Brain Fog Scale (BFS)

1. Abstract

The Brain Fog Scale (BFS), developed by Derya Atik and Ayşe İnel Manav in 2023, is a psychometrically robust, multidimensional self-report inventory designed to systematically quantify and evaluate subjective experiences of brain fog. Clinically conceptualized as a subacute or chronic altered cognitive state marked by subjective cloudiness, lack of mental clarity, reduced executive functioning, sustained attention deficits, and sluggish information processing, brain fog has increasingly emerged as a debilitating manifestation across diverse medical and psychiatric conditions, including post-acute sequelae of SARS-CoV-2 infection (long COVID), myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), fibromyalgia, autoimmune disorders, and chemotherapy-induced cognitive impairment. The BFS was constructed to transition this traditionally ambiguous clinical complaint into an objectively measurable psychological construct comprising three core empirical dimensions: cognitive symptoms, physical symptoms, and psychological symptoms.

The initial instrument pool of 33 candidate items was derived from an exhaustive interdisciplinary literature review, augmented to 35 items, and evaluated by independent expert panels for linguistic intelligibility, face validity, and content validity, demonstrating high Content Validity Ratios (CVR > 0.62). The psychometric validation was conducted in Osmaniye, Turkey, among an adult population sample. Psychometric distillation via exploratory factor analysis (principal components analysis with varimax rotation) yielded a refined 30-item instrument demonstrating a robust three-factor latent structure that accounts for 77.437% of the total variance, with factor loadings ranging from 0.522 to 0.895 and item-total correlations spanning 0.314 to 0.750. Each item is scored on a five-point Likert scale ranging from 1 (“never”) to 5 (“always”), containing zero reverse-scored items. Reliability analyses revealed superior internal consistency (Cronbach’s alpha = 0.945), robust split-half reliability (Spearman-Brown coefficient = 0.884; Guttman split-half coefficient = 0.874), and temporal stability over a 30-day test-retest interval (r = .952, p < .001). The BFS fills a critical gap in clinical neuropsychology, behavioural medicine, and nursing research by providing an empirical, standardized measure of cognitive fogging.

2. Keywords

Brain Fog, Cognitive Symptoms, Mental Clarity, Physical Symptoms, Psychological Symptoms, Psychometrics, Factor Analysis, Neurocognitive Impairment, Chronic Fatigue, Scale Validation

3. Authors

The Brain Fog Scale (BFS) was conceptualized, operationalized, and psychometrically validated by academic researchers affiliated with the Department of Nursing at Osmaniye Korkut Ata University in Turkey:

• Derya Atik, PhD, RN: Associate Professor / Faculty Member, Department of Nursing, Faculty of Health Sciences, Osmaniye Korkut Ata University, Osmaniye, Turkey. Email: [email protected]. Serving as corresponding investigator for psychometric instrumentation and validation protocols.
• Ayşe İnel Manav, PhD, RN: Assistant Professor / Faculty Member, Department of Nursing, Faculty of Health Sciences, Osmaniye Korkut Ata University, Osmaniye, Turkey. Co-investigator specializing in clinical nursing methodologies, patient-reported outcome measures, and symptom cluster evaluations.

4. Purpose

The primary clinical and psychometric objective of the Brain Fog Scale (BFS) is to deliver an empirical, reliable, and scientifically standardized measurement apparatus capable of measuring the severity, phenotypic expression, and multidimensional manifestations of subjective brain fog. Although frequently reported in clinical practice, the phrase “brain fog” has historically resided in a diagnostic gray zone, often dismissed as an informal colloquialism rather than a distinct neuropsychological symptom complex. Patients enduring neuroinflammatory conditions, systemic metabolic dysregulations, endocrinopathies, post-COVID-19 condition, or post-viral asthenia routinely articulate an overwhelming inability to think clearly, retain information, multitask, or maintain sustained vigilance. In the absence of targeted, psychometrically validated scales, clinicians have historically been forced to rely on generalized cognitive screening batteries—such as the Mini-Mental State Examination (MMSE) or Montreal Cognitive Assessment (MoCA)—which frequently fail to detect subtle subjective disruptions in processing speed, mental sharpness, and cognitive endurance.

From a research perspective, the BFS resolves this diagnostic shortcoming by establishing a standardized metric suitable for longitudinal, epidemiological, and intervention-based clinical trials. The tool captures cognitive complaints alongside accompanying physical and psychological symptoms, enabling researchers to explore etiology, track recovery trajectories, and evaluate pharmacotherapeutic or rehabilitative interventions. By operationalizing brain fog into a 30-item, three-dimensional framework, the BFS permits granular tracking of whether a therapeutic intervention selectively ameliorates psychological distress, cognitive slowing, or somatic lethargy. Furthermore, the instrument serves a preventative and diagnostic triage function in occupational health and nursing settings, detecting early cognitive fatigue before it results in clinical medical errors, professional burnout, or severe functional disability.

5. Psychological Construct

The psychological construct evaluated by the BFS conceptualizes brain fog as an altered state of consciousness characterized by blunted alertness, mental cloudiness, decreased processing efficiency, and pervasive cognitive sluggishness that compromises an individual’s psychological equilibrium and somatic functioning. Rather than representing an isolated intellectual deficit, brain fog manifests as a tripartite symptom cluster encompassing cognitive, physical, and psychological disruptions.

Cognitive Symptoms Subscale

The cognitive dimension represents the core of the brain fog construct, tapping into structural deficits in executive functioning, working memory, attentional allocation, and mental flexibility. Individuals experiencing this dimension report profound difficulties with tasks requiring cognitive manipulation, such as calculating figures, planning multi-step activities, or maintaining conversational flow. Specific manifestations include expressive word-finding pauses, instantaneous loss of train of thought, distractibility in noisy environments, degraded reading comprehension requiring repeated passes over identical text, and an acute breakdown of prospective memory (e.g., forgetting appointments or medication regimens). This dimension captures not merely intellectual capability, but the subjective sensation that one’s cognitive apparatus is operating through a dense, resistive medium.

Physical Symptoms Subscale

The physical dimension examines the neurosomatic concomitants of brain fog. Cognitive processes do not occur in an isolated neural silo; mental cloudiness is frequently coupled with profound somatic fatigue, visual exhaustion, psychomotor retrogression, sleep architecture disruption, and cephalic heaviness. Individuals experiencing physical brain fog report an overwhelming physical inertia that mirrors their mental slowing. Everyday somatic expressions include ocular strain, persistent non-migrainous head pressure, unrefreshing sleep despite normal duration, general muscular weakness, and physical lethargy that escalates following minimal cognitive or metabolic exertion (post-exertional malaise). By incorporating this subscale, the BFS recognizes the biological embodiment of cognitive exhaustion.

Psychological Symptoms Subscale

The psychological dimension addresses the affective, emotional, and motivational sequelae that arise alongside neurocognitive clouding. The sustained inability to navigate cognitive demands predictably triggers acute emotional distress, secondary anxiety, demoralization, loss of self-efficacy, and dysphoria. The psychological domain assesses feelings of detachment, depersonalization, emotional blunting, irritability stemming from cognitive frustration, panic associated with memory lapses, and the subjective terror of intellectual decline. It measures the affective toll of cognitive cloudiness, recognizing that mood alterations both amplify and stem from compromised cognitive capacity.

6. Theoretical Framework

The theoretical architecture of the Brain Fog Scale is grounded in contemporary neuropsychology, Cognitive Load Theory, psychoneuroimmunology, and the central fatigue hypothesis. Cognitive Load Theory posits that working memory possesses finite processing bandwidth; when neurobiological stress, systemic inflammation, or autonomic instability degrades central executive resources, the brain experiences intrinsic cognitive overload during baseline operational tasks. Under conditions of pathological brain fog, the neural resources allocated to filtering irrelevant stimuli, retrieving lexical targets, and maintaining attentional control become depleted, producing mental cloudiness.

From a psychoneuroimmunological standpoint, the BFS draws upon the sickness behavior paradigm conceptualized by Robert Dantzer and colleagues. Pro-inflammatory cytokines (such as IL-1β, IL-6, and TNF-α) traverse the blood-brain barrier or signal via afferent vagal pathways, triggering neuroinflammation, microglial activation, and disrupted neuroplasticity within the hippocampus and prefrontal cortex. This systemic neuroimmune response induces adaptive behavioral adjustments characterized by subjective lethargy, attentional withdrawal, affective blunting, and somatic slowing—the phenotypic profile measured across the BFS subscales.

Additionally, the BFS incorporates aspects of Baddeley’s Multicomponent Model of Working Memory and Posner’s Attentional Network Theory. Impairments across the alerting, orienting, and executive control networks account for the subjective perception of degraded mental clarity. When the central executive fails to effectively coordinate the phonological loop and visuospatial sketchpad, the subjective sensation of “fog” arises. By synthesizing neurocognitive architecture with somatic and psychological symptom clusters, the BFS provides a comprehensive framework bridging subjective patient reports with underlying neurobiological processes.

7. Validity

The psychometric validity of the Brain Fog Scale was established through rigorous qualitative and quantitative evaluations:

• Content Validity: Content validity was systematically developed using an initial pool of 33 candidate items generated through qualitative literature reviews and clinical observations. Two items were subsequently formulated, yielding a 35-item preliminary instrument. This version was submitted to an independent expert evaluation panel composed of nursing scientists, medical specialists, and psychological measurement experts. Content validity was evaluated using Lawshe’s technique; all retained items achieved a Content Validity Ratio (CVR) greater than 0.62, exceeding critical cutoff thresholds and confirming that each item represented an essential indicator of brain fog. Linguistic intelligibility, conceptual clarity, and cultural relevance were confirmed following minor iterative wording modifications.
• Construct Validity: Construct validity was examined through exploratory factor analysis (EFA). The 30 retained items demonstrated substantial structural integrity, coalescing cleanly into three distinct dimensions (Cognitive, Physical, and Psychological) without problematic secondary cross-loadings. Factor loadings ranged from 0.522 to 0.895, exceeding standard psychometric criteria (loading > 0.40) and confirming that each item contributes meaningfully to its assigned theoretical dimension.
• Convergent and Discriminant Validity: The scale demonstrated strong item-total score correlations ranging from 0.314 to 0.750 (all statistically significant at p < .001). These robust positive associations indicate that while each item measures specific features of its respective subscale, all items share common variance with the overarching construct of brain fog. Discriminant validity was supported by the emergence of three distinct factors accounting for unique portions of variance, demonstrating that the subscales capture differentiated facets of the condition rather than redundant cognitive traits.

8. Reliability

The Brain Fog Scale exhibits high statistical reliability across multiple testing methodologies:

• Internal Consistency: Across the global 30-item instrument, the BFS achieved a Cronbach’s alpha coefficient of 0.945. This elevated coefficient reflects high internal homogeneity among items without indicating excessive redundancy, confirming that the scale functions as an integrated assessment tool.
• Split-Half Reliability: Split-half internal consistency yielded a Spearman-Brown prophecy coefficient of 0.884 and a Guttman split-half coefficient of 0.874. These metrics confirm that the scale retains measurement consistency across split iterations.
• Item-Total Correlations: Classical item analysis demonstrated corrected item-total correlation coefficients spanning from 0.314 to 0.750 (p < .001), indicating that every retained item discriminates effectively between varying severities of brain fog.
• Test-Retest Temporal Stability: Temporal stability was evaluated by re-administering the BFS to a randomly selected subsample of participants following a 30-day interval. Pearson product-moment correlation analysis demonstrated a test-retest correlation coefficient of r = .952 (p < .001). This confirms the instrument’s stability over time, making it suitable for longitudinal tracking where symptom fluctuations must reflect clinical changes rather than measurement error.

9. Factor Analysis

The internal latent structure of the Brain Fog Scale was evaluated using exploratory factor analysis (EFA). Data suitability was confirmed through the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett’s Test of Sphericity, confirming sufficient correlation patterns within the matrix for meaningful factor extraction.

Principal components analysis with varimax orthogonal rotation was applied to the item correlation matrix. In accordance with the Kaiser-Guttman criterion (extracting factors with eigenvalues > 1.0) and confirmed via scree plot inspection, a clean three-factor solution emerged. The 30 finalized items demonstrated salient factor loadings well above the conservative threshold of 0.40, with individual loadings ranging between 0.522 and 0.895 across the factors.

Collectively, the three-factor model accounted for an impressive 77.437% of the total cumulative variance, a high level of explained variance for self-report psychometric scales in behavioural medicine. The variance was distributed across the three dimensions:

• Factor 1 (Cognitive Symptoms): Accounted for the largest proportion of common variance, capturing working memory degradation, lexical access challenges, attentional lapses, and slowed processing speeds.
• Factor 2 (Physical Symptoms): Accounted for the second variance share, representing somatic fatigue, ocular strain, physical slowing, sleep-wake disruption, and cephalic tension.
• Factor 3 (Psychological Symptoms): Accounted for the remaining variance, capturing subjective distress, anxiety over cognitive performance, demoralization, affective blunting, and irritability.

Item-total statistics confirmed that no individual item degradation was observed upon factor extraction. Confirmatory factor analysis (CFA) referenced within the structural validation framework supported the empirical fit of this tripartite model, establishing that the 30-item BFS captures the multidimensional nature of brain fog.

10. Instrument / Measurement Tool

• Instrument Name: Brain Fog Scale (BFS)
• Test Type: Original self-report psychological/neuropsychological questionnaire
• Item Count: 30 items
• Subscale Structure: 3 distinct subscales
  • Cognitive Symptoms Subscale
  • Physical Symptoms Subscale
  • Psychological Symptoms Subscale
• Response Format: Five-point Likert-type scale scored as:
  • 1 = Never
  • 2 = Sometimes
  • 3 = Undecided
  • 4 = Often
  • 5 = Always
• Reverse-Scored Items: None. All items are keyed in a uniform direction where higher numerical selections correspond to elevated symptom severity.
• Scoring Procedures:
  • Global Score: Calculated by summing the scores of all 30 items (theoretical range: 30 to 150).
  • Subscale Scores: Derived by summing the respective item scores for Cognitive, Physical, and Psychological domains.
  • Interpretation: Higher cumulative scores reflect greater perceived severity and functional impairment associated with brain fog.
• Administration Time: Approximately 15 to 20 minutes
• Target Population: Adults aged 18 years and older across healthy, clinical, and post-viral populations

11. Permissions & Fee and Test Year

• Year of Development: 2023
• Copyright & Intellectual Property: Held by the scale developers, Derya Atik and Ayşe İnel Manav, with publication rights held by Psychiatria Danubina.
• Fee: Free of charge for academic, non-commercial research and clinical practice.
• Permissions & Inquiries: Researchers and clinicians wishing to use, translate, or adapt the scale should contact the corresponding author, Derya Atik, at [email protected].

12. References

• Atik, D., & İnel Manav, A. (2023). A scale development study: Brain Fog Scale. Psychiatria Danubina, 35(1), 73–79. https://doi.org/10.24869/psyd.2023.73
• Baddeley, A. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4(11), 417–423. https://doi.org/10.1016/S1364-6613(00)01538-2
• Dantzer, R., O’Connor, J. C., Freund, G. G., Johnson, R. W., & Kelley, K. W. (2008). From inflammation to sickness and depression: When the immune system subjugates the brain. Nature Reviews Neuroscience, 9(1), 46–56. https://doi.org/10.1038/nrn2297
• Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
• Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13(1), 25–42. https://doi.org/10.1146/annurev.ne.13.030190.000325
• Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

13. Items of the Scale