An Item Bank for Abuse of Prescription Pain Medication from the Patient-Reported Outcomes Measurement Information System (PROMIS®).

OBJECTIVE: There is a need to monitor patients receiving prescription opioids to detect possible signs of abuse. To address this need, we developed and calibrated an item bank for severity of abuse of prescription pain medication as part of the Patient-Reported Outcomes Measurement Information System (PROMIS ® ). METHODS: Comprehensive literature searches yielded an initial bank of 5,310 items relevant to substance use and abuse, including abuse of prescription pain medication, from over 80 unique instruments. After qualitative item analysis (i.e., focus groups, cognitive interviewing, expert review, and item revision), 25 items for abuse of prescribed pain medication were included in field testing. Items were written in a first-person, past-tense format, with a three-month time frame and five response options reflecting frequency or severity. The calibration sample included 448 respondents, 367 from the general population (ascertained through an internet panel) and 81 from community treatment programs participating in the National Drug Abuse Treatment Clinical Trials Network. RESULTS: A final bank of 22 items was calibrated using the two-parameter graded response model from item response theory. A seven-item static short form was also developed. The test information curve showed that the PROMIS ® item bank for abuse of prescription pain medication provided substantial information in a broad range of severity. CONCLUSION: The initial psychometric characteristics of the item bank support its use as a computerized adaptive test or short form, with either version providing a brief, precise, and efficient measure relevant to both clinical and community samples.

The Key to Individualized Addiction Treatment is Comprehensive Assessment and Monitoring of Symptoms and Behavioral Change.

Modern health services now strive for individualized treatment. This approach has been enabled by the increase in knowledge derived from neuroscience and genomics. Substance use disorders are no exception to individualized treatment even though there are no gene-specific medications yet available. What is available is the ability to quickly and precisely assess and monitor biopsychosocial variables known to vary during addiction recovery and which place addicts at increased risk of relapse. Monitoring a broad spectrum of biopsychosocial health enables providers to address diverse genome-specific changes that might trigger withdrawal from treatment or recovery relapse in time to prevent that from occurring. This paper describes modern measurement tools contained in the NIH Patient-Reported Outcomes Measurement Information System (PROMIS) and the NIH Toolbox and suggests how they might be applied to support recovery from alcohol and other substance use disorders in both pharmacological and abstinence-oriented modalities of care.

Item banks for substance use from the Patient-Reported Outcomes Measurement Information System (PROMIS(®)): Severity of use and positive appeal of use.

BACKGROUND: Two item banks for substance use were developed as part of the Patient-Reported Outcomes Measurement Information System (PROMIS(®)): severity of substance use and positive appeal of substance use. METHODS: Qualitative item analysis (including focus groups, cognitive interviewing, expert review, and item revision) reduced an initial pool of more than 5300 items for substance use to 119 items included in field testing. Items were written in a first-person, past-tense format, with 5 response options reflecting frequency or severity. Both 30-day and 3-month time frames were tested. The calibration sample of 1336 respondents included 875 individuals from the general population (ascertained through an internet panel) and 461 patients from addiction treatment centers participating in the National Drug Abuse Treatment Clinical Trials Network. RESULTS: Final banks of 37 and 18 items were calibrated for severity of substance use and positive appeal of substance use, respectively, using the two-parameter graded response model from item response theory (IRT). Initial calibrations were similar for the 30-day and 3-month time frames, and final calibrations used data combined across the time frames, making the items applicable with either interval. Seven-item static short forms were also developed from each item bank. CONCLUSIONS: Test information curves showed that the PROMIS item banks provided substantial information in a broad range of severity, making them suitable for treatment, observational, and epidemiological research in both clinical and community settings.

The promise of PROMIS(®) for addiction.

The field of addiction treatment has a measurement problem that pervades efforts to help patients achieve self-sustainable recovery. The impact of using older measurement technology has increased the measurement burden on both service providers and patients, while at the same time limiting the scope and frequency of measurement. The resulting burden can affect provider performance, patient access, and addiction recovery. This paper underscores the need for applying modern measurement theory techniques to reduce the measurement burden currently affecting most if not all major aspects of treatment and recovery. It is currently possible to obtain information more precisely, over a broad spectrum of recovery-oriented domains, faster and at lower cost than current measurement practices allow. However, a persistent research effort will be necessary to achieve that goal.

What's next for translation research?

The National Institutes of Health (NIH) are under increasing pressure to identify practical, cost-effective interventions, therapies, and medications. Overall, the public health impact could be substantial if effective science-based prevention and treatment programs were implemented on large scales with sufficient fidelity. Yet penetration of even the most successful interventions rarely occurs at a quick pace. Research-to-practice gaps are pervasive throughout various fields of behavioral health and safety. In this article the authors explore factors contributing to the pace of translation and reaffirm that research advances or retreats the progress of scientific discovery as data accumulate in what can be described as a translational research loop that is iterative and bidirectional. They also touch on the challenges inherent in deploying science to the marketplace, and in an attempt to foreshadow what's next for translational efforts, they conclude by offering some ideas about how researchers might more accurately conceptualize "best practices."

Staff members are human subjects, too.

Top management, clinical supervisors, secretaries, government administrators, counselors, and patients are all examples of informants and agents used by health services researchers as they strive to learn how organizational and managerial factors affect the effectiveness, efficiency, quality, and the cost of substance abuse treatment and prevention services. Patients are clearly a vulnerable population, and researchers in clinical settings, as a rule, strive to protect patient safety and rights to privacy. However, as researchers begin to expand the scope of their study to the organizational contexts in which services are delivered, those responsible for providing services (staff members) are frequently enlisted to serve both as informants on policies and practices, and as participants acting as agents of the researchers in innovating therapeutic and business practices. Researchers need to be mindful that staff members, when acting as informants or as agents, are human subjects, too; and, as such, research procedures should be designed in a manner that minimizes their risk and conforms to sound ethical guidelines. In the interest of stimulating dialogue on ways to protect staff members from unintended harm, this essay overviews human subjects protection policy, describes examples of risks, and offers suggestions for preventing harm when designing studies.