Associations of Patient Health-Related Problem Solving with Disease Control, Emergency Department Visits, and Hospitalizations in HIV and Diabetes Clinic Samples

BACKGROUND: Patient problem solving and decision making are recognized as essential to effective self-management across multiple chronic diseases. However, a health-related problem-solving instrument that demonstrates sensitivity to disease control parameters in multiple diseases has not been established. OBJECTIVES: To determine, in two disease samples, internal consistency and associations with disease control of the Health Problem-Solving Scale (HPSS), a 50-item measure with 7 subscales assessing effective and ineffective problem-solving approaches, learning from past experiences, and motivation/orientation. DESIGN: Cross-sectional study. PARTICIPANTS: Outpatients from university-affiliated medical center HIV (N = 111) and diabetes mellitus (DM, N = 78) clinics. MEASUREMENTS: HPSS, CD4, hemoglobin A1c (HbA1c), and number of hospitalizations in the previous year and Emergency Department (ED) visits in the previous 6 months. RESULTS: Administration time for the HPSS ranged from 5 to 10 minutes. Cronbach’s alpha for the total HPSS was 0.86 and 0.89 for HIV and DM, respectively. Higher total scores (better problem solving) were associated with higher CD4 and fewer hospitalizations in HIV and lower HbA1c and fewer ED visits in DM. Health Problem-Solving Scale subscales representing negative problem-solving approaches were consistently associated with more hospitalizations (HIV, DM) and ED visits (DM). CONCLUSIONS: The HPSS may identify problem-solving difficulties with disease self-management and assess effectiveness of interventions targeting patient decision making in self-care

Optimal Design of Intervention Studies to Prevent Influenza in Healthy Cohorts

Background: Influenza cohort studies, in which participants are monitored for infection over an epidemic period, are invaluable in assessing the effectiveness of control measures such as vaccination, antiviral prophylaxis and nonpharmaceutical interventions (NPIs). Influenza infections and illnesses can be identified through a number of approaches with different costs and logistical requirements. Methodology and Principal Findings: In the context of a randomized controlled trial of an NPI with a constrained budget, we used a simulation approach to examine which approaches to measuring outcomes could provide greater statistical power to identify an effective intervention against confirmed influenza. We found that for a short epidemic season, the optimal design was to collect respiratory specimens at biweekly intervals, as well as following report of acute respiratory illness (ARI), for virologic testing by reverse transcription polymerase chain reaction (RT-PCR). Collection of respiratory specimens only from individuals reporting ARI was also an efficient design particularly for studies in settings with longer periods of influenza activity. Collection of specimens only from individuals reporting a febrile ARI was less efficient. Collection and testing of sera before and after influenza activity appeared to be inferior to collection of respiratory specimens for RT-PCR confirmation of acute infections. The performance of RT-PCR was robust to uncertainty in the costs and diagnostic performance of RT-PCR and serological tests

Design and analysis of household studies of influenza

Background: Influenza viruses cause substantial mortality and morbidity both worldwide and in Hong Kong. Furthermore, the possible emergence of future influenza pandemics remains a major threat to public health. Some studies have estimated that one third of all influenza transmission occurs in households. Household studies have been an important means of studying influenza transmissions and evaluating the efficacy of influenza control measures including vaccination, antiviral therapy and prophylaxis and non-pharmaceutical interventions. Household studies of influenza can be categorized as pertaining to one of two designs: household cohort and case-ascertained. In household cohort studies households are recruited before the start of an influenza season and then monitored during the influenza season for influenza infection. In case-ascertained studies a household is enrolled once influenza infection is identified in a household member. Objectives: This thesis comprises of two parts. The objective of the first part is to evaluate the resource efficiency of different designs for conducting household studies. The objective of the second part is to estimate community and household transmission parameters during the 2009 A(H1N1) pandemic in Hong Kong. Methods: Monte Carlo simulation parameterized with data from influenza studies in Hong Kong was used to compare the resource efficiency of competing study designs evaluating the efficacy of an influenza control intervention. Approaches to ascertaining infections in different types of studies, and their implications for resource efficiency were compared. With regard to the second part, extended Longini-Koopman models within a Bayesian framework were used on data from a Hong Kong household cohort study conducted from December 2008 to October 2009. Household and community transmission parameters were estimated by age-groups for two seasonal influenza strains circulating in the winter of 2008-09 and two seasonal and one pandemic strain circulating in the summer of 2009. Results: Simulations showed that RT-PCR outperformed both serology and self-report of symptoms as a resource efficient means of identifying influenza in household studies. Identification of influenza using self-report of symptomatology performed particularly poorly in terms of resource efficiency due to its low sensitivity and specificity when compared to laboratory methods. Case-ascertained studies appeared more resource efficient than cohort studies but the results were sensitive to the choice of parameter values particularly the serial interval of influenza. In statistical analyses of household data during the winter of 2008-09, it was found that transmissibility of seasonal influenza strains were similar to those previously reported in the literature. Analysis also showed for the summer 2009 the estimates of household transmissibility were similar for seasonal A(H3N2) and pandemic A(H1N1) especially after taking into account that some individuals were likely immune to infection. Conclusions: Careful consideration of study design can ensure that studies are resource efficient and have sufficient statistical power. Data from a household study suggested that during 2009 seasonal and pandemic influenza had similar transmission patterns.published_or_final_versionCommunity MedicineDoctoralDoctor of Philosoph

Comparison of alternative study designs.

<p>In the plot, the three rows indicate: (A) power, (B) total sample size per arm, and (C) estimated cumulative incidence of influenza in the control arm. Scenario I assumes the unbiased control non-influenza attack ARI and FARI rates are 0.4 and 0.1 respectively which exactly correspond to estimates made in advance of the study. Scenario II assumes the unbiased control non-influenza attack ARI and FARI rates are 0.4 and 0.1 but are underestimated at 0.2 and 0.06 when planning the study. Scenario III assumes the unbiased control non-influenza attack ARI and FARI rates are 0.4 and 0.1 and but are overestimated at 0.6 and 0.14 when planning the study. Control arm cumulative incidence proportion refers to the expected proportion of participants identified as having influenza infection among the control arm. “Combined” refers to paired serology analyzed by HAI plus RT-PCR upon ARI trigger. Black lines are used to denote design variants using RT-PCR confirmation. Grey lines are used to denote design variants using serologic confirmation or serologic plus RT-PCR confirmation.</p

Sample size per arm and total budget needed to achieve 80% power for differing methods of identification of influenza infections for both short (2 months) and long (6 months) influenza seasons.

<p>Sample size per arm and total budget needed to achieve 80% power for differing methods of identification of influenza infections for both short (2 months) and long (6 months) influenza seasons.</p

Parameter values and ranges of the input values in sensitivity analysis.

<p>Parameter values and ranges of the input values in sensitivity analysis.</p

Catastrophizing and Depressive Symptoms as Prospective Predictors of Outcomes Following Total Knee Replacement

Several recent reports suggest that pain-related catastrophizing is a risk factor for poor acute pain outcomes following surgical interventions. However, it has been less clear whether levels of catastrophizing influence longer-term postoperative outcomes. Data were analyzed from a relatively small number (n=43) of patients who underwent total knee replacement and were followed for 12 months after their surgery. Previous research has suggested that high levels of both catastrophizing and depression are associated with elevated acute postoperative pain complaints among patients undergoing knee surgery. In this sample, catastrophizing and depression at each of the assessment points were studied as prospective predictors of pain (both global pain ratings and pain at night) at the subsequent assessment point over the course of one year. The predictive patterns differed somewhat across measures of pain reporting; depressive symptoms were unique predictors of greater global pain complaints, while catastrophizing was a specific and unique predictor of elevated nighttime pain. While surgical outcomes following total knee replacement are, on average, quite good, a significant minority of patients continue to experience long-term pain. The present findings suggest that high levels of catastrophizing and depression may promote enhanced pain levels, indicating that interventions designed to reduce catastrophizing and depressive symptoms may have the potential to further improve joint replacement outcomes