***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Background Many promising technological innovations in health and social care are characterized by nonadoption or ab and onment by individuals or by failed attempts to scale up locally , spread distantly , or sustain the innovation long term at the organization or system level . Objective Our objective was to produce an evidence -based , theory-informed , and pragmatic framework to help predict and evaluate the success of a technology-supported health or social care program . Methods The study had 2 parallel components : ( 1 ) secondary research ( hermeneutic systematic review ) to identify key domains , and ( 2 ) empirical case studies of technology implementation to explore , test , and refine these domains . We studied 6 technology-supported programs — video outpatient consultations , global positioning system tracking for cognitive impairment , pendant alarm services , remote biomarker monitoring for heart failure , care organizing software , and integrated case management via data sharing — using longitudinal ethnography and action research for up to 3 years across more than 20 organizations . Data were collected at micro level ( individual technology users ) , meso level ( organizational processes and systems ) , and macro level ( national policy and wider context ) . Analysis and synthesis was aided by sociotechnically informed theories of individual , organizational , and system change . The draft framework was shared with colleagues who were introducing or evaluating other technology-supported health or care programs and refined in response to feedback . Results The literature review identified 28 previous technology implementation frameworks , of which 14 had taken a dynamic systems approach ( including 2 integrative review s of previous work ) . Our empirical data set consisted of over 400 hours of ethnographic observation , 165 semistructured interviews , and 200 documents . The final nonadoption , ab and onment , scale-up , spread , and sustainability ( NASSS ) framework included questions in 7 domains : the condition or illness , the technology , the value proposition , the adopter system ( comprising professional staff , patient , and lay caregivers ) , the organization(s ) , the wider ( institutional and societal ) context , and the interaction and mutual adaptation between all these domains over time . Our empirical case studies raised a variety of challenges across all 7 domains , each classified as simple ( straightforward , predictable , few components ) , complicated ( multiple interacting components or issues ) , or complex ( dynamic , unpredictable , not easily disaggregated into constituent components ) . Programs characterized by complicatedness proved difficult but not impossible to implement . Those characterized by complexity in multiple NASSS domains rarely , if ever , became mainstreamed . The framework showed promise when applied ( both prospect ively and retrospectively ) to other programs . Conclusions Subject to further empirical testing , NASSS could be applied across a range of technological innovations in health and social care . It has several potential uses : ( 1 ) to inform the design of a new technology ; ( 2 ) to identify technological solutions that ( perhaps despite policy or industry enthusiasm ) have a limited chance of achieving large-scale , sustained adoption ; ( 3 ) to plan the implementation , scale-up , or rollout of a technology program ; and ( 4 ) to explain and learn from program failures Abstract Background : Existing studies regarding e-health are mostly focused on information technology design and implementation , system architecture and infrastructure , and its importance in public health with ancillaries and barriers to mass adoption . However , not enough studies have been conducted to assess the end-users ' reaction and acceptance behavior toward e-health , especially from the perspective of rural communities in developing countries . Objective : The objective of this study is to explore the factors that influence rural end users ' acceptance of e-health in Bangladesh . Methods : Data were collected between June and July 2016 through a field survey with structured question naire form 292 r and omly selected rural respondents from Bheramara subdistrict , Bangladesh .  Technology Acceptance Model was adopted as the research framework . Logistic regression analysis was performed to test the theoretical model . Results : The study found social reference as the most significantly influential variable ( Coef . = 2.28 , odds ratio [ OR ] = 9.73 , p < 0.01 ) followed by advertisement ( Coef . = 1.94 , OR = 6.94 , p < 0.01 ) ; attitude toward the system ( Coef . = 1.52 , OR = 4.56 , p < 0.01 ) ; access to cellphone ( Coef . = 1.37 , OR = 3.92 , p < 0.05 ) , and perceived system effectiveness ( Coef . = 0.74 , OR = 2.10 , p < 0.01 ) . Among demographic variables , age , gender , and education were found significant while we did not find any significant impact of respondents ' monthly family expenditure on their e-health acceptance behavior . The model explains 54.70 % deviance ( R2 = 0.5470 ) in the response variable with its constructs . The “ Hosmer-Lemeshow ” goodness-of-fit score ( 0.539 ) is also above the st and ard threshold ( 0.05 ) , which indicates that the data fit well with the model . Conclusion : The study provides guidelines for the successful adoption of e-health among rural communities in developing countries . This also creates an opportunity for e-health technology developers and service providers to have a better underst and ing of their end users Background Numerous Web-based interventions have been implemented to promote health and health-related behaviors in persons with chronic conditions . Using r and omized controlled trials to evaluate such interventions creates a range of challenges , which in turn can influence the study outcome . Applying a critical perspective when evaluating Web-based health interventions is important . Objective The objective of this study was to critically analyze and discuss the challenges of conducting a Web-based health intervention as a r and omized controlled trial . Method The MODIAB-Web study was critically examined using an exploratory case study methodology and the framework for analysis offered through the Persuasive Systems Design model . Focus was on technology , study design , and Web-based support usage , with special focus on the forum for peer support . Descriptive statistics and qualitative content analysis were used . Results The persuasive content and technological elements in the design of the r and omized controlled trial included all four categories of the Persuasive Systems Design model , but not all design principles were implemented . The study duration was extended to a period of four and a half years . Of 81 active participants in the intervention group , a maximum of 36 women were simultaneously active . User adherence  varied greatly with a median of 91 individual log-ins . The forum for peer support was used by 63 participants . Although only about one-third of the participants interacted in the forum , there was a fairly rich exchange of experiences and advice between them . Thus , adherence in terms of social interactions was negatively affected by limited active participation due to prolonged recruitment process and r and omization effects . Lessons learned from this critical analysis are that technology and study design matter and might mutually influence each other . In Web-based interventions , the use of design theories enables utilization of the full potential of technology and promotes adherence . The r and omization element in a r and omized controlled trial design can become a barrier to achieving a critical mass of user interactions in Web-based interventions , especially when social support is included . For extended study periods , the technology used may need to be adapted in line with newly available technical options to avoid the risk of becoming out date d in the user realm , which in turn might jeopardize study validity in terms of r and omized controlled trial design s. Conclusions On the basis of lessons learned in this r and omized controlled trial , we give recommendations to consider when design ing and evaluating Web-based health interventions BACKGROUND Large-scale cohort studies are needed to confirm the relation between dementia and its possible risk factors . The inclusion of people with dementia in research is a challenge , however , children of people with dementia are at risk and are highly motivated to participate in dementia research . For technologies to support home-based data collection during large-scale studies , participants should be able and willing to use technology for a longer period of time . OBJECTIVE This study investigated acceptance and usability of iVitality , a research platform for home-based monitoring of dementia health indicators , in 151 children of people with dementia and investigated which frequency of measurements is acceptable for them . METHODS Participants were r and omized to fortnightly or monthly measurements . At baseline and after 3 months , participants completed an online question naire regarding the acceptance ( Technology Acceptance Model ; 38 items ) and usability ( Post- Study System Usability Question naire ; 24 items ) of iVitality . Items were rated from 1 ( I totally disagree ) to 7 ( I totally agree ) . Participants were also invited to take part in an online focus group ( OFG ) after 3 months of follow-up . Descriptive statistics and both two- sample /independent and paired t-tests were used to analyze the online question naires and a directed content analysis was used to analyze the OFGs . RESULTS Children of people with dementia accept iVitality after long-term use and evaluate iVitality as a user-friendly , useful , and trusted technology , despite some suggestions for improvement . Overall , mean scores on acceptance and usability were higher than 5 ( I somewhat agree ) , although the acceptance subscales " social influence " and " time " were rated somewhat lower . No significant differences in acceptance and usability were found between both protocol groups . Over time , " affect " significantly increased among participants measuring blood pressure fortnightly . CONCLUSION iVitality has the potential to be used in large-scale studies for home-based monitoring of health indicators related to the development of dementia Twenty counties in Kansas were r and omly selected from those design ated as rural on the basis of their population s. A sample of 356 physicians and physicians ’ assistants in these counties was chosen . A postal survey was sent to the identified providers up to three times . One hundred and eighty-six of the question naires were returned ( a response rate of 52 % ) . In all , 76 % of the respondents were physicians , 76 % were men and 42 % were family practitioners . Practitioners were classified as adopters or non-adopters of telemedicine , based on their report of whether they had ever referred one or more patients for a health-care consultation via telemedicine . Of the 167 participants who marked this item , 30 ( 18 % ) were adopters and 1 37 ( 82 % ) were non-adopters . Among the adopters , 16 ( 53 % ) said that they expected to use telemedicine with about the same frequency or more often in the future . In contrast , 61 ( 45 % ) non-adopters reported that they did not expect to refer patients by telemedicine  in the future and 51 ( 37 % ) were unsure . Neither age ( r=0.16 , P = 0.44 ) nor gender ( χ2 = 2.35 , P = 0.1 3 ) was related to the adoption variable or the number of referrals made to telemedicine clinics . The results suggest that adopters and non-adopters of telemedicine perceive its value very differently , and that an opportunity exists to promote the concept to non-adopters more effectively OBJECTIVE Cognitive support technologies that support clinical decisions and practice s in the emergency department ( ED ) have the potential to optimize patient care . However , limited uptake by clinicians can prevent successful implementation . A better underst and ing of acceptance of these technologies from the clinician perspective is needed . We conducted a scoping review to synthesize diverse , emerging evidence on clinicians ' acceptance of point-of-care ( POC ) cognitive support technology in the ED . METHOD We systematic ally search ed 10 electronic data bases and gray literature published from January 2006 to December 2016 . Studies of any design assessing an ED-based POC cognitive support technology were considered eligible for inclusion . Studies were required to report outcome data for technology acceptance . Two review ers independently screened studies for relevance and quality . Study quality was assessed using the Mixed- Methods Appraisal Tool . A descriptive analysis of the features of POC cognitive support technology for each study is presented , illustrating trends in technology development and evaluation . A thematic analysis of clinician , technical , patient , and organizational factors associated with technology acceptance is also presented . RESULTS Of the 1,563 references screened for eligibility , 24 met the inclusion criteria and were included in the review . Most studies were published from 2011 onward ( 88 % ) , scored high for method ologic quality ( 79 % ) , and examined POC technologies that were novel and newly introduced into the study setting ( 63 % ) . Physician use of POC technology was the most commonly studied ( 67 % ) . Technology acceptance was frequently conceptualized and measured by factors related to clinician attitudes and beliefs . Experience with the technology , intention to use , and actual use were also more common outcome measures of technology acceptance . Across studies , perceived usefulness was the most noteworthy factor impacting technology acceptance , and clinicians generally had positive perceptions of the use of POC cognitive support technology in the ED . However , the actual use of POC cognitive support technology reported by clinicians was low-use , by proportion of patient cases , ranged from 30 % to 59 % . Of the 24 studies , only two studies investigated acceptance of  POC cognitive support technology currently implemented in the ED , offering " real-world " clinical practice data . All other studies focused on acceptance of novel technologies . Technical aspects such as an unfriendly user interface , presentation of redundant or ambiguous information , and required user effort had a negative impact on acceptance . Patient expectations were also found to have a negative impact , while patient safety implication s had a positive impact . Institutional support was also reported to impact technology acceptance . CONCLUSIONS Findings from this scoping review suggest that while ED clinicians acknowledge the utility and value of using POC cognitive support technology , actual use of such technology can be low . Further , few studies have evaluated the acceptance and use of POC technologies in routine care . Prospect i ve studies that evaluate how ED clinicians appraise and consider POC technology use in clinical practice are now needed with diverse clinician sample s. While this review identified multiple factors contributing to technology acceptance , determining how clinician , technical , patient , and organizational factors mediate or moderate acceptance should also be a priority 
    Output:
    
The results show a superiority of technology acceptance versus original behavioral models .
Conclusions The main finding of this review is the applicability of technology acceptance models and theories on telemedicine adoption .
Characteristics of the technology , such as its usefulness , as well as attributes of the individual , such as his or her need for social support , inform end-user acceptance .