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Abstract Background Dissemination is a critical facet of implementing quality improvement in organizations. As a field, addiction treatment has produced effective interventions but disseminated them slowly and reached only a fraction of people needing treatment. This study investigates four methods of disseminating quality improvement (QI) to addiction treatment programs in the U.S. It is, to our knowledge, the largest study of organizational change ever conducted in healthcare. The trial seeks to determine the most cost-effective method of disseminating quality improvement in addiction treatment. Methods The study is evaluating the costs and effectiveness of different QI approaches by randomizing 201 addiction-treatment programs to four interventions. Each intervention used a web-based learning kit plus monthly phone calls, coaching, face-to-face meetings, or the combination of all three. Effectiveness is defined as reducing waiting time (days between first contact and treatment), increasing program admissions, and increasing continuation in treatment. Opportunity costs will be estimated for the resources associated with providing the services. Outcomes The study has three primary outcomes: waiting time, annual program admissions, and continuation in treatment. Secondary outcomes include: voluntary employee turnover, treatment completion, and operating margin. We are also seeking to understand the role of mediators, moderators, and other factors related to an organization's success in making changes. Analysis We are fitting a mixed-effect regression model to each program's average monthly waiting time and continuation rates (based on aggregated client records), including terms to isolate state and intervention effects. Admissions to treatment are aggregated to a yearly level to compensate for seasonality. We will order the interventions by cost to compare them pair-wise to the lowest cost intervention (monthly phone calls). All randomized sites with outcome data will be included in the analysis, following the intent-to-treat principle. Organizational covariates in the analysis include program size, management score, and state. Discussion The study offers seven recommendations for conducting a large-scale cluster-randomized trial: provide valuable services, have aims that are clear and important, seek powerful allies, understand the recruiting challenge, cultivate commitment, address turnover, and encourage rigor and flexibility. Trial Registration ClinicalTrials. govNCT00934141

The purpose of this study was to investigate the nature and effects of exchanging emotional support via a smartphone-based support group for patients with alcohol dependence. Of the 349 patients who met the Diagnostic and Statistical Manual of Mental Disorders (4th ed.) criteria for alcohol dependence, 153 patients participated in the discussion group within the Addiction-Comprehensive Health Enhancement Support System, a smartphone application aimed at reducing relapse. This was developed to prevent problem drinking by offering individuals in recovery for alcohol dependence automated 24/7 recovery support services and frequent assessment of their symptom status as part of their addiction care. The results showed that receiving emotional support from health care providers improved coping self-efficacy. Giving emotional support and receiving emotional support from health care providers acted as a buffer, protecting patients from the harmful effects of emotional distress on risky drinking. Clinicians and researchers should use the features of smartphone-based support groups to reach out to alcoholic patients in need and encourage them to participate in the exchange of emotional support with others. [ABSTRACT FROM AUTHOR]

Abstract Background The assessment of needs for cancer care is a critical step in providing high quality care and achieving cancer patients' and families' satisfaction. Instruments can be used to assess needs and guide cancer care planning. This study discusses the importance of the needs assessment, relationships between needs, satisfaction and quality of life; and reviews the assessment instruments of needs experienced by cancer patients and their families. Methods A systematic search was conducted in MEDLINE and CANCERLIT data bases. Instruments were evaluated based on their conceptual and measurement models as well as their demonstrated reliability and validity. The authors also sought information pertaining to instruments' burden of administration and responsiveness. Measures compromised by a lack of published psychometric description were not included. Results This search identified 17 patient needs assessment instruments and seven family needs assessment instruments. The development and psychometric proprieties of most of these instruments were well documented. However, data on their responsiveness and burden of administration were scarce. Conclusions Each selected instrument meets some but not all of our criteria for validity, reliability, responsiveness and burden. It is questionable whether any instrument can be developed meeting all the requirements. However, there is still a need to continue researching and developing needs assessment instruments leading to effective intervention and improving quality of cancer care.

Byline: Hsi-Peng Lu, David H. Gustafson Interactive computerised support systems (CSS) providing confidential, convenient and logical aids might be useful for crisis people (e.g. AIDS/HIV+) who are isolated from services for geographic, economic, emotional or social reasons. Such interactive systems are usually designed for voluntary and repeated use, and the individual's cognitive styles may be crucial to the success of the system design. This paper first introduces a theoretical framework of cognitive styles and repeated CSS use, then a medical CSS for HIV+/AIDS, and finally an empirical study on the relationships between individual cognitive styles and voluntary computer use over time is discussed.

Recent studies have devoted attention to the effects of both expression and reception in communication process. However, there remain both theoretical and methodological complexities concerning whether and under what condition message expression and reception play significant but different roles in explaining various psychosocial health outcomes. Relying on theoretical insights from the social support literature and methodological innovations offered by computational social science, this study aims to examine the effects of empathic exchanges on cancer patient's short- and long-term psychosocial health outcomes. Our findings suggest that both empathy expression and reception are crucial to attaining benefits for cancer patients, each predicting differential cognitive and affective health outcomes. Further, our finding supports the stress-buffering hypothesis such that empathy reception provides a beneficial effect for patients who experienced a higher degree of depression associated with their cancer diagnosis and follow-up treatments. [ABSTRACT FROM AUTHOR]

This study examined the interplay of depression and different types of e-health interventions on breast cancer patients' perceived healthcare competence, emotional processing, and social well-being over time. The three e-health interventions--Internet Only as a control condition, CHESS (Comprehensive Health Enhancement Support System) Only, and CHESS with a Human Mentor, a cancer information specialist--provided varying degrees of interactivity and presence. A total of 328 women with breast cancer participated in one of the three interventions for a 6-month period. Women were further split into two groups based on reported levels of depression. For perceived healthcare competence and social well-being, results revealed significant interaction effects for intervention type by depression over time, such that breast cancer patients with higher levels of depression benefited most from the CHESS with Mentor intervention over the 6-month study period. For emotional processing, depressed cancer patients benefited more from the CHESS with Mentor than the other two interventions, regardless of time. These findings have (a) theoretical implications on how mental health factors can intersect with interactivity and presence to influence psychosocial outcomes, (b) conceptual implications for the role of human interaction within e-health systems, and (c) practical implications for the development of e-health interventions for cancer patients with depression. [ABSTRACT FROM AUTHOR]

Increasingly, individuals with alcohol use disorder (AUD) seek and provide support for relapse prevention in text-based online environments such as discussion forums. This paper investigates whether language use within a peer-to-peer discussion forum can predict future relapse among individuals treated for AUD. A total of 104 AUD sufferers who had completed residential treatment participated in a mobile phone-based relapse-prevention program, where they communicated via an online forum over the course of a year. We extracted patterns of language use on the forum within the first four months on study using Linguistic Inquiry and Word Count (LIWC), a dictionary-based text analysis program. Participants reported their incidence of risky drinking via a survey at 4, 8, and 12 months. A logistic regression model was built to predict the likelihood that individuals would engage in risky drinking within a year based on their language use, while controlling for baseline characteristics and rates of utilizing the mobile system. Results show that all baseline characteristics and system use factors explained just 13% of the variance in relapse, whereas a small number of linguistic cues, including swearing and cognitive mechanism words, accounted for an additional 32% of the total 45% of variance in relapse explained by the model. Effective models for predicting relapse are needed. Messages exchanged on AUD forums could provide an unobtrusive and cost-effective window into the future health outcomes of AUD sufferers, and their psychological underpinnings. As online communication expands, models that leverage user-submitted text toward predicting relapse will be increasingly scalable and actionable. [ABSTRACT FROM AUTHOR]