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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

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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. �

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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.

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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?

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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:

  1. People who score higher in rigidity are predicted to use fewer emotion-regulation strategies. �
  2. People who score higher in rigidity are predicted to use more maladaptive emotion-regulation strategies.

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Participants & Recruitment

Historical Context | Case Study | Theory | Methods | Results | Discussion

28 Participants

(22 Female, 6 Male)

Recruited by in person means and digital solicitation.

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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)

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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.

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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

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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

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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)

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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

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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

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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

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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

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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

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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).

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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?

  1. Engage in psychotherapeutic modalities, such as ACT, CBT, and DBT
  2. Make small changes everyday to shift your mindset from “all-or-nothing” to “good enough
  3. When perfectionism strikes, foster self-compassion

“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

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References

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Thank You!

We would express our gratitude to

Heide Island as a mentor and professor, and Pacific University.

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