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10.1016/j.chb.2020.106456 http://scihub22266oqcxt.onion/10.1016/j.chb.2020.106456 C7305511!7305511 !32834465     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32834465 &cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Comput+Human+Behav 2020 ; 112 (?): 106456 Nephropedia Template TP {{tp|p=32834465 |t=2020. Mobile technology adoption across the lifespan: A mixed methods investigation to clarify adoption stages, and the influence of diffusion attributes |pdf=|usr=}}{{32834465 }} gab.com Text Mobile technology adoption across the lifespan: A mixed methods investigation to clarify adoption stages, and the influence of diffusion attributes JO: Comput Human Behav http://www.kidney.de/pget.php?&tw=1&pmid=32834465 #FOAvip We conducted a multi-study, mixed-methods, longitudinal investigation to examine how mobile technology diffuses across the lifespan, in real time, within a multi-generational population, while seeking local knowledge through community-based participatory research. Using qualitative methods (QUAL), we examined technology adoption within and across three iterations (16 weeks) of a nine-wave longitudinal community technology-training workshop, situated within a 15-wave study. In parallel, we interrogated existing conceptualization and operationalization of diffusion of technology variables, then deductively evaluated the dominant DOI-related variables re-conceptualized through the community study in a large cross-sectional quantitative (QUAN) investigation. We interpreted our results consistently and iteratively with a mixed-methods approach that included conceptualization, operationalization, and empirical testing. We discovered that oft-conflated concepts of knowledge, use, and ownership represent distinct stages of adoption. Our findings suggest constant feedback/permeable boundaries between these stages, and that DOI attributes may influence mobile technology adoption stages differentially. We suggest that innovators seeking to facilitate mobile technology adoption should focus on reducing complexity, and establishing calibration of complexity perceptions. We propose a lifespan mobile technology diffusion model, and call to question the language used in investigations related to the digital divide. We strive to clarify labels that may stereotype vulnerable populations, such as older adults. Our research contributes to theories of technology adoption - particularly after the introduction of digital communication - the diffusion of innovations in the community over time, and technology adoption process as affected by interpersonal communication and relationships, including among the technologically undercapitalized and the digitally privileged. Twit Text FOAVip Mobile technology adoption across the lifespan: A mixed methods investigation to clarify adoption stages, and the influence of diffusion attributes ????Comput Human Behav http://www.kidney.de/pget.php?&tw=1&pmid=32834465 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32834465 #FOAvip English Wikipedia <ref>{{Cite pmid|32834465 }}</ref> Mobile technology adoption across the lifespan: A mixed methods investigation to clarify adoption stages, and the influence of diffusion attributes #MMPMID32834465 Magsamen-Conrad K ; Dillon JM Comput Human Behav 2020[Nov]; 112 (?): 106456 PMID32834465 show ga We conducted a multi-study, mixed-methods, longitudinal investigation to examine how mobile technology diffuses across the lifespan, in real time, within a multi-generational population, while seeking local knowledge through community-based participatory research. Using qualitative methods (QUAL), we examined technology adoption within and across three iterations (16 weeks) of a nine-wave longitudinal community technology-training workshop, situated within a 15-wave study. In parallel, we interrogated existing conceptualization and operationalization of diffusion of technology variables, then deductively evaluated the dominant DOI-related variables re-conceptualized through the community study in a large cross-sectional quantitative (QUAN) investigation. We interpreted our results consistently and iteratively with a mixed-methods approach that included conceptualization, operationalization, and empirical testing. We discovered that oft-conflated concepts of knowledge, use, and ownership represent distinct stages of adoption. Our findings suggest constant feedback/permeable boundaries between these stages, and that DOI attributes may influence mobile technology adoption stages differentially. We suggest that innovators seeking to facilitate mobile technology adoption should focus on reducing complexity, and establishing calibration of complexity perceptions. We propose a lifespan mobile technology diffusion model, and call to question the language used in investigations related to the digital divide. We strive to clarify labels that may stereotype vulnerable populations, such as older adults. Our research contributes to theories of technology adoption - particularly after the introduction of digital communication - the diffusion of innovations in the community over time, and technology adoption process as affected by interpersonal communication and relationships, including among the technologically undercapitalized and the digitally privileged. ?Mobile technology adoption across the lifespan: A mixed methods invest(epmc).pdf DeepDyve Pubget Overpricing