Melanie Knopp

Background: A typical training plan is a mix of many training sessions with different intensities and durations to achieve a specific goal, like running a marathon in a certain time. Scientific publications provide little specific information to aid in writing a comprehensive training plan. This review aims to systematically and quantitatively analyse the last 12 weeks before a marathon as recommended in 92 sub-elite training plans. Methods: We retrieved 92 marathon training plans and linked their running training sessions to five intensity zones. Subsequently, each training plan was grouped based on the total running volume in peak week into high (> 90 km/week), middle (65–90 km/week), and low (< 65 km/week) training volume plan categories. Results: In the final 12 weeks before a race, recommended weekly running volume averaged 108 km, 59 km, and 43 km for high, middle, and low distance marathon training plans. The intensity distribution of these plans followed a pyramidal training structure with 15–67–10–5–3%, 14–63–18–2–3%, and 12–67–17–2–2% in zones 1, 2, 3, 4, and 5, for high, middle, and low volume training plans, respectively. Conclusions: By quantitatively analysing 92 recommended marathon training plans, we can specify typical recommendations for the last 12 weeks before a marathon race. Whilst this approach has obvious limitations such as no evidence for the effectiveness of the training plans investigated, it is arguably a useful strategy to narrow the gap between science and practice.

A growing number of companies are developing or using wearable sensor technologies that can monitor, analyse and transmit data from humans in real time that can be used by the sporting, biomedical and media industries. To explore this phenomenon, we describe and review two high-profile sporting events where innovations in wearable technologies were trialled: the Tokyo 2020 Summer Olympic Games (Tokyo 2020, Japan) and the 2022 adidas Road to Records (Germany). These two major sporting events were the first time academic and industry partners came together to implement real-time wearable solutions during major competition, to protect the health of athletes competing in hot and humid environments, as well as to better understand how these metrics can be used moving forwards. Despite the undoubted benefits of such wearables, there are well-founded concerns regarding their use including: (1) limited evidence quantifying the potential beneficial effects of analysing specific parameters, (2) the quality of hardware and provided data, (3) information overload, (4) data security and (5) exaggerated marketing claims. Employment and sporting rules and regulations also need to evolve to facilitate the use of wearable devices. There is also the potential to obtain real-time data that will oblige medical personnel to make crucial decisions around whether their athletes should continue competing or withdraw for health reasons. To protect athletes, the urgent need is to overcome these ethical/data protection concerns and develop wearable technologies that are backed by quality science. The fields of sport and exercise science and medicine provide an excellent platform to understand the impact of wearable sensors on performance, wellness, health, and disease.

A typical training plan is a mix of many training sessions with different intensities and durations to achieve a specific goal, like running a marathon in a certain time. Scientific publications provide little specific information to aid in writing a comprehensive training plan. This review aims to systematically and quantitatively analyse published subjective sub-elite marathon training plans and to synthesize the resultant recommendations for comparison with relevant research and as a starting point for hypothesis testing. We retrieved 92 marathon training plans and linked their running training sessions to five intensity zones. Subsequently, each training plan was grouped based on the total running volume in peak week into high (> 90 km/week), middle (65–90 km/week), and low (< 65 km/week) training volume plan categories. In the final eight weeks before a race, recommended weekly running volume averaged 105 km, 58 km, and 44 km for high, middle, and low distance marathon training plans. The intensity distribution of these plans followed a pyramidal training structure with 15-67-10-5-3%, 14-63-18-2-3%, and 10-68-17-3-2% in zones 1, 2, 3, 4, and 5, for high, middle, and low volume training plans, respectively. By quantitatively analysing 92 recommended marathon training plans, we can specify typical recommendations for marathon training plans and inform the discussion between sports scientists and coach practitioners. Whilst this approach has obvious limitations such as no evidence for the effectiveness of the training plans investigated, it is arguably a useful strategy to narrow the gap between science and practice.

Background: Advanced footwear technology improves average running economy compared with racing flats in sub-elite athletes. However, not all athletes benefit as performance changes vary from a 10% drawback to a 14% improvement. The main beneficiaries from such technologies, world-class athletes, have only been analyzed using race times. Objective: The aim of this study was to measure running economy on a laboratory treadmill in advanced footwear technology compared to a traditional racing flat in world-class Kenyan (mean half-marathon time: 59:30 min:s) versus European amateur runners. Methods: Seven world-class Kenyan and seven amateur European male runners completed a maximal oxygen uptake assessment and submaximal steady-state running economy trials in three different models of advanced footwear technology and a racing flat. To confirm our results and better understand the overall effect of new technology in running shoes, we conducted a systematic search and meta-analysis. Results: Laboratory results revealed large variability in both world-class Kenyan road runners, which ranged from a 11.3% drawback to a 11.4% benefit, and amateur Europeans, which ranged from a 9.7% benefit to a 1.1% drawback in running economy of advanced footwear technology compared to a flat. The post-hoc meta-analysis revealed an overall significant medium benefit of advanced footwear technology on running economy compared with traditional flats. Conclusions: Variability of advanced footwear technology performance appears in both world-class and amateur runners, suggesting further testing should examine such variability to ensure validity of results and explain the cause as a more personalized approach to shoe selection might be necessary for optimal benefit.

The introduction of carbon fiber plate shoes has triggered a plethora of world records in running, which has encouraged shoe industries to produce novel shoe designs to enhance running performance, including shoes containing conductor elements or “grounding shoes” (GS), which could potentially reduce the energy cost of running. The aim of this study was to examine the physiological and perceptual responses of athletes subjected to grounding shoes during running. Ten elite runners were recruited. Firstly, the athletes performed an incremental running test for VO₂max and anaerobic threshold (AT) determination, and were familiarized with the two shoe conditions (traditional training shoe (TTS) and GS, the latter containing a conductor element under the insole). One week apart, athletes performed running economy tests (20 min run at 80% of the AT) on a 400 m dirt track, with shoe conditions randomized. VO₂, heart rate, lactate, and perceived fatigue were registered throughout the experiment. No differences in any of the physiological or perceptual variables were identified between shoe conditions, with an equal running economy in both TTS and GS (51.1 ± 4.2 vs. 50.9 ± 5.1 mL kg⁻¹ min⁻¹, respectively). Our results suggest that a grounding stimulus does not improve the energy cost of running, or the physiological/perceptual responses of elite athletes.

Evaluative research of technological officiating aids in sports predominantly focuses on the respective technology and the impact on decision accuracy, whereas the impact on stakeholders is neglected. Therefore, the aim of this study was to investigate the immediate impact of the recently introduced Video Assistant Referee, often referred to as VAR, on the sentiment of fans of the English Premier League. We analyzed the content of 643,251 tweets from 129 games, including 94 VAR incidents, using a new variation of a gradient boosting approach to train two tree-based classifiers for text corpora: one classifier to identify tweets related to the VAR and another one to rate a tweet’s sentiment. The results of 10-fold cross-validations showed that our approach, for which we only took a small share of all features to grow each tree, performed better than common approaches (naïve Bayes, support vector machines, random forest and traditional gradient tree boosting) used by other studies for both classification problems. Regarding the impact of the VAR on fans, we found that the average sentiment of tweets related to this technological officiating aid was significantly lower compared to other tweets (-0.64 vs. 0.08; t = 45.5, p < .001). Further, by tracking the mean sentiment of all tweets chronologically for each game, we could display that there is a significant drop of sentiment for tweets posted in the periods after an incident compared to the periods before. A plunge that persisted for 20 minutes on average. Summed up, our results provide evidence that the VAR effects predominantly expressions of negative sentiment on Twitter. This is in line with the results found in previous, questionnaire-based, studies for other technological officiating aids and also consistent with the psychological principle of loss aversion.

Background: Conventional approaches to improve the quality of clinical patient imaging studies focus predominantly on updating or replacing imaging equipment; however, it is often not considered that patients can also highly influence the diagnostic quality of clinical imaging studies. Patient-specific artifacts can limit the diagnostic image quality, especially when patients are uncomfortable, anxious, or agitated. Imaging facility or environmental conditions can also influence the patient’s comfort and willingness to participate in diagnostic imaging studies, especially when performed in visually unesthetic, anxiety-inducing, and technology-intensive imaging centers. When given the opportunity to change a single aspect of the environmental or imaging facility experience, patients feel much more in control of the otherwise unfamiliar and uncomfortable setting. Incorporating commercial, easily adaptable, ambient lighting products within clinical imaging environments allows patients to individually customize their environment for a more personalized and comfortable experience. Objective: The aim of this pilot study was to use a customizable colored light-emitting diode (LED) lighting system within a clinical imaging environment and demonstrate the feasibility and initial findings of enabling healthy subjects to customize the ambient lighting and color. Improving the patient experience within clinical imaging environments with patient-preferred ambient lighting and color may improve overall patient comfort, compliance, and participation in the imaging study and indirectly contribute to improving diagnostic image quality. Methods: We installed consumer-based internet protocol addressable LED lights using the ZigBee standard in different imaging rooms within a clinical imaging environment. We recruited healthy volunteers (n=35) to generate pilot data in order to develop a subsequent clinical trial. The visual perception assessment procedure utilized questionnaires with preprogrammed light/color settings and further assessed how subjects preferred ambient light and color within a clinical imaging setting. Results: Technical implementation using programmable LED lights was performed without any hardware or electrical modifications to the existing clinical imaging environment. Subject testing revealed substantial variabilities in color perception; however, clear trends in subject color preference were noted. In terms of the color hue of the imaging environment, 43% (15/35) found blue and 31% (11/35) found yellow to be the most relaxing. Conversely, 69% (24/35) found red, 17% (6/35) found yellow, and 11% (4/35) found green to be the least relaxing. Conclusions: With the majority of subjects indicating that colored lighting within a clinical imaging environment would contribute to an improved patient experience, we predict that enabling patients to customize environmental factors like lighting and color to individual preferences will improve patient comfort and patient satisfaction. Improved patient comfort in clinical imaging environments may also help to minimize patient-specific imaging artifacts that can otherwise limit diagnostic image quality. Trial Registration: ClinicalTrials.gov NCT03456895; https://clinicaltrials.gov/ct2/show/NCT03456895

BACKGROUND Conventional approaches to improve the quality of clinical patient imaging studies focus predominantly on updating or replacing imaging equipment; however, it is often not considered that patients can also highly influence the diagnostic quality of clinical imaging studies. Patient-specific artifacts can limit the diagnostic image quality, especially when patients are uncomfortable, anxious, or agitated. Imaging facility or environmental conditions can also influence the patient’s comfort and willingness to participate in diagnostic imaging studies, especially when performed in visually unesthetic, anxiety-inducing, and technology-intensive imaging centers. When given the opportunity to change a single aspect of the environmental or imaging facility experience, patients feel much more in control of the otherwise unfamiliar and uncomfortable setting. Incorporating commercial, easily adaptable, ambient lighting products within clinical imaging environments allows patients to individually customize their environment for a more personalized and comfortable experience. OBJECTIVE The aim of this pilot study was to use a customizable colored light-emitting diode (LED) lighting system within a clinical imaging environment and demonstrate the feasibility and initial findings of enabling healthy subjects to customize the ambient lighting and color. Improving the patient experience within clinical imaging environments with patient-preferred ambient lighting and color may improve overall patient comfort, compliance, and participation in the imaging study and indirectly contribute to improving diagnostic image quality. METHODS We installed consumer-based internet protocol addressable LED lights using the ZigBee standard in different PET/CT scan rooms within a clinical imaging environment. We recruited healthy volunteers (n=35) to generate pilot data in order to develop a subsequent clinical trial. The visual perception assessment procedure utilized questionnaires with preprogrammed light/color settings and further assessed how subjects preferred ambient light and color within a clinical imaging setting. RESULTS Technical implementation using programmable LED lights was performed without any hardware or electrical modifications to the existing clinical imaging environment. Subject testing revealed substantial variabilities in color perception; however, clear trends in subject color preference were noted. In terms of the color hue of the imaging environment, 43% (15/35) found blue and 31% (11/35) found yellow to be the most relaxing. Conversely, 69% (24/35) found red, 17% (6/35) found yellow, and 11% (4/35) found green to be the least relaxing. CONCLUSIONS With the majority of subjects indicating that colored lighting within a clinical imaging environment would contribute to an improved patient experience, we predict that enabling patients to customize environmental factors like lighting and color to individual preferences will improve patient comfort and patient satisfaction. Improved patient comfort in clinical imaging environments may also help to minimize patient-specific imaging artifacts that can otherwise limit diagnostic image quality. CLINICALTRIAL ClinicalTrials.gov NCT03456895; https://clinicaltrials.gov/ct2/show/NCT03456895