You can, and should still install into Program Files, just don't expect to write into that folder. You can install software into App. Data if you want it to follow a user about in an Active Directory environment, which happens if you put it in App. Data\Roaming (the Special. Folder. Application. Data location). You can also install into App. Data if you want the software to be available to just the user that installs it. This can be useful if, for example, you have multiple users on the same machine, who all want to run different versions of the software in complete isolation. If you want settings to only apply on the local machine then you use App. Data\Local, which is Special. Folders. Local. Application. Data - this will make AD administrators very happen as the roaming profile size doesn't suddenly jump up 5. Mb or whatever the size of your software is. If you wanted to create settings which apply to all users then you're looking at Special. Folders. Common. Application. Data. You should remember never to rely on the actual name of the directory - localisation issues mean this can change and the location does change with OS versions two. You should be using the special folder enumeration in your software, or the equivalent in your installer. Could you not install into Program Files, but use App. Data as it's supposed to be used, and store your database in there?
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Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, SC, USAc. Abuse treatment between 19, was used to examine the impact of program transportation services on client retention in outpatient drug abuse treatment programs. DATOS methodology is described in detail elsewhere.Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USAAuthor for correspondence: Kathryn Magruder, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, 6. President Street, Charleston SC 2. USA. E- mail: ude. Drug Abuse Treatment Outcome Study US (DATOS-1991-1994). Transportation and retention in outpatient drug abuse treatment programs. Effects of readiness for drug abuse treatment on client retention and assessment of process. Research Notes Intensive Case Management Improves Welfare Clients Rates of Entry and Retention in Substance Abuse Treatment By Jon Morgenstern1, Annette Riordan2, Barbara S. McCrady3, Katharine H. McVeigh3, Kimberly A. SAMHSA's mission is to reduce the impact of substance abuse and mental illness on America's communities. 5600 Fishers Ln Rockville, MD 20857 1-877-SAMHSA-7 (1-877-726-4727). Transportation and retention in outpatient drug abuse treatment programs Friedmann, Peter D; Lemon, Stephenie C; Stein, Michael D To determine whether certain types of transportation assistance improve outpatient treatment. The publisher's final edited version of this article is available at Clin Trials. See other articles in PMC that cite the published article. Abstract. Background. Differential attrition by minority participants can be as limiting to interpreting final results as poor initial recruitment of minority participants. This is especially important in drug abuse treatment studies, as minorities are over- represented in substance abuse clinical treatment programs. Purpose. The specific aims of this secondary data analysis were to: (1) determine if there are differences in study retention rates by race/ethnicity and age, and (2) explore other client characteristics, as well as protocol and treatment program factors, that could account for differential retention rates. Methods. We conducted a secondary analysis using data from 1. NIDA Clinical Trials Network. Protocol level characteristics were also abstracted from these studies, and we used data from a study which assessed characteristics of community treatment programs that participated in these studies. Logistic regression was used to study the effect on retention of: client, protocol, and program characteristics. Results. In the model of client characteristics, a significant age by race/ethnicity interaction term was detected based on a threshold of 0. African Americans having the lowest odds of retention. To determine whether certain types of transportation assistance improve outpatient treatment retention beyond thresholds shown to have therapeutic benefits, we analyzed data from 1,144 clients in 22 outpatient methadone. Substance Abuse Outreach Programs: Comparative Effectiveness. Treatment Programs for Drug-Abusing Women. Retention Issues Involving Drug-Abusing Women in Treatment Research. Lack of transportation also influences treatment retention for many women. Drug programs rarely are found in. To determine whether certain types of transportation assistance improve outpatient treatment retention beyond thresholds shown to have therapeutic benefits, we. Primary drug of abuse was also a significant factor in determining study retention, with heroin, methadone, and opiate users having the greatest odds of retention and polydrug users the lowest. Similar analyses testing treatment program characteristics found that only the presence of HIV risk screening and decreasing levels of female admissions (as a percent of total admissions) were related to study retention. In our final model, there was an effect of age, but not race/ethnicity, with younger participants having lower odds of retention. A multivariable model including protocol variables could not be developed due to the high correlation among protocol variables. Limitations. We excluded those of multi- race/ethnicity and those from minority groups other than Hispanic or African American due to small numbers. Additionally, only three therapy types were represented among the six studies. Some potential variables that would influence retention, such as client housing, and client comorbidities, the race/ethnicity and gender of the staff who conducted study follow- up assessments, and reasons for loss to follow- up, were not collected by the CTN. Conclusions. Although in our client model older African Americans and Caucasians had the greatest odds of retention and younger African Americans the lowest, in our final model, only age was significantly related to study retention. Additionally, primary drug of abuse, having HIV risk screening as a program benefit, and lower percentages of female admissions were significantly related to study retention. Efforts should be made to increase the study retention of younger participants to improve the validity and generalizability of drug abuse treatment study results. Successful recruitment and retention of minority research participants is critical to addiction research and particularly for the National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) whose goal is to disseminate efficacious research findings in front- line community treatment programs. The CTN framework consists of 1. CTPs). By using front- line treatment settings as study sites, the CTN investigates the effectiveness of treatments which have demonstrated efficacy in academic medical settings. A core issue in effectiveness research is recruiting and retaining a heterogeneous study population so that the results will be generalizable to routine clinical practice. Much has been written concerning recruitment of minority participants in research projects (e. While retention is clearly related to recruitment (participants cannot complete a study unless recruited into it), recruitment and retention are still distinctly different components of the research process. Factors that influence a person to enroll in a research project may be different from those factors that influence a participant to drop out or stay in a project. It also should be noted that study retention is different from treatment retention. While clients who are retained in treatment may also be more apt to be retained in a research project, the two are not necessarily mutual. Some clients may be retained in a study for follow- up, but drop out of treatment, and vice versa. Under the intent- to- treat analytic approach to clinical trials, all patients randomized into the trial must be included in the primary analysis . Differential attrition by minority participants can be as limiting to interpreting final results as poor initial recruitment of minority participants. For this reason, it is imperative to study factors influencing minority participant retention in research, as without data on actual study endpoints it is impossible to understand the effects of an intervention and generalize findings to the intended patient subgroups. To date, the sparse data on reports of retention tend to support non- differential study attrition rates by minority status . Studies that look at retention in substance abuse treatment research have mixed reports of retention by minority status. These included: lifetime major depression (more common among Caucasian participants); unemployment problems (more severe for African Americans); and greater problem severity with substance abuse and psychological issues (higher for Caucasian participants). Retention issues may well be unique in research on substance use disorder (SUD) treatment, as SUDs are highly stigmatized conditions, and there are often legal, societal, and employment implications from being a person with a SUD as well as from undergoing treatment. The stigma of SUD treatment may be perceived differently by various ethnic/cultural groups. Furthermore, there may be differences in referral sources by race/ethnicity (e. Other factors which could impact retention rates differentially by race/ethnicity include: convenience and accessibility of treatment program, time of day, community and family pressures, special accommodations offered to participate (e. HIV testing, medical care), and research participation incentives. The modality of the investigational treatment may have different meaning for different race/ethnic groups. For example, reactions to pharmacotherapy, psychosocial, or group treatment may differ in various ethnic/cultural groups. The race/ethnicity of the treatment provider may also be a factor. It should be noted that gender and socio- economic class could also influence retention in a similar manner. To date, most studies have focused on individual participant characteristics as predictors of retention. A notable exception is a systematic review which identifies a number of active strategies (e. Studies with higher retention rates used more such strategies than studies with lower retention rates. Independent of active strategies, characteristics of specific sites that participate in studies (e. Additionally, characteristics of particular protocols (e. Archived CTN data offer a unique opportunity to examine not only individual client level characteristics, but also protocol and site characteristics in relation to participant study retention. The Resource Center on Minority Aging Research (RCMAR) at the Medical University of South Carolina (MUSC) includes a Community Liaison Core with the goal of assisting NIH- funded studies in addressing issues of minority recruitment and retention in older populations. RCMAR partnered with CTN investigators to design and conduct an analysis of secondary data from early studies conducted by the CTN. The specific aims of this secondary data analysis were to: (1) determine if there are differences in CTN study retention rates by race/ethnicity and age, and (2) explore protocol and treatment program factors and other client characteristics that could account for differential retention rates. Methods. Our study was approved by the Institutional Review Board of the Medical University of South Carolina. Additionally, each of the lead investigators of the CTN studies included in this secondary analysis signed data sharing agreements. Included in this analysis are data from the first six clinical trials whose databases were locked: CTN studies 1, 2, 5, 6, 7, and 1. We also made use of data from CTN study 8 which assessed characteristics of the community treatment programs that participated in the CTN. Appendix 1 shows the study title and principal investigator of each study. Participants were included in the retention analyses if they met study inclusion criteria and if they were randomized. The CTN data repository did not keep data on subjects who met eligibility criteria but were not randomized, nor did it collect data on reasons for loss to follow- up. Retention. An indicator variable was created and was set to 1 if the subject completed the final study assessment at which the major outcome variable was collected (as defined by the respective study protocols) or 0 if otherwise. This indicator variable was then used as the outcome of interest to conduct logistic regression analyses in SAS 9. Placement Report. 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