Based on scientific literature and interviews with clinicians and patients, we developed a quality of life instrument for use with people with MS called the Functional Assessment of Multiple Sclerosis (FAMS). The initial item pool consisted of 88 questions: 28 from the general version of the Functional Assessment of Cancer Therapy quality of life instrument, plus 60 generated by patients, providers, and literature review. The validation samples comprised a mail survey cohort (N = 377) and a clinical cohort (N = 56). Both cohorts provides evidence for internal consistency of the derived subscales, test-retest reliability, content validity, concurrent validity, and construct validity. Principal components and Rasch measurement model analyses were applied sequentially to survey sample data, reducing test length to 44 questions, divided into six subscales: mobility, symptoms, emotional well-being (depression), general contentment, thinking/fatigue, and family/social well-being. Fifteen initially rejected questions were added back as miscellaneous (unscored) questions for their potential clinical and empirical value. The mobility subscale was strongly predictive of the Kurtzke Extended Disability Status Scale and the Scripps Neurologic Rating Scales. The other five subscales were not, indicating they measure aspects of patient quality of life not captured by the neurologic exam. The final 59-item English language instrument (FAMS version 2) is available for inclusion in clinical trials and clinical practice.

Relatively small gains in HRQL have significant value. Comparable declines may be less meaningful, perhaps due to patients' tendency to minimize personal negative evaluations about one's condition. This has important implications for the interpretation of the meaningfulness of change scores in HRQL questionnaires. Factors such as adaptation to disease, response shift, dispositional optimism and the need for signs of clinical improvement may be contributing to the results and should be investigated in future studies.

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From the farms to the packing plants, essential workers in critical food production industries keep food on our tables while risking their and their families' health and well-being to bring home a paycheck. They work in essential industries but are often invisible. The disparities illuminated by COVID-19 are not new. Instead, they are the result of years of inequities built into practices, policies, and systems that reinforce societal power structures. As a society, we are now at an antagonizing moment where we can change our collective trajectory to focus forward and promote equity and justice for workers in agriculture and food-related industries. To that end, we describe our experience and approach in addressing COVID-19 outbreaks in meat processing facilities, which included three pillars of action based on public health ethics and international human rights: (1) worksite prevention and control, (2) community-based prevention and control, and (3) treatment. Our approach can be translated to promote the health, safety, and well-being of the broader agricultural workforce.

Use of the CMDI to assess separate dimensions of depression may help to clarify the complex interrelationships among aspects of depression and health-related behavior.

Prescription opioids are an important tool for physicians in treating pain but also carry significant risks of harm when prescribed inappropriately or misused by patients or others. Recent increases in opioid related morbidity and mortality has reignited scrutiny of prescribing practices by law enforcement, regulatory agencies, and state medical boards. At the same time, the predominant 4D model of misprescribers is outdated and insufficient; it groups physician misprescribers as dated, duped, disabled, or dishonest. The weaknesses and inaccuracies of the 4D model are explored, along with the serious consequences of its application. This article calls for development of an evidence base in this area and suggests an alternate model of misprescribers, the 3C model, which more accurately characterizes misprescribers as careless, corrupt, or compromised by impairment.

Cancer-related pain is often under-recognized and undertreated. This is partly due to the lack of appropriate assessments, which need to be comprehensive and precise yet easily integrated into clinics. Computerized adaptive testing (CAT) can enable precise-yet-brief assessments by only selecting the most informative items from a calibrated item bank. The purpose of this study was to create such a bank. The sample included 400 cancer patients who were asked to complete 61 pain-related items. Data were analyzed using factor analysis and the Rasch model. The final bank consisted of 43 items which satisfied the measurement requirement of factor analysis and the Rasch model, demonstrated high internal consistency and reasonable item-total correlations, and discriminated patients with differing degrees of pain. We conclude that this bank demonstrates good psychometric properties, is sensitive to pain reported by patients, and can be used as the foundation for a CAT pain-testing platform for use in clinical practice.

Identifying health-related quality of life concerns is a priority when caring for people with cancer. Specific problem areas such as pain, fatigue, emotional distress, disease- and treatment-related symptoms, as well as physical functioning can be routinely assessed using applications that draw upon item response theory. Item response theory measurement models can improve on the classical approach to health-related quality of life assessment with advantages that include comparison of patients across diverse instruments, flexibility in degree of precision desired, availability of multiple short forms, interval measurement and capability for individual assessment (real-time clinical monitoring) using computerized adaptive testing. This review describes a model of health-related quality of life in oncology and the contribution of item response theory to assessment using that model.