Abstract

This study investigates the dropout intentions of female community college transfer students enrolled at four-year universities, a population often overlooked in higher education research. Integrating Schlossberg’s Transition Theory with Similarity-Attraction Theory, the study proposes a conceptual framework that highlights how psychological and environmental misalignments—such as university disidentification, academic ambivalence, and perceived stress—contribute to students’ intent to leave. Using survey data from female transfer students, the study operationalizes these constructs with validated multi-item scales. A series of general linear models (GLM) were employed to test the hypothesized relationships within the proposed framework.

Our findings show that a student's academic self-image (comprised of their academic self-efficacy and competence) is linked to lower perceived stress. In turn, higher stress predicted greater dropout intentions, whereas higher self-efficacy predicted lower intentions.

By extending Schlossberg’s model with the interpersonal insights of Similarity-Attraction Theory, this research offers a more nuanced understanding of gender-specific challenges in university transitions.

The study underscores the importance of institutional practices that foster belonging, identity alignment, and targeted support for female transfer students. Practical implications include the development of orientation programs, mentoring initiatives, and advising strategies tailored to this unique population. Socially, the findings emphasize the need for more equitable educational environments that respond to the lived realities of women navigating complex academic pathways.

This research contributes to both theory and practice by addressing a gap in the literature and offering actionable insights for improving retention and success among female transfer students in higher education.

Keywords

Perceived stress; academic self-image; academic self-efficacy; academic and intellectual development; university disidentification

Introduction

Female transfer students transitioning from community colleges to four-year universities face distinct challenges that significantly influence their academic persistence and dropout intentions. These challenges often stem from factors around such as managing multiple roles and resposibilities (e.g., caregiving, employment), adapting to a different academic culture, limited social integration, and navigating financial constraints (Hochschild & Machung, 2012; Lin, 2016). They may encounter institutional practices and environments that insufficiently recognize acknowledge or support their unique needs and experiences.

Schlossberg’s transition theory (1981) conceptualizes transition as a change that alters self-perception and relationships, emphasizing four primary factors—situation, self, support, and strategies—that determine individuals' coping and adaptation. Although this theory effectively captures broad transitional experiences, it benefits from a perspective that specifically accounts for the interpersonal dimensions of university integration.

Similarity-attraction theory (Byrne, 1971) proposes that perceived similarity between individuals and their environments fosters greater comfort, attraction, and integration, whereas perceived dissimilarity can lead to feelings of discomfort, ambivalence, and disidentification. By merging similarity-attraction theory with Schlossberg’s framework, this study specifically explores how perceived similarity or dissimilarity between female transfer students and their university environment impacts critical outcomes such as university disidentification, perceived stress, academic ambivalence, and ultimately, dropout intentions.

Female community college transfer students constitute the majority of for-credit enrollees at public two-year colleges (women 57%, men 43%) (American Association of Community Colleges, 2025), yet the psychosocial mechanisms of their transition not well understood. This study aims to provide a deeper, integrated theoretical understanding of dropout intentions among female transfer students. By combining Schlossberg’s transition theory with similarity-attraction theory, it addresses gaps in existing literature related to gender-specific transitional experiences and offers targeted insights for higher education institutions to better support this important student population. This study focuses on female community college transfer students and examines how key psychosocial processes, including university disidentification, perceived stress, and academic ambivalence, relate to dropout intentions within a similarity-based transition framework.

Theoretical Background

Challenges faced by female community college transfer students
While much of the existing literature on transfer students focuses on general student populations or compares gender differences, few studies provide an in-depth exploration of female-specific experiences, and those that do often concentrate on particular fields such as nursing or STEM (Horrocks & Hall, 2024; Labrague et al., 2017). As a result, broader insights into the unique challenges female transfer students face during the transition to four-year institutions remain limited.

The present study addresses this gap by examining the attitudes, motivations, and coping strategies of female transfer students in a holistic, gender-specific context. Many of these students enter the new university with a heightened sense of uncertainty, only partially understanding institutional systems and expectations. This ambiguity can increase anxiety during adjustment.

Among female students pursuing academic and personal goals, transition experiences can be complicated by mediating factors such as guilt, loneliness, and reduced self-confidence. Coping is shaped by appraisals of capability and control: some students approach challenges with a sense of efficacy and autonomy, whereas others feel constrained by external circumstances. These perceptions of competence meaningfully influence coping styles and transition outcomes.

Social interactions are equally consequential. Supportive relationships—through guidance and a sense of belonging—foster integration and self-esteem. Yet access to such relationships depends on social and emotional skills that vary across individuals. Consequently, the psychological cost of managing transition-related stress is highly individualized, influencing attitudes, motivation, and persistence in heterogeneous ways.

These challenges are often amplified by gender-specific societal expectations. For instance, women, including female students, frequently bear a disproportionate burden of caregiving and domestic responsibilities, a phenomenon known as the "second shift” (Hochschild & Machung, 2012). This juggling of multiple roles directly impacts their available time and energy for academics, contributing to perceived stress (Lin, 2016). Furthermore, female students may internalize gender stereotypes related to academic competence, which can negatively affect their academic self-efficacy (ASE) and heighten their vulnerability to academic setbacks (Spencer et al., 1999; Correll, 2001).

Given these multifaceted challenges, theoretical lenses such as Schlossberg’s transition theory and similarity–attraction help illuminate why some female community college transfer students persist while others consider leaving.

Schlossberg’s transition theory
Schlossberg defines a transition as an event or non-event that alters assumptions about self and world, requiring corresponding changes in behavior and relationships (Schlossberg, 1981; Schlossberg, 2011). The model’s core revision adds four coping resources, the 4S: Situation, Self, Support, Strategies.

Situation concerns the specific features of the transition—trigger, timing, control, role change, duration, prior experience, concurrent stressors, and appraisal—which make each event or non-event experienced differently because situations differ. Self refers to personal and demographic characteristics and psychological resources; individuals bring distinct resources and liabilities, so the same transition is experienced differently depending on who they are. Support denotes the systems one can access or rely on, including family, friends, intimate relationships, and institutional or organizational supports.

Strategies are the responses initiated to prevent harm; they aim to change or reframe the situation, thereby reducing stress.

Similarity-Attraction theory
While Schlossberg’s model provides a robust framework for an individual’s adaptation process, understanding the interpersonal dynamics of university integration requires an additional lens. To address this, we incorporate similarity–attraction theory and an appraisal–identity perspective. Similarity-attraction theory (Byrne, 1971) posits that individuals are more likely to be attracted to and feel comfortable in environments where they perceive others to be similar to themselves.

In universities, perceived alignment between personal values/identities and institutional culture is associated with belonging and engagement, whereas perceived dissimilarity can fuel alienation and disidentification. For female community college transfer students entering unfamiliar and sometimes male-dominated or impersonal settings, low perceived similarity may intensify transitional stress and obscure a clear sense of fit.

We adopt an appraisal–identity view to explain how the 4S elements translate into outcomes. Academic self-efficacy reduces perceived stress by increasing perceived control over demands. Sustained stress signals poor fit and can catalyze university disidentification—psychological distancing from the institution’s identity. We also consider university ambivalence; wherein mixed evaluations create hesitation and dampen commitment even when objective supports exist. Together, these appraisals inform motivation to persist or to contemplate departure.

Focal Constructs
Perceived stress: Psychological stress arises when environmental and internal demands are appraised as taxing or exceeding one’s resources (Lazarus & Folkman, 1984). Among transfer students, stress reflects complex emotions—fear, anger, depression, hopelessness, and guilt—linked to academic performance, financial strain, workload balance, social acceptance, and institutional complexity (Monat & Lazarus, 1991). These responses are shaped by personality and role-specific self-conceptions, including efficacy beliefs.

Academic self-efficacy and academic competence: Academic self-efficacy (ASE) refers to students’ beliefs about their capability to achieve educational goals and complete tasks (Pajares & Miller, 1994). Higher ASE is linked to perseverance and success-oriented behaviors (Cassidy, 2012; Frydenberg & Brandon, 2002; Komarraju & Nadler, 2013; Lane et al., 2002), whereas lower ASE is associated with greater stress and poorer outcomes (Bandura, 1977, 1982; Devonport et al., 2003). Academic competence (AC) complements ASE by capturing perceived skills and knowledge relevant to the academic role. In this manuscript, academic self-image (ASI) is treated as a higher-order construct encompassing ASE and AC, and all analyses are specified at the two-factor level.

University Disidentification: Adapted from organizational disidentification, this construct captures psychological separation from the university’s social identity—characterized by detachment, dissatisfaction, and perceived dissimilarity (Levin & van Laar, 2006). Manifestations include alienation, regret about enrollment, and a perceived lack of fit with peers.

Intentions to depart prior to degree completion represent volitional decisions that emerge in action-crisis contexts (Tinto, 1993; Schnettler et al., 2020). Expectancy–value processes—anticipated benefits, attainment, and perceived costs—shape these intentions.

Determination to complete a degree is influenced by self-beliefs (e.g., self-esteem, expectancies, educational self-efficacy) and by academic and social integration (Tinto, 1993; Tinto, 2012). Intentions to persist typically forecast subsequent behavior.

Integration of Schlossberg’s transition theory with nomological network
While Schlossberg’s transition model provides a robust, holistic lens on student transitions, as a grand theory it lacks the specificity needed to explain proximal mechanisms in particular contexts (Pawson & Tilley, 1997; Pinder & Moore, 1980; Stank et al., 2017). To achieve that specificity for female community college transfer students, we follow Merton’s middle-range theory (MRT) to develop a testable nomological network (Merton, 1968).

Integrating MRT with Schlossberg’s 4S clarifies how personal attributes, environments, and outcomes (e.g., dropout intentions) interrelate, yielding actionable guidance for student support (Ketokivi, 2006). We operationalize the 4S as follows to build the network in Figure 1:

Situation: The transitional context and immediate triggers are captured by perceived stress and university ambivalence, stressors that are especially salient for transfer students and shape adaptation (Cohen et al., 1983; Elias & MacDonald, 2007).

Self: Academic self-image, comprising academic self-efficacy and academic competence, indexes personal and psychological resources, reflecting a student’s appraisal of her capacity to succeed in the new environment.

Support: Access to interpersonal and institutional resources (e.g., advising, mentoring, peer networks) (Tinto, 1993; Tinto, 2012; Wilkins et al., 2016). In our model, a perceived lack of support is operationalized as university disidentification, a felt detachment from the campus community.

Strategies: Coping responses to transition, measured as academic persistence (a proactive strategy) and dropout intentions (a maladaptive response often associated with high stress or a negative self-image) (Davenport et al., 2003; Kahn, 2023).

Bringing in similarity–attraction and appraisal–identity perspectives further links these elements: Self (efficacy, competence) shapes appraisals of Situation (stress); sustained stress and mixed evaluations foster disidentification; and these identity-relevant appraisals inform Strategies to persist or consider leaving (Byrne, 1971; Lazarus & Folkman, 1984).

Accordingly, our nomological network integrates MRT with Schlossberg’s 4S to provide a context-specific account of persistence and dropout intentions among female transfer students, aligning with transition logic while tailoring it to higher education and women’s distinctive experiences. Figure 1 presents the conceptual model.

Figure 1 . Nomological network

Hypotheses Development

Relationship between academic self-efficacy/academic competence and perceived stress.

It is critical to grasp the relations between academic self-image and perceived stress to understand stress management in students. Transfer students face heightened stress during their adjustment phase (Cohen et al., 1983). Academic self-efficacy (ASE) is crucial in this context, as it influences students’ ability to cope with academic challenges and pressures. ASE is defined as students’ beliefs in their capability to achieve their educational goals and complete specific tasks (Elias & MacDonald, 2007; Pajares & Miller, 1994). High ASE is linked to greater perseverance and engagement in behaviors conducive to academic success (Cassidy, 2012; Frydenberg & Brandon, 2002; Komarraju & Nadler, 2013; Lane et al., 2002; Pajares & Miller, 1994). Conversely, low ASE is associated with increased stress and poor academic outcomes (Bandura, 1982; Davenport et al., 2003).

Transfer students, who require an additional adjustment period as they transition from their previous institution to their new institution, are more likely to experience additional stress. However, students with high self-efficacy are more likely to believe in their ability to handle challenging academic tasks and situations (Zimmerman, 2000). Gender differences in ASE, with female students showing greater vulnerability to stress, further underscore its significance (Huang, 2013; Ye & Posada, 2018).

Based on the above findings, we propose the following hypotheses:
H1: The combined two-factor model of ASE and AC has a significant predictive relationship with perceived stress.
H1a: ASE is negatively related to perceived stress.
H1b: AC is negatively related to perceived stress.

Relationship between ASE/university ambivalence and academic persistence
We investigate the impacts of ASE and university ambivalence on academic persistence. This investigation is essential for understanding the dynamics of student retention and success in the higher education landscape. Thus far, several prior studies have indicated a strong association between learners’ ASE and their academic performance (e.g., Honicke & Broadbent, 2016; Richardson et al., 2012; Robbins et al., 2004). These investigations have consistently demonstrated that higher ASE scores are linked to superior academic performance outcomes. Moreover, Robbins et al. (2004) provided evidence that achievement motivation impacts academic performance. Based on the above findings, we propose the following hypotheses:

H2: The combined two-factor model of ASE and university ambivalence has a significant predictive relationship with academic persistence.
H2a: ASE is positively related to academic persistence.
H2b: University ambivalence is negatively related to academic persistence.

Relationship between academic persistence and university disidentification attitudes
Transfer students often experience significant adjustment challenges when adapting to new academic standards and social environments. Their ability to persist academically plays a crucial role in fostering a sense of belonging and identification with their new universities. In particular, female transfer students encounter additional hurdles, navigating gender stereotypes while juggling student, professional, and caregiver roles. These hurdles can significantly impact their academic engagement and commitment to the institution’s goals.

Academic and intellectual development, encompassing knowledge growth, enthusiasm for academic endeavors, and a sustained interest in learning, is a key factor in nurturing students’ sense of belonging. Pascarella and Terenzini (2005) and Cokley (2002) suggest that enhanced intellectual development is associated with decreased levels of university disidentification. This likely happens through a reduction in cognitive dissonance, as students begin to appreciate the value of their university education (Cokley, 2002). Additionally, Astin (1997) notes that students with higher academic and intellectual development often experience academic success, leading to greater alignment between their personal and institutional goals, further reducing disidentification.

Institutional goal commitment, as defined by Locke and Latham (2002), refers to students’ investment in the university’s goals and objectives. It positively correlates with persistence and goal achievement while showing an inverse relationship with disidentification attitudes. Tinto (1993) argues that students with strong institutional goal commitment perceive greater support from their university, leading to a deeper sense of belonging and decreased levels of university disidentification. Similarly, Wilkins et al. (2016) highlight that aligning personal and institutional values can reduce the likelihood of disidentification attitudes.

Based on the above findings, we propose the following hypotheses:
H3: The combined two-factor model of academic and intellectual development and institutional goal commitment has a significant predictive relationship with university disidentification attitudes.
H3a: Academic and intellectual development is negatively related to university disidentification attitudes.
H3b: Institutional goal commitment is negatively related to university disidentification attitudes.

Relationship between perceived stress/ASE/academic persistence and university dropout intentions
Research consistently demonstrates the significant role that perceived stress plays in students' academic journeys. For instance, Robbins et al. (2004) established a direct correlation between high stress levels and increased dropout intentions. This relationship highlights the crucial need for universities to implement supportive measures aimed at reducing stress among students, particularly those undergoing transitions such as transfers. Stress management workshops, counseling services, and peer support groups can play vital roles in minimizing stress levels, ultimately influencing students' retention rates. For example, research indicates that depression and anxiety under stress significantly elevate female students’ dropout risk (Fletcher, 2008). Furthermore, Andersson et al. (2009) stated that the inability to deal with stress can significantly affect students’ academic performance and persistence levels and that higher education institutions are usually expected to ensure that students receive sufficient support to minimize such stress. Regulators and prospective students often perceive high levels of stress, posing a threat to the long-term viability of programs or courses with high attrition rates (Wong & Chapman, 2022). Therefore, ASE levels positively relate to academic persistence and negatively relate to stress levels. These factors thus influence dropout intentions.

Based on the above findings, we propose the following hypotheses:
H4: The combined three-factor model of perceived stress, ASE, and academic persistence has a significant predictive relationship with dropout intentions.
H4a: Perceived stress is positively related to dropout intentions.
H4b: ASE is negatively related to dropout intentions.
H4c: Academic and intellectual development is negatively related to dropout intentions.

Materials and Methods

Sample and data collection
Upon obtaining approval from the Institutional Review Board (IRB) through the university research protection office for all recruitment materials and questionnaires, data collection occurred over two semesters. This period encompassed the Fall 2022 semester and the Spring 2023 semester. Recruitment emails were sent to female students who had transferred to the university during the Fall 2022 semester as first-semester transfer students.

Prospective participants expressing interest in the study clicked on the provided link, leading them to review and sign informed consent. Upon agreeing to participate, they proceeded to the questionnaire. After completing the study and submitting their responses, participants were directed to a separate survey in which they had the option to enter an email address (not linked to their data) to receive a $5 Starbucks gift card.

The initial data collection occurred in the first week of November, immediately following the midterm period, resulting in a total sample of 122 female students. In March of the Spring 2023 semester, the second round of recruitment emails was distributed to the initial 122 female participants. Among them, 55% participated in the second data collection, resulting in a final sample of 67 participants for the longitudinal study.

The participants' average age was 25 (Mage = 24.87, SD = 8.83), with 52.2% identifying as non-White. Approximately 52% of the sample comprised individuals who had transferred from a community college. Furthermore, around 57% of respondents reported a household income of less than $50,000. For a detailed overview of the sample's demographic profile, please refer to Table 1.

Measurement items and instruments
The measurement items for all constructs were developed based on the existing literature. The reliability (Cronbach’s alpha) for all scales reported below was calculated based on the current study’s sample of female transfer students. Ten items assessing perceived stress (α = .90) were adapted from Cohen et al. (1983). The assessment of perceived stress involved asking participants about their feelings and thoughts over the last month. As an example, participants responded to the question ‘In the last month, how often have you been upset because of something that happened unexpectedly?’ using a 5-point scale ranging from ‘Never’ to ‘Very often.’

University disidentification was measured with an eight-item, 5-point scale taken from previous research (Ikegami & Ishida, 2007). These items were ‘I am unhappy that I am a student of _____,’ ‘If I could, I would not be a student of _____,’ ‘I regret having entered _____,’ ‘I hate being a student of _____,’ ‘Being a _____ student is an important reflection of who I am,’ ‘I would feel good if I were described as a typical student of _____,’ ‘I am very interested in what others think about _____,’ and ‘When someone praises _____, it feels like a personal compliment’ (α = .83).

Adapted from Nielsen et al. (2018), ASE (α = .86) was assessed using a five-item, 5-point Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The statements were as follows: ‘I generally manage to solve difficult academic problems if I try hard enough,’ ‘I know I can stick to my aims and accomplish my goals in my field of study,’ ‘I will remain calm in my exam because I know I will have the knowledge to solve the problem,’ ‘I know I can pass the exam if I put in enough work during the semester,’ and ‘The motto “If other people can, I can too” applies to me when it comes to my field of study.’

Three dimensions of academic persistence were assessed (α = .85), as recommended (Pascarella & Terenzini, 1980): peer group interactions, academic and intellectual development, and institutional goal commitment. However, the peer group interactions dimension was omitted from the nomological network for theoretical reasons. This decision was made to maintain model parsimony and to focus on the internal psychological factors and the student-institution relationship central to our framework. In our study, we conceptualize Schlossberg's "Support" primarily at the institutional level (captured by university disidentification) rather than at the interpersonal peer level.

Dropout intentions were assessed with a five-item, 5-point scale (Dresel & Grassinger, 2013), including statements like ‘I often think about dropping out of my current course of studies’ and ‘The thought often crosses my mind that my current course of studies is not for me’ (α = .78).

Finally, academic competence (α = .77; Crocker et al., 2003) and university ambivalence (α = .87; Lipkkus et al., 2005) were measured using a 5-point Likert-type scale. Please refer to Appendix B for the items used in the scale.

Results

General linear modeling
The general linear modeling (GLM) procedure was employed for analyses. GLM is designed to construct a statistical model describing the impact of one or more factors on one or more dependent variables. These factors may encompass quantitative or categorical variables, be either crossed or nested, and fall under the fixed or random categories. The assumption in this analysis is that errors adhere to a normal distribution.

Hypothesis testing
The ANOVA table predicts that both ASE and academic competence affect perceived stress. The overall model is statistically significant, F(2,131) = 34.62, p < 0.0001, at the 95.0% confidence level. The individual predictors are significant (p <0.0001). The predictor ASE shows a significant effect, F(1, 131) = 43.07, p < .0001, accounting for a substantial portion of the variance in perceived stress. Similarly, the academic competence predictor is also significant, F(1, 131) = 35.42, p < 0.0001.

The Durbin-Watson statistic is p = 0.0007, which is less than 0.05, indicating that the null hypothesis is rejected. The standard error of the estimate (0.604164) is below 1.95 and displays an adequate fit between the actual and estimated data. The mean absolute error is insignificant (0.49990320), which shows that the analysis is relatively unbiased (see Table 2). These results suggest that the ASE and academic competence predictors are significant determinants of perceived stress.

Table 2. Relations between ASE/Academic Competence and Perceived Stress

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
Model	25.2755	2	12.6377	34.62	0.0000
Residual	47.8168	131	0.365014
Total (Corr.)	73.0922	133

Type III Sums of Squares

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
ASE	15.7207	1	15.7207	43.07	0.0000
AC	12.9296	1	12.9296	35.42	0.0000
Residual	47.8168	131	0.365014
Total (corrected)	73.0922	133

Expected Mean Squares

Source	EMS
ASE	(3)+Q1
AC	(3)+Q2
Residual	(3)

F-Test Denominators

Source	Df	Mean Square	Denominator
ASE	131.00	0.365014	(3)
AC	131.00	0.365014	(3)

Variance Components

Source	Estimate
Residual	0.365014

R-Squared = 34.5802%
R-Squared (adjusted for d.f.) = 33.5815%
Standard error of est. = 0.604164
Mean absolute error = 0.499032
Durbin-Watson statistic = 1.4546 (P=0.0007)

Residual Analysis

	Estimation	Validation
n	134	24
MSE	0.365014	0.394479
MAE	0.499032	0.529289
MAPE		47.4739
ME	-2.17073E-16	0.0716422
MPE		-24.5954

The ANOVA table predicts that both ASE and university ambivalence affect academic persistence. The overall model is statistically significant, F (2,1301) = 42.48, p <.001, at the 95.0% confidence level. Specifically, as individual predictors, ASE shows a significant effect on academic persistence, F (1,131) = 36.34, p <.001, as does university ambivalence, F (1,131) = 16.07, p < .001. The Durbin-Watson statistic is p < 0.001 (less than 0.05), signifying the rejection of the null hypothesis. The standard error of the estimate (0.446874) is below 1.95 and displays an adequate fit between the actual and estimated data. The mean absolute error is insignificant (0.357279), which shows that the analysis is relatively unbiased (see Table 3). These results suggest that both ASE and university ambivalence are significant predictors of academic persistence.

Table 3. Relations between ASE/University Ambivalence and Academic Persistence

Analysis of Variance for AP

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
Model	16.9656	2	8.48281	42.48	0.0000
Residual	26.1603	131	0.199697
Total (Corr.)	43.1259	133

Type III Sums of Squares

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
ASE	7.2572	1	7.2572	36.34	0.0000
AMB	3.20845	1	3.20845	16.07	0.0001
Residual	26.1603	131	0.199697
Total (corrected)	43.1259	133

Expected Mean Squares

Source	EMS
ASE	(3)+Q1
AMB	(3)+Q2
Residual	(3)

F-Test Denominators

Source	Df	Mean Square	Denominator
ASE	131.00	0.199697	(3)
AMB	131.00	0.199697	(3)

Variance Components

Source	Estimate
Residual	0.199697

R-Squared = 39.3398%
R-Squared (adjusted for d.f.) = 38.4137%
Standard error of est. = 0.446874
Mean absolute error = 0.357279
Durbin-Watson statistic = 1.37337 (P=0.0001)

Residual Analysis

	Estimation	Validation
n	134	24
MSE	0.199697	0.09304279
MAE	0.357279	0.243519
MAPE	10.2018	6.55738
ME	9.11377E-16	0.00213723
MPE	-1.6117	-0.666963

The ANOVA table predicts that both academic and intellectual development and institutional goal commitment affect university disidentification attitudes. The overall model is statistically significant, F (2,131) = 62.36, p < .001, at the 95.0% confidence level. The individual predictors are as follows: academic and intellectual development shows a significant effect on disidentification attitudes, F (1,131) = 54.30, p < 0.001. Similarly, institutional goal commitment has a significant effect, F (1,131) = 10.94, p=0.001. The Durbin-Watson statistic is p = 0.017, which is less than 0.05, indicating that the null hypothesis is rejected. The standard error of the estimate (0.530301) is below 1.95 and displays an adequate fit between the actual and estimated data. The mean absolute error (0.430135) is insignificant, indicating a relatively unbiased analysis (see Table 4).

Table 4. Relations between Academic and Institutional Development/Institutional Goal Commitment and University Disidentification Attitudes

Analysis of Variance for DIS

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
Model	35.0758	2	17.5379	62.36	0.0000
Residual	36.8397	131	0.281219
Total (Corr.)	71.9156	133

Type III Sums of Squares

 

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
AP_AcadIntel	15.2691	1	15.2691	54.30	0.0000
AP_InstGoal	3.08676	1	3.08676	10.98	0.0012
Residual	36.8397	131	0.281219
Total (corrected)	71.9156	133

Expected Mean Squares

Source	EMS
AP_AcadIntel	(3)+Q1
AP_InstGoal	(3)+Q2
Residual	(3)

F-Test Denominators

Source	Df	Mean Square	Denominator
AP_AcadIntel	131.00	0.281219	(3)
AP_InstGoal	131.00	0.281219	(3)

Variance Components

Source	Estimate
Residual	0.281219

R-Squared = 48.7736%
R-Squared (adjusted for d.f.) = 47.9915%
Standard error of est. = 0.530301
Mean absolute error = 0.430135
Durbin-Watson statistic = 1.63356 (P=0.0167)

Residual Analysis

	Estimation	Validation
n	134	24
MSE	0.281219	0.215286
MAE	0.430135	0.393726
MAPE	22.9949	23.8601
ME	1.37535E-16	-0.0498517
MPE	-6.80621	-8.40842

The ANOVA table, forecasting dropout intentions based on perceived stress, ASE, and academic and intellectual development, reveals that the overall model is statistically significant, F (3,130) = 33.78, p< 0.001, at the 95.0% confidence level (see Table 5).

Table 5. Relations between ASE/Perceived Stress/Academic and Intellectual Development and Dropout Intentions

Analysis of Variance for DI

 

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
Model	41.1841	3	13.728	33.78	0.0000
Residual	52.8242	130	0.40634
Total (Corr.)	94.0084	133

Type III Sums of Squares

Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
PS	2.59011	1	2.59011	6.37	0.0128
ASE	8.07086	1	8.07086	19.86	0.0000
AP_AcadIntel	2.778	1	2.778	6.84	0.0100
Residual	52.8242	130	0.40634
Total (corrected)	94.0084	133

Expected Mean Squares

Source	EMS
PS	(4)+Q1
ASE	(4)+Q2
AP_AcadIntel	(4)+Q3
Residual	(4)

F-Test Denominators

Source	Df	Mean Square	Denominator
PS	130.00	0.40634	(4)
ASE	130.00	0.40634	(4)
AP_AcadIntel	130.00	0.40634	(4)

Variance Components

Source	Estimate
Residual	0.40634

R-Squared = 43.809%
R-Squared (adjusted for d.f.) = 42.5123%
Standard error of est. = 0.637448
Mean absolute error = 0.489461
Durbin-Watson statistic = 1.21701 (P=0.0000)

Residual Analysis

	Estimation	Validation
n	134	24
MSE	0.40634	0.539777
MAE	0.489461	0.548331
MAPE	31.6192	27.6253
ME	-5.10371E-16	0.246799
MPE	-12.4051	5.50912

The individual predictors are as follows: perceived stress is found to have a significant effect on dropout intentions, F (1,130) = 6.37 p = 0.013, as is ASE, F (1,130) = 19.86, p < .001. Additionally, academic and intellectual development is a significant predictor, F (1,130) = 6.84, p= 0.01. The Durbin-Watson statistic is p < .001 (less than 0.05), which signifies the rejection of the null hypothesis. The standard error of the estimate (0.637448) is below 1.95 and displays an adequate fit between the actual and estimated data. The mean absolute error is negligible (0.489461), demonstrating a relatively unbiased analysis.

General Discussion

We found that ASE and perceived stress were directly associated with dropout intentions; ASE and self-assessed academic competence were inversely related to perceived stress; ASE together with university ambivalence predicted academic persistence; and a sense of academic and intellectual development was linked to university disidentification (Gigliotti & Huff, 1995; Hackett et al., 1992; Torres & Solberg, 2001; Zajacova et al., 2005).

Viewed through Schlossberg’s transition framework, these patterns suggest that situational and support pressures can depress the self (efficacy, confidence) and constrain strategies, thereby heightening stress, ambivalence, and disidentification that feed into dropout intentions (Schlossberg, 1981; Schlossberg, 2011). Prior evidence that self-efficacy covaries negatively with stress among college students helps explain why raising ASE is central to disrupting this pathway (Gigliotti & Huff, 1995; Hackett et al., 1992; Torres & Solberg, 2001; Zajacova et al., 2005). Accordingly, interventions that strengthen ASE (e.g., success coaching, targeted mentoring) and reduce stress/friction in academic and administrative processes are likely to yield the largest gains in persistence while lowering disidentification.

Our findings must be interpreted through a gender-specific lens, as the strong link between low academic self-efficacy (ASE), high perceived stress, and dropout intentions is particularly salient for women. Existing research shows that female students often report lower ASE than their male counterparts, a vulnerability that may stem from societal stereotypes that subtly question women's competence. When a female transfer student, perhaps with an already fragile ASE, encounters a challenging new academic environment, this can trigger the disproportionately high stress response our model demonstrates.

These challenges are amplified by the multiple roles many women navigate, including caregiving and employment, often within institutional structures that do not fully acknowledge these realities. In Schlossberg’s terms, these situational and support pressures can depress a student's 'Self' (e.g., their efficacy and confidence) and narrow their available 'Strategies.' This is why interventions that raise ASE and reduce stress—such as success coaching, tailored mentoring, and stress-management workshops—are especially critical for female transfer students, as they directly buffer against the gender-specific risks identified in our study.

Finally, a sense of personal academic and intellectual development was intertwined with university disidentification. A post-hoc study analysis revealed that nontraditional students (age 25 plus) have better adaptation experiences than traditional (under 25) students. Several factors may contribute to the enhanced adaptation of nontraditional students. First, maturity and prior life experiences likely play a significant role. Students over 25 have often navigated the workforce, managed personal finances, or balanced family responsibilities. Such experiences can foster advanced coping mechanisms, resilience, and time-management skills that are invaluable when facing the academic and bureaucratic stressors of a new university environment (Downey et al., 2006).

Furthermore, nontraditional students frequently return to higher education with a clearer sense of purpose and stronger intrinsic motivation (Kasworm, 2003). This goal clarity can serve as a powerful buffer against academic ambivalence and stress, fostering greater persistence compared to their younger peers who may still be exploring their identities and career paths (Pascarella & Terenzini, 2005; Merriam & Baumgartner, 2020). In the context of Schlossberg's model, nontraditional students may enter the transition with a more developed 'Self' (e.g., higher self-reliance) and a broader toolkit of 'Strategies' for managing stress, allowing them to navigate the challenges of the new 'Situation' more effectively. This suggests that while all transfer students need support, the nature of that support should be differentiated, with younger students potentially benefiting from more foundational guidance on managing autonomy and developing effective coping strategies.

Contributions

This research contributes to the existing body of knowledge in several distinct ways. Firstly, it extends the understanding of dropout intentions by focusing on female transfer students, a group often underrepresented in academic research. This study's findings emphasize the complex interplay of factors (e.g., perceived stress, academic persistence, and university disidentification) influencing dropout intentions, thereby enriching the existing literature on student retention.

Secondly, the study sheds light on the role of ASE in managing stress and fostering academic persistence, offering a nuanced view of how self-perceptions influence academic outcomes. This insight is particularly valuable for developing interventions aimed at enhancing self-efficacy among transfer students.

Thirdly, this study offers critical insights into the adaptation experiences of traditional students (under 25), who, as revealed, face more challenges than nontraditional students (age 25 plus). This finding is pivotal, as it challenges the prevailing assumption in higher education that younger, traditional students are inherently better equipped for academic adaptation. By highlighting the specific struggles of this demographic, the study calls for a reevaluation of universities’ support structures and engagement strategies, tailored to address the unique needs of traditional students.

Limitations and Future Directions

This study has several limitations that offer avenues for future research. Given the rapidly evolving landscape of higher education and shifting career trajectories for women, portions of the prior literature may no longer reflect current realities; our model offers a contemporary lens but is not without constraints. First, the final sample size for the longitudinal analysis (n = 67) limits the precision of estimates. Although a larger sample would increase statistical power, we mitigated this constraint through precision-focused reporting and robustness checks.

Second, the study was conducted at a single, public, regional, transfer-serving, predominantly commuter campus, which limits external validity. We therefore delineate boundary conditions under which our psychosocial pathway—linking perceived (dis)similarity to stress/ambivalence and disidentification, and ultimately to dropout intentions—is most likely to hold. Effects may vary by (a) institutional selectivity (open-admission vs. highly selective), (b) residential intensity (commuter vs. residential with cohort-based integration), and (c) advising models (generalist vs. intrusive/proactive). Future work should prioritize multi-site replications to test for measurement invariance and structural moderation. Specifically, studies should explore intersectional identities to understand how the interplay of gender, race, and socioeconomic status might moderate the psychosocial pathways we identified. Additionally, research should evaluate the longitudinal impacts of specific interventions, such as tracking a cohort of students through a new mentorship program to measure changes in their ASE and stress over time.

Third, we did not differentiate outcomes by course modality (online, face-to-face, or hybrid). Because many students engaged in hybrid participation, blurring these boundaries, our findings likely average across modality-specific experiences. Future work should model course modality as a contextual factor to determine whether hybrid engagement, for example, attenuates or amplifies stress and disidentification during the transition period.

Finally, future research should continue to generate a new and contemporary model of female transfer students’ adaptations that accounts for the evolving landscape of higher education. For practitioners, our findings can inform countermeasures targeting stress and university disidentification, including (a) specialized programs that promote involvement and belonging and (b) individualized counseling to identify and remove barriers to retention.

While future research undertakes these important directions, our current findings offer immediate, actionable insights for practitioners. The identified pathways linking self-efficacy, stress, and disidentification to dropout intentions provide a clear mandate for developing countermeasures. These can include specialized programs that promote involvement and belonging, and individualized counseling to identify and remove barriers to retention, as detailed further in our managerial implications.

Managerial Implications

The findings of this study have significant implications for university management and policymakers. Recognizing the pivotal role of ASE in reducing dropout intentions, universities should implement programs aimed at boosting students' confidence in their academic abilities. This could include student success coaching, mentorship programs, stress management workshops, mental health and well-being services, professional career development, and academic skills training.

Furthermore, academic advising should be more personalized for traditional students, considering their unique challenges and academic goals. Advisors should be trained to recognize and address the specific issues faced by this marginalized group of students.

Additionally, the research underscores the need for universities to foster a supportive and inclusive environment that acknowledges and values the unique experiences of transfer students since more than 30% of students in public universities nationwide are transfer students. This could involve creating dedicated support groups, specific scholarships and aid programs, alumni associations, or institutional services specifically aimed at improving transfer students’ social and academic life on campus. These supports would enhance the resources available to the campus community and their sense of belonging to the campus environment. In conclusion, by focusing on the specific challenges faced by female transfer students, this study provides valuable insights for universities to enhance student retention and success. Implementing these recommendations could lead to more effective educational strategies and a more inclusive academic environment.

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