A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

Impact of a modified dietary plan on the health related quality of life of minority participants in the Women's Healthy Eating and Living (WHEL) Study

Advances in medical technology, in genetics, and in clinical research have led to early detection of cancer, precise diagnosis, and effective treatment modalities. Decline in cancer incidence and mortality due to cancer has led to increased number of long-term survivors. However, the ethnic minority population has not experienced this decline and still continues to carry a disparate proportion of the cancer burden. Majority of the clinical research including survivorship studies have recruited and continue to recruit a convenient sample of middle- to upper-class Caucasian survivors. Thus, minorities are underrepresented in cancer research in terms of both clinical studies and in health related quality of life (HRQOL) studies. ^ Life style and diet have been associated with increased risk of breast cancer. High vegetable low fat diet has been shown to reduce recurrence of breast cancer and early death. The Women's Healthy Eating and Living Study is an ongoing multi-site randomized controlled trial that is evaluating the high-vegetable low fat diet in reducing the recurrence of breast cancer and early death. The purpose of this dissertation was to (1) compare the impact of the modified diet on the HRQOL during the first 12-month period on specific Minorities and matched Caucasians; (2) identify predictors that significantly impact the HRQOL of the study participants; and (3) using the structural equation modeling assess the impact of nutrition on the HRQOL of the intervention group participants. Findings suggest that there are no significant differences in change in HRQOL between Minorities and Caucasians; between Minorities in the intervention group and those in the comparison group; and between women in the intervention group and those in the comparison group. Minority indicator variable and Intervention/Comparison group indicator variable were not found to be good predictors of HRQOL. Although the structural equation models suggested viable representation of the relationship between the antecedent variables, the mediating variables and the two outcome variables, the impact of nutrition was not statistically significant to be included in the model. This dissertation, by analyzing the HRQOL of minorities in the WHEL Study, attempted to add to the knowledge base specific to minority cancer survivors. ^

Measuring the quality of life of patients with diabetes: Validating the tool and determining the effects on quality of life

There are several tools for measuring quality of life (QoL) and specifically, health-related quality of life (HRQoL) for persons with diabetes. A commonly-used measure, the Diabetes Quality of Life (DQOL) Survey, developed for the Diabetes Control and Complications Trial (DCCT), has been used in several experimental settings, and its reliability and validity are well-established. However, it is considered too long to be of practical use in clinical settings. Because of this, a shortened version of the tool was used recently in the Community Diabetes Education (CoDE) Project in Dallas, Texas, a clinic-based patient education program that uses a specially-trained community healthcare worker to provide patient education. However, the modified scale has never been tested for reliability and validity. Thus, one goal of this thesis was to measure these psychometric properties of the scale. After establishing the reliability and validity, the results of the scale were analyzed to determine the effects of the intervention on the subjects’ quality of life. The changes in QoL scales were compared with changes in physiologic measures which are most closely allied with diabetes, including blood glucose levels, weight/BMI, co-morbidities and health beliefs in order to determine if there is a relationship between such measures and quality of life. The results of the reliability and validity testing were not conclusive. Measures of reliability and criterion validity were established, but these contrasted with poor measures of repeatability and content validity. The effect of the intervention on quality of life, however, was more significant, particularly regarding the impact of diabetes. Those who received the counseling had significantly higher scores on the Impact scale than those who did not, and the former group had much greater improvement in scores over the twelve month period than the latter group. ^

Improving the Quality of Life of spousal caregivers of stroke survivors: A cost effectiveness analysis

Back ground and Purpose. There is a growing consensus among health care researchers that Quality of Life (QoL) is an important outcome and, within the field of family caregiving, cost effectiveness research is needed to determine which programs have the greatest benefit for family members. This study uses a multidimensional approach to measure the cost effectiveness of a multicomponent intervention designed to improve the quality of life of spousal caregivers of stroke survivors. Methods. The CAReS study (Committed to Assisting with Recovery after Stroke) was a 5-year prospective, longitudinal intervention study for 159 stroke survivors and their spousal caregivers upon discharge of the stroke survivor from inpatient rehabilitation to their home. CAReS cost data were analyzed to determine the incremental cost of the intervention per caregiver. The mean values of the quality-of-life predictor variables of the intervention group of caregivers were compared to the mean values of usual care groups found in the literature. Significant differences were then divided into the cost of the intervention per caregiver to calculate the incremental cost effectiveness ratio for each predictor variable. Results. The cost of the intervention per caregiver was approximately $2,500. Statistically significant differences were found between the mean scores for the Perceived Stress and Satisfaction with Life scales. Statistically significant differences were not found between the mean scores for the Self Reported Health Status, Mutuality, and Preparedness scales. Conclusions. This study provides a prototype cost effectiveness analysis on which researchers can build. Using a multidimensional approach to measure QoL, as used in this analysis, incorporates both the subjective and objective components of QoL. Some of the QoL predictor variable scores were significantly different between the intervention and comparison groups, indicating a significant impact of the intervention. The estimated cost of the impact was also examined. In future studies, a scale that takes into account both the dimensions and the weighting each person places on the dimensions of QoL should be used to provide a single QoL score per participant. With participant level cost and outcome data, uncertainty around each cost-effectiveness ratio can be calculated using the bias-corrected percentile bootstrapping method and plotted to calculate the cost-effectiveness acceptability curves.^