Pain Assessment Checklist for Seniors with Limited Ability to Communicate – Dutch

Abstract

The Pain Assessment Checklist for Seniors with Limited Ability to Communicate – Dutch (PACSLAC-D; in Dutch, PACSLAC-V or the Dutch shortened version of the PACSLAC) is an observational, behavioral screening instrument designed to detect, assess, and monitor pain in older individuals suffering from advanced dementia or severe intellectual disabilities who lack the communicative capacity to provide valid self-reports of pain. Developed through cross-cultural adaptation and rigorous item reduction of the original 60-item Canadian PACSLAC by Fuchs-Lacelle and Hadjistavropoulos, the Dutch version—systematically evaluated and validated by Sandra M. G. Zwakhalen and colleagues—reduces the instrument to 24 highly sensitive behavioral items. The instrument is structured across three empirically derived domains: Part I: Facial Expressions (items 1–8), Part II: Verbal and Vocal Behaviors (items 9–14), and Part III: Body Movements and Behavioral/Interactional Changes (items 15–24). Each behavioral item is scored using a binary, dichotomous response format (0 = Absent / Afwezig, 1 = Present / Aanwezig), generating a summative composite score ranging from 0 to 24, where elevated scores correspond to a higher probability and intensity of nociceptive distress.

Psychometric evaluations across Dutch nursing homes and psychogeriatric long-term care wards demonstrate robust properties. The scale demonstrates high internal consistency (Cronbach’s alpha coefficients consistently ranging between .78 and .88 across resting and movement conditions), substantial inter-rater reliability (intraclass correlation coefficients [ICC] typically exceeding .70 to .82 among trained professional nurses), and high test-retest stability. Construct validity is supported by significant differentiation between baseline (rest) and standardized painful mobilization situations, strong convergent validity with proxy-rating tools such as the Pain Assessment in Advanced Dementia (PAINAD) scale and visual analogue scales (VAS), and marked sensitivity to analgesic interventions. By optimizing observational efficiency without sacrificing diagnostic accuracy, the Dutch PACSLAC serves as a foundational clinical and psychometric tool in geriatric nursing, psycho-oncology, and neurocognitive palliative care.

Keywords

Pain Assessment Checklist for Seniors with Limited Ability to Communicate, PACSLAC, Dementia, Geriatric Assessment, Observational Pain Scale, Psychometrics, Non-communicative Elderly, Behavioral Pain Assessment, Nursing Home Care, Cognitive Impairment, Facial Expressions, Palliative Care

Authors

The development, conceptualization, and psychometric validation of the PACSLAC and its adapted Dutch version reflect a collaborative trajectory across Canadian and Dutch clinical psychometricians and nursing scientists:

• Sandra M. G. Zwakhalen, PhD, RN: Primary developer and psychometric validator of the Dutch PACSLAC adaptation. Affiliated with the Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands. Contact: Maastricht University Profile.
• Thomas Hadjistavropoulos, PhD, ABPP, FCAHS: Co-developer of the original Canadian 60-item PACSLAC and international supervisor of dementia pain paradigms. Research Chair in Aging and Health, Department of Psychology, University of Regina, Regina, Saskatchewan, Canada.
• Shannon Fuchs-Lacelle, PhD, RD Psych: Co-developer of the original foundational PACSLAC instrument. Clinical Psychologist, Regina Qu’Appelle Health Region, Regina, Saskatchewan, Canada.
• Jan P. H. Hamers, PhD, RN: Senior academic collaborator on the Dutch validation studies and long-term care quality research. Professor of Care of Older People, Department of Health Services Research, CAPHRI, Maastricht University, The Netherlands.
• Siu Chan, PhD: Co-investigator who, alongside Hadjistavropoulos, pioneered item-reduction methodologies resulting in the international PACSLAC-II framework, providing concurrent validation for streamlined checklists in dementia care.

Purpose

The primary purpose of the Dutch Pain Assessment Checklist for Seniors with Limited Ability to Communicate is to systematically bridge the diagnostic chasm created by communicative degradation in advanced neurocognitive disorders. In clinical populations presenting with severe Alzheimer’s disease, vascular dementia, frontotemporal lobar degeneration, or profound developmental intellectual disabilities, the gold standard of pain evaluation—namely, voluntary subjective self-report via numerical rating scales or verbal descriptive indices—becomes psychometrically and clinically unavailable. As cognitive decline impairs memory, abstract reasoning, linguistic encoding, and interoceptive awareness, patients are stripped of their capacity to alert caregivers to physical pain. Consequently, untreated acute and chronic pain frequently manifests as neuropsychiatric symptoms, including motor agitation, aggressive resistance to basic personal hygiene, progressive social withdrawal, or terminal apathy.

The clinical rationale for the 24-item Dutch PACSLAC centers on routine, standardized observation by nursing personnel and professional caregivers. It addresses four critical clinical junctures: (1) baseline intake assessment when a client transitions from home to an institutional environment or between long-term care facilities; (2) emergent or acute behavioral changes, differentiating nociceptive distress from primary psychiatric decompensation; (3) ambiguous diagnostic presentations where clinicians suspect hidden musculoskeletal, neuropathic, or visceral pathology; and (4) pre- and post-pharmacological or non-pharmacological analgesic interventions to assess treatment response.

In academic and clinical research contexts, the Dutch PACSLAC provides an operationalized, quantitative continuous variable of non-verbal pain behaviors. By condensing the original 60-item checklist into an empirically validated 24-item scale, the Dutch adaptation reduces caregiver survey fatigue and observation burden while maintaining psychometric fidelity. This efficiency is critical for epidemiological pain surveillance in psycho-geriatric wards, randomized clinical trials evaluating analgesic efficacy, and longitudinal investigations into neurodegenerative pain mechanisms.

Psychological Construct

The psychological and physiological construct quantified by the Dutch PACSLAC is non-verbal behavioral pain expression in cognitively compromised individuals. Pain is inherently a multidimensional, subjective experience encompassing sensory-discriminative, affective-motivational, and cognitive-evaluative components. When neurological damage uncouples the subjective experience of pain from semantic articulation, pain is manifested through reflexive and voluntary motor, acoustic, and interpersonal expressions. The Dutch PACSLAC captures this multidimensional construct across three discrete operational domains:

1. Part I: Facial Expressions (Items 1 to 8)

The face represents the most evolutionarily conserved, biologically hardwired medium for communicating visceral pain and threat. Based conceptually on Ekman’s Facial Action Coding System (FACS) adapted to human nociception, this subscale captures specific micro- and macro-expressions triggered by nociceptive stimulation. It records observable muscular actions including furrowing the brow (Fronsen / gefronste wenkbrauwen), orbital tightening and eye squeezing (Dichtknijpen van de ogen), wide-eyed apprehension or fearful expression (Pijnlijke blik in de ogen / bange blik, Ogen wijd open sperren), grimacing (Grimassen trekken), perioral muscle tension (Vertrokken mond / strakke lippen), and signs of distress such as pouting or looking sad (Verdrietige blik / pruillip). Additionally, it integrates sympathetic autonomic reactivity manifested cranially, such as acute pallor (Bleek zien).

2. Part II: Verbal and Vocal Behaviors (Items 9 to 14)

Vocalizations are critical acoustic distress signals modulated by subcortical limbic regions that remain functionally active even after cortical language centers experience neurodegeneration. In patients with profound expressive aphasia, acoustic output shifts from propositional language to non-propositional, primitive communicative signals. This subscale measures six distinct audible behaviors: low-frequency acoustic emissions such as groaning and sighing (Kreunen / zuchten), high-arousal distress outbursts including screaming and yelling (Schreeuwen / gillen), discontented grumbling, muttering, or persistent verbal complaints (Mopperen / brommen / klagen), acoustic manifestations of despair such as whimpering or weeping (Jammeren / huilen), autonomic-respiratory distress signs such as hyperventilation or gasping for air (Sneller ademhalen / naar adem happen), and sudden communicative cessation or speech inhibition (Plotseling stilvallen / stoppen met praten).

3. Part III: Body Movements and Behavioral/Interactional Changes (Items 15 to 24)

This subscale evaluates gross motor reactivity, defensive postures, and sociocommunicative alterations. Physical movement often exacerbates somatic or articular pain, precipitating observable protective behaviors. The items measure defensive motor resistance during care routines (Afweren / wegdraaien bij aanraking of verzorging), generalized muscle rigidity or contracted posture (Gespannen / verkrampte houding, Verstijven / verstarren), motor agitation and pacing or manual manipulation (Rusteloos bewegen / friemelen), active guarding or touching of an anatomically painful focus (Vasthouden of beschermen van een lichaamsdeel), reactive physical hostility during mobilization (Agressief gedrag), and refusal to ambulate or cooperate with functional tasks (Weigeren te bewegen of mee te werken). It also captures passive emotional changes, including apathy and affective withdrawal (Zich terugtrekken / apathisch gedrag), acute irritability (Prikkelbaar / snel geïrriteerd), and an inability to be comforted by standard environmental reassurance (Moeilijk te troosten of gerust te stellen).

Theoretical Framework

The Dutch PACSLAC is situated within modern biocognitive models of non-verbal pain communication, notably the Social-Communication Model of Pain developed by Kenneth Craig and further adapted to neurodegenerative populations by Thomas Hadjistavropoulos. This model posits that pain expression is a dynamic interpersonal communicative system comprising an internal biological event (tissue trauma or nociceptor activation), an encoding phase (automatic and controlled behavioral outputs), a transmission medium (visual and acoustic cues), and a decoding phase (the observer’s perception, cognitive appraisal, and clinical intervention).

Under ordinary physiological conditions, cortical integration allows an individual to consciously select verbal self-report as the primary communicative vehicle. However, in advanced neurodegenerative pathology—such as the neurofibrillary tangle progression and amyloid plaque deposition characterizing Alzheimer’s disease—cortical areas responsible for higher-order semantic processing and voluntary executive control deteriorate. In contrast, subcortical and limbic circuits (including the amygdala, anterior cingulate cortex, and periaqueductal gray) continue processing nociceptive inputs and drive automatic behavioral cascades.

Consequently, the theoretical foundation of the PACSLAC rests on the postulate of compensatory behavioral signaling: as semantic capacity declines, behavioral signaling becomes the primary channel for nociceptive information. Because these expressions can be subtle, sporadic, and confounded by dementia-related neuropsychiatric signs (e.g., wandering, general restlessness, or sundowning), unstructured clinical intuition often leads to diagnostic errors. The PACSLAC operationalizes Craig’s decoding process by providing clinical observers with an explicit, standardized taxonomy of behavioral markers. By applying psychometric structure to behavioral decoding, the tool transforms indirect observations into actionable clinical data.

Validity

The psychometric validity of the Dutch 24-item PACSLAC has been evaluated across long-term institutional care settings, psychogeriatric hospital centers, and specialized facilities for individuals with severe intellectual disabilities. Empirical investigations spearheaded by Sandra Zwakhalen and colleagues (2006, 2007, 2008) have established several forms of construct and criterion-related validity:

Construct and Criterion Validity

Construct validity has been demonstrated using known-groups and within-subject contrasting conditions paradigms. In validation trials evaluating nursing home residents with moderate-to-severe dementia, researchers observed participants across distinct clinical states: during quiet rest and during potentially painful physical activities (such as transfers, morning personal hygiene routines, passive joint mobilization, or wound management). The 24-item Dutch PACSLAC demonstrated significant score elevations during standardized movement conditions compared to baseline resting states ($p < .001$), confirming its capacity to discriminate movement-evoked mechanical and musculoskeletal pain.

Convergent and Concurrent Validity

Convergent validity has been established by cross-correlating PACSLAC-D scores with independent, established observational pain metrics evaluated simultaneously. Correlations between the Dutch PACSLAC and the Pain Assessment in Advanced Dementia (PAINAD) scale are high, ranging between $r = .65$ and $r = .80$. Furthermore, when compared with certified geriatric nurse and physician overall clinical impressions documented via 100-mm Visual Analogue Scales (VAS-Observed Pain), the Dutch PACSLAC exhibited correlation coefficients between $r = .55$ and $r = .72$.

Discriminant Validity

A central psychometric challenge in dementia assessment is differentiating nociceptive distress from neuropsychiatric disturbances such as primary delirium, mood disorders, or generalized neuropsychiatric agitation. Discriminant validity evaluations confirm that while PACSLAC-D scores demonstrate modest associations with baseline agitation inventories (such as the Cohen-Mansfield Agitation Inventory [CMAI]), specific subscales—particularly Facial Expressions and Vocalizations—maintain distinct variance directly attributable to acute nociceptive inputs rather than chronic non-pain agitation.

Sensitivity to Analgesic Intervention

In pharmacological longitudinal protocols, residents presenting with high baseline Dutch PACSLAC scores who were administered standardized analgesic interventions (e.g., scheduled acetaminophen, topical NSAIDs, or step-two/step-three opioid regimens) exhibited statistically and clinically significant score reductions upon reassessment ($p < .01$). This confirms that the checklist functions as an evaluative measure responsive to therapeutic interventions over time.

Reliability

The reliability of the Dutch 24-item PACSLAC has been documented across real-world psychogeriatric and nursing home environments, demonstrating stability and internal cohesion across diverse clinical settings:

Internal Consistency

In original and follow-up validation cohorts (e.g., Zwakhalen et al., 2007, 2008), the overall internal consistency for the 24-item composite scale consistently demonstrated Cronbach’s alpha values between .78 and .88 during movement and care-related observations. In passive resting situations, Cronbach’s alpha remains acceptable, typically falling between .70 and .77. The lower baseline coefficients at rest reflect a floor effect commonly encountered in clinical observational scales when non-verbal subjects are calm and experiencing negligible acute pain. When analyzing discrete subscales, Part I (Facial Expressions) routinely exhibits alpha values between .68 and .81, Part II (Verbal/Vocal) between .62 and .76, and Part III (Body Movements/Interaction) between .64 and .79.

Inter-Rater Reliability

Inter-rater agreement between independent nurse observers evaluating identical resident interactions (either via direct simultaneous observation or standardized dual-coded video analysis) has yielded strong agreement. Item-level inter-rater agreement calculated via Cohen’s kappa ($kappa$) ranges from .42 to .85 across individual items, with facial expressions and gross motor guarding yielding the highest discrete concordance. At the aggregate scale level, the Intraclass Correlation Coefficient (ICC) between clinical raters ranges from .72 to .84, confirming high scoring consistency across observers.

Test-Retest Stability

The temporal stability of the Dutch PACSLAC was established through test-retest paradigms assessing stable residents across short-term non-intervention windows (e.g., repeated observations during identical neutral morning care tasks on consecutive days). Under these controlled conditions, test-retest reliability yielded intraclass correlation coefficients ranging from .68 to .79, indicating consistent measurement across stable clinical states.

Factor Analysis

The structural morphology of the Dutch PACSLAC is based on classical exploratory factor analysis (EFA) and subsequent confirmatory factor analytic (CFA) modeling executed during the cross-cultural adaptation and psychometric streamlining of the original 60-item instrument. The Canadian parent version exhibited a four-factor structure; however, several items suffered from low communalities, high collinearity, or low base-rate prevalence among institutionalized populations.

Exploratory Factor Analysis (EFA) and Item Reduction

Zwakhalen and colleagues subjected observational datasets from hundreds of Dutch nursing home residents to principal component analyses (PCA) and common factor analyses with both Varimax (orthogonal) and Oblimin (oblique) rotations. Items demonstrating near-zero variance, extreme floor effects (rarely or never observed across cohorts), or ambiguous cross-loadings below .35 were removed. This reduction condensed the instrument from 60 to 24 items, yielding a clear three-factor solution explaining over 42% to 48% of the total variance across movement-observation models:

• Factor 1: Facial Expressions — Comprising items 1 through 8, this factor explained the largest proportion of unique variance (typically ~22–25%). Factor loadings for these items generally ranged between .45 and .78. Primary markers such as Fronsen (frowning) and Grimassen trekken (grimacing) loaded cleanly onto this latent dimension.
• Factor 2: Verbal and Vocal Behaviors — Comprising items 9 through 14, this factor explained approximately 11–13% of the variance. Items reflecting vocalized distress, such as Kreunen / zuchten (groaning/sighing) and Jammeren / huilen (whimpering/crying), exhibited loadings ranging from .52 to .81.
• Factor 3: Body Movements and Behavioral/Interactional Changes — Comprising items 15 through 24, this broad behavioral factor accounted for approximately 9–11% of the total variance. Items describing motor resistance, defensive posturing, and communicative withdrawal (such as Afweren and Vasthouden/beschermen) yielded loadings ranging from .38 to .72.

Confirmatory Factor Analysis (CFA) and Goodness-of-Fit

Subsequent confirmatory factor analyses validating this 3-factor hierarchical configuration yielded acceptable goodness-of-fit indices. The structural models exhibited a Root Mean Square Error of Approximation (RMSEA) of .058 to .065, a Comparative Fit Index (CFI) of .91 to .94, and a standardized root mean square residual (SRMR) < .07. These structural analyses confirm that the Dutch PACSLAC’s 24-item, three-subscale composition is statistically sound and psychometrically robust.

Instrument / Measurement Tool

The operational administration characteristics of the Dutch PACSLAC are structured as follows:

• Test Type: Behavioral proxy rating scale; observational clinical assessment instrument.
• Target Population: Older adults residing in nursing homes, assisted living facilities, residential homes, or hospices who present with moderate-to-severe dementia, cognitive deterioration, expressive aphasia, or acquired/developmental intellectual disabilities preventing verbal self-report.
• Administration Format: Direct real-time bedside observation or standardized post-care observational evaluation completed by certified nursing staff, clinical nurse specialists, physicians, or trained caregivers.
• Recommended Observation Window: Typically administered across a 5- to 10-minute observation interval, preferably during standardized physical care activities or movement (e.g., transfers, personal hygiene, dressing, repositioning), or following suspected acute pain episodes.
• Total Item Count: 24 dichotomous behavioral indicators.
• Subscale Architecture:
  • Deel I: Gezichtsuitdrukkingen (Facial Expressions): Items 1 to 8.
  • Deel II: Verbaal/vocaal gedrag (Verbal/Vocal Behaviors): Items 9 to 14.
  • Deel III: Lichaamsbewegingen en gedrag/interactie (Body Movements and Behavior/Interaction): Items 15 to 24.
• Response Format: Dichotomous scoring system:
  • 0 = Afwezig (Absent / No): The specific behavior was not exhibited during the observation window.
  • 1 = Aanwezig (Present / Yes): The behavior was clearly observed at least once during the evaluation window.
• Scoring and Quantification Rules: Each present behavioral sign is assigned 1 point; absent signs receive 0 points. Total scores are calculated by summing all 24 items, yielding a composite score range of 0 to 24.
  • Reverse Scoring: None. All items are positively keyed toward the presence of pain.
  • Score Interpretation: Higher scores reflect an increased likelihood and elevated behavioral intensity of pain. While the checklist does not establish an absolute universal diagnostic cut-off due to individualized baseline presentations, clinical guidelines commonly consider scores of 4 or higher—or any acute increase over a resident’s documented resting baseline—as a positive indication requiring clinical assessment, targeted repositioning, or analgesic intervention.

Permissions & Fee and Test Year

The original parent instrument, the Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC), was introduced in 2004 by Shannon Fuchs-Lacelle and Thomas Hadjistavropoulos. The standardized Dutch shortened adaptation (24-item version) was psychometrically developed and published by Sandra M. G. Zwakhalen and her academic colleagues in 2007 (with preliminary comparative exploratory foundations established in 2006).

Licensing and Usage Permissions: The Dutch PACSLAC is an open-access, royalty-free measurement tool intended for clinical, non-profit, educational, and academic research use. No licensing fees are required for nursing facilities, academic hospitals, or university research teams utilizing the paper-and-pencil or standard electronic versions. However, users must maintain the integrity of the scale by preserving the authentic wording, scoring rules, and 24-item structure, alongside appropriate academic citation of Sandra M. G. Zwakhalen and original instrument creators Thomas Hadjistavropoulos and Shannon Fuchs-Lacelle. Inclusion within proprietary commercial electronic health record (EHR) software platforms or large-scale digital health applications typically requires written permission from the copyright holders and publishing bodies.

References

• Chan, S., Hadjistavropoulos, T., Williams, J., & Lints-Martindale, A. (2014). Evidence-based development and initial validation of the Pain Assessment Checklist for Seniors with Limited Ability to Communicate-II (PACSLAC-II). The Clinical Journal of Pain, 30(9), 816–824. https://doi.org/10.1097/AJP.0000000000000039
• Craig, K. D. (2009). The social communication model of pain. Canadian Psychology / Psychologie canadienne, 50(1), 22–32. https://doi.org/10.1037/a0014772
• Fuchs-Lacelle, S., & Hadjistavropoulos, T. (2004). Development and preliminary validation of the Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC). Pain Management Nursing, 5(1), 37–49. https://doi.org/10.1016/j.pmn.2003.10.001
• Hadjistavropoulos, T., Herr, K., Prkachin, K. M., Craig, K. D., Gibson, S. J., Lukas, A., & Smith, J. H. (2014). Pain assessment in elderly adults with dementia. The Lancet Neurology, 13(12), 1216–1227. https://doi.org/10.1016/S1474-4422(14)70103-6
• Warden, V., Hurley, A. C., & Volicer, L. (2003). Development and psychometric evaluation of the Pain Assessment in Advanced Dementia (PAINAD) scale. Journal of the American Medical Directors Association, 4(1), 9–15. https://doi.org/10.1097/01.JAM.0000043422.31640.F7
• Zwakhalen, S. M. G., Hamers, J. P. H., Abu-Saad, H. H., & Berger, M. P. F. (2006). Pain in elderly people with severe dementia: A systematic review of behavioural pain assessment tools. BMC Geriatrics, 6, Article 3. https://doi.org/10.1186/1471-2318-6-3
• Zwakhalen, S. M. G., Hamers, J. P. H., & Berger, M. P. F. (2007). The psychometric quality of the Dutch version of the Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC-D). Pain Practice, 7(4), 289–296. https://doi.org/10.1111/j.1533-2500.2007.00150.x
• Zwakhalen, S. M. G., van der Steen, J. T., & Najafi, N. E. (2012). Assessment of pain in people with dementia. Dementia and Geriatric Cognitive Disorders Extra, 2(1), 384–398. https://doi.org/10.1159/000341774

Items of the Scale