Difference (%) between the accuracy of the expert and the baseline classifiers, when varying number of training subjects is used.

<p>Each gray line shows the accuracy difference when one subject’s deceptive data is used as test, and the black line shows the average and its standard deviation as error bars. In all tests the expert classifiers perform better than the baseline classifiers (the difference is positive). While the relationship between the accuracies and the number of training subjects is noisy, it does not vary much for each test dataset.</p

Experiment design overview.

<p>Each trial consisted of two types of activities: walking and sitting.</p

Difference (%) between the accuracy of the expert and the baseline classifiers, when varying number of training subjects is used.

<p>Each gray line shows the accuracy difference when one subject’s deceptive data is used as test, and the black line shows the average and its standard deviation as error bars. In all tests the expert classifiers perform better than the baseline classifiers (the difference is positive). While the relationship between the accuracies and the number of training subjects is noisy, it does not vary much for each test dataset.</p

Accuracy of the baseline (circles) and the expert (triangles) models in classifying deceptive (solid) and normal (dashed) data, as a function of the number of training subjects.

<p>Dotted line shows the chance level (50%) and the shaded areas show standard deviation of the accuracies.</p

Average success rate of subjects in walking and sitting trials, indicating how successful they are at cheating.

<p>Each colored dot represents a subject’s success rate at a trial. The dots which are not connected to any line belong to subjects who failed in the first deceptive activity trial.</p

2-dimensional representation of feature values collected from a single subject who succeeded in 3 trials.

<p>We used a 2-component factor analysis. Green circles show normal activity and grey crosses indicate fake activity factors. The changing location of fake activity data points across trials shows different strategies taken by the subject.</p

A Randomized Controlled Trial Evaluating a Manualized TeleCoaching Protocol for Improving Adherence to a Web-Based Intervention for the Treatment of Depression

<div><p>Background</p><p>Web-based interventions for depression that are supported by coaching have generally produced larger effect-sizes, relative to standalone web-based interventions. This is likely due to the effect of coaching on adherence. We evaluated the efficacy of a manualized telephone coaching intervention (TeleCoach) aimed at improving adherence to a web-based intervention (moodManager), as well as the relationship between adherence and depressive symptom outcomes.</p><p>Methods</p><p>101 patients with MDD, recruited from primary care, were randomized to 12 weeks moodManager+TeleCoach, 12 weeks of self-directed moodManager, or 6 weeks of a waitlist control (WLC). Depressive symptom severity was measured using the PHQ-9.</p><p>Results</p><p>TeleCoach+moodManager, compared to self-directed moodManager, resulted in significantly greater numbers of login days (<i>p</i> = 0.01), greater time until last use (<i>p</i> = 0.007), greater use of lessons (<i>p</i> = 0.03), greater variety of interactive tools used (<i>p</i> = 0.02), but total instances of tool use did not reach statistical significance. (<i>p</i> = 0.07). TeleCoach+moodManager produced significantly lower PHQ-9 scores relative to WLC at week 6 (<i>p</i> = 0.04), but there were no other significant differences in PHQ-9 scores at weeks 6 or 12 (<i>p</i>s>0.20) across treatment arms. Baseline PHQ-9 scores were no significantly related to adherence to moodManager.</p><p>Conclusions</p><p>TeleCoach produced significantly greater adherence to moodManager, relative to self-directed moodManager. TeleCoached moodManager produced greater reductions in depressive symptoms relative to WLC, however, there were no statistically significant differences relative to self-directed moodManager. While greater use was associated with better outcomes, most users in both TeleCoach and self-directed moodManager had dropped out of treatment by week 12. Even with telephone coaching, adherence to web-based interventions for depression remains a challenge. Methods of improving coaching models are discussed.</p><p>Trial Registration</p><p>Clinicaltrials.gov <a href="http://clinicaltrials.gov/ct2/show/NCT00719979?term=NCT00719979&rank=1" target="_blank">NCT00719979</a></p></div

Mean MADRS.

<p>Linear mixed effects model adjusted for age and MS disease duration, error bars indicate standard error of the mean. No difference between placebo and omega-3 FA was found over 3 months (p = 0.23).</p

MADRS Improvement.

<p>This figure reflects percent of subjects improved by 50% or more from baseline MADRS score. Mixed effects logistic regression model adjusted for age and MS disease duration. No difference between placebo and omega-3 FA was found over 3 months (p = 0.30).</p

Consort Flow Chart.

<p>Consort Flow Chart.</p