrustalev Vladislav Victorovich, Barkovsky Eugene Victorovich, Shedogubova Tatyana Aleksandrovna

American Journal of Medical Sciences and Medicine
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Clinical and Histological Features in Wegener Granulomatosis
Li Cavoli Gioacchino, Passantino Rita, Bono Luisa, Tortorici Calogera, Ferrantelli Angelo, Giammarresi Carlo, Rotolo Ugo

American Journal of Infectious Diseases and Microbiology
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The Curse of Lymphatic Filariasis: Would the Continual Use of Diethylcarbamazine Eliminate this Scourge in Papua New Guinea?
Anne Lanham, Lillian Mwanri

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Protective Factors for Literacy Achievement: The Role of Social-Emotional Learning and Executive Function in Reducing Academic and Behavioral Risk

Kimberly Moody*, CCC SLP, Jason Herron, Reagan Murnan

TALS, Wichita State University, Wichita, USA

Abstract: Students placed at academic and behavioral risk often face overlapping challenges that hinder engagement and long-term achievement. This study explored how social-emotional learning (SEL) and self-regulation capacity (SRC) serve as protective factors within a school-based mentoring and support program implemented across 24 schools. Guided by frameworks of resilience and active, self-regulated learning, the study examined how SEL and SRC support literacy growth and overall school engagement through improved attendance and behavior. Findings indicated that students demonstrating stronger SEL and SRC skills were more likely to show improvements in literacy performance and reductions in disciplinary incidents and absenteeism. These results highlight the importance of integrating regulation-based and trauma-informed supports within literacy and prevention initiatives. Implications for educational policy and practice emphasize the need for coordinated, cross-sector efforts that strengthen protective factors and promote equitable learning environments.

Keywords: academic risk, literacy, protective factors, self-regulation

Received April 03, 2026; Revised May 04, 2026; Accepted May 12, 2026

Citation: Kimberly Moody, CCC SLP, Jason Herron, Reagan Murnan, Protective Factors for Literacy Achievement: The Role of Social-Emotional Learning and Executive Function in Reducing Academic and Behavioral Risk. Research in Psychology and Behavioral Sciences, 14 (1). 1-12. January 2026. doi:10.12691/rpbs-14-1-1

1. Introduction

Students identified as at risk for academic and behavioral difficulties encounter multiple barriers that interfere with learning and long-term success [1]. These barriers often manifest as chronic absenteeism, frequent suspensions, and overall disengagement from school—factors that reduce instructional time and substantially increase the likelihood of academic failure [2,3]. Among the domains most affected by these risk factors is literacy. Reading proficiency, in particular, serves as a foundational gateway skill that predicts high school graduation, postsecondary attainment, and lifelong opportunities [4]. However, despite sustained national efforts to improve reading outcomes, large numbers of students continue to perform below grade level in English Language Arts (ELA), particularly those who experience difficulties with self-regulation and executive functioning [5,6,7,8].

Protective factors such as strong social-emotional learning (SEL) skills and self-regulation capacity (SRC) can mitigate the effects of risk [9]. SEL encompasses competencies such as self-awareness, self-management, and relationship skills that foster resilience and positive adjustment [10]. SRC reflects students' sense of self-efficacy, connection to school, and use of self-regulation strategies—capacities that support academic persistence and the ability to engage productively in instruction [11]. Together, SEL and SRC have been associated with stronger reading achievement, greater engagement, and lower behavioral risk [12,13]. These factors allow students to regulate frustration, sustain attention to text, and develop comprehension strategies, all of which protect against literacy difficulties [6].

2. Literature Review

Students placed at risk often face multiple, overlapping challenges that affect school success. Chronic absenteeism, typically defined as missing 10% or more of the school year, limits access to instruction and disrupts continuity of learning [2,14]. Absenteeism is strongly associated with lower literacy outcomes, weaker peer relationships, and higher dropout rates [15]. Similarly, exclusionary discipline practices such as in-school suspension (ISS) and out-of-school suspension (OSS) remove students from instructional settings and contribute to cumulative learning loss [3]. These practices are not distributed evenly; students from historically marginalized backgrounds and those with existing academic struggles are more likely to experience suspensions [16]. Together, absenteeism and disciplinary removals not only reduce instructional time but also weaken students' sense of belonging and engagement, increasing the likelihood of being placed at risk [2,16]. One of the most enduring consequences of these factors is difficulty attaining grade-level reading proficiency, which is essential for academic progression [4].

2.1. SEL as a Protective Factor

Protective factors are defined as individual or contextual attributes that moderate or buffer the effects of risk exposure, helping to promote positive adaptation in the face of adversity [17]. These factors support resilience by enabling individuals to access internal and external resources that foster competence and well-being. SEL represents one such protective factor, encompassing competencies such as self-awareness, self-management, social awareness, relationship skills, and responsible decision-making [10]. Large-scale meta-analyses confirm that SEL interventions yield positive outcomes across academic, behavioral, and emotional domains [18]. For example, SEL programming has been shown to reduce aggressive behavior, improve attendance, and increase cooperation in classrooms [19]. When students are able to identify emotions, regulate responses, and build constructive relationships, they are more engaged learners and less likely to exhibit disruptive behaviors [20]. In this way, SEL serves as a protective factor that reduces exposure to risk conditions, such as exclusionary discipline, while promoting cognitive engagement necessary for literacy learning.

2.2. SRC as a Protective Factor

SRC refers to the constellation of skills and dispositions that enable students to manage their behavior, emotions, and thinking in ways that support learning [11]. This includes self-efficacy, a sense of school connection, and the use of regulation strategies, all of which contribute to persistence, attention, and resilience in the classroom. SRC aligns closely with cognitive models of self-regulation, as it reflects students' ability to sustain focus, manage frustration, and engage productively with academic tasks. Research demonstrates that SRC contributes uniquely to reading development beyond traditional predictors such as phonological awareness and vocabulary [5]. For example, students with stronger regulation capacities are better able to concentrate on decoding, monitor their comprehension, and adjust strategies when meaning breaks down [21]. In addition, self-efficacy and a sense of belonging support engagement and reduce avoidance behaviors that undermine literacy learning. Emerging studies also indicate that deficits in regulation are associated with persistent reading difficulties, underscoring the importance of strengthening SRC within literacy interventions [6]. Thus, SRC can be understood as both a protective factor and a critical contributor to literacy success, enabling students to engage effectively in reading instruction and lowering their risk of falling behind academically.

2.3. Integrating SEL, SRC, and Academic Outcomes

Although SEL and SRC have often been examined independently [11,22], recent research suggests that they are interrelated constructs that jointly influence academic outcomes [12,13]. Both involve processes of self regulation, persistence, and goal-directed behavior, and both are predictive of classroom engagement and achievement [12]. SEL interventions strengthen regulatory capacities by fostering attention, emotion regulation, and social connectedness, while SRC reinforces the cognitive and motivational aspects of SEL, such as planning, monitoring one's actions, and sustaining effort [13]. Importantly, both constructs have been consistently linked to stronger academic performance and reduced disciplinary events [23,24]. Yet, much of the existing research in this area remains fragmented. Many studies focus either on academic outcomes (such as reading) or on behavioral outcomes (such as suspension reduction), rather than examining both simultaneously. This narrow scope limits understanding of how SEL and SRC may function together as protective factors across multiple domains of risk. Addressing this gap requires a more integrated approach, one that considers how SEL and SRC jointly reduce behavioral challenges while promoting literacy achievement and overall school success [25,26,27].

2.4. Theoretical Framework

This study is grounded in the Active View of Reading (AVR) [6], which conceptualizes reading as an active, self-regulated, and motivated process that draws upon cognitive, linguistic, and social-emotional systems. According to the AVR, reading achievement depends not only on linguistic knowledge but also on executive functions, motivation, and self-regulation capacities that enable students to flexibly coordinate attention, monitor comprehension, and persist through challenges [6]. This expanded view of reading provides a unifying lens for understanding how students' social-emotional and self-regulatory skills support literacy development.

The AVR builds upon foundational theories of self-regulation and resilience. Self-regulation theory emphasizes the interaction between cognitive and emotional processes in shaping learning outcomes [11], while resilience theory highlights the role of protective factors in buffering children against the negative effects of risk [17]. Within this integrated framework, SEL and SRC are conceptualized as protective factors that enable students to regulate behavior, build adaptive relationships, and sustain academic engagement even in the face of adversity such as absenteeism or disciplinary exclusion. These constructs align with the AVR's emphasis on the dynamic interplay between motivation, regulation, and cognition during reading.

By situating SEL and SRC within the Active View of Reading and drawing on the complementary insights of self-regulation and resilience theory, this study positions these skills as central mechanisms that promote literacy achievement and mitigate behavioral and academic risk. Students with stronger SRC are more capable of sustaining attention, monitoring comprehension, and adjusting strategies as they read, processes that exemplify the active, coordinated nature of skilled reading. In this way, SEL and SRC serve not only as protective factors within resilience theory but also as the behavioral and emotional engines that drive the active reading process itself.

2.5. Purpose of the Study

Grounded in the Active View of Reading, this study extends prior research by examining how SEL and SRC operate as protective factors across multiple domains of school functioning. Although prior research demonstrates that SEL and SRC promote positive youth outcomes [28,29], relatively few studies have examined how these skills function within the integrated cognitive, motivational, and emotional systems that support literacy and academic achievement [6,26]. Consistent with the Active View of Reading, which positions reading as an active, self-regulated process involving executive function, motivation, and social-emotional competence, this study explores how these same regulatory capacities extend beyond literacy to influence broader indicators of school success. SEL and SRC are often studied in isolation, typically focusing on academic or behavioral outcomes [22,30]. Yet evidence suggests that these skills may simultaneously influence literacy risk, attendance, and challenging behaviors [31]. However, research using applied, multi-school program data to explore these cross-domain effects remains limited [25,26]. Most existing evaluations focus narrowly on either academic or behavioral outcomes, without examining how SEL and SRC interact across both areas [23,24]. As a result, there is limited understanding of how these self-regulatory and social-emotional capacities function as protective factors that buffer the combined effects of academic and behavioral risk within school-based interventions.

The present study addresses this gap by evaluating outcomes from a prevention-oriented program designed to support youth placed at risk. Guided by the Active View of Reading and supported by resilience and self-regulation theory, the program model reflects the integration of cognitive, emotional, and behavioral supports that foster engagement and persistence in learning. Implemented in 24 schools, the program combines daily mentoring, weekly group sessions targeting SEL, SRC, and prosocial behaviors, academic support, and a trauma-informed de-escalation protocol rooted in Trust-Based Relational Intervention (TBRI) [32]. Using fall and spring data for 246 students with complete outcome records, the study examined whether SEL and SRC predicted changes in ELA risk, attendance, and disciplinary events. Specifically, this study asked: (1) To what extent do SEL and SRC skills serve as protective factors against academic and behavioral risk? (2) Do students with stronger SEL and SRC skills demonstrate lower risk in ELA compared to peers with weaker skills? (3) How strongly do SEL and SRC predict reductions in disciplinary events and chronic absenteeism? (4) What proportion of variance in academic and behavioral outcomes is explained by SEL and SRC beyond traditional indicators of risk? By framing SEL and SRC as protective factors and evaluating their influence across multiple domains, this study extends existing research and highlights the importance of holistic, school-based interventions for students placed at academic and behavioral risk.

3. Methodology

This study used a quantitative, predictive correlational design with quasi-experimental features to examine how students' SEL skills and SRC function as protective factors across academic and behavioral domains. The analyses combined correlational and regression methods to explore associations and predictive relationships, as well as pre-post comparisons using fall and spring data. Because this research was conducted within an applied, school-based context, program implementation emphasized ecological validity rather than experimental control. Although no formal fidelity checklists were implemented, program staff received consistent supervision and training to maintain model integrity, reflecting the program's clinical and relational nature. This section describes the study context, participants, program model, and outcome measures used to evaluate program effects across literacy, attendance, and behavior.

3.1. Participants

Table 1. Demographic Statistics

The study included data from 246 students with complete outcome records across 24 schools in a large Midwestern urban district during the 2024-2025 school year. In total, over 350 youth were served, but only those with matched fall and spring data were included in analyses. Participating schools represented a diverse range of settings, including elementary, middle, and high schools, with student populations characterized by high levels of economic disadvantage (i.e., the district reports over 80% of students come from homes of poverty) and exposure to academic and behavioral risk factors. Students were identified for participation through school-based referrals made by teachers, counselors, and administrators, based on academic, behavioral, or social-emotional need. Following referral, parental consent was obtained prior to enrollment in the program. Table 1 provides demographic statistics for youth participants. Table 2 provides descriptive data for the district.

Table 2. Demographic Statistics for Schools

3.2. Program Description

This research is embedded within a broader collective impact framework, a structured model for cross-sector collaboration that unites organizations around a common agenda, shared measurement, and mutually reinforcing activities [33]. In this initiative, a large urban school district, a regional university, and a community-based nonprofit—Prime Fit Youth Foundation—work in partnership to align resources, expertise, and supports in service of students and families. Prime Fit serves as the primary youth-serving organization within this partnership and delivers programming as an embedded layer of support within the school day, rather than as an after-school or pull-out service. Services are implemented primarily during instructional hours and are intentionally integrated into the school environment to complement, rather than replace, core academic instruction.

At the elementary level, student participation is determined through a school-based identification process led by building leadership teams (e.g., administrators, counselors, teachers, and support staff). Students are identified for participation based on a combination of social-emotional, behavioral, and academic indicators, including universal screening data, progress monitoring results, disciplinary and attendance patterns, teacher observations, and relevant contextual information such as family functioning or situational stressors. This multi-source, inclusionary approach allows schools to identify students who would benefit from additional relational and regulatory supports, even when they may not meet formal criteria for special education or intensive behavioral services.

At the elementary level, student participation is determined through a school-based identification process led by building leadership teams (e.g., administrators, counselors, teachers, and support staff). Students are identified for participation based on a combination of social- emotional, behavioral, and academic indicators, including universal screening data, progress monitoring results, disciplinary and attendance patterns, teacher observations, and relevant contextual information such as family functioning or situational stressors. This multi-source, inclusionary approach allows schools to identify students who would benefit from additional relational and regulatory supports, even when they may not meet formal criteria for special education or intensive behavioral services.

Once students are identified, families are provided with detailed program information and a parental consent and permission form. Services are initiated upon receipt of signed consent, at which point students are enrolled and begin receiving supports as part of their regular school day. This process ensures that participation is both voluntary and responsive to family-school collaboration, while allowing supports to be implemented promptly within the existing school structure.

Prime Fit Youth Foundation operates through a relational and clinically informed framework, emphasizing trust-based mentoring and trauma-informed practices. Grounded in collective impact principles, this approach ensures that interventions are coordinated rather than isolated, aligning academic, behavioral, and social-emotional supports across multiple levels of the school and broader community [34].

The program integrates several key components into students' daily school experiences: (1) Daily Check-Ins, in which mentors greet and connect with students to provide emotional support and monitor well-being; (2) Academic Support Sessions, delivered twice weekly and focused on targeted literacy instruction to reinforce skills, build confidence, and reduce academic risk; (3) Weekly Group Sessions, emphasizing executive function, emotional regulation and reactivity (ERR), and prosocial skill development; (4) Trauma-Informed De-escalation Protocols, implemented to reduce behavioral escalation and prevent exclusionary discipline; and (5) Family Engagement Nights, designed to strengthen family-school partnerships, provide resources, and promote shared learning.

The program is informed by Trust-Based Relational Intervention (TBRI), resilience theory [32], and the science of reading, positioning relationships, emotional safety, and self-regulation as core mechanisms for change. Through this integrated, school-embedded model, Prime Fit delivers evidence-based programming that is empirically supported through annual outcome evaluations, demonstrating reductions in disciplinary events, improvements in attendance, and decreases in academic risk in literacy.

3.3. Measures

To evaluate the impact of programming, multiple sources of student outcome data were collected across the 2024-2025 school year. These measures were selected to capture both academic and behavioral dimensions of risk, as well as protective factors related to social-emotional learning and executive function. Together, they provide a comprehensive picture of how students engaged with school and how the program influenced critical outcomes.

3.3.1. Attendance

Attendance was tracked through school-reported absences during the fall and spring semesters. Chronic absenteeism was defined, according to State Department of Education guidelines, as missing 10% or more of instructional days. Chronic absenteeism is widely recognized as a valid indicator of school engagement and a leading behavioral marker of academic risk [2,14]. Even moderate levels of absenteeism disrupt instructional continuity, reduce opportunities for practice and feedback, and are associated with lower achievement across grade levels [15]. Moreover, absenteeism is often intertwined with behavioral and emotional regulation difficulties, serving as an early warning sign for broader disengagement [14].

3.3.2. Challenging Behaviors (Emotional Regulation/Reactivity)

Challenging behaviors are defined as those that interfere with learning, social interaction, or classroom functioning [35]. In this study, challenging behaviors were operationalized via counts of in- school suspensions (ISS) and out-of-school suspensions (OSS). These exclusionary discipline events reflect instances when students' behavior reaches a level of disruption or dysregulation that leads to formal removal from instruction. The ISS and OSS counts were combined into a composite to reflect challenges in emotional reactivity and regulation (ERR), capturing how effectively students regulate behavior and remain engaged in the school environment. Research supports using suspension counts as proxies for behavioral dysregulation and poor self-regulation. For example, one study found that greater numbers of ISS and OSS predicted lower emotion regulation scores and higher disruptive behavior even after controlling for baseline functioning [36]. In this study, suspensions were used as overt indicators of behavioral dysregulation and emotional/psychological risk. Another intervention study showed that improvements in self-regulation skills were associated with large decreases in suspensions [37]. Finally, Rumberger & Losen (2016) framed ISS/OSS as indicators of serious behavioral incidents and school disengagement, highlighting suspension as a loss of instruction/behavioral risk marker.

3.3.3. Social-Emotional Skills

Students' social-emotional functioning was assessed using the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) [39]. Participants completed both the teacher- and student-report versions. The SAEBRS is a validated universal screener designed to evaluate students' strengths and risk levels across social, academic, and emotional domains, providing a comprehensive picture of social-emotional competence and school functioning [39].

Social-emotional skills were measured using the SEL Risk composite derived from the SAEBRS. On this measure, higher scores indicate stronger social-emotional skills and lower overall behavioral or emotional risk. SEL Risk scores were analyzed both as an outcome of interest and as a predictor of academic achievement, attendance, and behavioral outcomes, reflecting the dual role of SEL in supporting engagement and reducing risk.

The teacher-report version includes 19 items organized into one broad factor (General Behavior) and three subscales: Social Behavior (e.g., arguing, cooperation with peers, temper outbursts, disruptiveness, impulsivity), Academic Behavior (e.g., preparedness for instruction, independent work completion, attentional control, academic engagement), and Emotional Behavior (e.g., sadness, worry, adaptability, positive attitude, withdrawal). Each item is rated on a frequency scale, and subscale scores are summed to produce a Total Behavior score ranging from 0-57.

SAEBRS scores are categorized as "Low Risk," "Some Risk," or "High Risk," representing the frequency and intensity of behaviors associated with social, academic, or emotional difficulties. Higher scores indicate better social-emotional functioning and fewer behavior concerns. Prior studies have demonstrated the SAEBRS' strong reliability and predictive validity for both academic achievement and behavioral outcomes, making it a robust measure of SEL skills and school adjustment [38,39].

3.3.4. Self-Regulation Capacity

To capture students' broader regulatory skills, a Self-Regulation Capacity (SRC) composite was created from three validated self-report measures: sense of self-efficacy, sense of connectedness, and use of self- regulation strategies. Each measure represents a distinct but complementary dimension of students' ability to plan, monitor, and sustain goal-directed behavior. Scores from these measures were standardized and combined into a single composite variable, with higher values representing stronger overall self-regulation capacity. Creating a composite index allowed for a comprehensive assessment of how regulatory skills function as protective factors across academic and behavioral domains while reducing measurement redundancy and enhancing reliability [40].

Sense of self-efficacy was assessed using an adapted version of the Children's Self-Efficacy Scale [41], a widely used measure of students' beliefs in their ability to manage learning and social situations effectively. The instrument includes 15 items rated on a 4-point Likert scale, producing scores that reflect both self-regulated learning efficacy and self-assertive efficacy. Higher scores indicate a greater self-reported sense of efficacy and confidence in managing academic and interpersonal challenges. Participants completed the survey at three time points (pre-mentoring, midyear, and post-mentoring) to capture changes over time.

School connectedness was measured using the Sense of School Connectedness Scale [42], adapted for the current study. This 33-item instrument assesses students' perceptions of belonging and engagement across six categories: teacher support, peer belonging, fairness and safety, academic engagement, relatedness to school, and community involvement. Each item is rated on a 4-point Likert scale, with higher scores reflecting a stronger sense of inclusion, belonging, and perceived support within the school community. A robust sense of connectedness is strongly linked to academic persistence, lower behavioral risk, and greater emotional well-being [43].

Knowledge and use of self-regulation strategies were measured using the Self-Regulation Strategies Questionnaire [44]. The six-item survey employs a 4-point Likert scale to capture both knowledge of self-regulation (four items) and frequency of strategy use (two items). Higher scores indicate a stronger ability to apply regulatory strategies such as goal setting, self-monitoring, and reflection skills associated with academic success and emotional resilience. Using this measure alongside the efficacy and connectedness scales provided a multidimensional understanding of students' regulatory capacity in both cognitive and behavioral domains.

3.3.5. Academic Outcomes

Academic outcomes were assessed using students' risk levels in English Language Arts (ELA) as reported through the FastBridge assessment system. FastBridge provides universal screening and progress monitoring across multiple domains, including reading. Schools collected these data in both the fall and spring, with performance categorized into four levels: high risk, some risk, low risk, or college-prep. These risk levels are derived from nationally normed benchmarks that classify students' likelihood of meeting grade-level expectations.

FastBridge assessments have demonstrated strong psychometric properties, including high test-retest reliability, internal consistency, and predictive validity for later academic achievement [45,46]. Research has shown that FastBridge's curriculum-based measures (CBM) and computer-adaptive tests (CAT) correlate strongly with standardized assessments, making them appropriate tools for monitoring student growth and identifying risk. The use of these risk categories provided a way to track changes in students' academic standing over the course of the year, particularly movement out of high-risk classifications and into safer academic ranges.

4. Results

Paired-sample t-tests were conducted to compare fall and spring outcomes across academic and behavioral measures. Bivariate correlations examined associations between SEL Risk, ELA, SRC, and ERR (Challenging Behaviors). Simple linear regressions tested the extent to which SEL Risk and/or SRC predicted spring outcomes in ELA and ERR. For all analyses, statistical significance was evaluated at p < .05.

4.1. Research Question 1

To address research question 1 (To what extent do social-emotional learning (SEL) and self-regulation capacity (SRC) skills serve as protective factors against academic and behavioral risk?), we used the following data sources: composite SEL score from the SAEBRS, composite SRC score from the three surveys students completed, academic risk data, behavioral risk data, and attendance data. Table 3 provides descriptive statistics for these data sources.

Table 3. Descriptive Statistics of Outcome Variables

4.2. Research Question 2

To provide an overview of the sample and key study variables, we first conducted descriptive analyses. Means and standard deviations were calculated for continuous measures of SEL and SRC (Table 3). Frequency distributions were generated for categorical outcomes, including students' spring ELA risk levels (high, some, low, or college-prep), as well as disciplinary events (in-school suspensions, out-of-school suspensions, and expulsions, aggregated into a measure of emotional regulation/reactivity challenges). Attendance data were summarized in terms of total days absent and by identifying the proportion of students classified as chronically absent (>10% of instructional days missed). These descriptive statistics provided a baseline understanding of the sample and informed subsequent correlational and regression analyses.

Spring data were selected as the primary outcomes because they reflect student performance after participation in programming across the school year. Fall data were collected as baseline measures, but because they reflect students' pre-intervention status, they were not used as outcome indicators. Using spring data allows for a more accurate evaluation of program impact and ensures that academic, behavioral, and attendance outcomes reflect the period during which students received intervention and support.

Pearson product–moment correlations were conducted among SRC, SEL, ELA risk, ERR (disciplinary incidents), and attendance (coded as chronic absenteeism or not chronic). Results are presented in Table 4. Within this sample, higher protective factor scores (SRC and SEL) were associated with lower academic and behavioral risk. SRC was positively correlated with SEL, r(244) = .35, p < .001, indicating that students who reported stronger self-regulation capacities also tended to demonstrate stronger SEL skills.

Both SRC and SEL were significantly and negatively correlated with ELA risk (SRC: r(244) = –.44, p < .001, and SEL: r(244) = –.34, p < .001), suggesting that students with stronger social-emotional and self-regulation skills were less likely to be academically at risk.

Behavioral outcomes followed a similar pattern. SRC was significantly and negatively correlated with ERR (disciplinary events) (r(244) = –.29, p < .001), and SEL showed an even stronger negative association (r(244) = –.61, p < .01). Thus, students with stronger SEL and SRC experienced fewer disciplinary incidents.

Attendance was also significantly correlated with protective factors. Higher SRC (r(244) = –.29, p < .01) and higher SEL (r(244) = –.23, p < .001) were associated with fewer absences across the school year.

Finally, the academic and behavioral risk variables were interrelated. ELA and behavioral risk were strongly and positively correlated. ERR was positively related to ELA risk (r(244) = .42, p < .05), while attendance was positively correlated with ERR (r(244) = .43, p < .05).

Together, these results underscore the interconnected nature of academic, behavioral, and attendance outcomes, and demonstrate that SEL and SRC operate as protective factors across multiple domains.

4.3. Research Question 3

To examine the extent to which SEL and SRC predict reductions in behavioral incidents and attendance risk, we first described the distribution of disciplinary events and absenteeism across the sample. In the spring semester, 29.3% of students experienced at least one disciplinary event (in-school suspension, out-of-school suspension, or expulsion), while the average number of events per student was M = 0.83 (SD = 1.87). With respect to attendance, 10.6% of students were identified as chronically absent, defined as missing 10% or more of instructional days (>18 of 180 days).

To further address Research Question 3, we examined the bivariate associations between protective factors (SEL and SRC) and two key risk outcomes—disciplinary events and chronic absenteeism—to determine whether stronger skills were linked to lower levels of behavioral and attendance risk. Bivariate correlations between SEL, SRC, disciplinary events, and chronic absenteeism are presented in Table 4. As expected, both SEL and SRC were significantly and negatively correlated with ERR totals (SEL: r(244) = –.61, p < .01; SRC: r(244) = –.29, p < .001), indicating that students with stronger protective factor scores experienced fewer disciplinary events. Similarly, both SEL and SRC were negatively associated with chronic absenteeism (SEL: r(244) = –.23, p < .001; SRC: r(244) = –.29, p < .01), suggesting that higher social-emotional and self-regulation skills were linked to a lower likelihood of being chronically absent. These patterns provide preliminary evidence that SEL and SRC operate as protective factors against both behavioral and attendance risk.

Table 4. Bivariate Correlations Among SEL, SRC, and Outcome Data

To further address this research question, we conducted logistic regression analyses to test whether SEL and SRC predicted the likelihood of experiencing disciplinary incidents. This approach allowed us to determine whether students with stronger protective factor scores were significantly less likely to have any in-school suspensions, out-of-school suspensions, or expulsions during the spring semester. A binary logistic regression was conducted to examine whether SEL and SRC predicted the likelihood of experiencing any disciplinary event (ISS or OSS). The model included SEL (median split: high vs. low) and SRC (median split: high vs. low) as predictors. Results indicated that both SEL and SRC were significant protective factors. Students with higher SEL were significantly less likely to experience a disciplinary event, OR = 0.46, Wald χ²(1) = 5.10, p = .024, representing a 54% reduction in odds compared to peers with lower SEL. Similarly, students with higher SRC demonstrated significantly lower odds of ERR, OR = 0.36, Wald χ²(1) = 8.80, p = .003, representing a 64% reduction in odds.

In addition to disciplinary outcomes, logistic regression was also used to examine whether SEL and SRC predicted chronic absenteeism. This analysis assessed whether students with stronger protective factor scores were less likely to miss 10% or more of instructional days across the school year, a benchmark commonly used to define chronic absence.

A binary logistic regression was conducted to test whether SEL and SRC predicted chronic absenteeism (defined as missing 10% or more of instructional days). The overall model was statistically significant, χ²(2, N = 246) = 18.88, p < .001, explaining approximately 20% of the variance (Nagelkerke R² = .20). SRC emerged as a significant predictor of chronic absenteeism, OR = 0.09, Wald χ²(1) = 9.48, p = .002, indicating that students with higher self-regulation capacity were approximately 91% less likely to be chronically absent than their peers with lower SRC. In contrast, SEL did not significantly predict chronic absenteeism, OR = 0.55, Wald χ²(1) = 1.27, p = .259.

In summary, both SEL and SRC functioned as significant protective factors against disciplinary events, and SRC also strongly predicted reduced odds of chronic absenteeism. These findings suggest that students with stronger social-emotional and self-regulation skills are better equipped to avoid behavioral exclusions and maintain consistent attendance, highlighting the value of these skills as key buffers against school-related risks.

4.4. Research Question 4

To address research question 4 (What proportion of variance in academic and behavioral outcomes is explained by SEL and SRC, beyond traditional indicators of risk?) we examined the extent to which SEL and SRC explained unique variance in academic and behavioral outcomes beyond traditional indicators of risk. Because students’ prior performance and behaviors are often the strongest predictors of future outcomes, baseline fall measures were first entered into each model. SEL and SRC were then added in a second step to determine whether these protective factors contributed additional explanatory power. This analytic strategy allowed us to assess the incremental value of SEL and SRC in predicting spring ELA risk, disciplinary events, and chronic absenteeism, above and beyond what would be expected from fall risk indicators alone.

4.4.1. Challenging Behaviors (ERR)

The final research question (What proportion of variance in academic and behavioral outcomes is explained by SEL and SRC, beyond traditional indicators of risk?) was then addressed. While correlations and group comparisons establish associations, this question required examining whether SEL and SRC contribute unique predictive value after accounting for students’ baseline risk. To address this, hierarchical regression analyses were conducted for academic outcomes (ELA), and logistic regressions were used for behavioral outcomes (ERR and chronic absenteeism). These models allow us to determine the degree to which SEL and SRC function as protective factors above and beyond prior performance or risk, highlighting their incremental contribution to student success.

A binary logistic regression was conducted to examine whether SEL and SRC predicted the likelihood of students experiencing disciplinary incidents (ERR) in the spring. The overall model was statistically significant, χ²(2, N = 194) = 18.01, p < .001, indicating that the predictors reliably distinguished between students with and without ERR events. The model explained between 8.9% (Cox & Snell R²) and 12.6% (Nagelkerke R²) of the variance in ERR outcomes. Both predictors were statistically significant.

4.4.2. SRC

Students with higher SRC scores were significantly less likely to experience ERR events, B = –1.01, SE = .34, Wald = 8.80, p = .003. The odds ratio Exp(B) = .36 indicates that high-SRC students were about 64% less likely to have ERR events compared to peers with lower SRC.

4.4.3. SEL

Similarly, higher SEL scores predicted a reduced likelihood of ERR events, B = –.77, SE = .34, Wald = 5.10, p = .024. The odds ratio Exp(B) = .46 indicates that high-SEL students were about 54% less likely to have ERR events than those with lower SEL.

Taken together, the hierarchical and logistic regression models provide strong evidence that SEL and SRC explain meaningful variance in student outcomes beyond traditional risk indicators. For academic outcomes, SEL and SRC added predictive value for ELA risk. For behavioral outcomes, both SEL and SRC significantly reduced the likelihood of disciplinary incidents (ERR), with students high in SRC being 64% less likely and those high in SEL being 54% less likely to experience suspensions or expulsions. Attendance outcomes followed a similar trend, with stronger SEL and SRC associated with a lower probability of chronic absenteeism. Across domains, these findings demonstrate that social-emotional and self-regulation skills function as protective factors, buffering students against academic and behavioral risks even in high-need school contexts.

4.4.4. Academic Outcomes

A hierarchical linear regression was conducted to determine whether SEL and SRC explained unique variance in Spring ELA risk beyond Fall ELA scores. In Step 1, Fall ELA risk significantly predicted Spring ELA risk, R² = .54, F(1, 192) = 225.41, p < .001. In Step 2, adding SEL and SRC significantly improved the model, ΔR² = .02, F-change (2, 190) = 4.32, p = .015. The final model accounted for 56% of the variance in Spring ELA risk. These findings suggest that SEL and SRC contribute additional explanatory power beyond baseline academic risk, although the effect was modest.

In summary, for ELA, SEL and SRC explained an additional 2% of the variance in spring risk scores beyond fall baseline performance, a modest but statistically significant improvement. These findings suggest that SEL and SRC offer incremental predictive value for literacy outcomes.

5. Discussion

This study sought to examine the role of SEL and SRC as protective factors for youth at risk of academic and behavioral challenges. Specifically, we asked whether SEL and SRC predicted academic risk in ELA, reduced disciplinary events and chronic absenteeism, and explained variance beyond traditional indicators of risk.

5.1. SEL and SRC as Protective Factors

Findings from this study provide strong evidence that both SEL skills and SRC function as protective factors against academic and behavioral risk. Across domains, higher SEL and SRC scores were consistently associated with lower levels of academic risk in English Language Arts (ELA), fewer disciplinary incidents (ISS/OSS), and reduced likelihood of chronic absenteeism. These consistent correlations highlight the broad, cross-cutting role of SEL and SRC in supporting students' academic engagement and behavioral regulation.

These results align with resilience theory [17], which emphasizes the role of protective factors in buffering students from the negative effects of risk, and with self-regulation theory [17], which underscores the interplay between cognitive and emotional processes in sustaining learning and adaptive behavior. In particular, SRC, encompassing students' sense of efficacy, school connectedness, and use of regulation strategies, appears to provide students with the internal resources needed to persist in academic tasks and manage challenging situations effectively.

The findings are also consistent with prior research that has documented the links between SEL, executive function (EF), and achievement. For example, Cartwright [5] showed that self-regulatory processes contribute uniquely to reading achievement, while Vitiello and Williford [13] demonstrated that SEL interventions can enhance EF-related skills such as attention and planning. Similarly, Lyon et al. [24] found that SEL programs can reduce behavioral risk by strengthening emotion regulation.

The present study extends this body of work in important ways. Unlike many prior studies that have focused on small samples or highly controlled interventions, this research examined SEL and SRC in real-world, multi-school applied settings involving over 240 youth across 24 schools. The consistency of the protective effects observed here underscores the ecological validity of SEL and SRC as predictors of student success, suggesting that these skills are not only theoretically important but also practically meaningful within school-based prevention and intervention programming.

5.2. Differences between High and Low SRC/SEL Groups

Analyses comparing students in high versus low SEL and SRC groups demonstrated clear and meaningful differences across both academic and behavioral domains. Students with stronger SEL and SRC skills consistently showed lower risk levels in ELA compared to their peers with weaker skills. These differences were statistically significant with large effect sizes, underscoring the practical importance of these protective factors. In academic terms, this means that students with stronger self-regulation and social-emotional skills were not only less likely to be classified as “high risk” but were more likely to demonstrate progress into lower risk categories by spring.

The group comparisons also extended to behavioral outcomes. Students in the high SEL and SRC groups had significantly fewer disciplinary incidents, as measured by ISS, OSS, than those in the low groups. This reinforces the view that SEL and SRC provide students with strategies to manage frustration, regulate emotions, and engage in prosocial behavior—skills that reduce the likelihood of exclusionary discipline.

These findings are consistent with the Collaborative for Academic, Social, and Emotional Learning (CASEL) [28], which highlights SEL’s dual role in promoting academic achievement and reducing behavioral problems. They also align with prior research showing that SEL-focused interventions reduce disciplinary disparities and promote more equitable school climates [23]. Together, these results suggest that SEL and SRC skills not only correlate with positive outcomes but also distinguish meaningfully between groups of students at higher and lower risk, both academically and behaviorally.

By moving beyond simple associations and demonstrating group-level differences, the current study adds to the evidence base that SEL and SRC are core protective factors in youth development. They act as reliable indicators of which students are most vulnerable, while also providing schools with a concrete set of skills to target in prevention and intervention programming.

5.3. Predicting Reduction in Disciplinary Events and Absenteeism

Analyses addressing the third research question showed that SEL and SRC skills were powerful predictors of reductions in challenging behaviors and attendance risk. Logistic regression models indicated that students with stronger SEL and SRC skills had approximately 50–60% lower odds of experiencing disciplinary events (ISS/OSS) compared to their peers with weaker skills. Similarly, higher SEL and SRC scores were associated with a reduced likelihood of chronic absenteeism. These findings highlight the extent to which protective factors serve not only as correlates of student success but also as predictors of which students are less likely to engage in behaviors that compromise their learning.

This evidence positions SEL and SRC as central to preventive and protective mechanisms in school settings. Students who feel more connected, efficacious, and capable of regulating their emotions and behavior are less likely to disengage academically or require disciplinary removal. These results echo prior research on school connectedness and engagement as buffers against risk [19] and align with studies showing that prosocial skill development reduces disciplinary disparities and fosters safer learning environments.

From a programmatic perspective, these findings validate the model implemented by Prime Fit Youth Foundation. Daily mentoring and weekly group sessions intentionally target SEL and SRC skills, while the de-escalation protocol provides staff with tools to respond proactively to behavioral challenges before they escalate into ISS or OSS events. In this way, program strategies serve as the practical vehicles through which protective factors are cultivated and reinforced, yielding measurable reductions in disciplinary incidents and absenteeism.

Taken together, these results demonstrate that fostering SEL and SRC is not only beneficial for academic outcomes but is also a highly effective approach for preventing risk behaviors that lead to exclusion and lost instructional time.

5.4. Unique Variance Explained

The final research question asked whether SEL and SRC explain unique variance in student outcomes beyond traditional indicators of academic risk. Results from hierarchical regression models revealed that SEL and SRC contributed significant incremental predictive value for ELA outcomes, even after accounting for fall baseline performance. From the perspective of the SVR, which conceptualizes reading comprehension as the product of decoding and linguistic comprehension, these findings suggest that SEL and SRC operate as enabling conditions that support students’ ability to effectively engage with both components of the reading process. Self-regulation and social-emotional skills do not replace foundational decoding or language skills; rather, they support students’ capacity to sustain attention, manage frustration, persist through challenging text, and apply comprehension strategies—processes necessary for successful reading comprehension. In this way, SEL and SRC provide explanatory power beyond traditional skill-based predictors, aligning with contemporary extensions of the SVR that emphasize the role of cognitive and regulatory processes in literacy achievement [6].

For behavioral and attendance outcomes, however, SEL and SRC emerged as strong independent predictors. Logistic regressions indicated that these skills explained substantial variance in whether students experienced disciplinary incidents (ERR) or met the threshold for chronic absenteeism. Importantly, these effects held even in the absence of baseline disciplinary data, pointing to the robustness of SEL and SRC as protective mechanisms that reduce the likelihood of disengagement and exclusionary discipline.

Overall, these results demonstrate that SEL and SRC function as critical protective factors that extend beyond traditional academic indicators. While literacy outcomes appear partially mediated by self-regulation pathways, behavioral and attendance outcomes demonstrate even stronger and more direct effects. Collectively, these findings provide compelling evidence across all four research questions that SEL and SRC are foundational mechanisms of both academic resilience and behavioral regulation, reinforcing the importance of embedding these skills within multi-tiered systems of support and literacy instruction.

5.5. Overall Contribution to Extant Literature

This study makes several important contributions to the growing literature on SEL and self-regulation. First, it bridges gaps in prior research by examining academic, behavioral, and attendance outcomes simultaneously, rather than treating them as separate domains. This holistic approach reflects the lived realities of students in schools, where academic achievement, behavior, and engagement are deeply interconnected.

Second, the study draws on applied, multi-school program data from 24 schools, which is rare in the SEL and SRC literature. Much of the existing evidence base comes from small-scale interventions or controlled research settings, limiting generalizability. By leveraging program implementation data collected in authentic educational contexts, the present study adds ecological validity to claims about the protective effects of SEL and SRC.

Finally, this work directly addresses a critical gap in the extant literature by explicitly linking SEL and SRC to reading risk. Although prior studies have demonstrated the importance of self-regulation and executive function for reading development [5,6], few have explored these relationships using applied program data or across multiple outcome domains. By situating literacy within a broader framework of SEL and self-regulation, this study underscores the importance of targeting these protective factors not only for behavioral outcomes but also for closing persistent achievement gaps in reading.

Collectively, these contributions highlight the unique value of school–community partnerships that integrate SEL and SRC supports into daily practice, offering a model for how holistic, evidence-based interventions can reduce risk and promote resilience in youth.

5.6. Implications for Practice and Policy

The findings from this study carry important implications for both educational practice and policy. Results suggest that SEL and SRC should be embedded as core components of school-based interventions, not treated as add-ons. These skills function as protective factors that reduce students’ likelihood of falling into academic risk categories, experiencing disciplinary exclusion, or disengaging through chronic absenteeism.

In practice, this means that multi-tiered systems of support (MTSS), literacy interventions, and behavior frameworks should explicitly integrate self-regulation strategies alongside academic instruction. Embedding SEL and SRC within Tier 1 universal supports ensures that all students benefit from skill development, while targeted Tier 2 and Tier 3 supports can address the needs of students facing greater levels of risk. Such integration positions self-regulation as foundational to both literacy growth and behavioral success, echoing the science of reading’s emphasis on broader cognitive and regulatory pathways [6].

Students in today’s classrooms increasingly contend with complex stressors, including higher rates of poverty and adverse childhood experiences (ACEs) that can impair self-regulation, executive functioning, and academic engagement [48]. Given these rising challenges, teacher preparation programs and state standards should ensure that preservice educators receive training in trauma-informed and self-regulation practices. This alignment would better equip educators to address the complex needs of students placed at academic and behavioral risk and to implement evidence-based strategies that promote engagement, resilience, and literacy development.

The Prime Fit Youth Foundation model offers a promising example of how these principles can be implemented at scale through community-based partnerships. By combining daily mentoring, weekly group sessions, academic supports, and a trauma-informed de-escalation protocol, the model operationalizes Trust-Based Relational Intervention (TBRI), resilience theory, and the science of reading in ways that are accessible to schools and adaptable across sites. As such, Prime Fit demonstrates a scalable and replicable approach that aligns evidence-based practices with real-world needs, advancing both equity and effectiveness in youth development.

At the policy level, these findings underscore the importance of funding and sustaining cross-sector collaborations between schools, universities, and community-based organizations. Supporting the development of SEL and SRC within these partnerships can help reduce disciplinary disparities, improve academic outcomes, and ensure that students placed at risk have access to the protective factors necessary for resilience and long-term success.

5.7. Limitations and Future Directions

While this study makes important contributions to the literature on SEL and self-regulation, several limitations should be acknowledged. First, the academic risk measures used in this study were district-reported indicators (FastBridge categories) rather than standardized test scores. Although these data are valid for monitoring student progress within schools, they may not capture the full range of literacy achievement.

Second, measures of SRC were based on student self-report surveys. While these instruments have demonstrated reliability, self-reports are inherently subject to bias, including social desirability and students’ varying levels of self-awareness. Future research would benefit from triangulating SRC measures with teacher reports or observational data.

Third, the design of this study was non-experimental, which prevents causal conclusions about the impact of SEL and SRC on academic and behavioral outcomes. Although the correlations, group comparisons, and regression models provide strong evidence of association and predictive power, randomized controlled trials or quasi-experimental designs would allow for stronger claims regarding causality.

Fourth, no formal fidelity checklists were implemented during program delivery. Although this limits the ability to quantify implementation consistency, the intervention’s applied and clinically informed structure provided ongoing supervision and professional development for staff to ensure adherence to the model’s relational and trauma-informed principles. Future studies should include structured fidelity tools and independent observations to assess implementation quality more systematically.

Fifth, the intervention had a clinically informed, relationship-based structure in which mentors and staff were encouraged to respond flexibly to students’ immediate emotional and behavioral needs. This flexible delivery is a strength in practice. It reflects trauma-informed, individualized support and likely increased student engagement, but it also reduces experimental control. Because staff could adapt strategies in real time, isolating specific “active ingredients” of the program is challenging. Future research may benefit from hybrid approaches that preserve this responsive, clinical model while also embedding systematic documentation of which supports were delivered, to whom, and under what conditions.

Finally, the study was limited to one academic year and to risk categories as outcome measures. Future research should include longitudinal follow-up to examine the durability of SEL and SRC effects over time, as well as mediation models to explore whether improvements in self-regulation pathways explain gains in academic performance. In addition, future evaluations could explore how fidelity and implementation quality interact with student outcomes, providing insight into which elements of the program’s clinical and relational approach drive the greatest change. Additional work is also needed to develop finer-grained SRC measures that capture distinct subcomponents (e.g., persistence, emotional regulation, goal setting) and to expand literacy outcomes beyond categorical risk levels to include continuous growth scores and comprehension measures.

By addressing these limitations, future studies can build on the present findings to deepen understanding of how SEL and SRC operate as protective factors and to refine evidence-based models for embedding these skills in school and community interventions.

5.8. Conclusions

These findings highlight the critical role of SEL and SRC in reducing academic and behavioral risk among students experiencing multiple barriers to learning. By serving as protective factors across literacy, behavior, and attendance, these skills provide a foundation for both resilience and achievement. Students with stronger SEL and SRC skills were not only less likely to struggle academically but also less likely to face disciplinary exclusion or disengage from school through absenteeism.

Importantly, these results underscore that SEL and SRC are central mechanisms of learning, not peripheral supports. They enable students to regulate emotions, persist through challenges, and build meaningful connections with peers and educators—capacities that drive both academic growth and behavioral well-being. In doing so, SEL and SRC extend the Active View of Reading, affirming that literacy success depends on coordinated cognitive, emotional, and motivational processes.

Programs that intentionally cultivate these skills, such as Prime Fit Youth Foundation, demonstrate how evidence-based, community-driven models can translate research into practice. By embedding SEL and SRC into daily mentoring, academic support, group sessions, and trauma-informed de-escalation strategies, Prime Fit provides a scalable and replicable framework for closing opportunity gaps and fostering equity.

Embedding these competencies within school-based and community interventions can help educators and policymakers create learning environments where all students, especially those experiencing academic and behavioral risk, have the skills and supports needed to thrive academically, behaviorally, and emotionally.

ACKNOWLEDGEMENTS

Thank you to the school partners, families and youth who made this study possible. Connection changes everything.

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