Chronic Pain and Pain Management in Older Adults: Protocol and Pilot Results

Background Chronic pain occurs in 30% of older adults. This prevalence rate is expected to increase, given the growth in the older adult population and the associated growth of chronic conditions contributing to pain. No population-based studies have provided detailed, longitudinal information on the experience of chronic pain in older adults; the pharmacological and nonpharmacological strategies that older adults use to manage their chronic pain; and the effect of chronic pain on patient-reported outcomes. Objectives This article aims to describe the protocol for a population-based, longitudinal study focused on understanding the experience of chronic pain in older adults. The objectives are to determine the prevalence and characteristics of chronic pain; identify the pharmacological and nonpharmacological pain treatments used; evaluate for longitudinal differences in biopsychosocial factors; and examine how pain types and pain trajectories affect important patient-reported outcomes. Also included are the results of a pilot study. Methods A population-based sample of approximately 1,888 older adults will be recruited from the National Opinion Research Center at the University of Chicago’s AmeriSpeak Panel to complete surveys at three waves: enrollment (Wave 1), 6 months (Wave 2), and 12 months (Wave 3). To determine the feasibility, a pilot test of the enrollment survey was conducted among 123 older adults. Results In the pilot study, older adults with chronic pain reported a range of pain conditions, with osteoarthritis being the most common. Participants reported an array of pharmacological and nonpharmacological pain strategies. Compared to participants without chronic pain, those with chronic pain reported lower physical and cognitive function and poorer quality of life. Data collection for the primary, longitudinal study is ongoing. Discussion This project will be the first longitudinal population-based study to examine the experience and overall effect of chronic pain in older adults. Pilot study results provide evidence of the feasibility of study methods. Ultimately, this work will inform the development of tailored interventions for older patients targeted to decrease pain and improve function and quality of life.

Methodology for Analyzing Qualitative Data in Multiple Languages

Background Translation strategies are commonly used for qualitative interview data to bridge language barriers. Inconsistent translation of interviews can lead to conceptual inequivalence, where meanings of participants' experiences are distorted, threatening scientific rigor. Objectives Our objective is to describe a systematic method developed to analyze multilingual, qualitative interview data while maintaining the original language of the transcripts. Methods A literature review of translation strategies, cross-language, and multilingual qualitative research was conducted. Combined with criteria for qualitative content analysis and trustworthiness, the methodology was developed and used for a qualitative descriptive study. Results The study had interview data in both English and Spanish. The research team consisted of both native Spanish and English speakers, who were grouped based on language. Verbatim transcription of data occurred in the original languages. All codes were kept in English, allowing the research team to view the data set as a whole. Two researchers within each group coded each transcript independently before reaching a consensus. The entire research team discussed all transcripts, and finally, major themes were determined. Participants' quotes remained in the original language for publication, with an English translation included when needed. Discussion Analyzing transcripts in the original language brought forth cultural themes that otherwise may have been overlooked. This methodology promotes conceptual equivalence and trustworthiness that is paramount in cultural, linguistic, and social determinants of health research to advance health equity.

An Evaluation of the Multifactorial Model of Cancer-Related Cognitive Impairment

Background Up to 45% of patients report cancer-related cognitive impairment (CRCI). A variety of characteristics are associated with the occurrence and/or severity of CRCI. However, an important gap in knowledge of risk factors for CRCI is the relative contribution of each factor. The multifactorial model of cancer-related cognitive impairment (MMCRCI) is a conceptual model of CRCI that can be used to evaluate the strength of relationships between various factors and CRCI. Objectives The purpose of this study was to use structural regression methods to evaluate the MMCRCI using data from a large sample of outpatients receiving chemotherapy (n = 1,343). Specifically, the relationships between self-reported CRCI and four MMCRCI concepts (i.e., social determinants of health, patient-specific factors, treatment factors, and co-occurring symptoms) were examined. The goals were to determine how well the four concepts predicted CRCI and determine the relative contribution of each concept to deficits in perceived cognitive function. Methods This study is part of a larger, longitudinal study that evaluated the symptom experience of oncology outpatients receiving chemotherapy. Adult patients were diagnosed with breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding 4 weeks; were scheduled to receive at least two additional cycles of chemotherapy; were able to read, write, and understand English; and gave written informed consent. Self-reported CRCI was assessed using the attentional function index. Available study data were used to define the latent variables. Results On average, patients were 57 years of age, college educated, and with a mean Karnofsky Performance Status score of 80. Of the four concepts evaluated, whereas co-occurring symptoms explained the largest amount of variance in CRCI, treatment factors explained the smallest amount of variance. A simultaneous structural regression model that estimated the joint effect of the four exogenous latent variables on the CRCI latent variable was not significant. Discussion These findings suggest that testing individual components of the MMCRCI may provide useful information on the relationships among various risk factors, as well as refinements of the model. In terms of risk factors for CRCI, co-occurring symptoms may be more significant than treatment factors, patient-specific factors, and/or social determinants of health in patients receiving chemotherapy.