Evidence-based review of interventions for medically at-risk older drivers.
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ABSTRACT:
SUBMITTER: Classen S
PROVIDER: S-EPMC4086415 | biostudies-literature | 2014 Jul-Aug
REPOSITORIES: biostudies-literature
Publications
Evidence-based review of interventions for medically at-risk older drivers.
Classen Sherrilene S Monahan Miriam M Auten Beth B Yarney Abraham A
The American journal of occupational therapy : official publication of the American Occupational Therapy Association 20140701 4
OBJECTIVE. To conduct an evidence-based review of intervention studies of older drivers with medical conditions. METHOD. We used the American Occupational Therapy Association's classification criteria (Levels I-V, I = highest level of evidence) to identify driving interventions. We classified studies using letters to represent the strength of recommendations: A = strongly recommend the intervention; B = recommend intervention is provided routinely; C = weak evidence that the intervention can imp ...[more]
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Project description:BACKGROUND:With the aging of the population, the number of older drivers is on the rise. This poses significant challenges for public health initiatives, as older drivers have a relatively higher risk for collisions. While many studies focus on developing screening tools to identify medically at-risk drivers, little research has been done to develop training programs or interventions to promote, maintain or enhance driving-related abilities among healthy individuals. The purpose of this systematic review is to synopsize the current literature on interventions that are tailored to improve driving in older healthy individuals by working on components of safe driving such as: self-awareness, knowledge, behaviour, skills and/or reducing crash/collision rates in healthy older drivers. METHODS:Relevant databases such as Scopus and PubMed databases were selected and searched for primary articles published in between January 2007 and December 2017. Articles were identified using MeSH search terms: ("safety" OR "education" OR "training" OR "driving" OR "simulator" OR "program" OR "countermeasures") AND ("older drivers" OR "senior drivers" OR "aged drivers" OR "elderly drivers"). All retrieved abstracts were reviewed, and full texts printed if deemed relevant. RESULTS:Twenty-five (25) articles were classified according to: 1) Classroom settings; 2) Computer-based training for cognitive or visual processing; 3) Physical training; 4) In-simulator training; 5) On-road training; and 6) Mixed interventions. Results show that different types of approaches have been successful in improving specific driving skills and/or behaviours. However, there are clear discrepancies on how driving performance/behaviours are evaluated between studies, both in terms of methods or dependent variables, it is therefore difficult to make direct comparisons between these studies. CONCLUSIONS:This review identified strong study projects, effective at improving older drivers' performance and thus allowed to highlight potential interventions that can be used to maintain or improve older drivers' safety behind the wheel. There is a need to further test these interventions by combining them and determining their effectiveness at improving driving performance.
| S-EPMC7119079 | biostudies-literature
Project description:Fear of falling presents a significant problem for many older adults by reducing physical function and increasing the risk of future falls. Several different types of interventions have improved fear of falling and a summary of efficacious interventions will help clinicians recommend treatment options. Using the Arksey and O'Malley Framework for scoping reviews, the purpose of this review was to identify efficacious interventions for treating fear of falling among community-dwelling older adults in order to provide a list of potential treatment options for care providers. A total of 45 publications were identified for inclusion in this review.
| S-EPMC5862787 | biostudies-literature
Project description:BackgroundUntil now, the use of technology in health care was driven mostly by the assumptions about the benefits of electronic health (eHealth) rather than its evidence. It is noticeable that the magnitude of evidence of effectiveness and efficiency of eHealth is not proportionate to the number of interventions that are regularly conducted. Reliable evidence generated through comprehensive evaluation of eHealth interventions may accelerate the growth of eHealth for long-term successful implementation and help to experience eHealth benefits in an enhanced way.ObjectiveThis study aimed to understand how the evidence of effectiveness and efficiency of eHealth can be generated through evaluation. Hence, we aim to discern (1) how evaluation is conducted in distinct eHealth intervention phases, (2) the aspects of effectiveness and efficiency that are typically evaluated during eHealth interventions, and (3) how eHealth interventions are evaluated in practice.MethodsA systematic literature review was conducted to explore the evaluation methods for eHealth interventions. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were followed. We searched Google Scholar and Scopus for the published papers that addressed the evaluation of eHealth or described an eHealth intervention study. A qualitative analysis of the selected papers was conducted in several steps.ResultsWe intended to see how the process of evaluation unfolds in distinct phases of an eHealth intervention. We revealed that in practice and in several conceptual papers, evaluation is performed at the end of the intervention. There are some studies that discuss the importance of conducting evaluation throughout the intervention; however, in practice, we found no case study that followed this. For our second research question, we discovered aspects of efficiency and effectiveness that are proposed to be assessed during interventions. The aspects that were recurrent in the conceptual papers include clinical, human and social, organizational, technological, cost, ethical and legal, and transferability. However, the case studies reviewed only evaluate the clinical and human and social aspects. At the end of the paper, we discussed a novel approach to look into the evaluation. Our intention was to stir up a discussion around this approach with the hope that it might be able to gather evidence in a comprehensive and credible way.ConclusionsThe importance of evidence in eHealth has not been discussed as rigorously as have the diverse evaluation approaches and evaluation frameworks. Further research directed toward evidence-based evaluation can not only improve the quality of intervention studies but also facilitate successful long-term implementation of eHealth in general. We conclude that the development of more robust and comprehensive evaluation of eHealth studies or an improved validation of evaluation methods could ease the transferability of results among similar studies. Thus, the resources can be used for supplementary research in eHealth.
| S-EPMC6286426 | biostudies-literature
Project description:BackgroundIn primary and secondary care medically unexplained symptoms (MUS) or functional somatic syndromes (FSS) constitute a major burden for patients and society with high healthcare costs and societal costs. Objectives were to provide an overview of the evidence regarding the cost-effectiveness of interventions for MUS or FSS, and to assess the quality of these studies.MethodsWe searched the databases PubMed, PsycINFO, the National Health Service Economic Evaluation Database (NHS-EED) and the CEA registry to conduct a systematic review. Articles with full economic evaluations on interventions focusing on adult patients with undifferentiated MUS or fibromyalgia (FM), irritable bowel syndrome (IBS) and chronic fatigue syndrome (CFS), with no restrictions on comparators, published until 15 June 2018, were included. We excluded preventive interventions. Two reviewers independently extracted study characteristics and cost-effectiveness data and used the Consensus on Health Economic Criteria Checklist to appraise the methodological quality.ResultsA total of 39 studies out of 1,613 articles met the inclusion criteria. Twenty-two studies reported costs per quality-adjusted life year (QALY) gained and cost-utility analyses (CUAs). In 13 CUAs the intervention conditions dominated the control conditions or had an incremental cost-effectiveness ratio below the willingness-to-pay threshold of € 50,000 per QALY, meaning that the interventions were (on average) cost-effective in comparison with the control condition. Group interventions focusing on MUS (n = 3) or FM (n = 4) might be more cost-effective than individual interventions. The included studies were heterogeneous with regard to the included patients, interventions, study design, and outcomes.ConclusionThis review provides an overview of 39 included studies of interventions for patients with MUS and FSS and the methodological quality of these studies. Considering the limited comparability due to the heterogeneity of the studies, group interventions might be more cost-effective than individual interventions.RegistrationStudy methods were documented in an international prospective register of systematic reviews (PROSPERO) protocol, registration number: CRD42017060424.
| S-EPMC6188754 | biostudies-literature
Project description:BackgroundAlignment (i.e., the process of creating fit between elements of the inner and outer context of an organization or system) in conjunction with implementation of an evidence-based intervention (EBI) has been identified as important for implementation outcomes. However, research evidence has so far not been systematically summarized. The aim of this scoping review is therefore to create an overview of how the concept of alignment has been applied in the EBI implementation literature to provide a starting point for future implementation efforts in health care.MethodsWe searched for peer-reviewed English language articles in four databases (MEDLINE, Cinahl, Embase, and Web of Science) published between 2003 and 2019. Extracted data were analyzed to address the study aims. A qualitative content analysis was carried out for items with more extensive information. The review was reported according to the preferred reporting items for systematic reviews and meta-analyses extension for scoping review (PRISMA-ScR) guidelines.ResultsThe database searches yielded 3629 publications, of which 235 were considered potentially relevant based on the predetermined eligibility criteria, and retrieved in full text. In this review, the results of 53 studies are presented. Different definitions and conceptualizations of alignment were found, which in general could be categorized as structural, as well as social, types of alignments. Whereas the majority of studies viewed alignment as important to understand the implementation process, only a few studies actually assessed alignment. Outcomes of alignment were focused on either EBI implementation, EBI sustainment, or healthcare procedures. Different actors were identified as important for creating alignment and five overall strategies were found for achieving alignment.ConclusionsAlthough investigating alignment has not been the primary focus of studies focusing on EBI implementation, it has still been identified as an important factor for the implementation success. Based on the findings from this review, future research should incorporate alignment and put a stronger emphasize on testing the effectiveness of alignment related to implementation outcomes.
| S-EPMC8554825 | biostudies-literature
Project description:AimThis article reports the effects of three evidence-based interventions of varying intensity, each designed to improve outcomes of hospitalized cognitively impaired older adults.Materials & methodsIn this comparative effectiveness study, 202 older adults with cognitive impairment (assessed within 24 h of index hospitalization) were enrolled at one of three hospitals within an academic health system. Each hospital was randomly assigned one of the following interventions: Augmented Standard Care (ASC; lower dose: n = 65), Resource Nurse Care (RNC; medium dose: n = 71) or the Transitional Care Model (TCM; higher dose: n = 66). Since randomization at the patient level was not feasible due to potential contamination, generalized boosted modeling that estimated multigroup propensity score weights was used to balance baseline patient characteristics between groups. Analyses compared the three groups on time with first rehospitalization or death, the number and days of all-cause rehospitalizations per patient and functional status through 6-month postindex hospitalization.ResultsIn total, 25% of the ASC group were rehospitalized or died by day 33 compared with day 58 for the RNC group versus day 83 for the TCM group. The largest differences between the three groups on time to rehospitalization or death were observed early in the Kaplan-Meier curve (at 30 days: ASC = 22% vs RNC = 19% vs TCM = 9%). The TCM group also demonstrated lower mean rehospitalization rates per patient compared with the RNC (p < 0.001) and ASC groups (p = 0.06) at 30 days. At 90-day postindex hospitalization, the TCM group continued to demonstrate lower mean rehospitalization rates per patient only when compared with the ASC group (p = 0.02). No significant group differences in functional status were observed.ConclusionFindings suggest that the TCM intervention, compared with interventions of lower intensity, has the potential to decrease costly resource use outcomes in the immediate postindex hospitalization period among cognitively impaired older adults.
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Project description:BackgroundEvidence on technology-based psychological interventions (TBIs) for the treatment of depression is rapidly growing and covers a broad scope of research. Despite extensive research in this field, guideline recommendations are still limited to the general effectiveness of TBIs.ObjectiveThis study aims to structure evidence on TBIs by considering different application areas (eg, TBIs for acute treatment and their implementation in health care, such as stand-alone interventions) and treatment characteristics (eg, therapeutic rationale of TBIs) to provide a comprehensive evidence base and to identify research gaps in TBIs for diagnosed depression. Moreover, the reporting of negative events in the included studies is investigated in this review to enable subsequent safety assessment of the TBIs.MethodsRandomized controlled trials on adults diagnosed with unipolar depression receiving any kind of psychotherapeutic treatment, which was at least partly delivered by a technical medium, were eligible for inclusion in our preregistered systematic review. We searched for trials in CENTRAL (Cochrane Central Register of Controlled Trials; until August 2020), MEDLINE, PsycINFO, PSYNDEX, CINAHL; until the end of January 2018), clinical trial registers, and sources of gray literature (until the end of January 2019). Study selection and data extraction were conducted by 2 review authors independently.ResultsDatabase searches resulted in 15,546 records, of which 241 publications were included, representing 83 completed studies and 60 studies awaiting classification (ie, preregistered studies, study protocols). Almost all completed studies (78/83, 94%) addressed the acute treatment phase, being largely either implemented as stand-alone interventions (66/83, 80%) or blended treatment approaches (12/83, 14%). Studies on TBIs for aftercare (4/83, 5%) and for bridging waiting periods (1/83, 1%) were scarce. Most TBI study arms (n=107) were guided (59/107, 55.1%), delivered via the internet (80/107, 74.8%), and based on cognitive behavioral treatment approaches (88/107, 79.4%). Almost all studies (77/83, 93%) reported information on negative events, considering dropouts from treatment as a negative event. However, reports on negative events were heterogeneous and largely unsystematic.ConclusionsResearch has given little attention to studies evaluating TBIs for aftercare and for bridging waiting periods in people with depression, even though TBIs are seen as highly promising in these application areas; thus, high quality studies are urgently needed. In addition, the variety of therapeutic rationales on TBIs has barely been represented by identified studies hindering the consideration of patient preferences when planning treatment. Finally, future studies should use specific guidelines to systematically assess and report negative events.Trial registrationInternational Prospective Register of Systematic Reviews (PROSPERO) CRD42016050413; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42016050413.International registered report identifier (irrid)RR2-10.1136/bmjopen-2018-028042.
| S-EPMC7904404 | biostudies-literature
Project description:BackgroundHealth authorities recommend educating diabetic patients and their families and initiating measures aimed at improving self-management, promoting a positive behavior change, and reducing the risk of complications. Social media could provide valid channel to intervene in and deliver diabetes education. However, it is not well known whether the use of these channels in such interventions can help improve the patients' outcomes.ObjectiveThe objective of our study was to review and describe the current existing evidence on the use of social media in interventions targeting people affected with diabetes.MethodsA search was conducted across 4 databases (PubMed, Scopus, EMBASE, and Cochrane Library).The quality of the evidence of the included primary studies was graded according to the Grading of Recommendations Assessment, Development and Evaluation criteria, and the risk of bias of systematic reviews was assessed by drawing on AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines. The outcomes reported by these studies were extracted and analyzed.ResultsWe included 20 moderate- and high-quality studies in the review: 17 primary studies and 3 systematic reviews. Of the 16 publications evaluating the effect on glycated hemoglobin (HbA1c) of the interventions using social media, 13 reported significant reductions in HbA1c values. The 5 studies that measured satisfaction with the interventions using social media found positive effects. We found mixed evidence regarding the effect of interventions using social media on health-related quality of life (2 publications found positive effects and 3 found no differences) and on diabetes knowledge or empowerment (2 studies reported improvements and 2 reported no significant changes).ConclusionsThere is very little good-quality evidence on the use of social media in interventions aimed at helping people with diabetes. However, the use of these channels is mostly linked to benefits on patients' outcomes. Public health institutions, clinicians, and other stakeholders who aim at improving the knowledge of diabetic patients could consider the use of social media in their interventions.
| S-EPMC6109225 | biostudies-literature
Project description:BackgroundAdaptations of evidence-based interventions (EBIs) often occur. However, little is known about the reasons for adaptation, the adaptation process, and outcomes of adapted EBIs. To address this gap, we conducted a systematic review to answer the following questions: (1) What are the reasons for and common types of adaptations being made to EBIs in community settings as reported in the published literature? (2) What steps are described in making adaptations to EBIs? and (3) What outcomes are assessed in evaluations of adapted EBIs?MethodsWe conducted a systematic review of English language publications that described adaptations of public health EBIs. We searched Ovid PubMed, PsycINFO, PsycNET, and CINAHL and citations of included studies for adapted public health EBIs. We abstracted characteristics of the original and adapted populations and settings, reasons for adaptation, types of modifications, use of an adaptation framework, adaptation steps, and evaluation outcomes.ResultsForty-two distinct EBIs were found focusing on HIV/AIDS, mental health, substance abuse, and chronic illnesses. More than half (62%) reported on adaptations in the USA. Frequent reasons for adaptation included the need for cultural appropriateness (64.3%), focusing on a new target population (59.5%), and implementing in a new setting (57.1%). Common adaptations were content (100%), context (95.2%), cultural modifications (73.8%), and delivery (61.9%). Most study authors conducted a community assessment, prepared new materials, implemented the adapted intervention, evaluated or planned to evaluate the intervention, determined needed changes, trained staff members, and consulted experts/stakeholders. Most studies that reported an evaluation (k = 36) included behavioral outcomes (71.4%), acceptability (66.7%), fidelity (52.4%), and feasibility (52.4%). Fewer measured adoption (47.6%) and changes in practice (21.4%).ConclusionsThese findings advance our understanding of the patterns and effects of modifications of EBIs that are reported in published studies and suggest areas of further research to understand and guide the adaptation process. Furthermore, findings can inform better reporting of adapted EBIs and inform capacity building efforts to assist health professionals in adapting EBIs.
| S-EPMC6158804 | biostudies-literature
Project description:Machine-learning based risk prediction models have the potential to improve patient outcomes by assessing risk more accurately than clinicians. Significant additional value lies in these models providing feedback about the factors that amplify an individual patient's risk. Identification of risk factors enables more informed decisions on interventions to mitigate or ameliorate modifiable factors. For these reasons, risk prediction models must be explainable and grounded on medical knowledge. Current machine learning-based risk prediction models are frequently 'black-box' models whose inner workings cannot be understood easily, making it difficult to define risk drivers. Since machine learning models follow patterns in the data rather than looking for medically relevant relationships, possible risk factors identified by these models do not necessarily translate into actionable insights for clinicians. Here, we use the example of risk assessment for postoperative complications to demonstrate how explainable and medically grounded risk prediction models can be developed. Pre- and postoperative risk prediction models are trained based on clinically relevant inputs extracted from electronic medical record data. We show that these models have similar predictive performance as models that incorporate a wider range of inputs and explain the models' decision-making process by visualizing how different model inputs and their values affect the models' predictions.
| S-EPMC9200841 | biostudies-literature