Local Standards for Sample Size at CHI

We describe the primary ways researchers can determine the size of a sample of research participants, present the benefits and drawbacks of each of those methods, and focus on improving one method that could be useful to the CHI community: local standards. To determine local standards for sample size within the CHI community, we conducted an analysis of all manuscripts published at CHI2014. We find that sample size for manuscripts published at CHI ranges from 1 -- 916,000 and the most common sample size is 12. We also find that sample size differs based on factors such as study setting and type of methodology employed. The outcome of this paper is an overview of the various ways sample size may be determined and an analysis of local standards for sample size within the CHI community. These contributions may be useful to researchers planning studies and reviewers evaluating the validity of results

Investigating Contextual Cues as Indicators for EMA Delivery

In this work, we attempt to determine whether the contextual information of a participant can be used to predict whether the participant will respond to a particular Ecological Momentary Assessment (EMA) prompt. We use a publicly available dataset for our work, and find that by using basic contextual features about the participant\u27s activity, conversation status, audio, and location, we can predict whether an EMA prompt triggered at a particular time will be answered with a precision of 0.647, which is significantly higher than a baseline precision of 0.410. Using this knowledge, the researchers conducting field studies can efficiently schedule EMA prompts and achieve higher response rates

Patient Preferences in Controlling Access to Their Electronic Health Records: a Prospective Cohort Study in Primary Care

Introduction: Previous studies have measured individuals’ willingness to share personal information stored in electronic health records (EHRs) with health care providers, but none has measured preferences among patients when they are allowed to determine the parameters of provider access. Methods: Patients were given the ability to control access by doctors, nurses, and other staff in a primary care clinic to personal information stored in an EHR. Patients could restrict access to all personal data or to specific types of sensitive information, and could restrict access for a specific time period. Patients also completed a survey regarding their understanding of and opinions regarding the process. Results: Of 139 eligible patients who were approached, 105 (75.5 %) were enrolled, and preferences were collected from all 105 (100 %). Sixty patients (57 %) did not restrict access for any providers. Of the 45 patients (43 %) who chose to limit the access of at least one provider, 36 restricted access only to all personal information in the EHR, while nine restricted access of some providers to a subset of the their personal information. Thirty-four (32.3 %) patients blocked access to all personal information by all doctors, nurses, and/or other staff, 26 (24.8 %) blocked access by all doctors and/or nurses, and five (4.8 %) denied access to all doctors, nurses, and staff. Conclusions: A significant minority of patients chose to restrict access by their primary care providers to personal information contained in an EHR, and few chose to restrict access to specific types of information. More research is needed to identify patient goals and understanding of the implications when facing decisions of this sort, and to identify the impact of patient education regarding information contained in EHRs and their use in the clinical care settin

Provider Responses to Patients Controlling Access to their Electronic Health Records: A Prospective Cohort Study in Primary Care

Introduction: Applying Fair Information Practice principles to electronic health records (EHRs) requires allowing patient control over who views their data. Methods: We designed a program that captures patients’ preferences for provider access to an urban health system’s EHR. Patients could allow or restrict providers’ access to all data (diagnoses, medications, test results, reports, etc.) or only highly sensitive data (sexually transmitted infections, HIV/AIDS, drugs/alcohol, mental or reproductive health). Except for information in free-text reports, we redacted EHR data shown to providers according to patients’ preferences. Providers could “Break the Glass” to display redacted information. We prospectively studied this system in one primary care clinic, noting redactions and when users “Broke the Glass,” and surveyed providers about their experiences and opinions. Results: Eight of 9 eligible clinic physicians and all 23 clinic staff participated. All 105 patients who enrolled completed the preference program.. Providers did not know which of their patients were enrolled and nor their preferences for accessing their EHRs. During the six-month prospective study, 92 study patients (88%) returned 261 times during which providers viewed their EHRs 126 times (48%). Providers “broke the glass” 102 times, 92 times for patients not in the study and 10 times for 6 returning study patients, all of whom had restricted EHR access. Providers “broke the glass” for 6 (14%) of 43 returning study patients with redacted data vs. zero among 49 study patients without redactions (p=0.01). Although 54% of providers agreed that patients should have control over who sees their EHR information, 58% believed restricting EHR access could harm provider-patient relationships and 71% felt quality of care would suffer. Conclusions: Patients frequently preferred restricting provider access to their EHRs. Providers infrequently overrode patients’ preferences to view hidden data. Providers believed restricting EHR access would adversely impact patient care. Applying Fair Information Practice principles to EHRs will require balancing patient preferences, providers’ needs, and health care quality.This study was supported in part by grant number 90HT005 from the Office of the National Coordinator for Health Information Technology (ONC) to the Indiana Health Information Technology Corporation. The opinions expressed in this work are the authors’ and do not necessarily reflect the positions of ONC, IHIT, Eskenazi Health, Indiana University, or the Regenstrief Institute, Inc

Detecting Eating Episodes with an Ear-mounted Sensor

In this paper, we propose Auracle, a wearable earpiece that can automatically recognize eating behavior. More specifically, in free-living conditions, we can recognize when and for how long a person is eating. Using an off-the-shelf contact microphone placed behind the ear, Auracle captures the sound of a person chewing as it passes through the bone and tissue of the head. This audio data is then processed by a custom analog/digital circuit board. To ensure reliable (yet comfortable) contact between microphone and skin, all hardware components are incorporated into a 3D-printed behind-the-head framework. We collected field data with 14 participants for 32 hours in free-living conditions and additional eating data with 10 participants for 2 hours in a laboratory setting. We achieved accuracy exceeding 92.8% and F1 score exceeding 77.5% for eating detection. Moreover, Auracle successfully detected 20-24 eating episodes (depending on the metrics) out of 26 in free-living conditions. We demonstrate that our custom device could sense, process, and classify audio data in real time. Additionally, we estimateAuracle can last 28.1 hours with a 110 mAh battery while communicating its observations of eating behavior to a smartphone over Bluetooth

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Subjective response to antipsychotic treatment and compliance in schizophrenia. A naturalistic study comparing olanzapine, risperidone and haloperidol (EFESO Study)

BACKGROUND: In order to compare the effectiveness of different antipsychotic drugs in the treatment of schizophrenia it is very important to evaluate subjective response and compliance in patient cohorts treated according to routine clinical practice. METHOD: Outpatients with schizophrenia entered this prospective, naturalistic study when they received a new prescription for an antipsychotic drug. Treatment assignment was based on purely clinical criteria, as the study did not include any experimental intervention. Patients treated with olanzapine, risperidone or haloperidol were included in the analysis. Subjective response was measured using the 10-item version of the Drug Attitude Inventory (DAI-10), and treatment compliance was measured using a physician-rated 4 point categorical scale. RESULTS: A total of 2128 patients initiated treatment (as monotherapy) with olanzapine, 417 with risperidone, and 112 with haloperidol. Olanzapine-treated patients had significantly higher DAI-10 scores and significantly better treatment compliance compared to both risperidone- and haloperidol-treated patients. Risperidone-treated patients had a significantly higher DAI-10 score compared to haloperidol-treated patients. CONCLUSION: Subjective response and compliance were superior in olanzapine-treated patients, compared to patients treated with risperidone and haloperidol, in routine clinical practice. Differences in subjective response were explained largely, but not completely, by differences in incidence of EPS

Television viewing, food preferences, and food habits among children: A prospective epidemiological study

<p>Abstract</p> <p>Background</p> <p>Obesity has increased since the early 1980s, and despite numerous attempts, effective strategies to counter this worldwide epidemic are lacking. Food preferences are established early in life and are difficult to change later. There is therefore a need to identify factors that influence the development of food preferences. Our aim was therefore, to investigate cross-sectional and prospective associations between TV viewing habits and food preferences and habits, respectively. We hypothesized that more TV viewing was associated with less healthy concomitant and future food preferences and food habits.</p> <p>Methods</p> <p>Data are from the Danish part of European Youth Heart Study (EYHS) I and II, a prospective cohort study conducted among 8-10-year-old and 14-16-year-old Danes in 1997-98. Six years later 2003-04 the 8-10-year-olds were followed up at age 14-16 years, and a new group of 8-10-year olds were included. Data were analysed using mixed linear regression analysis. Cross-sectional analyses included 697 8-10-year-olds and 495 14-16-year-olds. Prospective analyses included 232 pupils with complete data at baseline and follow-up. Associations between TV viewing habits and the sum of healthy food preferences (ΣHFP), and the sum of healthy food habits (ΣHFH), respectively, were examined.</p> <p>Results</p> <p>Inverse cross-sectional associations between TV viewing (h/day) and both ΣHFP and ΣHFH were present for both the 8-10-year-old and the 14-16-year-old boys and girls. The frequency of meals in front of the TV (times/week) was also inversely associated with ΣHFP among 8-10-year-old boys, and with ΣHFH in all sex- and age groups. Among girls, baseline TV viewing (h/day) was directly associated with adverse development in the ΣHFP during follow-up. The concomitant 6-year changes in ΣHFH and TV viewing (h/day) were inversely associated in boys.</p> <p>Conclusions</p> <p>Long time spent on TV viewing, and possibly to a lesser degree, frequent consumption of meals during TV viewing, seem to be associated with generally having unhealthy food preferences and food habits among school-aged children. These associations, however, were not generally persistent after 6 years of follow-up.</p