23 research outputs found
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"Call a Teenager… That's What I Do!" - Grandchildren Help Older Adults Use New Technologies: Qualitative Study.
BackgroundAlthough family technical support seems intuitive, there is very little research exploring this topic.ObjectiveThe objective of this study was to conduct a subanalysis of data collected from a large-scale qualitative project regarding older adults' experiences in using health information technology. Specifically, the subanalysis explored older adults' experiences with technology support from family members to inform strategies for promoting older adults' engagement with new health technologies. Although the primary analysis of the original study was theoretically driven, this paper reports results from an inductive, open-coding analysis.MethodsThis is a subanalysis of a major code identified unexpectedly from a qualitative study investigating older adults' use experience of a widespread health technology, the patient portal. A total of 24 older patients (≥65 years) with multiple chronic conditions (Charlson Comorbidity Index >2) participated in focus groups conducted at the patients' primary clinic. While conducting the primary theoretically driven analysis, coders utilized an open-coding approach to ensure important ideas not reflected in the theoretical code book were captured. Open coding resulted in 1 code: family support. This subanalysis further categorized family support by who provided tech support, how tech support was offered, and the opinions of older participants about receiving family tech support.ResultsThe participants were not specifically asked about family support, yet themes around family assistance and encouragement for technology emerged from every focus group. Participants repeatedly mentioned that they called their grandchildren and adult children if they needed help with technology. Participants also reported that family members experienced difficulty when teaching technology use. Family members struggled to explain simple technology tasks and were frustrated by the slow teaching process.ConclusionsThe results suggest that older adults ask their family members, particularly grandchildren, to support them in the use of new technologies. However, family may experience difficulties in providing this support. Older adults will be increasingly expected to use health technologies, and family members may help with tech support. Providers and health systems should consider potential family support and engagement strategies to foster adoption and use among older patients
The Lantern Vol. 37, No. 1, Fall 1970
• Circumstance • Advice • For What You Do For Me • Blink • Love • Love II • Magic • To Be a Child • A Year Later • A Poem in February • The Crystal Brick Road • Ephemera • Life • Whiskers • Thoughts On Being Sick • A Non-Poem • A Gruk Anthology • Moon • A Thought • Dwarf in an Existential Dawn • Corridors To My Mind • Sadness • The Enzyme Song • Creatures of Sandhttps://digitalcommons.ursinus.edu/lantern/1098/thumbnail.jp
D. Messer, The development of communication: from social interaction to language. Chichester: John Wiley, 1994. Pp. ix + 325.
Recommended from our members
"Call a Teenager… That's What I Do!" - Grandchildren Help Older Adults Use New Technologies: Qualitative Study.
BackgroundAlthough family technical support seems intuitive, there is very little research exploring this topic.ObjectiveThe objective of this study was to conduct a subanalysis of data collected from a large-scale qualitative project regarding older adults' experiences in using health information technology. Specifically, the subanalysis explored older adults' experiences with technology support from family members to inform strategies for promoting older adults' engagement with new health technologies. Although the primary analysis of the original study was theoretically driven, this paper reports results from an inductive, open-coding analysis.MethodsThis is a subanalysis of a major code identified unexpectedly from a qualitative study investigating older adults' use experience of a widespread health technology, the patient portal. A total of 24 older patients (≥65 years) with multiple chronic conditions (Charlson Comorbidity Index >2) participated in focus groups conducted at the patients' primary clinic. While conducting the primary theoretically driven analysis, coders utilized an open-coding approach to ensure important ideas not reflected in the theoretical code book were captured. Open coding resulted in 1 code: family support. This subanalysis further categorized family support by who provided tech support, how tech support was offered, and the opinions of older participants about receiving family tech support.ResultsThe participants were not specifically asked about family support, yet themes around family assistance and encouragement for technology emerged from every focus group. Participants repeatedly mentioned that they called their grandchildren and adult children if they needed help with technology. Participants also reported that family members experienced difficulty when teaching technology use. Family members struggled to explain simple technology tasks and were frustrated by the slow teaching process.ConclusionsThe results suggest that older adults ask their family members, particularly grandchildren, to support them in the use of new technologies. However, family may experience difficulties in providing this support. Older adults will be increasingly expected to use health technologies, and family members may help with tech support. Providers and health systems should consider potential family support and engagement strategies to foster adoption and use among older patients
Social Media Vaccine Websites: A Comparative Analysis of Public and Moderated Websites
The internet is an important source of vaccine information for parents. We evaluated and compared the interactive content on an expert moderated vaccine social media (VSM) website developed for parents of children 24 months of age or younger and enrolled in a health care system to a random sample of interactions extracted from publicly available parenting and vaccine-focused blogs and discussion forums. The study observation period was September 2013 through July 2016. Three hundred sixty-seven eligible websites were located using search terms related to vaccines. Seventy-nine samples of interactions about vaccines on public blogs and discussion boards and 61 interactions from the expert moderated VSM website were coded for tone, vaccine stance, and accuracy of information. If information was inaccurate, it was coded as corrected, partially corrected or uncorrected. Using chi-square or Fisher’s exact tests, we compared coded interactions from the VSM website with coded interactions from the sample of publicly available websites. We then identified representative quotes to illustrate the quantitative results. Tone, vaccine stance, and accuracy of information were significantly different (all p \u3c .05). Publicly available vaccine websites tended to be more contentious and have a negative stance toward vaccines. These websites also had inaccurate and uncorrected information. In contrast, the expert moderated website had a more civil tone, minimal posting of inaccurate information, with very little participant-to-participant interaction. An expert moderated, interactive vaccine website appears to provide a platform for parents to gather accurate vaccine information, express their vaccine concerns and ask questions of vaccine experts
Exploring changes in middle-school student lunch consumption after local school food service policy modifications
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Recommendations for outcome measurement for deprescribing intervention studies.
Interpreting results from deprescribing interventions to generate actionable evidence is challenging owing to inconsistent and heterogeneous outcome definitions between studies. We sought to characterize deprescribing intervention outcomes and recommend approaches to measure outcomes for future studies. A scoping literature review focused on deprescribing interventions for polypharmacy and informed a series of expert panel discussions and recommendations. Twelve experts in deprescribing research, policy, and clinical practice interventions participating in the Measures Workgroup of the US Deprescribing Research Network sought to characterize deprescribing outcomes and recommend approaches to measure outcomes for future studies. The scoping review identified 125 papers reflecting 107 deprescribing studies. Common outcomes included medication discontinuation, medication appropriateness, and a broad range of clinical outcomes potentially resulting from medication reduction. Panel recommendations included clearly defining clinically meaningful medication outcomes (e.g., number of chronic medications, dose reductions), ensuring adequate sample size and follow-up time to capture clinical outcomes resulting from medication discontinuation (e.g., quality of life [QOL]), and selecting appropriate and feasible data sources. A new conceptual model illustrates how downstream clinical outcomes (e.g., reduction in falls) should be interpreted in the context of initial changes in medication measures (e.g., reduction in mean total medications). Areas needing further development include implementation outcomes specific to deprescribing interventions and measures of adverse drug withdrawal events. Generating evidence to guide deprescribing is essential to address patient, caregiver, and clinician concerns about the benefits and harms of medication discontinuation. This article provides recommendations and an initial conceptual framework for selecting and applying appropriate intervention outcomes to support deprescribing research
Using the Technology Acceptance Model to Explore User Experience, Intent to Use, and Use Behavior of a Patient Portal Among Older Adults With Multiple Chronic Conditions: Descriptive Qualitative Study
Recommendations for outcome measurement for deprescribing intervention studies
Interpreting results from deprescribing interventions to generate actionable evidence is challenging owing to inconsistent and heterogeneous outcome definitions between studies. We sought to characterize deprescribing intervention outcomes and recommend approaches to measure outcomes for future studies. A scoping literature review focused on deprescribing interventions for polypharmacy and informed a series of expert panel discussions and recommendations. Twelve experts in deprescribing research, policy, and clinical practice interventions participating in the Measures Workgroup of the US Deprescribing Research Network sought to characterize deprescribing outcomes and recommend approaches to measure outcomes for future studies. The scoping review identified 125 papers reflecting 107 deprescribing studies. Common outcomes included medication discontinuation, medication appropriateness, and a broad range of clinical outcomes potentially resulting from medication reduction. Panel recommendations included clearly defining clinically meaningful medication outcomes (e.g., number of chronic medications, dose reductions), ensuring adequate sample size and follow-up time to capture clinical outcomes resulting from medication discontinuation (e.g., quality of life [QOL]), and selecting appropriate and feasible data sources. A new conceptual model illustrates how downstream clinical outcomes (e.g., reduction in falls) should be interpreted in the context of initial changes in medication measures (e.g., reduction in mean total medications). Areas needing further development include implementation outcomes specific to deprescribing interventions and measures of adverse drug withdrawal events. Generating evidence to guide deprescribing is essential to address patient, caregiver, and clinician concerns about the benefits and harms of medication discontinuation. This article provides recommendations and an initial conceptual framework for selecting and applying appropriate intervention outcomes to support deprescribing research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/174967/1/jgs17894-sup-0001-Supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/174967/2/jgs17894.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/174967/3/jgs17894_am.pd