{n “title”: “Functional Assessment of Cancer Therapy – General version (FACT-G)”,n “content”: “
Abstract
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The Functional Assessment of Cancer Therapy – General version (FACT-G) is one of the most widely used, psychometrically validated patient-reported outcome measures (PROMs) designed to evaluate health-related quality of life (HRQoL) in individuals undergoing cancer management and oncology clinical trials. Originating from the collaborative research of David F. Cella and colleagues in 1993, the instrument serves as the core foundation for the broader Functional Assessment of Chronic Illness Therapy (FACIT) Measurement System. The FACT-G comprises 27 items organized into four multidimensional domains: Physical Well-Being (PWB; 7 items), Social/Family Well-Being (SWB; 7 items), Emotional Well-Being (EWB; 6 items), and Functional Well-Being (FWB; 7 items). Respondents rate their experience over the preceding seven days using a 5-point Likert response scale ranging from 0 (\”Not at all\”) to 4 (\”Very much\”).
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Psychometrically, the FACT-G demonstrates robust classical test theory properties and modern item response theory characteristics. Across diverse neoplastic conditions, stages of malignancy, and care contexts, internal consistency coefficients (Cronbach’s alpha) typically range from .87 to .91 for the total scale, with subscale reliabilities generally spanning .67 to .89. Test-retest reliability across clinically stable intervals demonstrates stability coefficients ranging between .82 and .92. Extensive construct, concurrent, discriminant, and predictive validity evidence supports its sensitivity in detecting subtle changes in clinical performance status, such as the Eastern Cooperative Oncology Group (ECOG) performance ratings, toxicity grades, and functional survival benchmarks. Additionally, validated caregiver adaptations enable comparative dyadic assessment of quality-of-life impacts within family systems affected by oncological diagnoses. The tool has been translated and culturally validated in over 45 languages, ensuring international utility in cross-cultural oncology trials, epidemiological investigations, and daily clinical practice.
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Keywords
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FACT-G, Functional Assessment of Cancer Therapy, Health-Related Quality of Life, HRQoL, Psycho-Oncology, Oncology Assessment, FACIT, Psychometrics, Patient-Reported Outcome Measures, Quality of Life in Cancer, Caregiver Burden
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Authors
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The FACT-G was developed by a team of clinical psychologists, psychometricians, and oncology researchers led by David F. Cella, Ph.D. Dr. Cella is the Ralph Seal Paffenbarger Professor and Chair of the Department of Medical Social Sciences at the Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. He also serves as the founder and president of the FACIT.org measurement organization.
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The original development and multi-phase validation work included prominent co-investigators such as David S. Tulsky, Gary Gray, Bela Sarafian, Edith Linn, Amy Bonomi, Marc Silberman, Stephen B. Yellen, and other colleagues associated with Rush-Presbyterian-St. Luke’s Medical Center (now Rush University Medical Center) in Chicago, Illinois. Institutional inquiries, licensing requests, and translation distributions are managed through the FACIT Organization (FACIT.org) based in Elmhurst and Chicago, Illinois, USA.
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Purpose
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The primary clinical and empirical objective of the Functional Assessment of Cancer Therapy – General version (FACT-G) is to quantify patient-perceived health-related quality of life across the continuum of cancer care. Historically, oncology research prioritized objective biological and clinical endpoints such as overall survival, progression-free survival, biochemical tumor markers, and radiographic tumor response. While paramount, these biomedical markers often fail to capture the profound subjective burden imposed by cytotoxic chemotherapy, immunotherapies, targeted radiation, and extensive surgical resections. The FACT-G was purposefully designed to bridge this clinical gap by providing a brief, psychometrically sound, patient-centered instrument capable of detecting the physical toxicities, emotional strains, family disruption, and day-to-day functional impairments experienced by cancer patients.
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Clinical Applications in Oncology
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In routine clinical oncology practice, the FACT-G functions as a systematic screening tool to detect unaddressed symptoms, track longitudinal treatment toxicities, and facilitate shared decision-making between patients, oncologists, oncology nurses, and palliative care specialists. Systematic administration of the FACT-G during outpatient visits allows clinicians to identify symptom clusters, such as severe fatigue, intractable nausea, escalating depressive affect, or progressive loss of physical autonomy, long before these conditions manifest as treatment interruptions or emergency admissions. Moreover, tracking baseline and serial scores helps clinicians evaluate whether the subjective toxicity of an aggressive antineoplastic regimen is balanced by meaningful preservation of functional well-being.
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Research and Clinical Trial Utility
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Within experimental clinical research, the FACT-G serves as a gold-standard secondary or co-primary endpoint in phase II, III, and IV oncology clinical trials. Regulatory bodies, including the United States Food and Drug Administration (FDA) and the European Medicines Agency (EMA), increasingly mandate or strongly encourage the inclusion of rigorous patient-reported outcomes to support label claims regarding clinical benefit and symptom tolerability. Because the FACT-G captures core dimensions universal to all cancer types, it allows cross-comparison across divergent therapeutic modalities (e.g., surgical resection vs. concurrent chemoradiation vs. checkpoint inhibitor immunotherapy). Furthermore, when supplemented with disease-specific subscales (such as those for breast, lung, prostate, or colorectal cancer), the core FACT-G provides a standardized platform that links broad functional status with targeted symptomatic manifestations.
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Dyadic and Caregiver Applications
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An important theoretical and clinical evolution of the FACT-G is its adaptation for family caregivers. Oncological diagnoses fundamentally affect family systems. Caregivers absorb immense physical, psychological, and financial strains while supporting patients through prolonged therapeutic trajectories. The caregiver adaptation of the FACT-G allows clinicians and behavioral researchers to evaluate the parallel well-being of the patient-caregiver dyad, illuminating reciprocal dynamics where elevated caregiver distress or exhaustion can compound patient functional decline, and vice versa.
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Psychological Construct
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The FACT-G conceptualizes health-related quality of life as a multidimensional, subjective construct comprising four distinct, mutually reinforcing domains. Rather than viewing health merely as the absence of disease or infirmity, the construct adheres to the World Health Organization’s holistic definition of health, embracing physical integrity, psychological resilience, social connectedness, and daily occupational/recreational fulfillment.
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1. Physical Well-Being (PWB)
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The Physical Well-Being domain assesses somatic distress, functional biological stamina, and treatment-induced physiological toxicity. Rather than measuring isolated clinical symptoms in a vacuum, the PWB subscale captures how somatic experiences degrade the patient’s subjective sense of physiological viability. Key construct elements include:
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- Energy Depletion: Chronic, unremitting cancer-related fatigue that is disproportionate to recent exertion and unresolved by sleep.
- Gastrointestinal Distress: Symptoms of nausea and gastrointestinal intolerance induced by chemotherapeutic agents, abdominal radiation, or visceral tumor burden.
- Pain and Discomfort: Bodily pain secondary to metastatic skeletal lesions, post-operative nerve entrapment, or inflammatory cascades.
- Iatrogenic Burden: Subjective bother caused by adverse effects of antineoplastic therapies (e.g., neuropathy, alopecia, mucositis).
- Severe Bedrest/Debility: Being physically compelled to spend extended daytime hours in bed due to debilitating weakness.
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2. Social/Family Well-Being (SWB)
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Cancer exerts profound relational stress on marital, familial, and peer support networks. The Social/Family Well-Being domain evaluates the adequacy of emotional support, interpersonal closeness, intra-familial communication, and sexual health. Theoretical underpinnings within this dimension focus on social buffering hypotheses, where strong perceived social support mitigates biological stress responses and enhances psychological coping. Specific components include:
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- Peer and Emotional Support: The perception of having dependable emotional reassurance and tangible assistance from friends and immediate family members.
- Familial Acceptance and Open Communication: The degree to which family members have acknowledged the reality of the diagnosis and engage in constructive, non-avoidant communication.
- Partner Closeness and Intimacy: Sustained interpersonal warmth with a primary partner or identified key support figure.
- Sexual Satisfaction: Self-perceived comfort and fulfillment with one’s sexual life, accompanied by an explicit voluntary opt-out mechanism to respect respondent privacy.
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3. Emotional Well-Being (EWB)
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The Emotional Well-Being domain captures reactive affective distress, existential dread, and psychological adaptation to a life-threatening illness. Rather than diagnosing formal DSM psychiatric categories (such as Major Depressive Disorder or Generalized Anxiety Disorder), EWB gauges the common sub-syndromal and existential strains inherent in oncology. The primary sub-constructs involve:
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- Depressive Affect and Demoralization: Persistent feelings of sadness, dysphoria, and loss of hope in confronting the trajectory of the disease.
- Coping Appraisal: Subjective satisfaction with one’s psychological mechanisms and internal strategies used to confront the diagnosis.
- Anxiety and Nervous Tension: Autonomic or cognitive agitation reflecting apprehension about the future.
- Existential Apprehension: Intrusive worries regarding premature mortality, impending physical deterioration, and loss of future biological continuity.
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4. Functional Well-Being (FWB)
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Functional Well-Being measures the degree to which an individual remains capable of engaging in meaningful vocational, domestic, recreational, and existential pursuits despite their clinical diagnosis. It reflects the operational realization of quality of life—the ability to translate physical and emotional resources into satisfying life activities. Central facets include:
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- Occupational and Domestic Capacity: Ability to perform work duties, manage household obligations, and maintain a sense of competence.
- Work Fulfillment: Deriving genuine psychological satisfaction and identity reinforcement from one’s occupational or home-based labor.
- Anhedonia vs. Hedonic Capacity: Preserved capacity to experience pleasure, enjoy life, and participate in habitual hobbies or fun activities.
- Illness Integration and Acceptance: Reaching a cognitive-emotional state where the illness is incorporated into one’s life narrative rather than experienced solely as catastrophic fragmentation.
- Sleep Quality and Global Life Contentment: Restorative rest and an overarching cognitive evaluation that one’s current life quality remains acceptable and worthwhile.
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Theoretical Framework
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The development of the FACT-G is anchored in transactional models of stress and coping, biopsychosocial medicine, and contemporary health-related quality of life theory. Three prominent theoretical orientations converge within its architecture:
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1. The Biopsychosocial Model
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Formulated by George L. Engel (1977), the biopsychosocial framework posits that disease manifestations cannot be divorced from their psychological contexts, interpersonal relationships, and socio-environmental dynamics. The FACT-G explicitly rejects narrow biomedical reductionism. By structuring the assessment into physiological (PWB), interpersonal (SWB), intrapsychic (EWB), and occupational/behavioral (FWB) quadrants, the instrument operationalizes Engel’s conceptualization, demonstrating that clinical interventions must be evaluated across all four operational spheres.
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2. Lazarus and Folkman’s Transactional Stress and Coping Theory
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The cognitive appraisal model developed by Richard Lazarus and Susan Folkman (1984) serves as a foundational cognitive framework for the FACT-G. Under this model, a cancer diagnosis represents an acute and chronic external stressor that evokes continuous cognitive appraisals:
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- Primary Appraisal: The patient evaluates the threat level of the disease (e.g., \”I worry about dying,\” \”I worry that my condition will get worse\”).
- Secondary Appraisal: The patient assesses available coping resources, including personal agency, familial support, and social networks (e.g., \”I am satisfied with how I am coping,\” \”I get emotional support from my family\”).
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The items of the FACT-G systematically measure the psychological outcomes of this continuous cognitive transaction, providing clinicians with insight into where coping resources are failing or thriving.
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3. Wilson and Cleary’s Model of Health-Related Quality of Life
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Wilson and Cleary (1995) proposed an integrative conceptual model linking clinical variables to overall quality of life across five hierarchical tiers: (1) biological and physiological variables, (2) symptom status, (3) functional status, (4) general health perceptions, and (5) overall quality of life. The FACT-G operationalizes this continuum seamlessly. It moves from symptom status (nausea, pain, fatigue in PWB), through functional limitations (ability to work, sleep disturbances in FWB), to subjective psychological integration and existential health perceptions (EWB and global contentment). This hierarchical mapping explains why the FACT-G possesses exceptional sensitivity to both biomedical shifts (chemotherapy toxicity) and existential shifts (palliative adaptation).
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Validity
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The psychometric validity of the FACT-G has been substantiated across three decades of international oncological research involving hundreds of thousands of diverse patients across all cancer stages and settings.
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Construct and Structural Validity
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Extensive construct validation during the initial validation studies by Cella et al. (1993) demonstrated that FACT-G scores cleanly differentiated cancer patients across distinct functional strata. When stratified by the Eastern Cooperative Oncology Group (ECOG) Performance Status rating (ranging from 0 = fully active to 4 = completely disabled), mean FACT-G total scores and subscale scores exhibited statistically significant, monotonic declines as functional impairment increased ($p < .001$). Patients with an ECOG rating of 0 demonstrated significantly higher Physical Well-Being and Functional Well-Being scores than those with ECOG ratings of 1, 2, or$\\ge 3$.
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Convergent and Discriminant Validity
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Convergent validity has been established through strong correlations with benchmark instruments evaluating overlapping constructs:
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- Functional Independence: The FACT-G Functional Well-Being and Physical Well-Being subscales correlate strongly ($r = .55$ to $.73$) with the Functional Living Index-Cancer (FLIC) and the Karnofsky Performance Scale (KPS).
- Emotional Distress: The Emotional Well-Being subscale exhibits substantial negative correlations ($r = -.60$ to $-.72$) with the Profile of Mood States (POMS) Total Mood Disturbance score, the Hospital Anxiety and Depression Scale (HADS), and the Beck Depression Inventory (BDI).
- General Health Status: Moderate-to-high correlations ($r = .50$ to $.68$) are routinely observed between the FACT-G total score and the physical and mental component summary scores of the SF-36 Health Survey.
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Discriminant validity is supported by weak correlations ($r < .25$) between FACT-G subscales and theoretically unrelated constructs, such as social desirability indices (e.g., Marlowe-Crowne Social Desirability Scale), confirming that respondent ratings reflect authentic symptomatic and psychological experiences rather than self-presentation biases.
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Predictive and Longitudinal Sensitivity (Responsiveness)
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The FACT-G exhibits exceptional responsiveness to clinically meaningful changes over time. Longitudinal clinical trials have confirmed that declines in FACT-G scores reliably herald disease progression, toxicity escalation, and loss of functional autonomy weeks before conventional radiographic or biomarker detection. Furthermore, multiple large-scale survival analyses have documented that baseline FACT-G scores independently predict overall survival, even after controlling for age, performance status, metastatic stage, and treatment modality. A 5-point to 7-point change in the FACT-G total score is widely recognized as the minimal clinically important difference (MCID), providing clinicians and researchers with an empirical benchmark for determining whether an intervention produces genuine patient-perceived benefit.
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Reliability
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The FACT-G demonstrates high levels of internal consistency, test-retest reproducibility, and inter-rater stability across diverse patient populations and caregiver cohorts.
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Internal Consistency Reliability
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In the foundational validation study by Cella et al. (1993), as well as subsequent confirmatory studies (e.g., Bonomi et al., 1996; Webster et al., 2003), the total FACT-G instrument demonstrated high internal consistency coefficients. Cronbach’s alpha ($\\alpha$) for the overall scale consistently exceeds $.89$, typically ranging from $.89$ to $.91$. Subscale alpha coefficients are similarly robust:
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- Physical Well-Being (PWB): $\\alpha = .82 – .89$ (Patient sample: $.89$; Caregiver sample: $.85$)
- Social/Family Well-Being (SWB): $\\alpha = .69 – .80$ (Patient sample: $.71$; Caregiver sample: $.80$)
- Emotional Well-Being (EWB): $\\alpha = .67 – .74$ (Patient sample: $.71$; Caregiver sample: $.67$)
- Functional Well-Being (FWB): $\\alpha = .80 – .88$ (Patient sample: $.87$; Caregiver sample: $.88$)
- Total FACT-G Score: $\\alpha = .89 – .92$ (Patient sample: $.91$; Caregiver sample: $.91$)
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These values demonstrate that the individual items within each subscale share substantial variance while collectively contributing to a coherent, unified assessment of general quality of life.
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Test-Retest Reliability
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Temporal stability has been established through repeated administrations among clinically stable oncology outpatients. Over test-retest intervals ranging from 3 to 7 days, intraclass correlation coefficients (ICCs) and Pearson correlation coefficients consistently range between $.82$ and $.92$ for the FACT-G total score. Subscale test-retest coefficients demonstrate similar reproducibility: PWB ($r = .88$), SWB ($r = .82$), EWB ($r = .82$), and FWB ($r = .84$). These findings verify that the instrument is resistant to random short-term measurement noise while remaining sensitive to true clinical shifts.
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Factor Analysis
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The structural integrity of the FACT-G has been rigorously examined using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) across diverse patient samples, linguistic translations, and disease stages.
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Exploratory Factor Analysis (EFA)
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During original scale development, principal components analyses with both orthogonal (Varimax) and oblique (Promax) rotations were conducted on the item pool. The analyses converged upon a stable four-factor solution accounting for approximately 56% to 62% of the total variance:
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- Factor 1 (Physical Well-Being): High factor loadings (.58 to .83) for items reflecting somatic toxicity, pain, fatigue, nausea, and forced bedrest.
- Factor 2 (Functional Well-Being): Strong loadings (.52 to .79) for items assessing occupational capacity, life enjoyment, sleep quality, and recreational satisfaction.
- Factor 3 (Social/Family Well-Being): Distinct loadings (.48 to .76) for items evaluating friend support, family communication, emotional closeness, and sexual satisfaction.
- Factor 4 (Emotional Well-Being): Focused loadings (.54 to .77) for items measuring sadness, nervousness, worry about dying, and coping efficacy.
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Confirmatory Factor Analysis (CFA) and Model Fit
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Subsequent large-scale confirmatory factor analytic studies (e.g., Winstead-Fry & Schultz, 1997; Dapueto et al., 2003; Kemmler et al., 2010) evaluated the empirical fit of the hypothesized four-factor model against alternative unidimensional and hierarchical models. The four-factor correlated model consistently demonstrates good-to-excellent goodness-of-fit indices across oncological populations:
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- Comparative Fit Index (CFI): Values typically range between $.92$ and $.96$, exceeding the standard .90 threshold for acceptable model fit.
- Tucker-Lewis Index (TLI): Coefficients regularly span $.91$ to $.95$.
- Root Mean Square Error of Approximation (RMSEA): Estimates consistently fall between $.048$ and $.062$ (with 90% confidence intervals below .070), indicating low residual approximation error.
- Standardized Root Mean Square Residual (SRMR): Values consistently remain below $.055$.
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Second-order hierarchical CFA models have also supported the presence of a single overarching general HRQoL construct that accounts for the moderate intercorrelations among the four primary latent factors ($r = .35$ to $.61$). Modern item response theory (IRT) and Rasch modeling analyses further confirm adequate item calibration, minimal differential item functioning (DIF) across age and gender cohorts, and monotonic item characteristic curves across the 5-point Likert scale.
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Instrument / Measurement Tool
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The FACT-G is structured as a brief, standardized, self-administered questionnaire. When necessary, it can also be administered via structured clinical interview by trained healthcare personnel.
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Instrument Specifications
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- Scale Name: Functional Assessment of Cancer Therapy – General version (FACT-G)
- Target Population: Adult cancer patients undergoing active treatment, post-treatment surveillance, or supportive/palliative care; validated caregiver adaptations are also available for family members.
- Administration Time: Approximately 5 to 8 minutes.
- Recall Period: Past 7 days (\”during the past 7 days\”).
- Total Item Count: 27 items distributed across four subscales:
- Physical Well-Being (PWB): 7 items
- Social/Family Well-Being (SWB): 7 items
- Emotional Well-Being (EWB): 6 items
- Functional Well-Being (FWB): 7 items
- Response Format: 5-point Likert scale scored as follows:
- 0 = Not at all
- 1 = A little bit (A Little)
- 2 = Some-what (Somewhat)
- 3 = Quite a bit
- 4 = Very much
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Scoring Methodology and Rules
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The FACT-G utilizes a straightforward scoring algorithm where higher scores consistently denote superior health-related quality of life. To achieve this, negatively phrased symptom items must be reverse-scored prior to calculating subscale and total scores.
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- Reverse-Scoring: Negatively stated items are reversed by subtracting the respondent’s raw rating from 4 ($4 – \\text{Score}$).\n
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- Physical Well-Being (PWB): All 7 items (GP1 through GP7) are negatively phrased and MUST be reverse-scored.
- Emotional Well-Being (EWB): Items GE1, GE3, GE4, GE5, and GE6 are negatively phrased and MUST be reverse-scored. Item GE2 (\”I am satisfied with how I am coping with my illness\”) is positively phrased and retains its raw score.
- Social/Family Well-Being (SWB) & Functional Well-Being (FWB): All items are positively phrased and retain their raw scores ($0 = 0, \\dots, 4 = 4$).
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- Subscale Score Ranges:\n
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- PWB Subscale Score: 0 to 28 points
- SWB Subscale Score: 0 to 28 points
- EWB Subscale Score: 0 to 24 points
- FWB Subscale Score: 0 to 28 points
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- FACT-G Total Score: Sum of the four subscale scores, ranging from 0 to 108 points.
- Trial Outcome Index (TOI): In clinical trials evaluating physical therapies, researchers frequently calculate the TOI by summing Physical Well-Being and Functional Well-Being subscales (PWB + FWB; range: 0 to 56 points).
- Handling Missing Data: If more than 50% of items within a subscale are missing, that subscale score cannot be calculated. If $\\ge 50\\%$ of items are answered, the subscale score is prorated using the formula: $\\text{Prorated Score} = (\\text{Sum of answered items}) \\times (\\text{Total number of items in subscale}) / (\\text{Number of answered items})$.
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Permissions & Fee and Test Year
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The FACT-G was originally published in 1993 by David F. Cella and colleagues. The instrument, along with its extensive disease-specific subscales and international language translations, is copyrighted by David Cella, Ph.D. and managed internationally by the FACIT Organization (FACIT.org).
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- Original Publication Year: 1993 (Version 4 is the current standard operational version).
- Academic and Non-Profit Research: The FACT-G is generally accessible free of charge for non-commercial academic researchers, unfunded student dissertations, and routine non-profit clinical practice upon registration and agreement with the standard terms of use via FACIT.org.
- Commercial and Funded Clinical Trials: For-profit entities, pharmaceutical corporations, contract research organizations (CROs), and commercially sponsored clinical trials are required to obtain formal licenses and pay user/licensing fees through FACIT.org. Fees support ongoing psychometric validation, professional linguistic translation services, and technical infrastructure.
- Caregiver and Specialized Versions: Specialized adaptations, including family caregiver versions and pediatrics (Peds-FACIT), are subject to the same licensing guidelines through the FACIT governance platform.
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References
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- Bonomi, A. E., Cella, D. F., Hahn, E. A., Webster, K., Hudgens, S., Sarafian, B., … & Silberman, M. (1996). Multilingual translation of the Functional Assessment of Cancer Therapy (FACT) quality of life measurement system. Quality of Life Research, 5(3), 309-320. https://doi.org/10.1007/BF00433915
- Caldwell, S. M. (2003). The Family Well-Being Assessment Tool. In O. L. Strickland & C. Dilorio (Eds.), Measurement of nursing outcomes (2nd ed., pp. 75-88). Springer Publishing Company.
- Cella, D. F., Tulsky, D. S., Gray, G., Sarafian, B., Linn, E., Bonomi, A., Silberman, M., Yellen, S. B., Winicour, P., & Brannon, J. (1993). The Functional Assessment of Cancer Therapy scale: Development and validation of the general measure. Journal of Clinical Oncology, 11(3), 570-579. https://doi.org/10.1200/JCO.1993.11.3.570
- Dapueto, J. J., Francolino, C., Servente, L., Chang, C. H., & Cella, D. (2003). Evaluation of the Functional Assessment of Cancer Therapy-General (FACT-G) Spanish version in Uruguayan cancer patients. Quality of Life Research, 12(8), 1107-1112. https://doi.org/10.1023/A:1026139626359
- Engel, G. L. (1977). The need for a new medical model: A challenge for biomedicine. Science, 196(4286), 129-136. https://doi.org/10.1126/science.847460
- Kemmler, G., Holzner, B., Kopp, M., Dünser, M., Margreiter, R., Greil, R., & Sperner-Unterweger, B. (2010). Comparison of two quality of life instruments for cancer patients: The Functional Assessment of Cancer Therapy-General and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30. Journal of Clinical Oncology, 17(9), 2932-2940. https://doi.org/10.1200/JCO.1999.17.9.2932
- Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer Publishing Company.
- McDonald, G. W. (1979). Family well-being and quality of life: Humanistic concerns of the family impact analyst. The Family Coordinator, 28(3), 313-320. https://doi.org/10.2307/581944
- Webster, K., Odom, L., Peterman, A., Lent, L., & Cella, D. (1999). The Functional Assessment of Chronic Illness Therapy (FACIT) measurement system: Validation of version 4 of the Functional Assessment of Cancer Therapy-General (FACT-G) in a clinically diverse sample. Quality of Life Research, 8(7), 604.
- Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life: A conceptual model of patient outcomes. JAMA, 273(1), 59-65. https://doi.org/10.1001/jama.1995.03520250075037
- Winstead-Fry, P., & Schultz, P. R. (1997). Psychometric assessment of the Functional Assessment of Cancer Therapy-General in a rural oncology sample. Cancer Nursing, 20(4), 246-252. https://doi.org/10.1097/00002820-199708000-00002
- Wisawatapnimit, P. (2009). Assessment of family quality of life among families with a member who has cancer (Doctoral dissertation). Vanderbilt University, Nashville, TN.
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