Mark A. Hall

As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more.

Despite the profound and pervasive importance of trust in medical settings, there is no commonly shared understanding of what trust means, and little is known about what difference trust actually makes, what factors affect trust, and how trust relates to other similar attitudes and behaviors. To address this gap in understanding, the emerging theoretical, empirical, and public policy literature on trust in physicians and in medical institutions is reviewed and synthesized. Based on this review and additional research and analysis, a formal definition and conceptual model of trust is presented, with a review of the extent to which this model has been confirmed by empirical studies. This conceptual and empirical understanding has significance for ethics, law, and public policy.

Existing scales to measure trust in physicians have differing content and limited testing. To improve on these measures, a detailed conceptual model was constructed and a large item pool (n = 78) was generated following a detailed conceptual model and expert review. After pilot testing, the best-performing items were validated with a random national sample (n = 959) and a regional sample of HMO members (n =1,199). Various psychometric tests produced a 10-item unidimensional scale consistent with most aspects of the conceptual model. Compared with previous scales, the Wake Forest physician trust scale has a somewhat improved combination of internal consistency, variability, and discriminability. The scale is more strongly correlated with satisfaction, desire to remain with a physician, willingness to recommend to friends, and not seeking second opinions; it is less correlated with insurer trust, membership in managed care, and choice of physician. Correlations are equivalent with lack of disputes, length of relationship, and number of visits [corrected].

Trust is a fundamentally important aspect of medical treatment relationships. Studies have established that patient trust predicts instrumental variables such as use of preventive services, adherence, and continued enrollment at least as well as satisfaction does, and is more salient for measuring the quality of ongoing relationships. Measuring trust would help to inform public policy deliberations and balance market forces that threaten the doctor-patient relationship. Several validated measures could be easily included in surveys. While further studies to evaluate the cost-effectiveness of measuring trust and test interventions to improve trust are desirable, the action merits serious consideration.

OBJECTIVE: To develop and test a multi-item measure for general trust in physicians, in contrast with trust in a specific physician. DATA SOURCES: Random national telephone survey of 502 adult subjects with a regular physician and source of payment. STUDY DESIGN: Based on a multidimensional conceptual model, a large pool of candidate items was generated, tested, and revised using focus groups, expert reviewers, and pilot testing. The scale was analyzed for its factor structure, internal consistency, construct validity, and other psychometric properties. PRINCIPAL FINDINGS: The resulting 11-item scale measuring trust in physicians generally is consistent with most aspects of the conceptual model except that it does not include the dimension of confidentiality. This scale has a single-factor structure, good internal consistency (alpha = .89), and good response variability (range = 11-54; mean = 33.5; SD = 6.9). This scale is related to satisfaction with care, trust in one's physician, following doctors' recommendations, having no prior disputes with physicians, not having sought second opinions, and not having changed doctors. No association was found with race/ethnicity. While general trust and interpersonal trust are qualitatively similar, they are only moderately correlated with each other and general trust is substantially lower. CONCLUSIONS: Emerging research on patients' trust has focused on interpersonal trust in a specific, known physician. Trust in physicians in general is also important and differs significantly from interpersonal physician trust. General physician trust potentially has a strong influence on important behaviors and attitudes, and on the formation of interpersonal physician trust.