A New Perspective on Maladaptive Coping:
The Role of Rigidity
Italia Castro, Jackson Cowherd, & Zach Vasquez�
Research Methods and Statistics II
April 28, 2026
Pacific University, OR
Historical Context; This Decade
Historical Context | Case Study | Theory | Methods | Results | Discussion
COVID-19: Heightened psychophysiological stress (e.g., Sousa et al., 2021).�
Geopolitical Conflict: Ukraine-Russia War, Israel-Palestine War.
Climate Change Crisis: Rise in temperatures—a global concern.
Increase in Polarization: Polarization has consistently been increasing among US adults.
Economic Crisis: The cost of goods have increased, while the job market remains sparse. �
Case Study: “Alex”
Historical Context | Case Study | Theory | Methods | Results | Discussion
Alex, a 37-year-old male, has anxiety and recently began psychotherapy. However, while in tx, his therapist noticed Alex is resistant to change. ��With each suggestion the therapist provided during tx(e.g., mindfulness and CBT), Alex pushed back.��One-month Post-therapy: Therapist diagnoses Alex with GAD.��But the therapist still wishes they could diagnose, and therefore better treat, Alex’s core issue: Stubbornness. ��Given the lack of a protocol on stubbornness, the therapist defaults to standard treatments for anxiety.
Case Study: “Alex”
Historical Context | Case Study | Theory | Methods | Results | Discussion
But what if treatment existed for stubbornness? How might therapy look different with targeted therapy for Alex’s core issue?
Historical Context | Case Study | Theory | Methods | Results | Discussion
Literature Review
Continuous patterns of perseverance behaviors and thinking
�Dispositional and Situational
(Morris & Mansell, 2018)
Rigid Thinking
Emotion Regulation (ER)
Emotional response before, during, & after distressing situation
Five categories:
rumination, suppression, distraction, reappraisal, and mindfulness
(Preece et al., 2025).
Ineffective ER
Effective Emotion Regulation�
Selection, implementation, and monitoring
(Schneiderman et al. 2005).
+
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Research Question; Hypothesis
Historical Context | Case Study | Theory | Methods | Results | Discussion
Does psychological rigidity limit a person’s ability to adjust their emotion-regulation strategies when confronted with changing stressors?
Our Hypotheses:
Participants & Recruitment
Historical Context | Case Study | Theory | Methods | Results | Discussion
28 Participants
(22 Female, 6 Male)
Recruited by in person means and digital solicitation.
Materials; Psychometric Scales
Historical Context | Case Study | Theory | Methods | Results | Discussion
12-item Clinical Perfectionism Questionnaire (CPQ)�
10-item Ruminative Response Scale (RRS-10)�
Obsessive-Compulsive Inventory Revised (OCI-R)
Situational Emotion-Regulation Scale (SERS)�
Brief Coping Orientation to Problems Experienced (COPE)�
Flexible Emotion Regulation Scale (Flex-ER)
Psychological Rigidity (Facets)
Emotion
Regulation (Facets)
Design/Procedures
Historical Context | Case Study | Theory | Methods | Results | Discussion
This descriptive, online survey was initiated through an informed consent procedure, where consent was acknowledged through “I agree.”
Participants then completed the survey, which took on average 30 minutes from IC to the debriefing.
Historical Context | Case Study | Theory | Methods | Results | Discussion
Sample Information
28 participants
Total response count
Average response age
72.4% female
22 years old
24.1% male
Sex
Sex
Cronbach’s Alpha for All Scales
Variable | Cronbach’s Alpha |
Ruminative Response Scale | 0.749 |
Clinical Perfectionism Questionnaire | 0.712 |
Flex Emotion-Regulation (Flex-ER) | 0.483 |
Obsessive-Compulsive Inventory Revised (OCI-R) | 0.884 |
Brief-COPE Problem-Focused | 0.849 |
Brief-COPE Emotion-Focused | 0.849 |
Brief-COPE Avoidant | 0.849 |
Situational Emotion-Regulation Scale (SERS) | 0.491 |
Variable | Acceptance | Reappraisal | Distraction | Suppression | Rumination |
Acceptance | — | | | | |
Reappraisal | -.246 N=28 | — | | | |
Distraction | .022 N=28� | -.386* N=28 | — | | |
Suppression | -.149 N=28 | -.215 N=28 | .054 N=28 | — | |
Rumination | -.371 N=28 | -.586** N=28 | .016 N=28 | -.270 N=28 | — |
Descriptive Statistics for the Situational Emotion-Regulation Scale (SERS)
Variable | OCI-R | CPQ | RRS | Brief: Problem- focused | Brief: Emotion- focused | Brief: Avoidant | Rumination | Acceptance | Reappraisal | Distraction | Suppression | Calculated SERS Flexibility | FlexER |
OCI-R | — | | | | | | | | | | | | |
CPQ | .489** | — | | | | | | | | | | | |
RRS | .443* | .444* | — | | | | | | | | | | |
Brief: Problem- focused | .130 | .258 | -.053 | — | | | | | | | | | |
Brief: Emotion- focused | .356 | .402* | .228 | .630** | — | | | | | | | | |
Brief: Avoidant | .507** | .242 | .468* | .147 | .341 | — | | | | | | | |
Rumination | -.085 | .148 | .171 | -.127 | -.005 | .075 | — | | | | | | |
Acceptance | -.083 | -.157 | -.240 | .094 | -.095 | -.167 | -.371 | — | | | | | |
Reappraisal | .010 | .095 | -.044 | .178 | .121 | -.228 | -.586** | -.246 | — | | | | |
Distraction | .095 | -.093 | .004 | -.120 | -.304 | .087 | .016 | .022 | -.386* | — | | | |
Suppression | .205 | -.119 | .102 | -.125 | .112 | .484** | -.270 | -.149 | -.215 | .054 | — | | |
Calculated SERS Flexibility | -.034 | -.390** | -.166 | -.332 | -.366 | -.086 | -.227 | .088 | -.116 | .215 | .342 | — | |
FlexER | .290 | .019 | .045 | .161 | .407* | .377* | .016 | -.116 | -.006 | -.081 | .177 | -.138 | — |
Pearson’s Correlation Matrix of All Measures
Predictor | B | Std. Error | Beta | t | Sig. |
(Constant) | 30.853 | 2.991 | — | 18.492 | <.001 |
OCI-R | 0.050 | 0.050 | 0.222 | 1.006 | 0.325 |
CPQ | -0.250 | 0.116 | -0.475 | -2.155 | 0.041 |
RRS | -0.028 | 0.115 | -0.053 | -0.246 | 0.808 |
Multiple Linear Regression of OCI-R, CPQ, and RRS Predicting the SERS
Predictor | B | Std. Error | Beta | t | Sig. |
(Constant) | 30.853 | 1.668 | — | 18.492 | <.001 |
OCI-R | 0.047 | 0.028 | 0.388 | 1.681 | 0.106 |
CPQ | -0.04 | 0.065 | -0.143 | -0.619 | 0.542 |
RRS | -0.018 | 0.064 | -0.063 | -0.281 | 0.781 |
Multiple Linear Regression of OCI-R, CPQ, and RRS Predicting the Flex-ER
Historical Context | Case Study | Theory | Methods | Results | Discussion
Strengths
✓ Hypothesis 1 Supported: People who score higher in rigidity (M=90.61, SD=17.92) use fewer emotion regulation strategies as measured by SERS (M=5.53 SD=2.67, p < 0.05).
✓ Moderately strong relationships between rigidity facets
✓ Moderately strong relationships within SERS facets
✓ Moderate predictive validity of CPQ on the SERS
Historical Context | Case Study | Theory | Methods | Results | Discussion
Limitations
✗ Hypothesis 2 Unsupported: People who score higher in rigidity will use more maladaptive emotion-regulation strategies
✗ Small and non-diverse sample
✗ Low reliability for SERS and FlexER
✗ Cannot assess ecological validity of FlexER or SERS
✗ Cannot rule out confounding variable like neuroticism
Significance
Historical Context | Case Study | Theory | Methods | Results | Discussion
For Researchers:
Provides evidence that psychological rigidity may inhibit emotion-regulation flexibility (ERF)
Reveals need for more research on ERF
For Clinicians:
New perspective on emotion-regulation can help fine turn interventions that meet clients where they’re at.
Better addresses core psychological isssues (i.e., transdiagnostic processes).
Historical Context | Case Study | Theory | Methods | Results | Discussion
What You Can Do
→ Psychological flexibility predicts various aspects of wellness.
→ Our results indicate that perfectionism might inhibit it.
Solutions?
“It is not distress itself that interferes with well-being and optimal functioning, but rather the countless ways of trying to escape distress.” – Tom Kashdan
References