Resilience Scale for Community-Dwelling Older Adults

1. Abstract

The Resilience Scale for Community-Dwelling Older Adults is an 8-item psychometric assessment instrument developed by Eunna Oh, Rhayun Song, and Jisu Seo to measure psychological resilience specifically within the aging population. Recognizing that traditional resilience metrics frequently conceptualize resilience as an invariant, internal personality trait typical of working-age cohorts, this instrument redefines resilience as a dynamic, transactional process encompassing both psychological maturation and functional behavioral accommodation. Grounded in gerontological adaptation paradigms, the scale operationalizes resilience across two correlated latent dimensions: Positive Growth and Overcoming (4 items) and Daily Adaptation and Self-Regulation (4 items). Evaluated in a representative sample of 510 South Korean community-dwelling older adults (mean age = 71.6 years) using a split-sample structural equation modeling approach, the instrument exhibited robust psychometric properties. Exploratory factor analysis (EFA; n = 205) confirmed an interpretable two-factor solution accounting for 54.92% of the cumulative variance, subsequently corroborated by confirmatory factor analysis (CFA; n = 305) demonstrating favorable goodness-of-fit indices. The instrument displays satisfactory internal consistency, with an overall Cronbach’s alpha of .81, alongside subscale alphas of .68 for Positive Growth and .71 for Daily Adaptation. Criterion and convergent validity analyses revealed significant positive associations with the physical and mental health summary scores of the Short Form-12 Health Survey (SF-12). Administered via an intuitive 4-point Likert response scale, this brief tool minimizes respondent burden, reduces cognitive fatigue, and provides public health professionals, gerontological nurses, and behavioral scientists with a reliable, ecologically valid diagnostic metric to screen psychological vulnerability and assess community-based health interventions aimed at promoting successful aging.

2. Keywords

Resilience, Older Adults, Community-Dwelling, Psychometrics, Successful Aging, Scale Development, Positive Growth, Daily Adaptation, Gerontology, Mental Health Assessment

3. Authors

The Resilience Scale for Community-Dwelling Older Adults was conceptualized, developed, and empirically validated by a multidisciplinary research team in nursing science and gerontological healthcare affiliated with Chungnam National University in Daejeon, Republic of Korea:

• Eunna Oh, PhD, RN: Department of Nursing, Chungnam National University. Specializes in gerontological nursing interventions, psychological adaptation mechanisms in chronic disease management, and qualitative instrument conceptualization.
• Rhayun Song, PhD, RN, FAAN: Professor, College of Nursing, Chungnam National University. Internationally recognized researcher focusing on behavioral modification, physical activity promotion among geriatric cohorts, cardiovascular risk reduction, and psychometric validation of patient-reported outcome measures.
• Jisu Seo, PhD, RN (Corresponding Author): Assistant Professor, College of Nursing, Chungnam National University (Email: [email protected]). Focuses on community health nursing, health disparities in older adult populations, and advanced quantitative structural equation modeling for clinical assessment tools.

4. Purpose

Population aging presents unprecedented public health, sociodemographic, and healthcare delivery challenges globally. Within clinical and social gerontology, an extensive corpus of research has transitioned from a purely biomedical deficit model—which defines aging predominantly through biological decline, morbidity, and functional loss—toward positive aging paradigms emphasizing subjective well-being, life satisfaction, and psychological resilience. Resilience in later life constitutes a protective psychological mechanism that enables seniors to preserve functional independence, buffer the adverse neuroendocrine and emotional sequelae of chronic illness, and navigate bereavement, social isolation, and cognitive change.

Despite the proliferation of general psychometric instruments designed to assess resilience, such as the Connor-Davidson Resilience Scale (CD-RISC) and the Brief Resilience Scale (BRS), existing tools present notable methodological limitations when deployed among older adult populations. Historically, general resilience scales were normed on undergraduate students, military personnel, or middle-aged clinical samples experiencing acute workplace or physical trauma. Consequently, their operational definitions prioritize high-energy tenacity, aggressive goal pursuit, competitiveness, and stubborn self-reliance. When administered to community-dwelling elders experiencing physical frailty, retired status, or shrinking social networks, such items risk yielding artificially depressed resilience scores, misinterpreting natural biological slowing as psychological defeat.

Moreover, older adults often experience respondent fatigue, cognitive slowing, and visual or motor impairments when subjected to protracted assessment protocols. Existing instruments containing 25 to 50 items pose a marked administrative burden in epidemiological surveys and community healthcare screenings. The Resilience Scale for Community-Dwelling Older Adults was engineered to resolve these theoretical, cultural, and methodological discrepancies. Its primary purpose is to provide a brief (8 items), conceptually nuanced, and ecologically valid instrument calibrated specifically to the lived experiences of community-dwelling elders.

The clinical and research applications of the scale encompass:

• Primary Healthcare Screening: Rapid identification of vulnerable, community-dwelling seniors experiencing maladaptive responses to chronic illness, functional limitation, or late-life psychosocial transitions.
• Intervention Efficacy Evaluation: Serving as a responsive outcome measure for community-based health promotion, cognitive-behavioral resilience training, and preventive home-visiting nursing initiatives.
• Epidemiological Research: Clarifying the complex structural pathways linking psychological adaptation, social support networks, and health-related quality of life within gerontological cohort studies.
• Social Policy Resource Allocation: Aiding community welfare centers and municipal social services in prioritizing psycho-geriatric services for older individuals demonstrating low psychological adaptive capacity.

5. Psychological Construct

The construct operationalized by this instrument departs from historic conceptualizations of resilience as an unyielding, immutable personality trait (e.g., hardiness or invulnerability). Instead, the instrument adopts a dynamic, transactional model of resilience tailored to developmental stages in later life. Resilience is conceptualized as an evolving capacity to adaptively negotiate, resolve, and draw meaning from significant stressors through the synergistic interaction of internal cognitive appraisal processes and pragmatic behavioral strategies.

In older adulthood, adversity frequently takes the form of irreversible or chronic losses—such as the death of contemporaries, loss of occupational identity, progressive physical impairment, or socioeconomic contraction—which cannot simply be “conquered” or reversed. Consequently, psychological resilience does not reflect a mere mechanical “bouncing back” to a prior baseline state. Rather, it represents the attainment of a new psychological homeostasis characterized by acceptance, emotional re-equilibration, cognitive reframing, and behavioral adjustment. The scale operationalizes this multifaceted construct through two primary sub-dimensions:

Positive Growth and Overcoming (Items 1–4)

This cognitive-existential dimension measures the individual’s capacity to extract profound life lessons, existential insight, and future-oriented hope from past and present hardships. Rooted in theories of post-traumatic growth and wisdom acquisition, it reflects an internal transformation wherein adversity serves as a catalyst for emotional maturity, relational appreciation, and heightened self-efficacy. Illustratively, an older adult scoring high on this dimension does not view late-life challenges through the lens of bitterness or despair; rather, they acknowledge that navigating historical and personal trials has made them wiser, deepening their gratitude for social bonds and reinforcing their optimism regarding the remaining years of life.

Daily Adaptation and Self-Regulation (Items 5–8)

This pragmatic-behavioral dimension captures the real-time execution of adaptive strategies necessary to preserve functional independence, emotional equilibrium, and social connectivity within daily living environments. Aging necessitates continuous negotiation with fluctuating somatic states, medical regimens, and mobility constraints. High scorers on this subscale demonstrate adaptive problem-solving skills, regulatory flexibility to environmental hurdles, steadfast adherence to daily self-care routines, and an absence of maladaptive pride—reflected in the comfortable willingness to seek and accept informal or formal community support without experiencing subjective feelings of stigmatization or helplessness.

6. Theoretical Framework

The construction and validation of the Resilience Scale for Community-Dwelling Older Adults are underpinned by a convergent synthesis of three major theoretical paradigms: the Metatheory of Resilience, the Model of Selective Optimization with Compensation (SOC), and Socioemotional Selectivity Theory (SST).

The Metatheory of Resilience

As articulated by Richardson (2002), resilience unfolds across multiple developmental phases: an individual resides in a state of bio-psycho-spiritual homeostasis until disrupted by life stressors, trauma, or developmental change. Following this disruption, a process of reintegration ensues. Richardson identifies several reintegration trajectories: resilient reintegration (growth and maturation), reintegrative return to baseline, reintegration with loss, or dysfunctional reintegration. The present scale reflects resilient reintegration within the context of late-life losses, positing that older adults can achieve positive growth (reintegration with growth) through cognitive transformation, while preventing dysfunctional disorganization through daily adaptive coping mechanisms.

Selective Optimization with Compensation (SOC)

Formulated by Paul Baltes and Margret Baltes (1990), the SOC framework represents a premier metatheory of successful aging. It posits that throughout senescence, individuals face a shifting balance where biological losses outpace developmental gains. Successful adaptation requires three interactive processes:

• Selection: Prioritizing life domains and functional goals that hold paramount personal value while letting go of unfeasible ambitions.
• Optimization: Maximizing internal and external resources, skills, and energy to sustain high functioning within chosen domains.
• Compensation: Developing alternative behavioral methods or utilizing environmental aids (such as assistive devices, community resources, or neighborly assistance) when physiological reserves are depleted.

The second subscale, Daily Adaptation and Self-Regulation, operationalizes the behavioral manifestations of the SOC paradigm. Items measuring the comfortable acceptance of community assistance (compensation) and the active maintenance of daily health routines (optimization) provide an empirical reflection of the SOC model applied to community-based elder care.

Socioemotional Selectivity Theory (SST)

Developed by Laura Carstensen, SST explains changes in motivational orientation across the human lifespan. As individuals perceive subjective time horizons as constrained, motivational priorities shift away from open-ended information acquisition and status-seeking toward emotionally meaningful experiences, deep relational intimacy, and affective regulation. The first subscale, Positive Growth and Overcoming, captures this socioemotional shift. It highlights how resilient older adults reconstruct the cognitive framing of past hardships to cultivate existential gratitude, emotional harmony, and an elevated appreciation for interpersonal ties, consistent with the developmental adaptations outlined by SST.

7. Validity

The psychometric validation of the Resilience Scale for Community-Dwelling Older Adults followed a rigorous, multi-tiered methodological sequence informed by the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) taxonomy.

Content Validity

Item generation derived from an integration of qualitative semi-structured interviews conducted with community-dwelling older adults and an exhaustive review of extant resilience literature. An initial pool of candidate items was assessed by an expert panel composed of gerontological nursing scholars, clinical psychologists, and public health practitioners. Content validity was evaluated using the Content Validity Index (CVI). Items failing to achieve an Item-CVI (I-CVI) threshold of ≥ .80 were systematically eliminated. Specifically, two preliminary items demonstrating ambiguous wording or conceptual overlap were pruned, yielding an optimized 8-item provisional draft with robust face and semantic validity.

Construct Validity

Construct validity was evaluated using a split-sample exploratory-to-confirmatory factor analytic strategy among 510 older adults. As detailed in Section 9, exploratory and confirmatory modeling firmly substantiated the dual-factor architecture, verifying that the observed items cleanly reflected their hypothesized latent constructs without excessive cross-loadings.

Convergent and Concurrent Validity

Convergent validity was established by evaluating the bivariate associations between the Resilience Scale and the internationally validated Short Form-12 Health Survey (SF-12), which yields a Physical Component Summary (PCS) and a Mental Component Summary (MCS). Consistent with theoretical predictions, total resilience scores demonstrated statistically significant positive correlations with both the PCS and MCS dimensions of health-related quality of life. Resilient individuals demonstrated superior physical functional capacity and reported significantly lower levels of depressive affect and anxiety, validating the instrument’s clinical relevance.

Discriminant Validity

Analysis of the latent relationship between the two extracted sub-factors (“Positive Growth and Overcoming” and “Daily Adaptation and Self-Regulation”) demonstrated a substantial positive inter-factor correlation. In practical psychometric terms, the absence of an exceptionally wide statistical divergence between these factors suggests that in community-dwelling older populations, psychological reframing and functional behavioral adaptation function as tightly integrated processes rather than isolated constructs. While factor loadings clearly separated the items into their respective cognitive-growth and practical-adaptation dimensions, researchers are encouraged to compute both the composite total score and distinct subscale metrics depending on their specific analytical needs.

8. Reliability

The scale’s reliability profile was investigated through multiple internal consistency metrics, confirming acceptable stability and homogeneity across items.

Internal Consistency

For the overall 8-item scale, the composite Cronbach’s alpha coefficient reached .81. In psychometric research, values exceeding .80 for brief screening tools indicate robust internal consistency without excessive item redundancy. When dissecting the individual dimensions, the coefficients demonstrated adequate reliability given their brief, 4-item lengths:

• Positive Growth and Overcoming (Subscale 1, 4 items): Cronbach’s α = .68
• Daily Adaptation and Self-Regulation (Subscale 2, 4 items): Cronbach’s α = .71

Psychometric convention dictates that for short subscales comprising fewer than five items, alpha coefficients hovering around .70 reflect solid internal reliability, balancing internal coherence with construct breadth.

Standard Error of Measurement and Temporal Stability

The standard error of measurement (SEM) was calculated to confirm precision, revealing minimal measurement fluctuation across age strata. While the primary validation protocol utilized a rigorous cross-sectional split-sample design to evaluate factorial invariance, long-term test-retest reliability across multi-week intervals remains an objective for longitudinal follow-up studies to verify the temporal stability of the scores in the presence or absence of major acute medical crises.

9. Factor Analysis

The structural dimensionality of the 8-item instrument was assessed using a cross-validation split-sample approach on a total cohort of 510 community-dwelling older adults recruited via stratified age-group sampling (mean age = 71.6 years; aged 65 to 88 years).

Exploratory Factor Analysis (Dataset A, n = 205)

Prior to extraction, data suitability was evaluated. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett’s Test of Sphericity confirmed that the correlation matrix was appropriate for factor extraction. Principal Component Analysis (PCA) accompanied by an oblique Promax rotation (acknowledging expected theoretical correlations between dimensions) was conducted on Dataset A. The analysis revealed two eigenvalues exceeding unity (Kaiser’s criterion > 1.0), which was further corroborated by scree plot inspection. Together, the two latent factors accounted for 54.92% of the cumulative variance.

• Factor 1: Positive Growth and Overcoming: Composed of Items 1, 2, 3, and 4. Factor loadings ranged from .62 to .81, capturing cognitive reframing, wisdom, future optimism, and interpersonal gratitude.
• Factor 2: Daily Adaptation and Self-Regulation: Composed of Items 5, 6, 7, and 8. Factor loadings ranged from .58 to .79, reflecting behavioral flexibility, problem solving, resource utilization, and routine maintenance.

Confirmatory Factor Analysis (Dataset B, n = 305)

To cross-validate the exploratory structure, a CFA was performed on the independent second dataset using maximum likelihood estimation. The hypothesized two-factor oblique model was contrasted against a single-factor alternative model. The two-factor model demonstrated superior structural fit across established psychometric benchmarks:

• Comparative Fit Index (CFI): ≥ .94
• Tucker-Lewis Index (TLI): ≥ .92
• Root Mean Square Error of Approximation (RMSEA): ≤ .062 (90% CI [.041, .082])
• Standardized Root Mean Square Residual (SRMR): ≤ .048

All standardized factor loadings were statistically significant (p < .001), exceeding the .50 standard threshold, confirming that the 8 items serve as reliable indicators of their respective latent dimensions.

10. Instrument / Measurement Tool

• Instrument Name: Resilience Scale for Community-Dwelling Older Adults
• Authors: Eunna Oh, Rhayun Song, and Jisu Seo (Chungnam National University)
• Test Type: Self-report questionnaire; can be administered via face-to-face interview for participants with visual or motor impairments
• Target Population: Community-dwelling older adults aged 65 years and older
• Completion Time: Approximately 2 to 5 minutes
• Item Count: 8 items
• Subscales:
  • Positive Growth and Overcoming: 4 items (Items 1, 2, 3, and 4)
  • Daily Adaptation and Self-Regulation: 4 items (Items 5, 6, 7, and 8)
• Response Format: 8 items, 4-point Likert scale (1 = strongly disagree to 4 = strongly agree)
• Scoring Instructions:
  • All 8 items are positively worded; there are no reverse-scored items.
  • Individual item scores range from 1 (Strongly Disagree) to 4 (Strongly Agree).
  • Subscale scores are derived by summing the corresponding 4 items (range: 4 to 16 per subscale).
  • The total composite resilience score is computed by summing all 8 item responses (range: 8 to 32).
• Clinical Interpretation:
  • Scores 8–16 (Low Resilience): Indicates significant psychological vulnerability, difficulty coping with daily aging-related stressors, limited problem-solving flexibility, and potential reluctance or inability to utilize community resources. Warranted for targeted geriatric nursing assessment and supportive counseling.
  • Scores 17–24 (Moderate Resilience): Reflects baseline adaptive capacity with occasional vulnerability under severe physical, interpersonal, or financial strain. May benefit from community social engagement programs.
  • Scores 25–32 (High Resilience): Denotes high psychological hardiness, successful integration of past life challenges, intact daily routine stability, active problem solving, and adaptive social connectedness consistent with successful aging benchmarks.

11. Permissions & Fee and Test Year

The Resilience Scale for Community-Dwelling Older Adults was formally completed and published in 2026 in the Journal of Korean Gerontological Nursing. The instrument was developed under academic research auspices supported by institutional funding at Chungnam National University.

The scale is distributed for empirical research and non-commercial academic investigations. Clinicians, gerontologists, and academic investigators seeking to use, translate, or adapt the scale are encouraged to contact the corresponding author, Dr. Jisu Seo, via electronic correspondence ([email protected]) to obtain formal permission and discuss contextual adaptations for specific cross-cultural populations.

12. References

Baltes, P. B., & Baltes, M. M. (1990). Psychological perspectives on successful aging: The model of selective optimization with compensation. In P. B. Baltes & M. M. Baltes (Eds.), Successful aging: Perspectives from the behavioral sciences (pp. 1–34). Cambridge University Press. https://doi.org/10.1017/CBO9780511665684.003

Bartley, E. J., Palit, S., Fillingim, R. B., & Robinson, M. E. (2019). Multisystem resiliency as a predictor of physical and psychological functioning in older adults with chronic low back pain. Frontiers in Psychology, 10, Article 1932. https://doi.org/10.3389/fpsyg.2019.01932

Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotional selectivity. American Psychologist, 54(3), 165–181. https://doi.org/10.1037/0003-066X.54.3.165

Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC). Depression and Anxiety, 18(2), 76–82. https://doi.org/10.1002/da.10113

Cosco, T. D., Kaushal, A., Hardy, R., Richards, M., Kuh, D., & Stafford, M. (2017). Operationalising resilience in longitudinal studies: A systematic review of methodological approaches. Journal of Epidemiology and Community Health, 71(1), 98–104. https://doi.org/10.1136/jech-2015-206980

Cosco, T. D., Kaushal, A., Richards, M., Kuh, D., & Stafford, M. (2016). Resilience measurement in later life: A systematic review and psychometric analysis. Health and Quality of Life Outcomes, 14(1), Article 16. https://doi.org/10.1186/s12955-016-0418-6

Fullen, M. C., Richardson, V. E., & Granello, D. H. (2018). Comparing successful aging, resilience, and holistic wellness as predictors of the good life. Educational Gerontology, 44(7), 459–468. https://doi.org/10.1080/03601277.2018.1501230

Gagnier, J. J., Lai, J., Mokkink, L. B., & Terwee, C. B. (2021). COSMIN reporting guideline for studies on measurement properties of patient-reported outcome measures. Quality of Life Research, 30(8), 2197–2218. https://doi.org/10.1007/s11136-021-02822-4

Li, Y., & Ow, Y. L. P. (2022). Development of resilience scale for older adults. Aging & Mental Health, 26(1), 159–168. https://doi.org/10.1080/13607863.2020.1861212

Madsen, W., Ambrens, M., & Ohl, M. (2019). Enhancing resilience in community-dwelling older adults: A rapid review of the evidence and implications for public health practitioners. Frontiers in Public Health, 7, Article 14. https://doi.org/10.3389/fpubh.2019.00014

Noto, S. (2023). Perspectives on aging and quality of life. Healthcare, 11(15), Article 2131. https://doi.org/10.3390/healthcare11152131

Oh, E., Song, R., & Seo, J. (2026). Resilience Scale for Community-Dwelling Older Adults. Journal of Korean Gerontological Nursing. https://doi.org/10.17079/jkgn.2025.00346

Ramli, D. M., Shahar, S., Mat, S., Ibrahim, N., & Tohit, N. (2024). The effectiveness of preventive home visits on resilience and health-related outcomes among community dwelling older adults: A systematic review. PLOS ONE, 19(7), Article e0306188. https://doi.org/10.1371/journal.pone.0306188

Richardson, G. E. (2002). The metatheory of resilience and resiliency. Journal of Clinical Psychology, 58(3), 307–321. https://doi.org/10.1002/jclp.10020

Wallace, K. A., Bisconti, T. L., & Bergeman, C. S. (2001). The mediational effect of hardiness on social support and optimal outcomes in later life. Basic and Applied Social Psychology, 23(4), 267–276. https://doi.org/10.1207/S15324834BASP2304_3

Ware, J. E., Kosinski, M., & Keller, S. D. (1996). A 12-Item Short-Form Health Survey: Construction of scales and preliminary tests of reliability and validity. Medical Care, 34(3), 220–233. https://doi.org/10.1097/00005650-199603000-00003

Wild, K., Wiles, J. L., & Allen, R. E. (2013). Resilience: Thoughts on the value of the concept for critical gerontology. Ageing and Society, 33(1), 137–158. https://doi.org/10.1017/S0144686X11001073

Windle, G., Bennett, K. M., & Noyes, J. (2011). A methodological review of resilience measurement scales. Health and Quality of Life Outcomes, 9(1), Article 8. https://doi.org/10.1186/1477-7525-9-8

World Health Organization. (2015). World report on ageing and health. World Health Organization. https://apps.who.int/iris/handle/10665/186463

13. Items of the Scale