Carmen Lucia Albuquerque de Santana1,2*
Nina Wallerstein3
Lucas Ferreira Libonati Boldi2
Olivia Ramos Morais Braga2
Fernando Akira Kurokawa2Francisco Lotufo Neto1
Antonio Carlos Seabra2- 1School of Medicine, University of São Paulo, São Paulo, Brazil
- 2Polytechnic School of the University of São Paulo, São Paulo, Brazil
- 3Center for Participatory Research, College of Population Health, University of New Mexico, Albuquerque, NM, United States
Background: Engineering students face growing mental health challenges driven by heavy workloads, competitive assessment, and a culture that normalizes stress. These vulnerabilities are compounded by structural inequalities disproportionately affecting women, marginalized racial and ethnic groups, first-generation students, and those from lower socioeconomic backgrounds. The intersection of academic pressure with social inequities amplifies dropout risks and undermines diversity in higher education. At the Polytechnic School of the University of São Paulo, ongoing curricular reforms and the growing presence of affirmative-action students from national inclusion policies offer a unique opportunity to transform institutional culture and examine these dynamics in depth.
Methods: This protocol outlines a four-year longitudinal, two-cohort study investigating how individual, contextual, and institutional factors—including intersectionality, affirmative action, and curricular reforms—affect engineering students’ mental health, motivation, and engagement. Grounded in Community-Based Participatory Research, Bronfenbrenner’s Bioecological Model, and Self-Determination Theory, the study assesses the impact of institutional reforms aligned with national policies, identifies barriers and facilitators to equity, and co-develops actionable recommendations to transform academic practices and policy. A mixed-methods, multiphase design will collect surveys and data for all students entering from 2025 to 2028 (3,480 students). Two 2025 cohorts from distinct curricular models will be followed longitudinally, with no study-based selection and proportional representation of affirmative-action, gender, and sociodemographic groups. Qualitative activities will also engage 20 faculty, alongside students; quantitative data will be analyzed with descriptive and longitudinal models, and qualitative data will undergo thematic coding. Participatory processes ensure collaborative data interpretation and co-design of a mental-health promotion intervention with students, faculty, and staff within the research-governance structure.
Discussion: The study will illuminate how institutional, individual, and contextual factors intersect to shape students’ well-being and academic experiences. Findings are expected to reveal structural barriers, protective factors, and effects of curricular reforms and affirmative-action policies. Its participatory, systemic approach offers a model for other university settings—including public and population health—showing pathways to foster culture change and co-create evidence-based policies that promote well-being and equity. The study also seeks to strengthen students’ capacity to apply these principles in their future practice.
Clinical trial registration: Open Science Framework (OSF), DOI 10.17605/OSF.IO/N43TD.
1 Introduction
Higher education institutions are not only spaces of technical training, academic experience, and campus life; they are also places where inequalities are produced and reproduced (Lechner et al., 2025). Such structural inequalities persist worldwide, disproportionately affecting racialized students and those from disadvantaged backgrounds, and are especially visible in historically elitist and competitive fields (Bersoto et al., 2025).
Globally, universities are now called to become more equitable, dismantling structural racism, fostering inclusive excellence, and addressing the social determinants of academic success (Association of Schools and Programs of Public Health, 2021; Robert Wood Johnson Foundation, 2024). This aligns with the Transforming Academia for Equity agenda, which calls for adaptive strategies, culturally responsive engagement, and the dismantling of structural barriers in academic institutions (Venkateswaran et al., 2023). Within this broader agenda, student mental health has emerged as a critical dimension of equity and institutional sustainability.
WHO’s World Mental Health International College Student initiative (WMH-ICS) recognizes student mental health as a global public health priority, requiring systemic responses that integrate education and health sectors as emphasized by Cuijpers et al. (2019). These inequities extend beyond access and representation to affect students’ health and well-being, as mental health has increasingly been recognized as a key indicator of equity in academic environments (Association of Schools and Programs of Public Health, 2021; Cuijpers et al., 2019; Evans et al., 2018).
Building on this perspective, recent works highlight that universities themselves are critical arenas for health equity. Adsul et al. (2025) and Doubeni et al. (2022) underscore that universities, health institutions, and community-engaged academic centers must create supportive organizational contexts to sustain student engagement and mitigate health inequities. This growing body of evidence positions higher education transformation as both an educational goal and a structural public-health intervention.
A large-scale international study indicates that approximately one-third of university students worldwide experience anxiety, depression, or burnout (Auerbach et al., 2018), a pattern mirrored in Brazil, where between 30–50% of medical students report common mental disorders (de Sousa et al., 2023). These problems reflect the combined effects of academic pressure, institutional culture, and broader social inequities. Factors such as socioeconomic hardship, discrimination, racial identity, gender diversity, and belonging to the LGBTQIA+ community increase vulnerability (Evans et al., 2018; Gulliver et al., 2023). Consequences include poor academic performance, dropout, and even suicidal ideation—reported by about 60% of Brazilian students, primarily linked to exhausting routines and the challenges of adapting to new environments and relationships (de Sousa et al., 2023). In the UK, over 40% of university students reported experiencing suicidal thoughts at least once in the past 12 months (Akram et al., 2020). Financial stress, inadequate sleep, and excessive workloads further exacerbate these risks, undermining both well-being and academic performance (Barros and Sousa, 2022; Hasim et al., 2023; Radan et al., 2023).
Beyond individual or behavioral factors, structural conditions within universities also shape student well-being (American College Health Association, 2024). Curriculum design, pedagogical practices, institutional culture, and workload exert a strong influence, especially for underrepresented groups, and student-centered principles and practices are central to promoting well-being (Hurtado et al., 2012). A growing body of evidence highlights that the classroom climate, perceived instructor support, and equitable access to institutional resources are as critical as individual resilience in determining outcomes (Konstantinidis, 2024).
Accumulating evidence suggests that intersectionality-informed interventions, addressing gender, race, and socioeconomic background, can significantly improve students’ mental health, engagement, and retention. However, systematic application of this approach in institutional programs and policies remains limited (Suyo-Vega et al., 2022).
In Brazil, the adoption of affirmative action policies since 2012—ensuring access for Black, Brown, Indigenous, and public-school students to federal universities—has significantly diversified the student profile in higher education (Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (Inep), 2022; Campos and Lima, 2025). The University of São Paulo, a tuition-free public institution, now admits half of its students through affirmative action policies across all programs. However, advances in access have not been accompanied by equivalent improvements in conditions for persistence, well-being, and more inclusive institutional practices.
The Polytechnic School of the University of São Paulo (EPUSP) offers a unique context to examine how affirmative-action policies, curricular reforms, and participatory learning practices may contribute to converting structural stressors into health-promoting institutional conditions, as high rates of depression, anxiety, and burnout have been documented among students in comparable contexts (Gulliver et al., 2023; Hasim et al., 2023; Jehangir et al., 2024). Its entrance exam now reserves 50% for students admitted through affirmative action, a goal reached by 2021 following the national policy implemented in 2012. Nevertheless, mental health outcomes are unequally distributed, with students from marginalized groups, such as those admitted through affirmative action, facing additional challenges linked to socioeconomic status, racial inequities, and institutional climate (Auerbach et al., 2018; de Sousa et al., 2023; Fagundes et al., 2014; Vasconcelos-Raposo et al., 2016; Vick et al., 2025).
While previous research has described the prevalence of mental health problems in student populations, few studies have adopted a longitudinal, participatory, and theoretically grounded approach that integrates individual, contextual, and temporal factors in examining student well-being and academic outcomes (Park et al., 2023). The intervention research gap is particularly relevant given the absence of studies evaluating the impact of curricular reforms on students’ mental health, academic motivation, or sense of belonging, particularly among those who face historical barriers in higher education.
Accordingly, this study protocol is intended to examine institutional transformation as a health-promoting process in higher education, analyzing how participatory governance and institutional change function as structural determinants of student mental health, motivation, and engagement. By incorporating intersectionality and affirmative action into its design, it moves beyond an individualizing view of mental health problems (e.g., depression, anxiety) to analyze how institutional and structural factors shape the student experience. The study aims to co-develop evidence-based institutional strategies with students, shifting attention from individual outcomes to the systemic effects of curricular and structural reforms. These efforts contribute to the monitoring and evaluation of recent public education policies and may serve as a model for other university disciplines that seek to integrate student mental health into equity-oriented policy implementation. The specific objectives of the study are detailed in Section 2.1.
2 Methods and analysis
2.1 Objectives and study design
Objectives and research protocol were defined through participatory processes, including conversation circles with students, listening sessions with faculty and staff, and lessons from the previous mentoring initiatives (Duarte et al., 2022). Guided by the principles of Community-Based Participatory Research (CBPR) (Wallerstein et al., 2018), the Bioecological Model of Human Development (Bronfenbrenner and Morris, 2006), and Self-Determination Theory (Ryan and Deci, 2018), these inputs highlighted mental health, engagement, and motivation as key concerns, and pointed to the influence of curricular reforms and institutional policies on student success. From this process, four objectives were established:
1. to longitudinally assess changes in mental health, engagement, and academic motivation in two cohorts of engineering students over 4 years (2025–2028);
2. to examine the effects of curricular, institutional, and contextual factors on these outcomes;
3. to identify barriers and facilitators to equitable learning environments;
4. to co-develop evidence-based recommendations and indicators for institutional transformation.
These objectives collectively reflect the participatory and iterative nature of the project. Consistent with CBPR, these objectives will be revisited and refined throughout the study in dialogue with students, faculty, and other stakeholders.
The overall study design is a mixed-methods comparative longitudinal study over 4 years to follow two cohorts of students. It includes a cross-sectional baseline of all students admitted from 2025 to 2028 and a longitudinal follow-up of two cohorts admitted in 2025, one in the student-centered curriculum and one in the course-centered curriculum (both described in detail in section 2.3), combining validated instruments, structured observations, participatory data co-construction, and institutional records. This design enables both cross-sectional and longitudinal analyses, capturing intra-cohort trajectories and inter-cohort differences over time.
The study is implemented within a single institutional context, encompassing all undergraduate programs at the Polytechnic School of the University of São Paulo (EPUSP). It includes all undergraduate students admitted from 2025 to 2028, who together constitute the cross-sectional component, providing population-level data on mental health, engagement, and motivation among all incoming students during this 4-year period.
Within this broader frame, the longitudinal component tracks two cohorts of students admitted in 2025: one following the new student-centered curriculum and another following the course-centered curriculum. Each cohort includes approximately 280 students (student-centered n ≈ 282; course-centered n ≈ 271) and reflects the overall distribution of open-competition and affirmative-action entrants. These cohorts are followed from 2025 through 2028 to examine individual trajectories of motivation, engagement, wellbeing, and mental health.
The overall study population thus comprises roughly 3,480 students across the 2025–2028 admission cycles and a sample of about 20 faculty members, including at least one representative from each EPUSP department.
Inclusion criteria encompass undergraduate students regularly enrolled in the programs described above and faculty members invited or nominated from different departments. Exclusion criteria include students, faculty, or staff who do not wish to participate, those who fail to complete questionnaires within the established timeframe, or participants who withdraw consent at any stage. Participation is voluntary and without incentives. All participants provide informed consent prior to enrollment, and data collection complies with institutional research-ethics procedures.
The study adopts a CBPR approach within a multiphase mixed-methods cohort design as its central methodological foundation. This approach is a collaborative strategy that engages participants equitably, integrating diverse forms of knowledge around a shared problem and enabling researchers and students to jointly identify challenges, co-develop responses, and generate actionable solutions (Wallerstein et al., 2018). At EPUSP, this process is formally organized through a Research Steering Committee (students, faculty, and staff) that ensures shared decision-making across all phases of the study.
Grounded in the ethics of inclusion, CBPR provides safe spaces for dialogue and a framework for examining the social determinants of health in higher education contexts. As a methodological strategy, it advances epistemic justice and practical intervention by positioning students as co-producers of knowledge and action.
The multiphase design integrates quantitative and qualitative methods in sequential or concurrent connections (Creswell and Plano Clark, 2017). This approach is particularly suited for program evaluation—as it enables each phase to address specific questions, such as exploratory analysis of contextual and institutional conditions, needs assessment, program development, and outcome evaluation—while contributing to a comprehensive understanding of student mental health, engagement, and academic motivation over time. Longitudinal follow-ups occur annually with identical core instruments.
2.2 Theoretical framework
This study combines the three complementary frameworks: Community-Based Participatory Research (CBPR), Bronfenbrenner’s Bioecological Model of Human Development, and Self-Determination Theory (SDT). The Bioecological Model, originally conceptualized as the socioecological model and later expanded, emphasizes the PPCT structure (Proximal Processes, Person, Context, and Time) to examine how individual characteristics interact with multiple layers of the academic environment over time, influencing mental health, engagement, and motivation (Bronfenbrenner and Morris, 2006). CBPR, in turn, promotes equitable stakeholder participation across all phases of the research process, emphasizing shared decision-making and institutional co-responsibility (Wallerstein et al., 2018). SDT complements these frameworks by offering a psychological foundation for understanding motivation and well-being within processes of institutional change. It highlights that the satisfaction of basic psychological needs for autonomy, competence, and relatedness promotes and sustains the type and quality of motivation, engagement, and active participation (Deci and Ryan, 2000). When integrated, these three perspectives provide a comprehensive lens for examining higher education as an ecological and participatory system, where institutional changes—such as curricular reforms—function as key strategies for promoting cultural transformation, equity, and mental health.
Building on this theoretical integration, the project adopts CBPR as the central methodological foundation, integrated with Bronfenbrenner’s PPCT structure and SDT as analytical lenses. CBPR guides co-learning, safe spaces for dialogue, shared decision-making, and mutual benefit; the PPCT framework structures analysis of how individual, contextual, and temporal factors interact to shape student experiences; and SDT informs interpretation of motivational and well-being outcomes by linking the satisfaction of psychological needs to broader ecological and institutional conditions. Through this integration, the study advances an ecological-participatory understanding of student engagement and mental health, situating personal motivation within the social, institutional, and historical systems that influence mental health, wellbeing, and engagement.
The study is designed around the four core CBPR model dimensions—context, partnership processes, intervention and research, and outcomes (Wallerstein et al., 2020), as shown in Figure 1, explicitly linking each dimension to a PPCT component and an SDT contribution. This integration highlights how relational, motivational, and structural processes interact to shape institutional environments that promote well-being and equity.
Figure 1. CBPR conceptual model adapted from Wallerstein et al. (2018).
By framing universities as health-promoting institutions, the theoretical framework connects educational transformation with broader public health outcomes: participatory structures strengthen social connectedness and belonging, motivational climates enhance engagement and performance, and sustained institutional reforms act as long-term determinants of mental health and health equity. Table 1 summarizes the interrelations among these frameworks and illustrates how they contribute to public health by fostering institutional health promotion.
Table 1. Integrating CBPR, bioecological (PPCT), and self-determination (SDT) frameworks for institutional health promotion.
Within the CBPR Model, the four dimensions are integrated (see Figure 1). The first context dimension recognizes that inequities in engineering education are shaped by social, cultural, institutional, and historical conditions. Following the PPCT perspective, these contexts are examined across multiple ecological levels, from the Microsystem of classrooms and laboratories, through the Mesosystem of family–university relations, the Exosystem of policies and financial support, and the Macrosystem of cultural values and norms, to the Chronosystem of curricular reforms and broader societal events. From an SDT standpoint, contextual features that support autonomy, competence, and relatedness through choice, recognition, and inclusion promote autonomous motivation and well-being.
The second partnership processes dimension emphasizes principles of trust, co-learning, and shared decision-making, which are enacted through the creation of a steering committee composed of students, faculty, and administrators. In PPCT terms, these dynamics are conceptualized as proximal processes: reciprocal and enduring interactions that drive development, engagement, and collaboration within the academic environment. SDT complements this view by explaining how reciprocal and sustained interactions satisfy needs for relatedness and competence, enhancing collective efficacy, psychological safety, and sustained participation.
Within the third intervention and research design dimension, participatory practices are central. Surveys and focus group guides are co-developed with students, who also engage as co-researchers in qualitative data coding and instrument validation to ensure cultural and contextual relevance. From a PPCT perspective, this dimension focuses on person-level factors such as motivation, mental health, and socioeconomic conditions, analyzing them not in isolation but in relation to both proximal processes and broader contexts. SDT provides a psychological interpretation of these patterns by linking students’ perceptions of autonomy support, feedback quality, and collaborative involvement to the quality of their motivation (autonomous versus controlled) (Deci and Ryan, 2000). In this way, the design dimension connects participatory practice with the psychological mechanisms that foster persistence, engagement, and adaptive coping within academic settings.
Finally, the fourth outcomes dimension emphasizes the co-production of knowledge and action to strengthen students’ research and leadership capacity, supporting mental health and engagement, and informing inclusive curricular reforms. In line with the PPCT structure, outcomes are assessed longitudinally across temporal levels: Microtime (day-to-day peer and faculty interactions), Mesotime (sustained initiatives across semesters), and Macrotime (policy reforms, historical changes, and institutional transformations). From an SDT perspective, the sustained satisfaction of psychological needs across these temporal levels predicts enduring engagement, well-being, and institutional attachment.
Together, these integrated frameworks establish a dynamic model that connects motivation, participation, and institutional context, positioning higher-education reform as a structural determinant of student mental health, equity, and institutional sustainability.
2.3 Setting
The Polytechnic School of the University of São Paulo (EPUSP), one of Latin America’s leading engineering schools with over 5,000 undergraduates, offers 17 distinct five-year engineering programs, admitting about 870 new students annually (with class sizes of 40–70 students per program). Affirmative-action policies were implemented in 2018 and, by 2021, accounted for more than 50% of admissions. In addition, EPUSP began a substantial curricular reform aimed at strengthening students’ sense of belonging and enhancing relationships among faculty, between faculty and students, and among students themselves within each program.
Curriculum redesign in each program was guided by national guidelines (Brasil Ministério da Educação, Conselho Nacional de Educação, Câmara de Educação Superior, 2019) and program-specific needs, within a broader competency-based framework in which technical competencies integrate disciplinary knowledge, methodological skills, and problem-solving attitudes, while socio-emotional competencies combine interpersonal knowledge, transversal skills such as communication and teamwork, and the values and behaviors that support collaboration, resilience, and ethical practice. This design incorporated active-learning methodologies and shifted pedagogical practices not only from teacher-centered to student-centered instruction, but also from a course-centered to a student-centered curriculum.
As depicted in Figure 2, in the former course-centered curriculum, interaction was designed to occur primarily among faculty within the same course. This approach applied identical examinations across all student groups, disregarding the specific characteristics of each program and its students’ backgrounds. This structure created a disconnect not only among faculty from different courses but also between faculty and students, which has continued to limit curricular coherence, interdisciplinary integration, and the supportive relationships essential for students’ well-being.
Figure 2. Comparison of course-centered and student-centered curricular structures and their implications for institutional determinants of student health and learning—mental health, motivation, engagement, and academic performance. Left: In the course-centered curriculum (indicated by the left rounded rectangle), faculty interactions are primarily organized within each course (e.g., Course 1 in the solid-line rectangle), with limited consideration of student profiles distributed across Programs 1 to n. Right: In the student-centered curriculum (indicated by the right rounded rectangle), faculty interactions are organized around a common cohort of students (e.g., students within Program 1 spanning multiple courses from Course 1 to Course n), emphasizing individual profiles and learning trajectories.
In the student-centered curriculum, instruction and assessment are coordinated across multiple subjects for the same student cohort. Faculty collaborate across courses, adapting teaching and evaluation to the group’s pace and needs, emphasizing curricular integration and student engagement. Its multidisciplinary design fosters the development of both technical and socio-emotional competencies, while actively addressing the diverse backgrounds, experiences, and needs of its students.
At a broader level, recent evidence suggests that such strategies transcend disciplinary boundaries. Consistent with this perspective, Bersoto et al. (2025) highlight that strategies for promoting equity are not course-specific, but cross-cutting among higher education institutions. Although initiatives may emerge from localized contexts, institutional support mechanisms—such as interdepartmental collaboration, curricular reform, psychosocial support, and evidence-based decision-making—are broadly transferable across fields of knowledge.
Within this context of transformation, this study aims to compare the effects of modifications in curricular structures—such as workload, program organization, and disciplinary diversity—on students’ mental health, academic performance, motivation, and engagement, applying the CBPR-PPCT-SDT integrated framework.
2.4 Study phases
Table 2 summarizes the sequential and iterative phases of the study, structured according to a CBPR framework that integrates participatory governance, co-learning, empowerment, and sustainability. Each phase combines research and action elements to ensure that findings contribute to both scientific knowledge and institutional transformation toward equity and well-being.
Table 2. Study phases, time windows, activities, data sources, and outputs.
In summary, the 2024 preparatory phase focused on co-constructing the study design, instruments, and ethical framework. The first year (2025) centers on the exploratory phase, baseline data collection, and stakeholder engagement. The second year (2026) includes follow-up data collection, preliminary analysis, and workshops. The third year (2027) continues data collection and cross-cohort analysis, and the fourth (2028) concludes with final data collection, integrated analysis, and recommendations.
2.5 Data collection instruments
Quantitative data will consist of scores from validated self-report scales (GAD-7, PHQ-9, CBI-S, ASSIST, UWES-S, AMS, SIQ, PSQI, and ESS), document analyses, and a sociodemographic questionnaire administered to all students admitted between 2025 and 2028. Pilot administration of selected instruments was completed in 2024 to refine procedures and ensure cultural and linguistic validity. The full baseline data collection began in early 2025 and will continue annually through 2028, as scheduled in Section 2.4 (Phases 3 and 6). This longitudinal design allows assessment of within-person changes over time and between-cohort comparisons across curricular models, while annual administrations support cross-sectional comparisons across admission years.
The longitudinal component follows two cohorts of students admitted in 2025: one enrolled in the new student-centered curriculum and another in the previous course-centered curriculum. Each cohort comprises all students admitted in 2025 to the engineering programs selected for cohort composition, maintaining the exact admission characteristics of these programs. For these two cohorts, the study continues to administer the instruments and conduct structured observations (COPUS and DART), interviews, focus groups, field diaries, classroom observations, and document analyses. Acronyms are defined in the following paragraphs.
Generalized anxiety symptoms will be assessed using the Generalized Anxiety Disorder–7 (GAD-7), a seven-item instrument that evaluates nervousness, uncontrollable worry, restlessness, and related DSM-5 criteria over the past 2 weeks on a four-point scale (Gonçalves et al., 2023), capturing data primarily at Bronfenbrenner’s Person level, reflecting individual psychological functioning.
Depressive symptoms will be measured with the Patient Health Questionnaire–9 (PHQ-9), a nine-item self-report instrument covering DSM-5 criteria for major depression, including depressed mood, anhedonia, fatigue, sleep and appetite changes, guilt, concentration problems, psychomotor changes, and suicidal ideation, rated on a 0–3 Likert scale (Santos et al., 2013). Similar to the GAD-7, the PHQ-9 addresses the Person level while highlighting how individual distress is shaped by relational contexts in the Microsystem.
Burnout related to academic life will be evaluated with the Copenhagen Burnout Inventory – Student version (CBI-S), a 25-item instrument validated for Brazilian university students that assesses four domains (personal, studies, peers, professors) on a 1–5 frequency scale (Campos et al., 2013). This instrument extends the focus from the Person to the Microsystem, as it measures exhaustion and relational strains within immediate academic environments.
Substance-use involvement will be assessed with the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), a structured eight-item instrument covering nine psychoactive substances and producing risk scores that distinguish occasional use, abuse, and dependence (Henrique et al., 2004). While centered on the Person, the ASSIST is also sensitive to Microsystem and Mesosystem influences, since patterns of use are strongly linked to peer groups and institutional norms.
Academic engagement will be measured using the Utrecht Work Engagement Scale for Students (UWES-S), a 17-item instrument with three subscales—vigor, dedication, and absorption—each rated on a seven-point Likert scale. The scale shows high internal consistency and will be used to compute a mean engagement score (Schaufeli and Bakker, 2004; Silva et al., 2018). Engagement is situated at the Microsystem, reflecting the direct relationship between students and their learning environments.
Academic motivation will be assessed using the Academic Motivation Scale (AMS), a 28-item instrument aligned with Self-Determination Theory (SDT). The scale distinguishes amotivation, extrinsic motivation (external, introjected, and identified regulation), and intrinsic motivation (to know, to accomplish, and to experience stimulation), with responses rated on a seven-point Likert scale (Vallerand et al., 1992; Souza et al., 2021; Kirn and Benson, 2013). Motivation originates at the Person level but is shaped by Microsystem dynamics (e.g., classroom context) and Mesosystem interactions across settings such as family, peers, and the university.
Suicidal ideation will be measured using the Suicidal Ideation Questionnaire (SIQ), adapted for the Portuguese population (Gomes, 2008). It consists of 30 items rated on a six-point scale; higher scores indicate greater ideation, scores ≥ 41 suggest clinical risk (Vasconcelos-Raposo et al., 2016; Gomes, 2008). This construct reflects critical processes at the Person level but is also linked to dynamics of belonging and exclusion within the Microsystem.
Sleep quality will be assessed with the Pittsburgh Sleep Quality Index (PSQI), a widely validated instrument that evaluates sleep quality and disturbances over the previous month (Bertolazi et al., 2011; Buysse et al., 1989). Daytime sleepiness will be measured with the Epworth Sleepiness Scale (ESS), an eight-item questionnaire assessing the likelihood of dozing in common daily situations, with scores > 10 indicating excessive daytime sleepiness. Both instruments primarily capture Person-level patterns while acknowledging the role of the Microsystem (academic routines, study schedules) in shaping sleep and alertness.
Complementing psychological and self-report data, classroom-observation tools provide behavioral evidence of learning dynamics and instructional practices. Student and instructor behaviors in undergraduate classrooms will be observed using the Classroom Observation Protocol for Undergraduate STEM (COPUS), designed to document classroom practices with minimal observer training (Smith et al., 2013). COPUS records 12 instructor and 13 student behaviors at 2-min intervals, estimating engagement at low (<20%), medium (20–80%), or high (>80%) levels. Observations are non-participatory and conducted by paired observers in a non-intrusive manner. The protocol avoids subjective judgments such as “good teaching,” increasing faculty acceptance, though it provides limited information on instructional quality. COPUS is objective, quantitative, reliable across observers, and enables comparisons among instructors, courses, and institutions, with a minimum requirement of four observations per course. It can be applied either through in-person observation or analysis of video recordings.
Speech patterns and instructional activities will be used as a complement to observational measures using the Decibel Analysis for Research in Teaching (DART), which automatically distinguishes discussion, reflection, and traditional lecturing (Owens et al., 2017). DART does not require prior training and, unlike COPUS, performs continuous analysis rather than fixed-interval coding. Its purpose is to help instructors recognize how class time is distributed across different modes of teaching. Application is based on audio recordings of classroom sessions.
The sociodemographic questionnaire and academic records provide a detailed description of each participant’s socio-territorial background, including educational history, living conditions, and mobility. This territorial dimension will be further characterized using two complementary analytical tools: the Social Vulnerability Index (IVS) (Ipea, 2015) and the Human Development Units (UDHs) (Nakamura and Veneziani, 2015). The IVS quantifies social vulnerability across three core dimensions—urban infrastructure (including access to neighborhood services and transportation), human capital, and income and labor conditions—while UDHs delineate intra-urban microregions with relatively homogeneous socioeconomic profiles. Each student’s residential address will be geocoded to its corresponding UDH, which carries a standardized IVS score. These spatial indicators will then be integrated with individual-level data to position each participant within their territorial environment and enable multilevel analyses of how neighborhood and structural factors interact with individual well-being, motivation, and academic outcomes.
The coexistence of curriculum models enables both cross-sectional population analyses and longitudinal tracking of the two 2025 cohorts. Together, these data sources provide a multidimensional view of students’ experiences, linking individual trajectories with curricular structures, institutional practices, and broader territorial and social inequalities.
2.6 Data analysis
This protocol adopts an integrated approach to evaluate institutional transformation, linking the structural changes being implemented (curriculum reform, affirmative-action policies) with individual and psychosocial outcomes (mental health, motivation, engagement). Following this conceptual overview, the analytical plan for quantitative, qualitative, and mixed-methods integration is presented.
Table 3 summarizes the institutional determinants of health, equity, and academic performance examined in this study, operationalizing a “whole-institution” and intersectoral approach that links structural and psychosocial dimensions through validated quantitative scales and participatory qualitative methods.
Table 3. Institutional determinants of health, equity, and academic performance.
The cross-sectional component of the study (Phase 3) involves administering the standardized instruments and the sociodemographic questionnaire to all students admitted each year from 2025 to 2028. This stage is based on a closed population frame defined by the institutional registry and official course enrollments. All eligible students are included in this frame and invited to complete the instruments during scheduled class sessions. Although participation is voluntary, the study uses a complete institutional frame in which every eligible student is invited and has an equal opportunity to participate. This design preserves the key properties of finite-population inference by ensuring that nonresponse can be explicitly evaluated and adjusted using available auxiliary data.
Consistent with best practices in survey methodology, and as noted by Groves (2006), well-defined sampling frames make it possible to evaluate coverage error relative to the target population before data collection, and auxiliary variables available on the frame can later be used for post-survey adjustments. To minimize potential frame error, make-up sessions and secure institutional e-mail invitations will be offered to absent students. Auxiliary variables such as admission pathway, race/ethnicity, gender, age, and program will support calibration weighting and nonresponse adjustments to reduce residual bias in final estimates. These procedures establish the baseline for subsequent quantitative analyses.
Quantitative data will be computed following the published scoring procedures for each instrument. The resulting scale scores will be analyzed using descriptive, exploratory, and inferential methods, including multivariate regression and mixed-effects longitudinal modeling, to examine associations with sociodemographic characteristics, territorial indicators, and classroom practices.
Analyses may be refined once data are collected and explored. Initial steps are expected to include examining internal consistency and dimensionality for each scale, followed by descriptive and exploratory analyses to characterize score distributions and assess assumptions. Preliminary between-group differences (e.g., curriculum type, gender, admission pathway) will likely be explored using standard inferential approaches such as t-tests, ANOVA, and confidence intervals to generate baseline comparisons and effect-size estimates. Contingent on data properties, scale scores will be modeled as continuous outcomes in multivariate and mixed-effects longitudinal frameworks, allowing for repeated measures, hierarchical structure, and multiple predictors. Missing data will be managed using maximum-likelihood estimation within mixed-effects models, supplemented by multiple imputation for sensitivity analyses (Graham, 2009; Biering et al., 2015). We will privilege finite-population inference procedures, appropriate when sampling from complete institutional cohorts, to ensure appropriate precision and contextual validity. Quantitative analysis will be conducted using R (version 4.3.2) and Python (version 3.11), with version-controlled analytical scripts and data dictionaries to support transparency and reproducibility. Software citations for R and Python are provided in the reference list (R Core Team, 2025; Python Software Foundation, 2025).
For the longitudinal component, we will follow two 2025 cohorts: (i) the course-centered cohort, encompassing all 271 students enrolled in that curriculum model; and (ii) the student-centered cohort, comprising 282 students drawn from four complete programs within that model (282 / 599 = 47.1% of all 2025 entrants). Both cohorts are defined by complete enrollment groups rather than individual selection, ensuring that no study-based allocation occurs and that each retains the proportional representation of affirmative-action, gender, and other sociodemographic characteristics observed in its full population. Annual data-collection waves for these two cohorts will be conducted from 2025 through 2028 to examine trajectories of motivation, engagement, and mental health. Analyses will employ mixed-effects longitudinal models with individual random effects, adjusting for covariates such as admission pathway, race/ethnicity, gender, age, and program. When necessary, post-survey weighing will reinforce cross-cohort comparability between curriculum models. Retention procedures—including supervised in-class sessions and secure make-up windows—will be implemented at each wave to mitigate attrition and reduce nonresponse bias. Based on attrition patterns observed in comparable multi-year higher-education and mental-health studies (Cuijpers et al., 2019; Auerbach et al., 2018), we anticipate an overall attrition of approximately 20–30% across waves. This expected range will guide sample-size monitoring and post-survey adjustments to maintain representativeness of cohort estimates. To ensure comparability of scale scores over time, measurement invariance (configural, metric, and scalar) will be tested for each psychometric instrument before modeling change.
During Phase 6, extensive qualitative procedures will be implemented in both cohorts, covering the 3rd to 7th semesters. Each cohort will be invited to participate in focus groups to discuss their experiences and, subsequently, in co-analysis sessions in which students jointly examine and interpret emerging quantitative and qualitative results. This phase will integrate these activities through systematic triangulation across methods and data sources to ensure robustness and contextual validity.
Given the cohort sizes (n₁ = 271, n₂ = 282), a two-sample comparison (two-tailed, α = 0.05, 80% power) can detect standardized differences of approximately 0.24 SD in a single wave. In the longitudinal design, where repeated measures reduce error variance through within-subject correlations, the effective detectable effect size will be smaller (≈ 0.18–0.21 SD), ensuring sufficient sensitivity to detect modest changes in motivation, engagement, and mental health across time and between cohorts.
The IVS and UDH data, linked through residential postal codes to the sociodemographic questionnaire, standardized instruments, and academic records, will allow contextual variables—such as access to neighborhood services, transportation, urban infrastructure, income, and human capital—to be included as Level-2 predictors in multilevel models. These indicators will enable the assessment of contextual effects on mental health, motivation, and well-being outcomes while controlling for individual-level covariates.
Classroom observation using COPUS and DART will occur from 2025 to 2028 across the course-centered and student-centered cohorts (≈ 280 students each). Each year, four courses per cohort will be observed, with four class sessions per course coded by two trained observers using COPUS, yielding 32 observed sessions annually (128 total). This design ensures consistent coverage across curricular models and allows examination of instructional variation over time. COPUS and DART generate structured categorical indicators of classroom activity, providing frequency and proportion data for descriptive and comparative analysis across classes and years. DART outputs will complement COPUS findings, with COPUS serving as the primary quantitative observation tool. Although not included as inferential predictors, COPUS and DART observations will contextualize the learning environments of each cohort, serving as triangulation tools that link proximal classroom processes with institutional and psychosocial determinants of wellbeing.
Qualitative data will be analyzed through thematic coding in ATLAS.ti software (ATLAS.ti Scientific Software Development GmbH, 2025). The coding framework will be informed by the PPCT components of Bronfenbrenner’s bioecological model (Proximal Processes, Person, Context, and Time) while remaining open to emergent themes identified through CBPR processes. This hybrid approach combines deductive (theory-driven) and inductive (data-driven) strategies, allowing for the integration of a priori categories and context-specific insights. Thematic analysis will follow the steps articulated by Braun and Clarke (2006)—familiarization, coding, theme development, review, and reporting—further detailed in their practical guide (Braun and Clarke, 2013). Building on these foundations, the study will adopt a reflexive stance consistent with applied health and education research, emphasizing researcher reflexivity, iterative coding, and participatory interpretation workshops (Campbell et al., 2021). To ensure contextual validity and stakeholder engagement, the process will also draw on a hybrid model of thematic analysis that combines deductive theoretical categories with inductive coding of emergent issues in educational research (Xu and Zammit, 2020). Participatory validation workshops with students, faculty, and staff will be conducted to review and refine interpretations, thereby enhancing credibility and reinforcing principles of epistemic justice.
Integration will be achieved through mixed-methods triangulation and participatory interpretation to ensure that findings are analytically robust and contextually relevant. This process will link individual, relational, institutional, and territorial dimensions, while enabling stakeholders to co-validate interpretations and co-develop actionable strategies for academic and policy change.
3 Discussion
This protocol presents a longitudinal and participatory study designed to analyze institutional transformation as a structural health-promoting process in higher education. Grounded in the Transforming Academia for Equity agenda, the study integrates three complementary frameworks—Community-Based Participatory Research (CBPR), the Bioecological Model of Human Development (PPCT), and Self-Determination Theory (SDT)—to investigate how curricular structures and academic environments influence motivation, engagement, mental health, and academic performance, particularly those from historically marginalized groups. Together, these perspectives provide a multilevel and participatory lens for examining higher education as an ecological system in which institutional conditions and governance processes shape individual and collective well-being, and whether they serve students who come from widely different backgrounds of vulnerability. CBPR emphasizes equitable power-sharing and co-responsibility throughout all research phases, enhancing contextual validity and inclusion in mental-health promotion (Collins et al., 2018; Yau et al., 2024). Bronfenbrenner’s PPCT structure situates student outcomes within reciprocal interactions between personal characteristics, proximal processes, and multiple layers of context over time (Bronfenbrenner and Morris, 2006). SDT adds a psychological foundation for understanding how autonomy, competence, and relatedness sustain engagement and motivation during curricular reform. In concert, these frameworks align with adaptive-change strategies in public health that seek to build environments consistent with democratic values and social justice, emphasizing systemic transformation rather than individual-level remediation (Burns et al., 2024; Pieraccini, 2019).
As an exemplary case, we are conducting a study at Polytechnic School of the University of São Paulo (EPUSP). The field of engineering is globally recognized for its intense academic demands, competitiveness, and disciplinary norms that normalize chronic stress and marginalize non-dominant identities. In Brazil, engineering remains predominantly male and accessible mainly to high-income students, marked by racial and gender disparities (Howard-Bostic et al., 2020). These challenges are magnified for underrepresented groups—such as quota students, Black and Indigenous individuals, LGBTQIA+ students, and those from low-income backgrounds—due to the intersection of individual vulnerabilities (mental distress, financial stress, social isolation) with structural barriers (curriculum design, institutional climate, unequal access to academic and health support) (Silveira et al., 2019; de Souza et al., 2015; Tormon et al., 2023).
While such issues are increasingly documented, most studies employ cross-sectional designs and treat students as subjects of analysis rather than agents of transformation (Bork and Mondisa, 2022). In this context, recent curricular reforms at EPUSP—such as competence-based and student-centered programs represent a unique opportunity for structural transformation (Rehder et al., 2024). These reforms aim to replace fragmented, content-heavy curricula with student-centered, active learning methodologies focused on both technical and socio-emotional skills. Their goal is to improve academic performance, foster well-being, and promote belonging and engagement.
To assess this transition, the research design integrates subjective, structural, and relational dimensions. Key strengths include a broad sample of approximately 3,500 students, the use of validated instruments to measure mental health, motivation, and engagement, and triangulation with classroom observations, institutional records, and geographic vulnerability indicators. This comprehensive approach allows for a richer understanding of how institutional and personal factors intersect. Importantly, the study includes comparison groups—students enrolled in traditional versus reformed curricula—enabling robust structural comparisons.
The adoption of participatory evaluation strategies promotes equitable power sharing across all phases of the study—priority setting, data analysis, and dissemination—through steering committees, conversation circles, and co-validation of instruments, thereby supporting principles of epistemic justice. These participatory practices are grounded in participatory action research approaches that challenge traditional academic hierarchies and foster student–staff partnerships capable of shifting power dynamics and enhancing epistemic confidence among marginalized students (Davis and Parmenter, 2020). Such strategies are particularly effective in contexts marked by epistemic inequality and have been linked to expanding students’ epistemic capabilities, creating inclusive knowledge environments, and contributing to social transformation (Boni and Walker, 2020). Within this framework, the PPCT structure offers an ecological perspective for analyzing how proximal processes (e.g., peer and faculty interactions), individual characteristics (motivation, stress), and multiple contexts (family, institutional, cultural) interact over time to shape academic trajectories, providing ecological validity and emphasizing the developmental complexity of student experiences (Bronfenbrenner and Morris, 2006). Complementarily, SDT informs the interpretation of motivational and well-being outcomes by linking the satisfaction of psychological needs for autonomy, competence, and relatedness to broader ecological and institutional conditions. Together, these frameworks move beyond the individualizing lens often applied to mental health in higher education. Rather than treating depression, anxiety, or burnout as isolated conditions, the study situates them within broader institutional dynamics—pedagogical practices, retention policies, institutional climate, and historical inequities—that influence student well-being.
In Brazil, the adoption of affirmative action policies since 2012 has significantly diversified the student profile in higher education and the implementation of a curricular reform at EPUSP makes the present study especially timely: while important changes are underway, their consolidation requires systematic evaluation and participatory processes. The protocol is designed to follow this transition closely and to produce recommendations that can further support equity and student well-being in engineering education (Fernandes and Filho, 2015).
Practically, the study aims to inform institutional action beyond academic publication. It includes co-creating mental health and engagement interventions, providing recommendations for curricular development, producing policy-oriented reports, and organizing training workshops for faculty and students. It also seeks to build participatory monitoring and evaluation strategies to guide long-term institutional policy reform.
Expected limitations include the heterogeneity of curricular reform implementation, potential attrition in the longitudinal cohort, and the non-experimental nature of the study. Nevertheless, predictive models will be used to identify robust associations and generate hypotheses for future interventions (Silveira et al., 2019; Mariano et al., 2022).
By combining assessment with active community participation, this protocol offers a replicable model of curricular transformation for other higher education institutions, particularly in contexts marked by inequality. Its results are expected to support new strategies for promoting well-being, inform institutional planning, refine evaluation metrics, and inspire curricular reforms grounded in technical competence, equity, and mental health promotion.
4 Conclusion
This protocol outlines a longitudinal and participatory study designed to analyze institutional transformation as a health-promoting and equity-building process through the combined lenses of Community-Based Participatory Research (CBPR), the Bioecological Model of Human Development (PPCT), and Self-Determination Theory (SDT). By integrating these frameworks, the study advances an ecological and psychologically grounded understanding of how curricular and institutional conditions influence motivation, engagement, and mental health in higher education. It emphasizes systemic transformation and the creation of equity-oriented environments rather than individual-level remediation.
The Polytechnic School of the University of São Paulo (EPUSP) provides a timely and exemplary case for this investigation. In a context where engineering education is marked by high academic demands and persistent inequalities, the convergence of curricular reform and affirmative-action policies offers a unique opportunity to evaluate the impact of structural change on student well-being and academic success. By aligning with national inclusion policies and ongoing curricular modernization efforts in Brazilian higher education, the study contributes both to academic research and to the advancement of institutional policy. Following a cohort throughout this transition reflects a commitment to systematic impact evaluation and continuous improvement—an essential step toward more equitable, inclusive, and health-promoting models of engineering education.
Building on this context, the study addresses key knowledge gaps by examining how institutional transformation affects mental health, academic engagement, and motivation among engineering students at EPUSP. Grounded in the principles of health promotion and equity, the research adopts a participatory approach informed by CBPR, which actively involves students in data collection and interpretation. This design not only deepens the understanding of lived experiences but also fosters collective reflection and the co-production of institutional transformation strategies.
Methodologically, the study integrates quantitative and qualitative strategies with participatory validation, ensuring that diverse perspectives inform analysis and interpretation. Through conversation circles, steering committees, and the co-creation of instruments, it promotes epistemic justice and empowers historically marginalized students to take part in defining institutional priorities.
More broadly, this protocol advances a vision of higher education committed to democratic participation, social justice, and health promotion. Its expected contributions extend beyond academic outcomes: they include building institutional capacities for inclusive governance and providing evidence-based pathways toward more equitable, supportive, and resilient universities.
Beyond the context of engineering, this case study has critically important implications for the field of public health. It examines mental health as a key dimension of equity within the academic environment, engaging with a wide diversity of student backgrounds. Importantly, the research provides a transferable framework for other disciplines undergoing curricular transitions toward student-centered learning. The CBPR approach further enables real-time reflections on data collection, analysis, and interpretation, thereby generating timely and contextually grounded recommendations for institutional transformation.
5 Expected outcomes and impact
• Development of culturally responsive indicators and participatory monitoring tools for tracking student well-being, motivation, and engagement.
• Generation of longitudinal, equity-focused evidence on the mental health, engagement, and motivation of engineering students.
• Production of context-specific recommendations for curricular reform and institutional policy.
• Delivery of concrete outputs for institutional stakeholders, including management reports, proposals for policy adjustments, and participatory workshops with faculty and students.
• Establishment of an adaptable framework for equity-driven curricular transformation in higher education, offering principles to inform initiatives in other engineering schools and universities in Brazil and internationally.
Ethics statement
The studies involving humans were approved by Hospital das Clínicas, Faculty of Medicine, University of São Paulo (HCFM/USP) Ethics Committee Approval No. 7,214,210. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
CS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing. NW: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing. LL: Writing – original draft. OB: Writing – original draft. FK: Conceptualization, Investigation, Methodology, Writing – review & editing. FL: Conceptualization, Methodology, Validation, Writing – review & editing. AS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. The authors gratefully acknowledge the participation of students, faculty, and staff of the Polytechnic School of the University of São Paulo (EPUSP), as well as the support of the Department of Psychiatry of the University of São Paulo Medical School (FMUSP) and CEPEDOC Cidades Saudáveis, a PAHO/WHO Collaborating Center.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
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References
Adsul, P., Sanchez-Youngman, S., Dickson, E., Jacquez, B., Kuhlemeier, A., Muhammad, M., et al. (2025). Assessing the context within academic health institutions toward improving equity-based, community and patient-engaged research. J. Clin. Transl. Sci. 9:e6. doi: 10.1017/cts.2024.675,
Akram, U., Ypsilanti, A., Gardani, M., Irvine, K., Allen, S., Akram, A., et al. (2020). Prevalence and psychiatric correlates of suicidal ideation in UK university students. J. Affect. Disord. 272, 191–197. doi: 10.1016/j.jad.2020.03.185,
American College Health Association. The influence of environmental factors on the emotional well-being of students, staff, and faculty: a white paper. Silver Spring (MD): ACHA.
Association of Schools and Programs of Public Health. Dismantling racism and structural racism in academic public health: a framework [Internet]. ed. ASPPH. Washington, DC.
ATLAS.ti Scientific Software Development GmbH. ATLAS.ti (Version 24) [software]. Berlin (DE): ATLAS.ti Scientific Software Development GmbH; 2025
Auerbach, R. P., Mortier, P., Bruffaerts, R., Alonso, J., Benjet, C., Cuijpers, P., et al. (2018). WHO world mental health surveys international college student project: prevalence and distribution of mental disorders. J. Abnorm. Psychol. 127, 623–638. doi: 10.1037/abn0000362,
Barros, J. P., and Sousa, C. E. B. (2022). Privação crônica do sono e desempenho escolar-acadêmico: uma revisão sistemática. Rev. Neurocienc. 30, 1–24. doi: 10.34024/rnc.2022.v30.13010
Bersoto, M. A., Manigbas, M. J. V., Perez, R. P., and Magpantay, D. M. (2025). Addressing barriers to educational equity. Int. J. Basic Appl. Sci. 14, 722–729. doi: 10.14419/p0b6mp97
Bertolazi, A. N., Fagondes, S. C., Hoff, L. S., Dartora, E. G., Miozzo, I. C. S., Barba, M. E. F., et al. (2011). Validation of the Brazilian Portuguese version of the Pittsburgh sleep quality index. Sleep Med. 12, 70–75. doi: 10.1016/j.sleep.2010.04.020
Biering, K., Hjollund, N. H., and Frydenberg, M. (2015). Using multiple imputation to deal with missing data and attrition in longitudinal studies with repeated measures of patient-reported outcomes. Clin. Epidemiol. 7, 91–106. doi: 10.2147/CLEP.S72247,
Boni, A., and Walker, M. (2020). “Potential of participatory action research” in Participatory research, capabilities and epistemic justice. eds. M. Walker and A. Boni (Cham: Palgrave Macmillan).
Bork, SJ, and Mondisa, J 2022. Exploring the relationship between culture and science, engineering, and mathematics graduate students’ mental health. In: ASEE Annual Conference & Exposition
Brasil. (2019) Ministério da Educação. Conselho Nacional de Educação. Câmara de Educação Superior. Resolução CNE/CES nº 2, de 24 de abril de 2019. Institui as Diretrizes Curriculares Nacionais do Curso de Graduação em Engenharia. Diário Oficial da União. (2019 Apr 24). Available online at: https://www.semesp.org.br/legislacao/resolucao-cne-ces-no-02-de-24-de-abril-de-2019/ (Accessed November, 11, 2025).
Braun, V., and Clarke, V. (2006). Using thematic analysis in psychology. Qual. Res. Psychol. 3, 77–101. doi: 10.1191/1478088706qp063oa
Braun, V., and Clarke, V. (2013). Successful qualitative research: A practical guide for beginners. London: SAGE Publications.
Bronfenbrenner, U, Morris, PA. The bioecological model of human development. In: W Damon and RM Lerner, editors. Handbook of child psychology. 6th ed. Vol. 1. Hoboken (NJ): Wiley; (2006). 793–828.
Burns, A., Kampman, H., Magee, L., Blackburn, J., Alton, M., and Pescosolido, B. (2024). Implementation and sustainability of systems change for mental health promotion and substance misuse prevention: a qualitative study. BMC Health Serv. Res. 24:1477. doi: 10.1186/s12913-024-11962-5,
Buysse, D. J., Reynolds, C. F. 3rd, Monk, T. H., Berman, S. R., and Kupfer, D. J. (1989). The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 28, 193–213. doi: 10.1016/0165-1781(89)90047-4,
Campbell, K. A., Orr, E., Durepos, P., Nguyen, L., Li, L., Whitmore, C., et al. (2021). Reflexive thematic analysis for applied qualitative health research. Qual. Rep. 26, 2011–2028. doi: 10.46743/2160-3715/2021.5010
Campos, J. A. D. B., Carlotto, M. S., and Marôco, J. (2013). Copenhagen burnout inventory—student version: adaptation and transcultural validation for Portugal and Brazil. Psicol. Reflex. Crit. 26, 87–97. doi: 10.1590/S0102-79722013000100010
Campos, LA, and Lima, M, eds. O impacto das cotas: duas décadas de ação afirmativa no ensino superior brasileiro. Belo Horizonte (MG): Autêntica Editora; 2025. 272 p.
Collins, S., Clifasefi, S. L., Stanton, J., The LEAP Advisory BoardStraits, K. J. E., Gil-Kashiwabara, E., Rodriguez Espinosa, P., et al. (2018). Community-based participatory research (CBPR): towards equitable involvement of community in psychology research. Am. Psychol. 73, 884–898. doi: 10.1037/amp0000167
Creswell, J. W., and Plano Clark, V. L. (2017). Designing and conducting mixed methods research. 3rd Edn. Thousand Oaks (CA): SAGE Publications.
Cuijpers, P., Auerbach, R. P., Benjet, C., Bruffaerts, R., Ebert, D., Karyotaki, E., et al. (2019). The World Health Organization world mental health international college student initiative: an overview. Int. J. Methods Psychiatr. Res. 28:e1761. doi: 10.1002/mpr.1761,
Davis, C., and Parmenter, L. (2020). Student-staff partnerships at work: epistemic confidence, research-engaged teaching and vocational learning in the transition to higher education. Educ. Action Res. 29, 292–309. doi: 10.1080/09650792.2020.1792958
de Sousa, M. N. A., Medeiros, G. S., Rebouças Júnior, H. J., Apolinário, P. A., Sousa, A. B. V., Batista, C. P., et al. (2023). Prevalência de ideação suicida e correlação com características sociais e demográficas de universitários. Observ. Econ. Latinoam. 21, 7425–7444. doi: 10.55905/oelv21n7-089
de Souza, M. V. C., Lemkuhl, I., and Bastos, J. L. (2015). Discrimination and common mental disorders of undergraduate students of the Universidade Federal de Santa Catarina. Rev. Bras. Epidemiol. 18, 525–537. doi: 10.1590/1980-5497201500030001,
Deci, E. L., and Ryan, R. M. (2000). The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychol. Inq. 11, 227–268. doi: 10.1207/S15327965PLI1104_01
Doubeni, C. A., Nelson, D., Cohn, E. G., Paskett, E., Asfaw, S. A., Sumar, M., et al. (2022). Community engagement education in academic health centers, colleges, and universities. J. Clin. Transl. Sci. 6:e109. doi: 10.1017/cts.2022.424,
Duarte, F., Zilbovicius, M., and Seabra, A. C. (2022). “Programa de Tutoria Acadêmica para Ingressantes da Escola Politécnica da USP” in XLX COBENGE – Congresso Brasileiro de Educação em Engenharia (Associação Brasileira de Educação em Engenharia – ABENGE). Available online at: https://admin.abenge.org.br/public/conteudo/artigo?cod_trab=4110
Evans, T. M., Bira, L., Gastelum, J. B., Weiss, L. T., and Vanderford, N. L. (2018). Evidence for a mental health crisis in graduate education. Nat. Biotechnol. 36, 282–284. doi: 10.1038/nbt.4089,
Fagundes, C. V., Luce, M. B., and Rodriguez Espinar, S. (2014). O desempenho acadêmico como indicador de qualidade da transição Ensino Médio–Educação Superior. Ensaio Aval. Pol. Públ. Educ. 22, 635–669. doi: 10.1590/S0104-40362014000300004
Fernandes, LR, and Lobo e Silva Filho, RL. (2015). Strengthening engineering education in Brazil. International Conference on Interactive Collaborative Learning. Available online at: https://www.institutolobo.org.br/core/uploads/artigos/anexo_c5f7a112098956970778a8fc96f5535f.pdf
Gomes, FJB. Ideação suicida nos estudantes universitários. Master's thesis. Lisboa: Instituto Superior de Psicologia Aplicada; 2008
Gonçalves, A. P., Zuanazzi, A. C., Salvador, A. P., and Jaloto, A. (2023). Evidências de validade para Generalized Anxiety Disorder 7-Item (GAD-7). Rev. Psicol. Saude 15:e15101743. doi: 10.20435/pssa.v15i1.1743
Graham, J. W. (2009). Missing data analysis: making it work in the real world. Annu. Rev. Psychol. 60, 549–576. doi: 10.1146/annurev.psych.58.110405.085530. 18652544,
Groves, R. M. (2006). Nonresponse rates and nonresponse bias in household surveys. Public Opin. Q. 70, 646–675. doi: 10.1093/poq/nfl033
Gulliver, A., Wysoke, T., Calear, A. L., and Farrer, L. M. (2023). Factors associated with engagement in university life, and help-seeking attitudes and behaviour in first-year undergraduate students. Int. J. Environ. Res. Public Health 20:120. doi: 10.3390/ijerph20010120,
Hasim, N., Yusof, J., Ibrahim, F. A., Bungsu, M. S., Yakub, N. A. Y., and Shari, N. I. (2023). Stress and sleep quality among engineering students. Sains Humanika 15, 29–40. doi: 10.11113/sh.v15n3.2033
Henrique, I. F. S., De Micheli, D., Lacerda, R. B., Lacerda, L. A., and Formigoni, M. L. S. (2004). Validação da versão brasileira do teste de triagem do envolvimento com álcool, cigarro e outras substâncias (ASSIST). Rev. Assoc. Med. Bras. 50, 199–206. doi: 10.1590/S0104-42302004000200039,
Howard-Bostic, C., Andrade, D. A., and Machado, M. S. (2020). Women, engineering and gender equality. Rev. Bras. Estud. Polit. 121, 171–202.
Hurtado, S., Alvarez, C. L., Guillermo-Wann, C., Cuellar, M., and Arellano, L. (2012). A model for diverse learning environments: the scholarship on creating and assessing conditions for student success. Los Angeles (CA): Higher Education Research Institute, University of California, Los Angeles.
Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (Inep) (2022). Resumo técnico: Censo Escolar da Educação Básica 2021 [Internet]. Brasília: Inep.
Ipea. (2015). Atlas of social vulnerability| Brasília, DF: Instituto de Pesquisa Econômica Aplicada (Ipea); [cited 2025 Oct 21]. Available online at: http://ivs.ipea.gov.br/ (Accessed November, 11, 2025).
Jehangir, R. R., Stebleton, M. J., and Do, T. (2024). I wasn’t supposed to be there: examining the experiences of first-generation women of color in undergraduate STEM majors. J. First-Gener. Stud. Success 4, 22–43. doi: 10.1080/26906015.2024.2302346
Kirn, A., and Benson, L. (2013). Quantitative assessment of student motivation to characterize differences between engineering majors. Front. Educ. Conf, 69–74. doi: 10.1109/FIE.2013.6684790
Konstantinidis, A. (2024). An integrative review of the literature on factors influencing student well-being in the learning environment. Int. J. Educ. Res. Open 7:100384. doi: 10.1016/j.ijedro.2024.100384
Lechner, I. M., de Ridr, J., van Woudenberg, R., and Anttila, S. (2025). The university, epistemic power, and institutional epistemic responsibilities. Soc. Epistemol., 1–15. doi: 10.1080/02691728.2025.2553111
Mariano, A. M., Ferreira, A. B. M. L., Santos, M. R., Castilho, M. L., and Bastos, A. C. F. L. C. (2022). Decision trees for predicting dropout. Procedia Comput. Sci. 214, 1113–1120. doi: 10.1016/j.procs.2022.11.285
Nakamura, E. T., and Veneziani, Y. (2015). “Unidades de desenvolvimento humano e a oferta de saúde, educação e emprego na Região Metropolitana de São Paulo” in Territórios em Números: insumos para políticas públicas a partir da análise do IDHM e do IVS de UDHs e regiões metropolitanas brasileiras (Brasília (DF): Instituto de Pesquisa Econômica Aplicada (IPEA)), 194–225.
Owens, M. T., Seidel, S. B., Wong, M., Bejines, T. E., Lietz, S., Perez, J. R., et al. (2017). Classroom sound can be used to classify teaching practices in college science courses. Proc. Natl. Acad. Sci. USA 114, 3085–3090. doi: 10.1073/pnas.1618693114,
Park, C., McClure Fuller, M., Echevarria, T. M., Nguyen, K., Perez, D., Masood, H., et al. (2023). A participatory study of college students' mental health during the first year of the COVID-19 pandemic. Front. Public Health 11:1116865. doi: 10.3389/fpubh.2023.1116865,
Pieraccini, M. (2019). Towards just resilience: representing and including new constituencies in adaptive governance and law. J. Environ. Law 31. doi: 10.1093/jel/eqz002
Python Software Foundation. Python: A Programming Language (Version 3.x) [software]. Wilmington (DE): Python Software Foundation; 2025
R Core Team. R: A Language and Environment for Statistical Computing. Vienna (AT): R Foundation for Statistical Computing; 2025
Radan, S., Hassan, S., Wilson, A., and Basurra, S. (2023). “A review of mental health issues prevalent in science, technology, engineering, and mathematics (STEM)” in Handbook of research on innovative frameworks and inclusive models for online learning (Hershey (PA): IGI Global), 1–20.
Rehder, G. P., Serrano, A. L. C., Grimoni, J. B., Brandão, A. A. F., Silva, M. M. T., Moriya, H. T., et al. (2024). Innovative competency-based electrical engineering curriculum. IEEE Front. Educ. Conf. doi: 10.1109/FIE61694.2024.10893505
Robert Wood Johnson Foundation (2024) in Transforming academia for equity initiative [Internet]. ed. RWJF (Princeton, NJ).
Ryan, R. M., and Deci, E. L. (2018). Self-determination theory: Basic psychological needs in motivation, development, and wellness. 2nd Edn. New York: Guilford Press.
Santos, I. S., Tavares, B. F., Munhoz, T. N., Almeida, L. S. P., Silva, N. T. B., Tams, B. D., et al. (2013). Sensibilidade e especificidade do Patient Health Questionnaire-9 (PHQ-9) entre adultos da população geral. Cad. Saude Publica 29, 1533–1543. doi: 10.1590/0102-311X00144612,
Schaufeli, W., and Bakker, A. (2004). Utrecht Work Engagement Scale: preliminary manual [Internet]. Utrecht: Utrecht University. Available online at: https://www.wilmarschaufeli.nl/publications/Schaufeli/Test%20Manuals/Test_manual_UWES_English.pdf
Silva, J. O. M., Pereira Junior, G. A., Coelho, I. C. M. M., Picharschi, G. L., and Zagonel, I. P. S. (2018). Engajamento entre estudantes do ensino superior nas ciências da saúde (validação do questionário Utrecht Work Engagement Scale—UWES-S). Rev. Bras. Educ. Med. 42. doi: 10.1590/1981-52712015v42n2RB20170112
Silveira, RF, Holanda, M, Victorino, M.C, and Ladeira, M. 2019 Educational data mining: analysis of drop out of engineering majors at the UnB - Brazil. In: 18th IEEE International Conference on Machine Learning and Applications (ICMLA)
Smith, M. K., Jones, F. H. M., Gilbert, S. L., and Wieman, C. E. (2013). The classroom observation protocol for undergraduate STEM (COPUS): a new instrument to characterize university STEM classroom practices. CBE Life Sci. Educ. 12, 618–627. doi: 10.1187/cbe.13-08-0154,
Souza, G. C., Meireles, E., Mira, V. L., and Leite, M. M. J. (2021). Academic motivation scale—reliability and validity evidence among undergraduate nursing students. Rev. Latinoam. Enfermagem 29:e3420. doi: 10.1590/1518-8345.3848.342,
Suyo-Vega, J., Meneses-La-Riva, M., Fernández-Bedoya, V., Da Costa Polonia, A., Miotto, A., Alvarado-Suyo, S., et al. (2022). Mental health projects for university students: a systematic review of the scientific literature available in Portuguese, English, and Spanish. Front. Sociol. 7:922017. doi: 10.3389/fsoc.2022.922017
Tormon, R., Lindsay, B., Paul, R., Boyce, M., and Johnston, K. (2023). Predicting academic performance in first-year engineering students: the role of stress, resiliency, student engagement, and growth mindset. Learn. Individ. Differ. doi: 10.1016/j.lindif.2023.102383
Vallerand, R., Pelletier, L., Blais, M., Brière, N., Senécal, C., and Vallières, E. (1992). The academic motivation scale: a measure of intrinsic, extrinsic, and amotivation in education. Educ. Psychol. Meas. 52, 1003–1017. doi: 10.1177/0013164492052004025
Vasconcelos-Raposo, J., Soares, A. R., Silva, F., Fernandes, M. G., and Teixeira, C. M. (2016). Níveis de ideação suicida em jovens adultos. Estud. Psicol. (Campinas) 33. doi: 10.1590/1982-02752016000200016
Venkateswaran, N., Feldman, J., Hawkins, S. L., Lewis, M. A., Armstrong-Brown, J., Comfort, M., et al. (2023). Bringing an equity-centered framework to research: transforming the researcher, research content, and practice of research. Research Triangle Park (NC): RTI Press. Available at: https://www.ncbi.nlm.nih.gov/books/NBK592588/ (Accessed November, 11, 2025)
Vick, E, Wilson, SA, Hammer, JH, Whitwer, M, and Gentry, AN Engineering student mental health status across gender identities: analysis of data from the Healthy Minds Study. In ASEE Annual Conference & Exposition, Minorities in Engineering Division (MIND) Technical Session 5; 2025 Jun–Jul; Seattle, WA Washington (DC) ASEE 2025
Wallerstein, N., Duran, B., Oetzel, J., and Minkler, M. (2018). Community-based participatory research for health: Advancing social and health equity. 3rd Edn. San Francisco (CA): Jossey-Bass.
Wallerstein, N., Oetzel, J., Sanchez-Youngman, S., Boursaw, B., Dickson, E., Kastelic, S., et al. (2020). Engage for equity: a long-term study of community based participatory research and community engaged research practices and outcomes. Health Educ. Behav. 47, 380–390. doi: 10.1177/1090198119897075,
Xu, W., and Zammit, K. (2020). Applying thematic analysis to education. Int J Qual Methods 19. doi: 10.1177/1609406920918810
Keywords: community based participatory research (CBPR), bioecological model of human development, process-person-context-time (PPCT), self-determination theory (SDT), engineering curriculum, mental health, equity and inclusion in STEM education, mixed methods
Citation: Santana CLA, Wallerstein N, Libonati Boldi LF, Braga ORM, Kurokawa FA, Lotufo Neto F and Seabra AC (2025) Advancing equity and diversity in engineering education through community based participatory research: study protocol for promoting student mental health, engagement, and motivation. Front. Educ. 10:1696510. doi: 10.3389/feduc.2025.1696510
Edited by:
Darren Moore, University of Exeter, United KingdomReviewed by:
Rudy Tawie, Universiti Teknologi MARA, MalaysiaMarinés Mejía Alvarez, Asociación Proyecto Aiglé Guatemala, Guatemala
Copyright © 2025 Santana, Wallerstein, Libonati Boldi, Braga, Kurokawa, Lotufo Neto and Seabra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Carmen Lucia Albuquerque de Santana, Y2FybWVuLnNhbnRhbmFAdXNwLmJy