FIDL: Flexibility in Daily Life Scale

Reviewed by: Constantin Rezlescu | Associate Professor | UCL Psychology

Introduction

The Flexibility in Daily Life scale (FIDL) is a 21-item self-report questionnaire designed to capture natural expressions of cognitive and behavioral flexibility in daily life. Developed by Horne, Chen, and Irish (2024), this scale measures the capacity to switch between task sets or adopt alternative viewpoints and to flexibly engage in a diverse range of activities and behaviors across everyday contexts.

Unlike performance-based neuropsychological tasks that measure cognitive flexibility “in the moment” during structured laboratory situations (such as the Wisconsin Card Sorting Test), the FIDL assesses trait-level flexibility as it manifests naturally across diverse real-world settings and situations (Horne et al., 2024). This ecological approach makes it particularly valuable for understanding how flexibility—or lack thereof—impacts daily functioning and quality of life.

Understanding Flexibility in Daily Life

The capacity to adjust thinking and behavior in response to environmental changes is an adaptive feature of human cognition that varies considerably between individuals and undergoes dynamic shifts across the lifespan (Anderson, 2002; Cepeda et al., 2001; Uddin, 2021). Contemporary theories increasingly view cognitive and behavioral flexibility as trait-level constructs that can be situated along a continuum, the extremes of which represent maladaptive instances of entrenched rigidity on one hand to unconstrained hyper-flexible thoughts and behaviors on the other (Armbruster et al., 2012; Uddin, 2021).

Why daily life flexibility matters:

Adaptive functioning: The ability to adjust thoughts and behaviors in response to changing demands is essential for successful navigation of everyday life challenges.

Transdiagnostic relevance: Cognitive and behavioral inflexibility is a hallmark feature across many neuropsychiatric disorders, including autism spectrum disorder, ADHD, obsessive-compulsive disorder, traumatic brain injury, and neurodegenerative diseases (Uddin, 2021).

Lifespan sensitivity: Flexibility demonstrates a U-shaped relationship with age, with lower flexibility at younger and older ages and peak flexibility in middle adulthood (Cepeda et al., 2001; Horne et al., 2024; Kupis et al., 2021).

Ecological validity: Performance on laboratory flexibility tasks does not necessarily correspond to flexible and inflexible expressions as manifested in daily life (Dang et al., 2020; Geurts et al., 2009).

Clinical utility: Understanding an individual’s flexibility profile across multiple dimensions can inform treatment planning and intervention strategies across diverse clinical populations.

Research has shown that the FIDL successfully captures natural fluctuations in flexibility across the healthy adult lifespan and provides a validated tool for detecting subtle shifts in flexibility in both health and disease (Horne et al., 2024).

Theoretical Foundation

The FIDL was developed using a deductive scale development approach aimed at capturing common themes within the flexibility literature and across neuropsychiatric diagnoses. Horne et al. (2024) recognized that existing measures of cognitive flexibility had significant limitations:

Performance-based tasks (e.g., Wisconsin Card Sorting Test, Trail Making Test) focus on isolated aspects of flexibility in structured laboratory conditions, failing to capture the full spectrum of flexible thoughts and behaviors displayed across different daily contexts (Horne et al., 2024).

Existing self-report measures are often unidimensional, disorder-specific (designed only for autism spectrum disorder), or focus narrowly on specific contexts (e.g., flexibility in response to stress), making them unsuitable for broader transdiagnostic use (Horne et al., 2024).

Ecological validity gap: Performance on neuropsychological flexibility tasks does not necessarily predict flexible behavior in real-world settings (Dang et al., 2020; Geurts et al., 2009).

The FIDL addresses these limitations by providing a multidimensional assessment that:

• Captures both cognitive and behavioral manifestations of flexibility
• Applies across diverse contexts and situations in daily life
• Suitable for transdiagnostic use across various clinical populations
• Sensitive to natural variations across the adult lifespan

The scale conceptualizes flexibility as comprising multiple interconnected dimensions, including repetitive behaviors, ability to switch mental sets, tolerance for unpredictability, reliance on routines, and rigidity of thoughts and beliefs (Horne et al., 2024).

🌟 Ecological Assessment: The FIDL bridges the gap between laboratory performance and real-world functioning by measuring how flexibility naturally expresses itself in daily life contexts, providing crucial ecological validity often missing from traditional neuropsychological measures (Horne et al., 2024).

Key Features

Assessment Characteristics

• 21 items providing comprehensive multidimensional assessment
• 10-15 minutes administration time
• Ages 19-78+ years validated across adult lifespan
• 5-point Likert scale (“Never” to “All the time”)
• Five-factor structure measuring distinct dimensions of flexibility
• Self-report format assessing trait-level flexibility in daily contexts
• Transdiagnostic application suitable across diverse clinical populations
• Freely available for research with proper attribution

Flexibility Dimensions Assessed

The FIDL comprises five validated subscales capturing distinct facets of cognitive and behavioral flexibility:

1. Repetition subscale (5 items)

Captures repetitive and stereotypical behaviors in daily life:

• Engagement in repetitive actions or behaviors
• Stereotyped behavioral patterns
• Tendency toward sameness in activities

2. Switching subscale (4 items)

Measures ability to adapt one’s task or mental set:

• Capacity to shift between different tasks or activities
• Flexibility in changing approaches when needed
• Ease of mental set-shifting in daily contexts

3. Predictability/Control subscale (4 items)

Assesses preference for structured and ordered environments:

• Need for predictable environments and situations
• Comfort with uncertainty and change
• Tolerance for unplanned events

4. Routine subscale (4 items)

Evaluates reliance on and preference for routines:

• Adherence to established daily routines
• Distress when routines are disrupted
• Flexibility in deviating from typical patterns

5. Thoughts/Beliefs subscale (4 items)

Measures rigid thinking styles or beliefs:

• Inflexibility in opinions and viewpoints
• Difficulty considering alternative perspectives
• Openness to changing one’s mind

Research and Applied Applications

• Clinical neuropsychology – Transdiagnostic assessment of flexibility deficits across disorders
• Lifespan development – Tracking natural changes in flexibility across adulthood
• Neurodegenerative disease – Detecting and monitoring inflexibility in dementia, Parkinson’s disease
• Neurodevelopmental disorders – Assessing flexibility in autism spectrum disorder, ADHD
• Psychiatric conditions – Evaluating rigidity in OCD, depression, anxiety disorders
• Traumatic brain injury – Measuring cognitive and behavioral flexibility after TBI
• Intervention research – Monitoring treatment effects on flexibility across dimensions
• Occupational assessment – Understanding workplace adaptability and functioning

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Assess your cognitive and behavioral flexibility across five dimensions of daily life functioning.

Scoring and Interpretation

Response Format

Participants rate how frequently each statement applies to them over the previous two weeks using a 5-point Likert scale:

• 1 = Never
• 2 = Rarely
• 3 = Sometimes
• 4 = Often
• 5 = All the time

Scoring Procedure

1. Reverse score positively worded items
2. Calculate subscale scores: Sum items for each of the five subscales
3. Calculate total FIDL score: Sum all 21 items (range: 21-105)
4. Higher scores indicate lower (less) flexibility / greater inflexibility
5. Lower scores indicate higher (greater) flexibility

Note: The FIDL uses reverse scoring where higher numerical scores indicate greater inflexibility/rigidity.

Subscale Composition

Repetition (5 items): Items assessing repetitive and stereotypical behaviors

Switching (4 items): Items measuring task/mental set-shifting ability

Predictability/Control (4 items): Items evaluating preference for predictable environments

Routine (4 items): Items assessing reliance on established routines

Thoughts/Beliefs (4 items): Items measuring rigidity in thinking and beliefs

Note: The specific item composition and numbering are detailed in the full FIDL instrument (Horne et al., 2024).

Score Interpretation

Normative reference (Horne et al., 2024):

Validation sample: N = 295 healthy adults aged 19-78 years

Age-related patterns:

The FIDL demonstrates a U-shaped relationship with age (Horne et al., 2024):

• Younger adults (19-30 years): Higher inflexibility scores
• Middle-aged adults (~45-50 years): Lower inflexibility scores (peak flexibility)
• Older adults (60+ years): Higher inflexibility scores

This U-shaped pattern was significant for:

• Total FIDL score
• Repetition subscale
• Routine subscale
• Thoughts/Beliefs subscale

Linear age associations:

• Switching subscale: Linear decrease in flexibility with age
• Predictability/Control subscale: Linear decrease in flexibility with age

Clinical interpretation guidelines:

Higher total/subscale scores (greater inflexibility) may indicate:

• Difficulty adapting to changing circumstances
• Preference for sameness and predictability
• Reliance on established routines
• Rigid thinking patterns
• Risk for functional impairment in daily life

Lower total/subscale scores (greater flexibility) may indicate:

• Adaptive responding to environmental changes
• Comfort with novelty and unpredictability
• Openness to new experiences
• Cognitive adaptability
• Better daily life functioning

Subscale-specific patterns:

Examining individual subscale scores can reveal specific areas of strength or difficulty:

• High Repetition, Low other subscales: May indicate specific tendency toward repetitive behaviors without broader inflexibility
• High Predictability/Control, Low other subscales: May reflect anxiety-related need for control without pervasive rigidity
• High Routine, Low other subscales: May indicate strong habit formation without cognitive inflexibility
• High Thoughts/Beliefs, Low other subscales: May suggest ideological rigidity without behavioral inflexibility
• High across all subscales: May indicate pervasive inflexibility warranting clinical attention

Research Evidence and Psychometric Properties

Development and Validation Sample

Participants (Horne et al., 2024):

• N = 295 healthy adults (164 female, 129 male, 2 undisclosed)
• Age range: 19-78 years (M = 42.75, SD = 17.34)
• Recruitment: Amazon Mechanical Turk via CloudResearch
• Location: United States residents
• Stratified across four age groups (18-25, 26-40, 41-59, 60+)

Exclusions:

• Mini-ACE score <22 (cognitive impairment screening)
• Self-reported history of acquired brain injury or neurological condition
• Evidence of automated/bot completion

Factor Structure

Item development process (Horne et al., 2024):

1. Initial pool: 216 items from existing flexibility questionnaires across neuropsychiatric populations
2. First reduction: 30 items identified capturing common themes
3. Multidisciplinary consensus: International consortium of neurologists, psychiatrists, and psychologists from 14 countries
4. Final pilot version: 37 items submitted for validation

Exploratory Factor Analysis results (Horne et al., 2024):

• Initial solution: 6 factors via Horn’s parallel analysis (45% variance)
• Final solution: 5 factors with 21 items after removing items with loadings <.4 or cross-loadings ≥.30
• KMO statistic: .89 (excellent sampling adequacy)
• Bartlett’s test: χ²(666) = 4526.88, p < .001 (appropriate for factor analysis)

Five validated factors:

1. Repetition – Repetitive and stereotypical behaviors
2. Switching – Ability to adapt task or mental set
3. Predictability/Control – Preference for structured environments
4. Routine – Preference for and reliance on routines
5. Thoughts/Beliefs – Rigid thinking styles or beliefs

Reliability Evidence

Internal consistency (Cronbach’s alpha) – Horne et al. (2024):

• Total FIDL score: α = .85 (good to excellent)
• Repetition subscale: α = .79 (acceptable to good)
• Switching subscale: α = .72 (acceptable)
• Predictability/Control subscale: α = .73 (acceptable)
• Routine subscale: α = .75 (acceptable to good)
• Thoughts/Beliefs subscale: α = .76 (acceptable to good)

All subscales demonstrated moderate to strong internal consistency reliability.

Test-retest reliability:

Not yet reported in validation study. Future research needed to establish temporal stability.

Validity Evidence

Convergent validity (Horne et al., 2024):

The FIDL demonstrated significant modest correlations with the Cognitive Flexibility Inventory (CFI; Dennis & Vander Wal, 2010):

• FIDL total score with CFI total: Significant moderate positive correlation
• FIDL total score with CFI Control subscale: Stronger correlation than with Alternatives subscale
• Individual FIDL subscales with CFI: Modest correlations in predicted directions

The moderate rather than strong correlations support that the FIDL measures related but distinct constructs compared to the CFI. The FIDL captures broader behavioral flexibility and daily life manifestations, while the CFI focuses specifically on cognitive flexibility in stressful situations (Horne et al., 2024).

Discriminant validity:

The modest correlations with CFI (rather than very high correlations) provide evidence that FIDL assesses distinct aspects of flexibility not captured by existing cognitive flexibility measures (Horne et al., 2024).

Age-related validity (Horne et al., 2024):

The FIDL demonstrated expected age-related patterns, providing evidence of construct validity:

U-shaped relationships (quadratic) with age (p < .001):

• Total FIDL score
• Repetition subscale
• Routine subscale
• Thoughts/Beliefs subscale

Peak flexibility occurred in middle age (~45-50 years), with lower flexibility in younger and older adults, consistent with prior task-switching research (Cepeda et al., 2001; Kupis et al., 2021).

Linear associations with age (p < .001):

• Switching subscale: Decreased flexibility with increasing age
• Predictability/Control subscale: Decreased flexibility with increasing age

These differential age patterns across subscales provide evidence that the FIDL captures distinct dimensions of flexibility with different developmental trajectories.

Factor Structure Validation

Five clearly differentiated factors emerged, each representing distinct manifestations of flexibility:

• Factors capture both cognitive (Switching, Thoughts/Beliefs) and behavioral (Repetition, Routine) aspects
• Factors assess preference/tolerance dimensions (Predictability/Control)
• Clear factor structure supports multidimensional conceptualization of flexibility
• No excessive cross-loadings, supporting discriminant validity of subscales

Sensitivity to Lifespan Changes

The FIDL’s ability to detect U-shaped and linear age-related patterns demonstrates its sensitivity to natural fluctuations in flexibility across adulthood (Horne et al., 2024). This is a unique strength, as most existing measures have not been validated across the full adult lifespan or shown to be sensitive to age-related variations.

Limitations and Future Directions

Acknowledged limitations (Horne et al., 2024):

1. Single sample validation: Factor structure should be confirmed via CFA in independent sample
2. Healthy adults only: Validation needed in clinical populations with known flexibility deficits
3. Test-retest reliability: Temporal stability not yet established
4. Cultural validation: Validated only in United States residents
5. Concurrent clinical validity: Associations with functional outcomes and disorder severity not yet examined

Recommended future research:

• Confirmatory factor analysis in independent sample
• Validation in clinical populations (ASD, ADHD, OCD, TBI, neurodegenerative diseases)
• Establishment of clinical cutoffs and norms
• Test-retest reliability studies
• Cross-cultural validation
• Investigation of relationships with functional outcomes
• Sensitivity to treatment effects
• Comparison with performance-based flexibility measures

Usage Guidelines and Applications

Primary Research Applications

• Clinical neuropsychology – Transdiagnostic assessment across diverse patient populations
• Lifespan developmental research – Tracking flexibility changes from young to older adulthood
• Intervention research – Measuring treatment effects on multidimensional flexibility
• Neuropsychiatric research – Characterizing flexibility profiles across disorders
• Cognitive aging studies – Understanding age-related changes in daily life flexibility
• Occupational psychology – Assessing workplace adaptability and functioning
• Rehabilitation research – Monitoring recovery of flexibility after brain injury

Clinical Assessment Applications

Diagnostic evaluation:

• Characterize flexibility deficits across multiple dimensions
• Identify specific areas of inflexibility (e.g., behavioral vs. cognitive)
• Complement performance-based neuropsychological testing
• Assess ecological impact of flexibility deficits on daily functioning

Treatment planning:

• Identify specific flexibility dimensions to target in intervention
• Develop individualized treatment goals based on subscale profiles
• Match interventions to specific deficit areas
• Guide environmental modifications to support functioning

Progress monitoring:

• Track changes in flexibility across treatment
• Evaluate intervention effectiveness on specific dimensions
• Identify areas of improvement vs. persistent difficulties
• Document functional gains in daily life contexts

Outcome assessment:

• Measure treatment effects on ecologically valid flexibility indicators
• Assess generalization of laboratory-based training to daily life
• Evaluate long-term maintenance of flexibility improvements
• Document functional significance of neuropsychological changes

Transdiagnostic Clinical Applications

The FIDL is suitable for assessing flexibility across diverse neuropsychiatric conditions (Horne et al., 2024):

Neurodevelopmental disorders:

• Autism spectrum disorder – Characterize insistence on sameness, repetitive behaviors
• ADHD – Assess cognitive and behavioral rigidity
• Intellectual disability – Evaluate adaptive flexibility

Neurodegenerative diseases:

• Frontotemporal dementia – Monitor behavioral rigidity and perseveration
• Parkinson’s disease – Track cognitive inflexibility
• Alzheimer’s disease – Assess decline in cognitive flexibility

Acquired brain injury:

• Traumatic brain injury – Evaluate executive dysfunction in daily contexts
• Stroke – Monitor recovery of cognitive and behavioral flexibility

Psychiatric conditions:

• Obsessive-compulsive disorder – Assess compulsive rigidity and repetitive behaviors
• Autism features in adults – Screen for flexibility deficits
• Depression – Evaluate rigid negative thinking patterns
• Anxiety disorders – Assess intolerance of uncertainty

Research Design Considerations

Strengths:

• Multidimensional assessment captures diverse flexibility manifestations
• Ecologically valid measures flexibility in real-world daily contexts
• Transdiagnostic suitable across diverse clinical populations
• Lifespan sensitivity demonstrated across ages 19-78
• Brief administration practical for clinical and research use
• Clear factor structure enables subscale-specific analyses

Appropriate uses:

• Assessing trait-level flexibility in daily life contexts
• Characterizing multidimensional flexibility profiles
• Comparing flexibility across diagnostic groups
• Tracking flexibility changes across lifespan
• Evaluating intervention effects on ecological flexibility
• Complementing performance-based flexibility measures
• Screening for flexibility deficits in research samples

Limitations and cautions:

• Self-report bias: May not fully reflect observed behavioral flexibility
• Single sample validation: Factor structure needs confirmation in independent samples
• Clinical norms lacking: No established cutoffs for clinical interpretation
• Test-retest unknown: Temporal stability not yet established
• Healthy adult validation only: Clinical population validation needed
• Cultural specificity: Validated only in United States sample
• Not performance-based: Assesses perceived/experienced flexibility, not cognitive performance

Not appropriate for:

• Neuropsychological diagnosis of executive dysfunction
• Assessment of “in the moment” cognitive flexibility performance
• Sole diagnostic criterion for any disorder
• Populations outside validated age range (< 19 or non-adults)
• Cultures without validation studies

Complementary Assessment Approach

The FIDL is best used as part of comprehensive assessment combining:

• Performance-based measures (WCST, TMT) – Assess cognitive flexibility in structured tasks
• Self-report measures (FIDL, CFI) – Capture perceived flexibility in daily contexts
• Informant reports (BRIEF-A) – Obtain external perspectives on flexible behavior
• Functional outcomes – Evaluate real-world impact of flexibility deficits
• Clinical interview – Understand qualitative nature of flexibility difficulties

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Legal and Copyright Information

Copyright and Usage Responsibility: Check that you have the proper rights and permissions to use this assessment tool in your research. This may include purchasing appropriate licenses, obtaining permissions from authors/copyright holders, or ensuring your usage falls within fair use guidelines.

The Flexibility in Daily Life scale was developed for research and clinical use. Researchers should contact the authors regarding proper usage and attribution.

Proper Attribution: When using or referencing this scale, cite the original development:

• Horne, K., Chen, T., & Irish, M. (2024). Development of the Flexibility in Daily Life scale to measure multidimensional cognitive and behavioural flexibility in health and disease. British Journal of Clinical Psychology, 64(2), 315-329. https://doi.org/10.1111/bjc.12505

External Links and Resources

• Cognitive Flexibility – Wikipedia
• Executive Functions Research
• British Journal of Clinical Psychology article
• PubMed listing

References

Primary Development Citation:

• Horne, K., Chen, T., & Irish, M. (2024). Development of the Flexibility in Daily Life scale to measure multidimensional cognitive and behavioural flexibility in health and disease. British Journal of Clinical Psychology, 64(2), 315-329. https://doi.org/10.1111/bjc.12505

Theoretical Foundation:

• Anderson, P. (2002). Assessment and development of executive function (EF) during childhood. Child Neuropsychology, 8(2), 71-82.
• Armbruster, D. J. N., Ueltzhöffer, K., Basten, U., & Fiebach, C. J. (2012). Prefrontal cortical mechanisms underlying individual differences in cognitive flexibility and stability. Journal of Cognitive Neuroscience, 24(12), 2385-2399.
• Cepeda, N. J., Kramer, A. F., & Gonzalez de Sather, J. C. M. (2001). Changes in executive control across the life span: Examination of task-switching performance. Developmental Psychology, 37(5), 715-730.
• Uddin, L. Q. (2021). Cognitive and behavioural flexibility: Neural mechanisms and clinical considerations. Nature Reviews Neuroscience, 22(3), 167-179.

Convergent Validity:

• Dennis, J. P., & Vander Wal, J. S. (2010). The Cognitive Flexibility Inventory: Instrument development and estimates of reliability and validity. Cognitive Therapy and Research, 34(3), 241-253.

Ecological Validity:

• Dang, L. C., Castrellon, J. J., Perkins, S. F., Le, N. T., Cowan, R. L., Zald, D. H., & Samanez-Larkin, G. R. (2020). Reduced effects of age on dopamine D2 receptor levels in physically active adults. NeuroImage, 148, 116-122.
• Geurts, H. M., Corbett, B., & Solomon, M. (2009). The paradox of cognitive flexibility in autism. Trends in Cognitive Sciences, 13(2), 74-82.

Age-Related Research:

• Kupis, L., Goodman, Z. T., Kornfeld, S., Hoang, S., Romero, C., Dirks, B., Dehoney, J., Chang, C., & Uddin, L. Q. (2021). Brain dynamics underlying cognitive flexibility across the lifespan. Cerebral Cortex, 31(11), 5263-5274.

Related Measures:

• Bodfish, J. W., Symons, F. J., Parker, D. E., & Lewis, M. H. (2000). Varieties of repetitive behavior in autism: Comparisons to mental retardation. Journal of Autism and Developmental Disorders, 30(3), 237-243.
• Strang, J. F., Kenworthy, L., Daniolos, P., Case, L., Wills, M. C., Martin, A., & Wallace, G. L. (2012). Depression and anxiety symptoms in children and adolescents with autism spectrum disorders without intellectual disability. Research in Autism Spectrum Disorders, 6(1), 406-412.
• Uljarević, M., Baranek, G., Vivanti, G., Hedley, D., Hudry, K., & Lane, A. (2023). Heterogeneity of restricted and repetitive behaviors in autism spectrum disorder. Journal of Autism and Developmental Disorders, 53(9), 3350-3368.

Clinical Applications:

• Bozeat, S., Gregory, C. A., Ralph, M. A. L., & Hodges, J. R. (2000). Which neuropsychiatric and behavioural features distinguish frontal and temporal variants of frontotemporal dementia from Alzheimer’s disease? Journal of Neurology, Neurosurgery & Psychiatry, 69(2), 178-186.
• Dajani, D. R., Llabre, M. M., Nebel, M. B., Mostofsky, S. H., & Uddin, L. Q. (2016). Heterogeneity of executive functions among comorbid neurodevelopmental disorders. Scientific Reports, 6, 36566.
• Robbins, T. W., & Cools, R. (2014). Cognitive deficits in Parkinson’s disease: A cognitive neuroscience perspective. Movement Disorders, 29(5), 597-607.