This paper reports on the findings of a technical expert panel convened by the Agency for Healthcare Research and Quality and the National Institute of Mental Health, charged with reviewing the state of research on behavioral intervention technologies (BITs) in mental health and identifying the top research priorities. BITs is the comprehensive term used to refer to behavioral and psychological interventions that use information and communication technology features to address behavioral and mental health outcomes. Mental health BITs using videoconferencing and standard telephone technologies to deliver psychotherapy have been wellvalidated. Web-based interventions have shown efficacy across a broad range of mental health outcomes, although outcomes vary widely. Social media such as online support groups have produced generally disappointing outcomes when used alone. Mobile technologies have received limited attention for mental health outcomes, although findings from behavioral health suggest they are promising. Virtual reality has shown good efficacy for anxiety and pediatric disorders. Serious gaming has received relatively little work in mental health. Recommendations for next step research in each of these are made. Research focused on understanding of reach, adherence, barriers and cost is recommended. As BITs can generate large amounts of data, improvements in the collection, storage, analysis, and visualization of big data will be required. Traditional psychological and behavioral theories have proven insufficient to understand how BITs produce behavioral change. Thus new theoretical models, as well as new evaluation strategies, will be required. Finally, for BITs to have a public health impact, research on implementation and application to prevention will be required.

PURPOSE This study aimed to identify the demographic, psychiatric, and attitudinal predictors of treatment adherence during the maintenance phase of antidepressant treatment, ie, after symptoms and regimen are stabilized. METHODSWe surveyed 81 primary care patients given maintenance antidepressant medications regarding general adherence, recent missed doses, depression and treatment features, medication beliefs (necessity, concerns, harmfulness, and overprescription), and other variables. Additional data were collected from medical and payer records. RESULTSMedian treatment duration was 75 weeks. Adherence and beliefs were broadly dispersed and unrelated to treatment duration and type, physical functioning, and demographics. Multivariate analysis adjusting for social desirability, depression severity, and treatment duration indicated that an antidepressantspecifi c "necessity-minus-concerns" composite was strongly associated with both adherence outcomes. Specifi cally, adherence was highest when necessity exceeded concerns and lowest when concerns exceeded necessity. We crossed these 2 dimensions to characterize 4 patient attitudes toward antidepressants: skepticism, indifference, ambivalence, and acceptance.CONCLUSIONS Patients given maintenance antidepressants vary widely in adherence. This variation is primarily explained by the balance between their perceptions of need and harmfulness of antidepressant medication, in that adherence is lowest when perceived harm exceeds perceived need, and highest when perceived need exceeds perceived harm. We speculate on ways to tailor adherence strategies to patient beliefs. Subsequent research should determine whether patients' perceptions about medication predict depression outcomes, can be used to improve clinical management, and respond to behavioral intervention.

Misidentification of depression in primary care may be in part an artifact of the use of the psychiatric model of caseness in the primary care setting. Our results are most consistent with a chronic disease-based model of depressive disorder, in which patients classified as false positive and false negative occupy a clinical middle ground between clearly depressed and clearly nondepressed patients. Family physicians appear to respond to meaningful clinical cues in assigning the diagnosis of depression to these distressed and impaired patients.

For outpatients with nonpsychotic MDD, depressive symptoms and severity vary little between primary care and specialty care settings. In this large, broadly inclusive US sample, the risk factors for chronic and recurrent depressive illness were frequently present, highlighting a clear risk for treatment resistance and the need for aggressive management strategies in both settings.

Identical remission and response rates can be achieved in primary and specialty settings when identical care is provided.

PURPOSEPatients' beliefs about antidepressants vary widely and probably infl uence adherence, yet little is known about what underlies such beliefs. This study's objective was to identify the demographic and clinical characteristics that account for patients' beliefs about antidepressants.METHODS Participants were 165 patients with unipolar nonpsychotic major depression from primary care and psychiatry clinics who were participating in the baseline phase of a multistaged trial of medication and psychotherapy. Before patients started antidepressants, interview and self-report measures were used to assess treatment beliefs, depression features, and comorbid conditions. Linear multivariate regression was used to identify the strongest correlates of perceived medication necessity and harmfulness after adjusting for age, sex, education, and the random effects of patients within clinical site. RESULTSPerceived necessity was associated with older age (P <.001), more severe symptoms (P = .03), longer anticipated duration of symptoms (P = .001), and attribution of symptoms to chemical imbalance (P = .005). Perceived harmfulness was highest among patients who had not taken antidepressants before (P = .02), attributed their symptoms to random factors (P = .04), and had a subjectively unclear understanding of depression (P = .003). Neither belief was signifi cantly associated with sex, education, age at fi rst depressive episode, presence of melancholia or anxiety, psychiatric comorbidity, or clinical setting.CONCLUSIONS Skepticism about antidepressants is strongest among younger patients who have never taken antidepressants, view their symptoms as mild and transient, and feel unclear about the factors affecting their depression. Perhaps these patients would benefi t the most from adherence promotion focusing on treatment beliefs. INTRODUCTIONA lthough depression treatment guidelines recommend continuation of medication for at least 8 months after symptom remission, [1][2][3] 50% to 83% of patients prescribed antidepressants either discontinue their medication prematurely or take it too inconsistently to derive any clinical benefi t, 4-6 which appears to increase their risks for relapse and recurrence. [7][8][9] A large body of literature indicates that patients' beliefs and attitudes about medication predict medication adherence, treatment outcome, or both-in general 10 and in depression. 4,5,[11][12][13] Our prior study of 573 primary care patients indicated that the only identifi able baseline predictor of early discontinuation was beliefs about the appropriateness of taking medication for depression. 11 In another study of patients who were well established in the maintenance phase of antidepressant therapy, we found patient beliefs about antidepressant necessity vs harmfulness to be the only identifi able correlate of adherence.14 In neither study did demographic or depression characteristics account for adherence.Despite 24 PAT IEN T S' BEL IEF S A B OU T A N T IDEPR ES S A N T Santidepressant beliefs. Beca...

Electronic health records (EHRs) must support primary care clinicians and patients, yet many clinicians remain dissatisfied with their system. This article presents a consensus statement about gaps in current EHR functionality and needed enhancements to support primary care. The Institute of Medicine primary care attributes were used to define needs and meaningful use (MU) objectives to define EHR functionality. Current objectives remain focused on disease rather than the whole person, ignoring factors such as personal risks, behaviors, family structure, and occupational and environmental influences. Primary care needs EHRs to move beyond documentation to interpreting and tracking information over time, as well as patient-partnering activities, support for team-based care, population-management tools that deliver care, and reduced documentation burden. While stage 3 MU's focus on outcomes is laudable, enhanced functionality is still needed, including EHR modifications, expanded use of patient portals, seamless integration with external applications, and advancement of national infrastructure and policies.

Primary care differs considerably from specialist mental health settings: problems are presented in undifferentiated forms, with consequent difficulties in distinguishing between distress and disorder, and a complex relationship between psychological, mental and social problems and their temporal variations. Existing psychiatric diagnostic systems, including ICD-10-PHC and DSM-IV-PC, are often difficult to apply in primary care. They do not adequately address co-morbidity, the substantial prevalence of sub-threshold disorders or problems with cross-cultural applications. Their focus on diagnosis may be too restrictive, with a need to consider severity and impairment separately. ICPC-2, a classification system created specifically for use in primary care, provides advantages in that it allows for simple linkage between reason for encounter, diagnosis and intervention. It is both necessary and feasible to develop a classification system for mental health in primary care that can meet four basic criteria: (1) characterized by simplicity; (2) addressing not only diagnosis but also severity, chronicity and disability; (3) feasible for routine data gathering in primary care as well as for training; and (4) enabling efficient communication between primary and specialty mental health care.