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A main objective of this study is to assess the opinions of 50 behavioral health patients on selective control over their behavioral and physical health information. We explored patients' preferences regarding current consent models, what health information should be shared for care and research and whether these preferences vary based on the sensitivity of health information and/or the type of provider involved. The other objective of this study was to solicit opinions of 8 behavioral health providers on patient-driven granular control of health information and potential impact on care.Electronic surveys were implemented at an outpatient Behavioral Health facility that provides care for behavioral health patients with non-serious mental illnesses. The Patient Survey included questions regarding patients' demographics and about their concerns and preferences for data sharing for care and research. The Provider Survey included questions about their view on the current consent process and perceptions on barriers and facilitators to implement patient-controlled granular consent models.This novel study provides valuable preliminary data that can help guide future studies to better understand privacy choices of this underrepresented patient group.

This study explores behavioral health professionals’ perceptions of granular data. Semi-structured in-person interviews of 20 health professionals were conducted at two different sites. Qualitative and quantitative analysis was performed. While most health professionals agreed that patients should control who accesses their personal medical record (70%), there are certain types of health information that should never be restricted (65%). Emergent themes, including perceived reasons that patients might share or withhold certain types of health information (65%), care coordination (12%), patient comprehension (11%), stigma (5%), trust (3%), sociocultural understanding (3%), and dissatisfaction with consent processes (1%), are explored. The impact of care role (prescriber or non-prescriber) on data-sharing perception is explored as well. This study informs the discussion on developing technology that helps balance provider and patient data-sharing and access needs.

This pilot study compares medical record data sensitivity (e.g., depression is sensitive) and categorization perspective (e.g., depression categorized as mental health information) of patients with behavioral health conditions and healthcare providers using a mixed-methods approach employing patient’s own EHR. Perspectives of 25 English- and Spanish-speaking patients were compared with providers. Data categorization comparisons resulted in 66.3% agreements, 14.5% partial agreements, and 19.3% disagreements. Sensitivity comparisons obtained 54.5% agreement, 11.9% partial agreement, and 33.6% disagreements. Patients and providers disagreed in classification of genetic data, mental health, drug abuse, and physical health information. Factors influencing patients’ sensitivity determination were sensitive category comprehension, own experience, stigma towards category labels (e.g., drug abuse), and perception of information applicability (e.g., alcohol dependency). Knowledge of patients’ sensitivity perceptions and reconciliation with providers could expedite the development of granular and personalized consent technology.

Summary In the current paper, we studied downtime at work. Downtime represents a unique aspect of work time, as employees have low workload and more discretion about their activities but are still paid to be at work. Despite its prevalence and potentially significant implications for productivity and well‐being, the experience of downtime has not been a focus in the literature. To study this phenomenon, we first used a qualitative method involving 15 focus groups. Results from 95 employees showed that downtime is distinct from formal breaks and withdrawal behavior and is generally a negative subjective experience. Categories of antecedents of experience and downtime activities were classified. Next, to further explore the phenomenon, and based on Study 1 and relevant literature, we proposed several hypotheses and tested them using an experience sampling method. Results from 86 employees (across 5 workdays and 689 data points) indicated that the amount of downtime was negatively related to day level job satisfaction, job performance, and subjective health. The duration of relaxation activities during downtime mitigated the negative effects of downtime on fatigue. The effects of enjoyment level of the activities, job autonomy, work engagement, and boredom proneness were also examined. Implications, limitations, and future research are discussed.