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BackgroundThe COVID-19 pandemic spurred publication of a rapid proliferation of studies on potential therapeutic agents. While important for the advancement of clinical care, pressure to collect, analyze, and report data in an expedited manner could potentially increase the rate of important errors, some of which would be captured in published errata. We hypothesized that COVID-19 therapeutic studies published in the early years of the pandemic would be associated with a high rate of published errata and that, within these errata, there would be a high prevalence of serious errors.MethodsWe performed a review of published errata associated with empirical studies of COVID-19 treatments. Errata were identified via a MEDLINE and Embase search spanning January 2020 through September 2022. Errors located within each published erratum were characterized by location within publication, error type, and error seriousness.ResultsOf 47 studies on COVID-19 treatments with published errata, 18 met inclusion criteria. Median time from publication of the original article to publication of the associated erratum was 76 days (range, 12-511 days). A majority of errata addressed issues with author attribution or conflict of interest disclosures (39.5%) or numerical results (25.6%). Only one erratum contained a serious error: a typographical error which could have misled readers into believing that the treatment in question had serious adverse effects when in fact it did not.ConclusionsDespite accelerated publication times, we found among studies of COVID-19 treatments the majority of errata (17/18) reported minor errors that did not lead to misinterpretation of the study results. Retractions, an indicator of scientific misdirection even more concerning than errata, were beyond the scope of this review.

In recent years, there has been increasing discussion of the limitations of traditional randomized controlled trial (RCT) methodologies for the evaluation of eHealth and mHealth interventions, and in particular, the requirement that these interventions be locked down during evaluation. Locking down these interventions locks in defects and eliminates the opportunities for quality improvement and adaptation to the changing technological environment, often leading to validation of tools that are outdated by the time that trial results are published. Furthermore, because behavioral intervention technologies change frequently during real-world deployment, even if a tested intervention were deployed in the real world, its shelf life would be limited. We argue that RCTs will have greater scientific and public health value if they focus on the evaluation of intervention principles (rather than a specific locked-down version of the intervention), allowing for ongoing quality improvement modifications to the behavioral intervention technology based on the core intervention principles, while continuously improving the functionality and maintaining technological currency. This paper is an initial proposal of a framework and methodology for the conduct of trials of intervention principles (TIPs) aimed at minimizing the risks of in-trial changes to intervention technologies and maximizing the potential for knowledge acquisition. The focus on evaluation of intervention principles using clinical and usage outcomes has the potential to provide more generalizable and durable information than trials focused on a single intervention technology.

Many preventive trials randomize individuals to intervention condition which is then delivered in a group setting. Other trials randomize higher levels, say organizations, and then use learning collaboratives comprised of multiple organizations to support improved implementation or sustainment. Other trials randomize or expand existing social networks and use key opinion leaders to deliver interventions through these networks. We use the term contextually driven to refer generally to such trials (traditionally referred to as clustering, where groups are formed either pre-randomization or post-randomization - i.e., a cluster-randomized trial), as these groupings or networks provide fixed or time-varying contexts that matter both theoretically and practically in the delivery of interventions. While such contextually driven trials can provide efficient and effective ways to deliver and evaluate prevention programs, they all require analytical procedures that take appropriate account of non-independence, something not always appreciated. Published analyses of many prevention trials have failed to take this into account. We discuss different types of contextually driven designs and then show that even small amounts of non-independence can inflate actual Type I error rates. This inflation leads to rejecting the null hypotheses too often, and erroneously leading us to conclude that there are significant differences between interventions when they do not exist. We describe a procedure to account for non-independence in the important case of a two-arm trial that randomizes units of individuals or organizations in both arms and then provides the active treatment in one arm through groups formed after assignment. We provide sample code in multiple programming languages to guide the analyst, distinguish diverse contextually driven designs, and summarize implications for multiple audiences.

The term data science usually refers to the process of extracting value from big data obtained from a large group of individuals. An alternative rendition, which we call personalized data science (Per-DS), aims to collect, analyze, and interpret personal data to inform personal decisions. This article describes the main features of Per-DS, and reviews its current state and future outlook. A Per-DS investigation is of, by, and for an individual, the Per-DS investigator, acting simultaneously as her own investigator, study participant, and beneficiary, and making personalized decisions for study design and implementation. The scope of Per-DS studies may include systematic monitoring of physiological or behavioral patterns, case-crossover studies for symptom triggers, pre-post trials for exposure-outcome relationships, and personalized (N-of-1) trials for effectiveness. Per-DS studies produce personal knowledge generalizable to the individuals future self (thus benefiting herself) rather than knowledge generalizable to an external population (thus benefiting others). This endeavor requires a pivot from data mining or extraction to data gardening, analogous to home gardeners producing food for home consumption-the Per-DS investigator needs to cultivate the field by setting goals, specifying study design, identifying necessary data elements, and assembling instruments and tools for data collection. Then, she can implement the study protocol, harvest her personal data, and mine the data to extract personal knowledge. To facilitate Per-DS studies, Per-DS investigators need support from community-based, scientific, philanthropic, business, and government entities, to develop and deploy resources such as peer forums, mobile apps, virtual field guides, and scientific and regulatory guidance.

The mainstay of evidence development in medicine is the parallel-group randomized controlled trial (RCT), which generates estimates of treatment efficacy or effectiveness for the average person in the trial. In contrast, personalized trials (sometimes referred to as 'single-person trials' or 'N-of-1 trials') assess the comparative effectiveness of two or more treatments in a single individual. These single-subject, randomized crossover trials have been used in a scattershot fashion in medicine for over 40 years but have not been widely adopted. An important barrier is the paucity of strong evidence that personalized trials improve outcomes. However, the principal impediment may have less to do with proof of efficacy than with practical aspects of design and implementation. These include decisions about treatment regimen flexibility, blinding, and washout periods as well as organizational, clinician, and patient-level challenges. After reviewing the essential elements of personalized trials, this article addresses these speed bumps and fundamentally asks, 'Why have personalized trials not been more widely adopted, and how can they be made more readily deployable and useful?' The article concludes by suggesting ways in which emerging technologies and approaches promise to overcome existing barriers and open promising vistas for the next generation of personalized-trial researchers and practitioners.

ObjectivesOpioids and non-steroidal anti-inflammatory drugs (NSAIDs) are frequently prescribed for chronic musculoskeletal pain, despite limited evidence of effectiveness and well-documented adverse effects. We assessed the effects of participating in a structured, personalized self-experiment ("N-of-1 trial") on analgesic prescribing in patients with chronic musculoskeletal pain.MethodsWe randomized 215 patients with chronic pain to participate in an N-of-1 trial facilitated by a mobile health app or to receive usual care. Medical records of participating patients were reviewed at enrollment and 6 months later to assess analgesic prescribing. We established thresholds of ≥ 50, ≥ 20, and > 0 morphine milligram equivalents (MMEs) per day to capture patients taking relatively high doses only, patients taking low-moderate as well as relatively high doses, and patients taking any dose of opioids, respectively.ResultsThere was no significant difference between the N-of-1 and control groups in the percentage of patients prescribed any opioids (relative odds ratio (ROR) = 1.05; 95% confidence interval [CI] = 0.61 to 1.80, p = 0.87). There was a clinically substantial but statistically not significant reduction of the percentage of patients receiving ≥ 20 MME (ROR = 0.58; 95% CI = 0.33 to 1.04, p = 0.07) and also in the percentage receiving ≥ 50 MME (ROR = 0.50; 95% CI = 0.19 to 1.34, p = 0.17). There was a significant reduction in the proportion of patients in the N-of-1 group prescribed NSAIDs compared with control (relative odds ratio = 0.53; 95% CI = 0.29 to 0.96, p = 0.04), with no concomitant increase in average pain intensity. There was no significant change in use of adjunctive medications (acetaminophen, gabapentenoids, or topicals).DiscussionThese exploratory results suggest that participation in N-of-1 trials may reduce long-term use of NSAIDs; there is also a weak signal for an effect on use of opioids. Additional research is needed to confirm these results and elucidate possible mechanisms.Trial registrationClinicalTrials.gov Identifier: NCT02116621.

OBJECTIVE:Despite their promise for increasing treatment precision, Personalized Trials (i.e., N-of-1 trials) have not been widely adopted. We aimed to ascertain patient preferences for Personalized Trials. STUDY DESIGN AND SETTING:We recruited 501 adults with ≥2 common chronic conditions from Harris Poll Online. We used Sawtooth Software to generate 45 plausible Personalized Trial designs comprising combinations of eight key attributes (treatment selection, treatment type, clinician involvement, blinding, time commitment, self-monitoring frequency, duration, and cost) at different levels. Conditional logistic regression was used to assess relative importance of different attributes using a random utility maximization model. RESULTS:Overall, participants preferred Personalized Trials with no costs vs. $100 cost (utility difference 1.52 [standard error 0.07], P

ImportanceIndividually designed single-patient multi-crossover (n-of-1) trials can facilitate tailoring of treatments directed at various conditions, including chronic musculoskeletal pain (CMSP) but are potentially burdensome, which may limit uptake in research and practice.ObjectivesTo determine whether patients randomized to participate in an n-of-1 trial supported by a mobile health (mHealth) app would experience less pain and improved global health, adherence, satisfaction, and shared decision making compared with patients assigned to usual care.Design, setting, and participantsThis randomized clinical trial compared participation in an individualized, mHealth-supported n-of-1 trial vs usual care. The participating 215 patients had CMSP for at least 6 weeks, had a smartphone or tablet with a data plan, were enrolled in northern California from July 2014 through July 2016, and were followed for up to 1 year by 48 clinicians in academic, community, Veterans Affairs, and military settings.InterventionsIntervention patients met with their clinicians and used a desktop interface to select treatments and trial parameters for an n-of-1 trial comparing 2 pain-management regimens. The mHealth app provided reminders to take designated treatments on assigned days and to upload responses to daily questions on pain and treatment-associated adverse effects. Control patients received care as usual.Main outcomes and measuresThe primary outcome was change in the PROMIS (Patient-Reported Outcomes Measurement Information System) pain-related interference 8-item short-form scale (full scale range, 41-78) from baseline to 6 months. Secondary outcomes included patient-reported pain intensity, overall health, analgesic adherence, trust in clinician, satisfaction with care, medication-related shared decision making, and, for the n-of-1 group only, participant engagement and experience.ResultsAmong 215 patients (108 randomized to the n-of-1 intervention and 107 to control), 102 (47%) were women, and the mean (SD) age was 55.5 (11.1) years. At the 6-month follow-up, pain interference was reduced in both groups, though there was no difference between the intervention and control groups (-1.36 points; 95% CI, -2.91 to 0.19 points; P = .09). There were no advantages in secondary outcomes for intervention patients vs control patients except for higher medication-related shared decision making at 6 months (between-group difference, 11.9 points; 95% CI, 2.6-21.2 points; P = .01). Among patients assigned to the n-of-1 group, 88% (n = 86) affirmed that the mHealth app could help people like them manage their pain.Conclusions and relevanceIn this population of patients with CMSP, mHealth-supported n-of-1 trials were feasible and associated with a satisfactory user experience, but n-of-1 trial participation did not significantly improve pain interference at 6 months vs usual care.Trial registrationClinicalTrials.gov identifier: NCT02116621.

ObjectivesMaladaptive cognitions related to loss are thought to contribute to development of complicated grief and are crucial to address in treatment, but tools available to assess them are limited. This paper introduces the Typical Beliefs Questionnaire (TBQ), a 25-item self-report instrument to assess cognitions that interfere with adaptation to loss.DesignStudy participants completed an assessment battery during their initial evaluation and again after completing treatment at 20 weeks. Test-retest reliability was assessed on a subsample of the participants who did not show change in complicated grief severity after the first 4 weeks of treatment. To examine latent structure of the TBQ, an exploratory factor analysis (EFA) was performed.SettingAcademic medical centers in Boston, New York, Pittsburgh, and San Diego from 2010-2014.Participants394 bereaved adults who met criteria for complicated grief.MeasurementsThe TBQ along with assessments of complicated grief symptoms and related avoidance, depression symptoms, functional impairment, and perceived social support.ResultsThe TBQ exhibited good internal consistency (α = 0.82) and test-retest reliability (N = 105; intraclass correlation coefficient = 0.74). EFA indicated a five-factor structure: "Protesting the Death," "Negative Thoughts About the World," "Needing the Person," "Less Grief is Wrong" and "Grieving Too Much." The total score and all factors showed sensitivity to change with treatment.ConclusionsThis new tool allows a clinician to quickly and reliably ascertain presence of specific maladaptive cognitions related to complicated grief, and subsequently, to use the information to aid a diagnostic assessment, to structure the treatment, and to measure treatment outcomes.

BackgroundWhen subgroup analyses are not correctly analyzed and reported, incorrect conclusions may be drawn, and inappropriate treatments provided. Despite the increased recognition of the importance of subgroup analysis, little information exists regarding the prevalence, appropriateness, and study characteristics that influence subgroup analysis. The objective of this study is to determine (1) if the use of subgroup analyses and multivariable risk indices has increased, (2) whether statistical methodology has improved over time, and (3) which study characteristics predict subgroup analysis.MethodsWe randomly selected randomized controlled trials (RCTs) from five high-impact general medical journals during three time periods. Data from these articles were abstracted in duplicate using standard forms and a standard protocol. Subgroup analysis was defined as reporting any subgroup effect. Appropriate methods for subgroup analysis included a formal test for heterogeneity or interaction across treatment-by-covariate groups. We used logistic regression to determine the variables significantly associated with any subgroup analysis or, among RCTs reporting subgroup analyses, using appropriate methodology.ResultsThe final sample of 416 articles reported 437 RCTs, of which 270 (62 %) reported subgroup analysis. Among these, 185 (69 %) used appropriate methods to conduct such analyses. Subgroup analysis was reported in 62, 55, and 67 % of the articles from 2007, 2010, and 2013, respectively. The percentage using appropriate methods decreased over the three time points from 77 % in 2007 to 63 % in 2013 (p

ObjectivesTo evaluate the quality of reporting of single-patient (N-of-1) trials published in the medical literature based on the CONSORT Extension for N-of-1 Trials (CENT) statement and to examine factors that influence reporting quality in these trials.Study design and settingThrough a search of 10 electronic databases, we identified N-of-1 trials in clinical medicine published between January 1, 1985, and December 31, 2013. Two reviewers screened articles for eligibility and independently extracted data. Quality assessment was performed using the CENT statement. Discrepancies were resolved by consensus.ResultsWe identified 112 eligible N-of-1 trials published in 87 journals and involving a total of 2,278 patients. Overall, kappa agreement between the two evaluators for compliance with CENT criteria was 0.80 (95% confidence interval: 0.79, 0.82). Trials assessed pharmacology and therapeutics (87%), behavior (11%), or diagnosis (2%). Although 87% of articles described the trial design (including the planned number of subjects and length of treatment period), the median percentage of specific CENT elements reported in the Methods was 41% (range, 16-87%), and the median percentage in the Results was 38% (range, 32-93%). First authors were predominantly from North America (46%), Europe (29%), and Australia (17%). Quality of reporting was higher in articles published in journals with relatively high-impact factors (P = 0.004).ConclusionThe quality of reporting of published N-of-1 trials is variable and in need of improvement. Because the CENT guidelines were not published until near the end of the period of this review, these results represent a baseline from which improvement may be expected in the future.

ImportanceTo our knowledge, this is the first placebo-controlled randomized clinical trial to evaluate the efficacy of antidepressant pharmacotherapy, with and without complicated grief psychotherapy, in the treatment of complicated grief.ObjectiveTo confirm the efficacy of a targeted complicated grief treatment (CGT), determine whether citalopram (CIT) enhances CGT outcome, and examine CIT efficacy without CGT.Design, setting, and participantsIncluded in the study were 395 bereaved adults who met criteria for CG recruited from March 2010 to September 2014 from academic medical centers in Boston, Massachusetts; New York, New York; Pittsburgh, Pennsylvania; and San Diego, California. Co-occurring substance abuse, psychosis, mania, and cognitive impairment were exclusionary. Study participants were randomized using site-specific permuted blocks stratified by major depression into groups prescribed CIT (n = 101), placebo (PLA; n = 99), CGT with CIT (n = 99), and CGT with PLA (n = 96). Independent evaluators conducted monthly assessments for 20 weeks. Response rates were compared under the intention-to-treat principle, including all randomized participants in a logistic regression with inverse probability weighting.InterventionsAll participants received protocolized pharmacotherapy optimized by flexible dosing, psychoeducation, grief monitoring, and encouragement to engage in activities. Half were also randomized to receive manualized CGT in 16 concurrent weekly sessions.Main outcomes and measuresComplicated grief-anchored Clinical Global Impression scale measurments every 4 weeks. Response was measured as a rating of "much improved" or "very much improved."ResultsOf the 395 study participants, 308 (78.0%) were female and 325 (82.3%) were white. Participants' response to CGT with PLA vs PLA (82.5% vs 54.8%; relative risk [RR], 1.51; 95% CI, 1.16-1.95; P = .002; number needed to treat [NNT], 3.6) suggested the efficacy of CGT, and the addition of CIT did not significantly improve CGT outcome (CGT with CIT vs CGT with PLA: 83.7% vs 82.5%; RR, 1.01; 95% CI, 0.88-1.17; P = .84; NNT, 84). However, depressive symptoms decreased significantly more when CIT was added to treatment (CGT with CIT vs CGT with PLA: model-based adjusted mean [standard error] difference, -2.06 [1.00]; 95% CI, -4.02 to -0.11; P = .04). By contrast, adding CGT improved CIT outcome (CIT vs CGT with CIT: 69.3% vs 83.7%; RR, 1.21; 95% CI, 1.00-1.46; P = .05; NNT, 6.9). Last, participant response to CIT was not significantly different from PLA at week 12 (45.9% vs 37.9%; RR, 1.21; 95% CI, 0.82-1.81; P = .35; NNT, 12.4) or at week 20 (69.3% vs 54.8%; RR, 1.26; 95% CI, 0.95-1.68; P = .11; NNT, 6.9). Rates of suicidal ideation diminished to a substantially greater extent among participants receiving CGT than among those who did not.Conclusions and relevanceComplicated grief treatment is the treatment of choice for CG, and the addition of CIT optimizes the treatment of co-occurring depressive symptoms.Trial registrationclinicaltrials.gov Identifier: NCT01179568.

Integrating two distinct and complementary paradigms, science and engineering, may produce more effective outcomes for the implementation of evidence-based practices in health care settings. Science formalizes and tests innovations, whereas engineering customizes and optimizes how the innovation is applied tailoring to accommodate local conditions. Together they may accelerate the creation of an evidence-based healthcare system that works effectively in specific health care settings. We give examples of applying engineering methods for better quality, more efficient, and safer implementation of clinical practices, medical devices, and health services systems. A specific example was applying systems engineering design that orchestrated people, process, data, decision-making, and communication through a technology application to implement evidence-based depression care among low-income patients with diabetes. We recommend that leading journals recognize the fundamental role of engineering in implementation research, to improve understanding of design elements that create a better fit between program elements and local context.

BackgroundComplicated grief (CG) has been recently included in the DSM-5, under the term "persistent complex bereavement disorder," as a condition requiring further study. To our knowledge, no psychometric data on any structured clinical interview for CG (SCI-CG) is available to date. In this manuscript, we introduce the SCI-CG, a 31-item "SCID-like" clinician-administered instrument to assess the presence of CG symptoms.MethodsParticipants were 281 treatment-seeking adults with CG (77.9% [n = 219] women, mean age = 52.4, standard deviation [SD] = 17.8) who were assessed with the SCI-CG and measures of depression, posttraumatic stress, anxiety, functional impairment.ResultsThe SCI-CG exhibited satisfactory internal consistency (α = .78), good test-retest reliability (interclass correlation [ICC] 0.68, 95% CI [0.60-0.75]), and excellent interrater reliability (ICC = 0.95, 95% CI [0.89-0.98]). Exploratory factor analyses revealed that a five-factor structure, explaining 50.3% of the total variance, was the best fit for the data.ConclusionsThe clinician-rated SCI-CG demonstrates good internal consistency, reliability, and convergent validity in treatment-seeking individuals with CG and therefore can be a useful tool to assess CG. Although diagnostic criteria for CG have yet to be adequately validated, the SCI-CG may facilitate this process. The SCI-CG can now be used as a validated instrument in research and clinical practice.

BackgroundChronic pain is prevalent, costly, and clinically vexatious. Clinicians typically use a trial-and-error approach to treatment selection. Repeated crossover trials in a single patient (n-of-1 trials) may provide greater therapeutic precision. N-of-1 trials are the most direct way to estimate individual treatment effects and are useful in comparing the effectiveness and toxicity of different analgesic regimens. The goal of the PREEMPT study is to test the 'Trialist' mobile health smartphone app, which has been developed to make n-of-1 trials easier to accomplish, and to provide patients and clinicians with tools for individualizing treatments for chronic pain.Methods/designA randomized controlled trial is being conducted to test the feasibility and effectiveness of the Trialist app. A total of 244 participants will be randomized to either the Trialist app intervention group (122 patients) or a usual care control group (122 patients). Patients assigned to the Trialist app will work with their clinicians to set up an n-of-1 trial comparing two pain regimens, selected from a menu of flexible options. The Trialist app provides treatment reminders and collects data entered daily by the patient on pain levels and treatment side effects. Upon completion of the n-of-1 trial, patients review results with their clinicians and develop a long-term treatment plan. The primary study outcome (comparing Trialist to usual care patients) is pain-related interference with daily functioning at 26 weeks.DiscussionTrialist will allow patients and clinicians to conduct personalized n-of-1 trials. In prior studies, n-of-1 trials have been shown to encourage greater patient involvement with care, which has in turn been associated with better health outcomes. mHealth technology implemented using smartphones may offer an efficient means of facilitating n-of-1 trials so that more patients can benefit from this approach.Trial registrationClinicalTrials.gov: NCT02116621 , first registered 15 April 2014.

BackgroundAlthough Complicated Grief (CG) has been associated with comorbid Panic Disorder (PD), little is known about panic attacks in CG, and whether panic symptoms may be grief-related. The present study examines the presence and impact of grief-related panic symptoms in CG.MethodsIndividuals with CG (n=146, 78% women, mean (SD) age=52.4(15.0)) were assessed for CG, DSM-IV diagnoses, work and social impairment, and with the Panic Disorder Severity Scale modified to assess symptoms "related to or triggered by reminders of your loss" and anticipatory worry.ResultsOverall, 39.7% reported at least one full or limited-symptom grief-related panic attack over the past week, and 32.2% reported some level of anticipatory worry about grief-related panic. Of interest, 17% met DSM criteria for PD. Among those without PD, 34.7% reported at least one full or limited-symptom grief-related panic attack over the past week, and this was associated with higher CG symptom severity (t=-2.23, p

BackgroundDecade-long delays in successful implementation of Hepatitis B vaccines and ongoing obstacles in HPV vaccine roll-out suggest the importance of an implementation science approach to prepare for the effective translation of future HIV vaccines from clinical trials into routine practice. The objective of this study was to test HIV vaccine attitude items to develop reliable scales and to examine their association with HIV vaccine acceptability.MethodsHIV vaccine attitude items were assessed as part of the L.A. VOICES survey, a large-scale study conducted among underserved residents of Los Angeles, to identify factors that may influence HIV vaccine acceptability. Participants (n=1225) were randomly selected from public STD clinics, needle exchange sites and Latino community clinics using three-stage, venue-based time space sampling.ResultsExploratory factor analysis across 20 items revealed four distinct factors - mistrust, HIV vaccine social concerns, risk compensation, and altruistic vaccination - with acceptable reliability coefficients for each subscale (Cronbach's α range 0.61-0.84). We found no significant differences in reliability by gender or by vaccine acceptability. Risk compensation (odds ratio (OR)=1.49; 95% CI=[1.18, 1.89]; p=0.001) and altruistic vaccination (OR=1.40; 95% CI=[1.14, 1.71]; p=0.001) were significantly and positively associated with HIV vaccine acceptability.ConclusionsWe identified four HIV vaccine attitude scales with sound internal reliability parameters. In the aftermath of the first candidate vaccine to demonstrate efficacy against HIV infection, these scales may be helpful in bridging expectable research-to-practice gaps in future HIV vaccine dissemination among populations at risk. As HIV vaccine trials progress in the United States and globally, these measures also may be useful as a tool to assess and facilitate effective responses to community concerns about HIV vaccine trials and to target interventions to support recruitment and mitigate risk compensation.

Compulsory vaccination is a frequently implemented policy option for ensuring comprehensive vaccine coverage. Ongoing controversies around human papillomavirus vaccine dissemination, and suboptimal coverage, suggest the value of assessing acceptability of compulsory vaccinations-particularly among likely target populations-in advance of their public availability to support evidence-informed interventions. With the first HIV vaccine to demonstrate partial efficacy in a large-scale clinical trial, we examined individual characteristics and attitudes associated with support for compulsory HIV vaccination policy among a diverse, representative sample of adults attending probable HIV vaccine dissemination venues in a large urban county. Participants were recruited using three-stage probability sampling from likely venues for future HIV vaccine dissemination. We used Audio-CASI to administer a 60-min structured questionnaire. Items included endorsement of compulsory HIV vaccination policy, sociodemographic characteristics, injecting drug use, vaccine attitudes and perceived HIV risk. Among 1,225 participants (mean age = 36.8 years; 55.6 % males, 37.6 % non-English speaking Hispanic, 78.8 % heterosexual, 25.7 % injection drug users), almost half (48.2 %) endorsed a compulsory HIV vaccination policy. Non-English speaking Hispanics compared to whites, participants with less than high school education, higher positive vaccine attitude scores and higher perceived HIV risk were significantly more likely, and people who inject drugs significantly less likely to endorse compulsory HIV vaccination. Public health interventions to promote positive vaccine attitudes and accurate perceptions of HIV risk among vulnerable populations, and strategies tailored for people who inject drugs, may build support for compulsory HIV vaccination policy and promote broad HIV vaccine coverage.

Behavioral intervention technologies (BITs) are web-based and mobile interventions intended to support patients and consumers in changing behaviors related to health, mental health, and well-being. BITs are provided to patients and consumers in clinical care settings and commercial marketplaces, frequently with little or no evaluation. Current evaluation methods, including RCTs and implementation studies, can require years to validate an intervention. This timeline is fundamentally incompatible with the BIT environment, where technology advancement and changes in consumer expectations occur quickly, necessitating rapidly evolving interventions. However, BITs can routinely and iteratively collect data in a planned and strategic manner and generate evidence through systematic prospective analyses, thereby creating a system that can "learn." A methodologic framework, Continuous Evaluation of Evolving Behavioral Intervention Technologies (CEEBIT), is proposed that can support the evaluation of multiple BITs or evolving versions, eliminating those that demonstrate poorer outcomes, while allowing new BITs to be entered at any time. CEEBIT could be used to ensure the effectiveness of BITs provided through deployment platforms in clinical care organizations or BIT marketplaces. The features of CEEBIT are described, including criteria for the determination of inferiority, determination of BIT inclusion, methods of assigning consumers to BITs, definition of outcomes, and evaluation of the usefulness of the system. CEEBIT offers the potential to collapse initial evaluation and postmarketing surveillance, providing ongoing assurance of safety and efficacy to patients and consumers, payers, and policymakers.

Growing awareness of health and health care disparities highlights the importance of including information about race, ethnicity, and culture (REC) in health research. Reporting of REC factors in research publications, however, is notoriously imprecise and unsystematic. This article describes the development of a checklist to assess the comprehensiveness and the applicability of REC factor reporting in psychiatric research publications. The 16-item GAP-REACH checklist was developed through a rigorous process of expert consensus, empirical content analysis in a sample of publications (N = 1205), and interrater reliability (IRR) assessment (N = 30). The items assess each section in the conventional structure of a health research article. Data from the assessment may be considered on an item-by-item basis or as a total score ranging from 0% to 100%. The final checklist has excellent IRR (κ = 0.91). The GAP-REACH may be used by multiple research stakeholders to assess the scope of REC reporting in a research article.

ObjectiveTo assess HIV vaccine acceptability among high-risk adults in Los Angeles.Study settingSexually transmitted disease clinics, needle/syringe exchange programs, Latino community health/HIV prevention programs.Study designCross-sectional survey using conjoint analysis. Participants were randomly selected using three-stage probability sampling.Data collectionSixty-minute structured interviews. Participants rated acceptability of eight hypothetical vaccines, each with seven dichotomous attributes, and reported post-vaccination risk behavior intentions.Principal findingsParticipants (n=1164; 55.7 percent male, 82.4 percent ethnic minority, mean age=37.4 years) rated HIV vaccine acceptability from 28.4 to 88.6; mean=54.5 (SD=18.8; 100-point scale). Efficacy had the greatest impact on acceptability, followed by side effects and out-of-pocket cost. Ten percent would decrease condom use after vaccination.ConclusionsFindings support development of social marketing interventions to increase acceptability of "partial efficacy" vaccines, behavioral interventions to mitigate risk compensation, and targeted cost subsidies.

BackgroundSome patients will experience more or less benefit from treatment than the averages reported from clinical trials; such variation in therapeutic outcome is termed heterogeneity of treatment effects (HTE). Identifying HTE is necessary to individualize treatment. The degree to which heterogeneity is sought and analyzed correctly in the general medical literature is unknown. We undertook this literature sample to track the use of HTE analyses over time, examine the appropriateness of the statistical methods used, and explore the predictors of such analyses.MethodsArticles were selected through a probability sample of randomized controlled trials (RCTs) published in Annals of Internal Medicine, BMJ, JAMA, The Lancet, and NEJM during odd numbered months of 1994, 1999, and 2004. RCTs were independently reviewed and coded by two abstractors, with adjudication by a third. Studies were classified as reporting: (1) HTE analysis, utilizing a formal test for heterogeneity or treatment-by-covariate interaction, (2) subgroup analysis only, involving no formal test for heterogeneity or interaction; or (3) neither. Chi-square tests and multiple logistic regression were used to identify variables associated with HTE reporting.Results319 studies were included. Ninety-two (29%) reported HTE analysis; another 88 (28%) reported subgroup analysis only, without examining HTE formally. Major covariates examined included individual risk factors associated with prognosis, responsiveness to treatment, or vulnerability to adverse effects of treatment (56%); gender (30%); age (29%); study site or center (29%); and race/ethnicity (7%). Journal of publication and sample size were significant independent predictors of HTE analysis (p < 0.05 and p < 0.001, respectively).ConclusionHTE is frequently ignored or incorrectly analyzed. An iterative process of exploratory analysis followed by confirmatory HTE analysis will generate the data needed to facilitate an individualized approach to evidence-based medicine.

This study examined HIV vaccine acceptability among immigrant Thai residents in Los Angeles, California. We combined a qualitative research method (focus groups) with an innovative market research method (conjoint analysis). Focus groups explored social issues, concerns, barriers and motivators associated with HIV vaccine acceptability. Conjoint analysis was used to assess preferences among eight hypothetical HIV vaccines with varying attribute profiles and the impact of various attributes on acceptability. Five main themes were identified in the focus groups regarding acceptance and utilization of preventive HIV vaccines: (1) vaccine characteristics, such as efficacy, physical side-effects and cost, (2) fear of a vaccine, (3) vaccine acceptability and optimism, (4) social and family responses and (5) behavioral disinhibition. Conjoint analysis revealed HIV vaccine acceptability ranging from 7.4 (SD = 19.4) to 85.2 (SD = 24.3) across eight hypothetical vaccines. The vaccine with the highest acceptability had the following attributes: 99% efficacy, no side-effects, 10 years of protection, protects against one sub-type, free, one dose and given by injection. Vaccine efficacy had the greatest impact on acceptability (51.4, p=.005), followed by side-effects (11.1, p=.005) and duration of protection (8.3, p=.005). Despite some apprehensions and concerns, Thai residents perceived an HIV vaccine as making an important contribution to society and to protecting oneself and one's family from HIV infection. Nevertheless, acceptability of a partially efficacious vaccine may be low, suggesting the need for tailored social marketing interventions that might emphasize a collectivistic rather than an individualistic focus. Assessing HIV vaccine acceptability using a mixed-method approach is feasible with Thai residents and should lend itself to HIV vaccine research with other Asian Pacific Islander populations in the US.

ObjectivesWe examined the associations between social support and mental and behavioral outcomes among adolescents whose parents were infected with or died of HIV/AIDS.MethodsFamilies (parents who were HIV infected and their adolescent children) were randomly assigned to a coping skills intervention or a standard care group. After completing the intervention, the parents and adolescents were assessed for 2 years.ResultsAdolescents who had more social support providers reported significantly lower levels of depression and fewer conduct problems; adolescents who had more negative influence from role models reported more behavior problems. Reductions in depression, multiple problem behaviors, and conduct problems were significantly associated with better social support.ConclusionsOur findings underscore the complex relations between social support and mental and behavioral outcomes among adolescents affected by HIV/AIDS. Future prevention programs must focus on increasing social support to reduce negative outcomes among adolescents affected by HIV/AIDS as well as the need to reduce influence from negative role models.

ObjectivesTo assess willingness to participate (WTP) in hypothetical Phase III preventive HIV vaccine trials, and the impact of trial attributes on WTP, among low socioeconomic, ethnically diverse adults from communities at elevated risk for HIV infection.MethodParticipants (n=123; median age=38; 69% male; 37% Latino; 14% African-American) were recruited in Los Angeles in 2003 using multi-site, venue-based sampling. WTP was assessed for eight hypothetical HIV vaccine trials that varied across seven dichotomous attributes, using a 2(7-4) fractional factorial experimental design. Individual-specific impact of vaccine trial attributes on WTP was estimated using within-individual ANOVA and then meta-analyzed across individuals.ResultsMean WTP for eight hypothetical vaccine trials ranged from 1.74 to 3.81 (1=highly unlikely, 5=highly likely). Lower WTP was associated with vaccine-induced infection risk (impact=0.88, p

Adolescents of parents infected with HIV/AIDS (HIV-affected adolescents) were recruited from August 1993 to March 1995 to examine their depression as a function of their social support. Adolescent depression and the size, frequency of contact, satisfaction, negative role model influence, and positive social support were examined. Adolescent depression was associated with higher parent depression score, parental HIV disclosure, conduct problems, and was inversely related to higher self-esteem, being male, and a positive living situation. Negative social support was significantly associated with higher adolescent depression, indicating negative role model influence may be more salient than size, frequency of contact, perception, or positive social support. The findings underscore the complex relationships between social support and mental/behavioral outcomes among HIV-affected adolescents as well as the need to examine HIV disclosure in more detail within the context of adolescent social support.

Objective: Given the growing number of military service members with families and the multiple combat deployments characterizing current war time duties, the impact of deployments on military children requires clarification. Behavioral and emotional adjustment problems were examined in children (aged 6 through 12) of an active duty Army or Marine Corps parent currently deployed (CD) or recently returned (RR) from Afghanistan or Iraq. Method: Children (N = 272) and their at-home civilian (AHC) (N = 163) and/or recently returned active duty (AD) parent (N = 65) were interviewed. Child adjustment outcomes were examined in relation to parental psychological distress and months of combat deployment (of the AD) using mixed effects linear models. Results: Parental distress (AHC and AD) and cumulative length of parental combat-related deployments during the child's lifetime independently predicted increased child depression and externalizing symptoms. Although behavioral adjustment and depression levels were comparable to community norms, anxiety was significantly elevated in children in both deployment groups. In contrast, AHC parental distress was greater in those with a CD (vs. RR) spouse. Conclusions: Findings indicate that parental combat deployment has a cumulative effect on children that remains even after the deployed parent returns home, and that is predicted by psychological distress of both the AD and AHC parent. Such data may be informative for screening, prevention, and intervention strategies. (Contains 3 figures and 5 tables.)