Video
EZ Aim® HardRock Steel Targets - Steel Gong Targets, IPSC Style Silhouette, Target SpinnersAc personalized targets -
a Department of Renal Medicine, Royal North Shore Hospital, Northern Sydney Local Health District, Sydney, New South Wales, Australia. b Renal Research, Kolling Institute of Medical Research, The University of Sydney, Sydney, New South Wales, Australia. This Site. Google Scholar. Dimitrios Poulikakos ; Dimitrios Poulikakos.
c Department of Renal Medicine, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Salford, UK. Helen Hurst ; Helen Hurst.
e Paula Ormandy School of Health and Society, University of Salford, Salford, UK. David Lewis ; David Lewis. chinnadurai postgrad. Kidney Dis 9 5 : — Article history Received:. Cite Icon Cite. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest.
Journal Section:. Table 1. Summary of commonly used frailty screening tools. Frailty assessment tool. Criteria and scoring system. Tools based on physical frailty Frailty Phenotype [22] Measures physiological deficits across 5 domains: 1 weight loss; 2 exhaustion; 3 physical activity; 4 muscle strength; 5 walking speed Scoring based on clinician judgment over previous 2 week period and does not take into account any occurrence of acute reversible illness.
Currently, a 9-point global scale ranging from very fit to severely frail to terminally ill. Conventionally conducted in both acute care and community settings.
Initially used within the oncology specialty context, before being applied to other specialties including nephrology. Commonly applied in hospital acute care as well as community settings.
View Large. View large Download slide. Table 2. Decision on PD prescription strategy. Key considerations. Table 3. Management options for common symptoms experienced by older patients during PD. CBT, cognitive behavioral therapy; PD, peritoneal dialysis.
Pathophysiological mechanisms of PEW in older peritoneal dialysis patients. The authors have no conflicts of interest to declare. No external funding was provided for this manuscript. Burden of kidney disease, health-related quality of life, and employment among patients receiving peritoneal dialysis and in-center hemodialysis: findings from the DOPPS program.
Search ADS. Renal Data System. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases. COVID pandemic era: is it time to promote home dialysis and peritoneal dialysis. Functional dependence and mortality in the International dialysis outcomes and practice patterns study DOPPS.
Frailty and chronic kidney disease: current evidence and continuing uncertainties. Decline in independence after three years and its association with dietary patterns and IADL-related factors in community-dwelling older people: an analysis by age stage and sex. Effects of increased peritoneal clearances on mortality rates in peritoneal dialysis: ADEMEX, a prospective, randomized, controlled trial.
The relative importance of residual renal function compared with peritoneal clearance for patient survival and quality of life: an analysis of The Netherlands Cooperative Study on the Adequacy of Dialysis NECOSAD Relative contribution of residual renal function and peritoneal clearance to adequacy of dialysis: a reanalysis of the CANUSA study.
Association of mortality risk with various definitions of intradialytic hypotension. International Society for Peritoneal Dialysis practice recommendations: Prescribing high-quality goal-directed peritoneal dialysis. Delivering peritoneal dialysis for the multimorbid, frail and palliative patient.
Dialysis initiation, modality choice, access, and prescription: conclusions from a kidney disease: improving global outcomes KDIGO controversies conference.
Establishing a core outcome measure for life participation in patients receiving peritoneal dialysis: a Standardised Outcomes in Nephrology—Peritoneal Dialysis consensus workshop report. Frailty and mortality in dialysis: evaluation of a clinical frailty scale.
Frailty among patients receiving hemodialysis: evolution of components and associations with mortality. Screening older cancer patients: first evaluation of the G-8 geriatric screening tool. Operationalizing a frailty index from a standardized comprehensive geriatric assessment.
van Loon. Systematic comprehensive geriatric assessment in elderly patients on chronic dialysis: a cross-sectional comparative and feasibility study.
Incorporating geriatric assessment into a nephrology clinic: preliminary data from two models of care. The prevalence and impact of falls in elderly dialysis patients: frail elderly Patient Outcomes on Dialysis FEPOD study.
Kidney supportive care in peritoneal dialysis: developing a person-centered kidney disease care plan. Person-centered peritoneal dialysis prescription and the role of shared decision-making. Automated vs continuous ambulatory peritoneal dialysis: a systematic review of randomized controlled trials.
Comparative outcomes between continuous ambulatory and automated peritoneal dialysis: a narrative review. Automated peritoneal dialysis in Hong Kong: there are two distinct groups of patients.
International comparison of peritoneal dialysis prescriptions from the peritoneal dialysis outcomes and practice patterns study PDOPPS. Assisted peritoneal dialysis as a method of choice for elderly with end-stage renal disease.
Incidence and risk factors of peritoneal dialysis-related peritonitis in elderly patients: a retrospective clinical study. A systematic review and jurisdictional scan of the evidence characterizing and evaluating assisted peritoneal dialysis models. Is peritonitis risk increased in elderly patients on peritoneal dialysis?
Report from the French Language Peritoneal Dialysis Registry RDPLF. Implementing assisted peritoneal dialysis in renal care: a Chinese-German perspective.
ISPD cardiovascular and metabolic guidelines in adult peritoneal dialysis patients Part II—management of various cardiovascular complications. Benefits of biocompatible PD fluid for preservation of residual renal function in incident CAPD patients: a 1-year study.
Angiotensin-converting enzyme inhibitors and angiotensin receptor blockers for preserving residual kidney function in peritoneal dialysis patients.
Role of diuretics in the preservation of residual renal function in patients on continuous ambulatory peritoneal dialysis. Preserving residual renal function in dialysis patients: an update on evidence to assist clinical decision making.
Association between pulse pressure and mortality in patients undergoing peritoneal dialysis. The association between BP and mortality in patients on chronic peritoneal dialysis.
Blood pressure and volume management in dialysis: conclusions from a kidney disease: improving global outcomes KDIGO controversies conference. Polypharmacy predicts onset and transition of frailty, malnutrition, and adverse outcomes in peritoneal dialysis patient. Association of anemia with outcomes in men with moderate and severe chronic kidney disease.
Association of kidney function with anemia: the third national health and nutrition examination Survey International anemia prevalence and management in peritoneal dialysis patients.
Controversies in optimal anemia management: conclusions from a kidney disease: improving global outcomes KDIGO conference. Hypoxia-inducible factor regulates hepcidin via erythropoietin-induced erythropoiesis.
Hypoxia-inducible factor and its role in the management of anemia in chronic kidney disease. A comparison of symptom prevalence in far advanced cancer, AIDS, heart disease, chronic obstructive pulmonary disease and renal disease.
Health-related quality of life in peritoneal dialysis patients: a narrative review. Longitudinal trends in quality of life and physical function in frail older dialysis patients: a comparison of assisted peritoneal dialysis and in-center hemodialysis.
Comparison of quality of life in patients undergoing hemodialysis and peritoneal dialysis: a systematic review and meta-analysis.
Comparisons of quality of life between patients underwent peritoneal dialysis and hemodialysis: a systematic review and meta-analysis. De Rooij. Identification and treatment of depression in a cohort of patients maintained on chronic peritoneal dialysis.
The influence of cognitive-behavioral therapy on depression in dialysis patients - meta-analysis. Sleep disorders and cognitive impairment in peritoneal dialysis: a multicenter prospective cohort study. Clinical management of chronic kidney disease-associated pruritus: current treatment options and future approaches.
Validation of a Core patient-reported outcome measure for fatigue in patients receiving hemodialysis: the SONG-HD fatigue instrument. Circling around in tiredness: perspectives of patients on peritoneal dialysis. Fatigue in peritoneal dialysis patients and an exploration of contributing factors: a cross-sectional study.
Psychosocial factors in patients with chronic kidney disease: the identification and treatment of depression in patients maintained on dialysis. Prevention and treatment of protein energy wasting in chronic kidney disease patients: a consensus statement by the International Society of Renal Nutrition and Metabolism.
Peritoneal protein loss, leakage or clearance in peritoneal dialysis, where do we stand. Low serum potassium levels and clinical outcomes in peritoneal dialysis — international results from PDOPPS. Get in touch with us today to get started on enhancing your next target shooting experience.
Rimfire Rifle. Centerfire Pistol. Centerfire Rifle. View as: Grid List Sort By Position Target Ratings Name Price. Show 12 24 36 per page. Showing 1 to 12 of 82 total Page: 1 2 3 4 5.
Add to Cart. WARRANTY We offer a LIFETIME warranty on all of our products. CUSTOM TARGETS Custom shapes and sizes are available. SUPPORT If you have questions on which target style fits your need call us today to discuss! Backward elimination starts with all predictors included in the model, with variables subsequently being eliminated one at a time.
In total, unique participants joined the study, and they were randomly assigned to a treatment: 82 Of the participants, 83 These data are summarized in Figure 3 , which displays a cohort diagram that details the number of participants engaged in different study phases.
Table 3 displays sample demographics based on the results of the posttest survey, which was filled out by Gender, age group, and personality scores are displayed for the entire sample as well as per treatment.
The demographic characteristics in the control group and treatment group are distributed similarly. Hence, it is assumed that these groups were comparable at baseline. Figure 4 displays the decrease in the number of participants who visited the mobile app during a given wave.
The number of participants who joined the campaign for the first time during a given wave are displayed in green. The number of participants who dropped out during a specific wave are displayed in red.
The number of participants who checked the mobile app during a specific wave, although they dropped out during an earlier wave ie, reclaimed users are displayed in yellow. No significant differences in dropout rates between treatments could be detected.
In addition, no significant interaction effect between time ie, the wave number and treatment was detected. Hence, it is assumed that dropouts were spread equally over treatments. a Posttest personality scores were not available for the participant who was not assigned a treatment.
The complexity parameters of the dynamic tasks that the control participants were assigned are presented in Table 2. However, the complexity parameters for the treatment group were different for each individual in that group and were only determined at the start of a new wave.
The mean SD , minimum, and maximum values of the 3 complexity parameters are displayed per wave in Table 4. Of the participants, 10 5. In addition, of these participants, 55 Figure 5 displays the number of days participants visited the app on average per wave per treatment.
Figure 6 displays the number of days participants visited the app on average per type of goal they set. From the second set of statistical analyses, it was found that the number of days participants visited the app dropped over time ie, —1.
No significant difference between treatments was detected, although it did matter whether participants completed the intake survey. Finally, no significant interaction effects were detected; all treatments were affected equally by the impact of time. Figure 7 displays the average number of activities participants registered per treatment.
Figure 8 displays the average number of activities participants registered per type of goal they set. Multimedia Appendix 3 displays an overview of the number of times a particular suggested task was registered per organization. Moreover, from the second set of statistical analyses, it was found that the number of activities participants registered decreased over time ie, —0.
Finally, no significant interaction effects were detected; again, all treatments were affected equally by the impact of time ie, relative wave number.
The third set of analyses zoomed in on the experimentally controlled tasks ie, the longer walk, the longer bike ride, and the sport sessions to evaluate treatment differences at the level of individual activity types Figure 9.
For each activity type, a hierarchical linear model was built to predict the number or times a participant registered a task for that particular activity type. No significant predictors were found for estimating the number of longer bike rides a participant registered.
When zooming in on the perceived impact on performance of individual activity types ie, walks, bike rides, and sports sessions , no significant predictors were found for estimating the perceived impact on walk performance Figure Nevertheless, for both the control and treatment groups, the perception of capability diminished over time ie, —0.
The aim of this study is to evaluate the impact of personalized goal setting in a gamified health promotion program on participant engagement levels. Our results show that engagement with the program inevitably dropped over time, both in the personalized condition and in the control condition.
Although this pattern is common in digital health promotion programs [ 39 ], several factors may be relevant for explaining this tendency in this particular context. Hence, a great proportion of our sample seemed to be still in the precontemplation or contemplation phase, phases in which they were actually not yet planning for a more active lifestyle.
Still, the participants who had set themselves a goal ie, by completing the intake survey were more engaged than those who had not. In particular, these participants visited the app more frequently and also registered more of the healthy tasks they were prescribed.
Hence—as proposed by Goal-Setting Theory—setting a goal is in itself a motivating task [ 33 ]. Nevertheless, improvement goals—which are arguably more difficult to achieve than maintenance goals—did not seem to be significantly more motivating in general than maintenance goals.
This finding seems to contradict both Flow Theory and Goal-Setting Theory, which propose that difficult—but still attainable—goals are more engaging than easier goals [ 31 , 33 ].
Then again, it should be noted that the descriptive means were mostly in the expected direction ie, improvement goals were more engaging than maintenance goals and the impact of improvement goals was actually significantly larger for promoting sports sessions: if a participant explicitly expressed a need to improve their current performance, they perceived their sports performance to be improved significantly.
Finally, the impact of the personalized treatment on engagement levels seemed to be generally limited. However, descriptive means were mostly in the expected direction ie, personalized goals were more engaging than generically suggested goals.
The seemingly limited impact of personalized goal setting may be explained by the actual strategy for personalizing the set of tasks. Moreover, we found that personalizing the suggested minimum number of sports sessions did stimulate participants to perform significantly more sports sessions, as well as significantly improved their perception of their sports performance.
Upon close examination of this complexity parameter, we found that it can be characterized as a frequency parameter, whereas the parameters for personalizing walks and bike rides are typically characterized as intensity parameters.
A frequency parameter defines how many times a particular activity should be performed in a given time frame, whereas an intensity parameter defines how a particular activity should be executed eg, for how long and how far. We are unaware of context-specific factors that could have influenced this effect.
However, we cannot claim generalizability yet either. Hence, our personalization strategy may have suggested tasks that were perceived as too difficult or too easy by our target users, thereby potentially compromising self-efficacy and engagement with the program [ 30 , 31 ].
The execution of this study was subject to several limitations. First, participants could take part without completing the intake survey. As a result, it was unknown in the case of some participants whether they explicitly choose not to set goals for themselves or whether they actually did aim to maintain or improve their current capability levels.
Second, participants may have felt that the number of points they were awarded for their activities, which affected their position on the social leaderboard, was unfair. Although, objectively speaking, this tailoring strategy makes the whole competition actually more fair, we received reports from several participants perceiving it as unfair that they had to seemingly expend more effort than their colleagues to be awarded the same number of points.
Third, an additional design choice that participants may have perceived as unfair was the decision to reward walks and bike rides on a per-trip basis, instead of, for example, on a daily aggregate basis. As a result, participants who went out for multiple shorter walks may not have been sufficiently rewarded for their effort.
Then again, our aim was to promote activities with a minimum duration of 10 minutes, but perhaps it is worthwhile exploring this trade-off in more depth. Fourth, the study outcomes were largely based on self-reported measures.
Although participants could automatically ie, objectively prove their engagement with a certain task using Google Fit, Strava, or a built-in GPS-based activity tracker, they were also allowed to manually ie, subjectively claim that they had engaged in a certain task.
This design choice could have introduced fraudulent activity registrations. This low response rate on the posttest survey may have introduced a selection bias in the fourth set of analyses of subjective measures.
Finally, this study evaluated the impact of our intervention on a particular target group ie, government staff within a specific context ie, the work environment. A follow-up study should better control how participants set goals for themselves ie, by means of the intake survey.
For example, participants could be required to complete the intake survey before they are allowed to engage in the gamified program. It seems natural to set different goals for participants who are in the precontemplation or contemplation phase ie, the phase in which participants are not [yet] planning for a more active lifestyle and for participants who are already actively improving their lifestyle ie, participants in the action phase.
Perhaps these 2 groups need to be assigned a different gamified program altogether. In addition, future work should focus on evaluating different strategies for personalizing goal parameters. A particular opportunity is exploring in more detail the potential impact of personalizing the frequency parameters, rather than the intensity parameters.
Focusing on promoting activity frequency particularly satisfies physical activity guidelines, which suggest that frequently interrupting periods of sitting with short bouts of physical activity is essential to remain healthy because sitting for prolonged periods can in itself compromise health [ 9 ].
Does personalization based on frequency parameters also have a larger impact on engagement levels in general? And if so, why?
Finally, future work could explore the impact of allowing participants to add personalized goals for other types of activities too eg, healthy dietary intake.
Although we have not yet been able to generalize our findings to support the claim that personalizing activity frequency fosters engagement levels better than personalizing activity intensity, we still suggest that practitioners focus on setting personalized goals based on activity frequency, in particular, because focusing on activity frequency implies performing physical activity more often instead of for longer duration or performing more intense physical activity.
This focus adheres especially well to physical activity guidelines, which suggest that frequently interrupting periods of sitting with short bouts of physical activity is essential to remaining healthy because sitting for prolonged periods can in itself compromise health [ 9 ].
Meanwhile, we encourage scholars to replicate our study setup to gain a deeper understanding of the potential impact of different strategies for tailoring health goals.
To this end, we recommend that scholars also apply Goal-Setting Theory [ 33 ] and Flow Theory [ 31 ] when designing their studies. Similarly, we encourage scholars to evaluate the relationship between strategies of adaptive goal setting and contextual factors eg, whether outcomes can be replicated with other target audiences.
In this study, we evaluated a gamified program that was designed to promote engagement in physical activity with sedentary government staff. Our aim is to investigate the impact of adaptive goal-setting strategies on end-user engagement levels with the program.
In particular, through the program, study participants were stimulated to engage in a set of health-related activities eg, to go for a walk, run, or sports session. Our results indicated that end-user engagement with the program inevitably decreased over time.
However, compared with a control group, it was found that tailoring the frequency of suggested activities ie, as opposed to tailoring the intensity of activities does promote engagement in that activity ie, engaging in sports sessions. This effect was reported to be especially strong in participants who expressed an intention to improve their health-related capabilities at the beginning of the program.
In fact, engagement was generally higher in participants who expressed an intention to improve their capabilities on at least one health dimension. Hence, when designing a gamified health promotion program, end-user engagement levels may be fostered by having end users explicitly state their current and desired capabilities and by setting health goals that tailor the suggested frequency of engaging in activities that constitute these goals.
This work is part of the research program Gamification for Overweight Prevention and Active Lifestyle , which is partly financed by the Netherlands Organization for Health Research and Development.
PVG, RN and AK were involved in the development of the GameBus mHealth platform. Editorial notice : This randomized study was only retrospectively registered.
The authors explained that this is due to them not being aware that it was classified as a randomized controlled trial. The editor granted an exception of ICMJE rules for prospective registration of randomized trials because the risk of bias appears low. However, readers are advised to carefully assess the validity of any potential explicit or implicit claims related to primary outcomes or effectiveness, as retrospective registration does not prevent authors from changing their outcome measures retrospectively.
Overview of the number of times a particular suggested task was registered per organization. Edited by L Buis; submitted org , Skip to Main Content Skip to Footer. Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Results From a 2-Month Randomized Controlled Trial Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Results From a 2-Month Randomized Controlled Trial Authors of this article: Raoul Nuijten 1 ; Pieter Van Gorp 1 ; Alireza Khanshan 2 ; Pascale Le Blanc 1 ; Pauline van den Berg 3 ; Astrid Kemperman 3 ; Monique Simons 4.
Article Authors Cited by 8 Tweetations 6 Metrics. Original Paper. Raoul Nuijten 1 , MSc ; Pieter Van Gorp 1 , PhD ; Alireza Khanshan 2 , MSc ; Pascale Le Blanc 1 , Prof Dr ; Pauline van den Berg 3 , PhD ; Astrid Kemperman 3 , PhD ; Monique Simons 4 , PhD 1 Department of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands 2 Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands 3 Department of the Built Environment, Eindhoven University of Technology, Eindhoven, Netherlands 4 Department of Social Sciences, Wageningen University and Research, Wageningen, Netherlands.
Corresponding Author: Raoul Nuijten, MSc Department of Industrial Engineering Eindhoven University of Technology Groene Loper 3 Eindhoven, AE Netherlands Phone: 31 Email: r.
nuijten tue. mHealth ; health promotion ; physical activity ; personalization ; adaptive goal setting ; gamification ; office workers. Table 1. Maximum number of points that could be obtained per suggested activity. Table 2. Estimated time needed to complete a dynamic task per activity type, as suggested to the control group.
Parameter Wave 1 Wave 2 Wave 3 Wave 4 Minimum duration of the longer walk, minutes distance; m Table 3. Table 4. Mean SD , minimum, and maximum values of the complexity parameters per dynamic task as presented to the treatment group. Parameter Wave 1 Wave 2 Wave 3 Wave 4 Minimum distance of the longer walk m Mean SD Minimum Maximum Minimum distance of the longer bike ride m Mean SD Minimum Maximum 17, 17, 17, 17, Suggested sports sessions Mean SD 2.
Multimedia Appendix 1 Posttest survey. PDF File Adobe PDF File , 89 KB. Multimedia Appendix 2 Detailed output of statistical analysis.
Tsrgets H. WuDimitrios Ttargets Ac personalized targets, Helen Hurst Home injury prevention, David LewisPersonalizedd Chinnadurai; Delivering Personalized, Goal-Directed Care personalozed Older Patients Receiving Ac personalized targets Dialysis. Tagets Ac personalized targets 2 October ; peesonalized 5 : — Background: An aging population living with chronic kidney disease and progressing to kidney failure, subsequently receiving peritoneal dialysis PD is growing. A significant proportion of these patients are also living with multi-morbidities and some degree of frailty. Recent practice recommendations from the International Society of Peritoneal Dialysis advocate for high-quality, goal-directed PD prescription, and the Standardized Outcomes of Nephrology-PD initiative emphasized the need for an individualized, goal-based care approach in all patients receiving PD treatment. In older patients, this approach to PD care is even more important. Molecular Cancer Energy gels for long runs 14Article number: Acc this Glucagon synthesis. Metrics details. Recent advances in gene expression Ac personalized targets have led personqlized the identification Ac personalized targets at least Ac personalized targets personalizd molecular subtypes of DLBCL: personalizee germinal center Ac personalized targets cell-like subtype, an activated Perdonalized cell-like subtype, personalize a primary mediastinal B-cell lymphoma subtype. Several novel potential drug targets have been recently identified such as the BET bromodomain protein BRD -4, phosphoribosyl-pyrophosphate synthetase PRPS -2, macrodomain-containing mono-ADP-ribosyltransferase ARTD -9 also known as PARP9deltexlike E3 ubiquitin ligase DTX3L also known as BBAPNF-kappaB inducing kinase NIK and transforming growth factor beta receptor TGFβR. We also provide a comprehensive and updated list of current drugs, drug targets and preclinical and clinical experimental studies in DLBCL. A special focus is given on STAT1, ARTD9, DTX3L and ARTD8 also known as PARP14 as novel potential drug targets in distinct molecular subsets of DLBCL.
Sie sprechen sachlich
Welche Wörter... Toll, die prächtige Phrase
Moskau nicht wurde sofort gebaut.
die Verständliche Mitteilung
Und dass daraufhin.