{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T02:28:05Z","timestamp":1793500085483,"version":"4.5.0"},"reference-count":76,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100008205","name":"Auckland University of Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100008205","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sports Med"],"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Sports nutrition guidelines recommend carbohydrate (CHO) intake be individualized to the athlete and modulated according to changes in training load. However, there are limited methods to assess CHO utilization during training sessions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Objectives<\/jats:title>\n            <jats:p>We aimed to (1) quantify bivariate relationships between both CHO and overall energy expenditure (EE) during exercise and commonly used, non-invasive measures of training load across sessions of varying duration and intensity and (2) build and evaluate prediction models to estimate CHO utilization and EE with the same training load measures and easily quantified individual factors.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>This study was undertaken in two parts: a primary study, where participants performed four different laboratory-based cycle training sessions, and a validation study where different participants performed a single laboratory-based training session using one of three exercise modalities (cycling, running, or kayaking). The primary study included 15 cyclists (five female; maximal oxygen consumption [<jats:inline-formula>\n                <jats:alternatives>\n                  <jats:tex-math>$$\\dot{V}$$<\/jats:tex-math>\n                  <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:mover>\n                      <mml:mi>V<\/mml:mi>\n                      <mml:mo>\u02d9<\/mml:mo>\n                    <\/mml:mover>\n                  <\/mml:math>\n                <\/jats:alternatives>\n              <\/jats:inline-formula>O<jats:sub>2<\/jats:sub>max], 51.9\u2009\u00b1\u20097.2\u00a0mL\/kg\/min), the validation study included 21 cyclists (seven female; <jats:inline-formula>\n                <jats:alternatives>\n                  <jats:tex-math>$$\\dot{V}$$<\/jats:tex-math>\n                  <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:mover>\n                      <mml:mi>V<\/mml:mi>\n                      <mml:mo>\u02d9<\/mml:mo>\n                    <\/mml:mover>\n                  <\/mml:math>\n                <\/jats:alternatives>\n              <\/jats:inline-formula>O<jats:sub>2<\/jats:sub>max 53.5\u2009\u00b1\u200911.0\u00a0mL\/kg\/min), 20 runners (six female; <jats:inline-formula>\n                <jats:alternatives>\n                  <jats:tex-math>$$\\dot{V}$$<\/jats:tex-math>\n                  <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:mover>\n                      <mml:mi>V<\/mml:mi>\n                      <mml:mo>\u02d9<\/mml:mo>\n                    <\/mml:mover>\n                  <\/mml:math>\n                <\/jats:alternatives>\n              <\/jats:inline-formula>O<jats:sub>2<\/jats:sub>max 57.5\u2009\u00b1\u20097.2\u00a0mL\/kg\/min), and 18 kayakers (five female; <jats:inline-formula>\n                <jats:alternatives>\n                  <jats:tex-math>$$\\dot{V}$$<\/jats:tex-math>\n                  <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:mover>\n                      <mml:mi>V<\/mml:mi>\n                      <mml:mo>\u02d9<\/mml:mo>\n                    <\/mml:mover>\n                  <\/mml:math>\n                <\/jats:alternatives>\n              <\/jats:inline-formula>O<jats:sub>2<\/jats:sub>max 45.6\u2009\u00b1\u20094.8\u00a0mL\/kg\/min). Training sessions were quantified using six training load metrics: two using heart rate, three using power, and one using perceived exertion. Carbohydrate use and EE were determined separately for aerobic (gas exchange) and anaerobic (net lactate accumulation, body mass, and O<jats:sub>2<\/jats:sub> lactate equivalent method) energy systems and summed. Repeated-measures correlations were used to examine relationships between training load and both CHO utilization and EE. General estimating equations were used to model CHO utilization and EE, using training load alongside measures of fitness and sex. Models were built in the primary study and tested in the validation study. Model performance is reported as the coefficient of determination (<jats:italic>R<\/jats:italic>\n              <jats:sup>2<\/jats:sup>) and mean absolute error, with measures of calibration used for model evaluation and for sport-specific model re-calibration.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Very-large to near-perfect within-subject correlations (<jats:italic>r<\/jats:italic>\u2009=\u20090.76\u20130.96) were evident between all training load metrics and both CHO utilization and EE. In the primary study, all models explained a large amount of variance (<jats:italic>R<\/jats:italic>\n              <jats:sup>2<\/jats:sup>\u2009=\u20090.77\u20130.96) and displayed good accuracy (mean absolute error; CHO\u2009=\u200916\u201321\u00a0g [10\u201314%], EE\u2009=\u200953\u201382\u00a0kcal [7\u201311%]). In the validation study, the mean absolute error ranged from 16\u201350\u00a0g [15\u201345%] for CHO models to 53\u2013182\u00a0kcal [9\u201331%] for EE models. The calibrated mean absolute error ranged from 9\u201320\u00a0g [8\u201318%] for CHO models to 36\u201372\u00a0kcal [6\u201312%] for EE models.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>At the individual level, there are strong linear relationships between all measures of training load and both CHO utilization and EE during cycling. When combined with other measures of fitness, EE and CHO utilization during cycling can be estimated accurately. These models can be applied in running and kayaking when used with a calibration adjustment.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s40279-024-02131-z","type":"journal-article","created":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T18:04:59Z","timestamp":1730484299000},"page":"753-774","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Novel Method to Predict Carbohydrate and Energy Expenditure During Endurance Exercise Using Measures of Training Load"],"prefix":"10.1007","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0014-5878","authenticated-orcid":false,"given":"Jeffrey A.","family":"Rothschild","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stuart","family":"Hofmeyr","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0480-3209","authenticated-orcid":false,"given":"Shaun J.","family":"McLaren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2329-959X","authenticated-orcid":false,"given":"Ed","family":"Maunder","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,1]]},"reference":[{"issue":"3","key":"2131_CR1","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1249\/MSS.0000000000000852","volume":"48","author":"DT Thomas","year":"2016","unstructured":"Thomas DT, Erdman KA, Burke LM. American College of Sports Medicine Joint Position Statement: nutrition and athletic performance. Med Sci Sports Exerc. 2016;48(3):543\u201368. https:\/\/doi.org\/10.1249\/MSS.0000000000000852.","journal-title":"Med Sci Sports Exerc"},{"issue":"5","key":"2131_CR2","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1123\/ijsnem.2018-0289","volume":"28","author":"LM Burke","year":"2018","unstructured":"Burke LM, Hawley JA, Jeukendrup A, Morton JP, Stellingwerff T, Maughan RJ. Toward a common understanding of diet-exercise strategies to manipulate fuel availability for training and competition preparation in endurance sport. Int J Sport Nutr Exerc Metab. 2018;28(5):451\u201363. https:\/\/doi.org\/10.1123\/ijsnem.2018-0289.","journal-title":"Int J Sport Nutr Exerc Metab"},{"issue":"2\u20133","key":"2131_CR3","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/s0034-5687(99)00083-3","volume":"118","author":"PE di Prampero","year":"1999","unstructured":"di Prampero PE, Ferretti G. The energetics of anaerobic muscle metabolism: a reappraisal of older and recent concepts. Respir Physiol. 1999;118(2\u20133):103\u201315. https:\/\/doi.org\/10.1016\/s0034-5687(99)00083-3.","journal-title":"Respir Physiol"},{"issue":"Suppl. 1","key":"2131_CR4","doi-asserted-by":"publisher","first-page":"S28","DOI":"10.1055\/s-2004-830512","volume":"26","author":"AE Jeukendrup","year":"2005","unstructured":"Jeukendrup AE, Wallis GA. Measurement of substrate oxidation during exercise by means of gas exchange measurements. Int J Sports Med. 2005;26(Suppl. 1):S28-37. https:\/\/doi.org\/10.1055\/s-2004-830512.","journal-title":"Int J Sports Med"},{"issue":"8","key":"2131_CR5","doi-asserted-by":"publisher","first-page":"1681","DOI":"10.1113\/JP285762","volume":"602","author":"CT Schytz","year":"2024","unstructured":"Schytz CT, Ortenblad N, Gejl KD, Nielsen J. Differential utilisation of subcellular skeletal muscle glycogen pools: a comparative analysis between 1 and 15 min of maximal exercise. J Physiol. 2024;602(8):1681\u2013702. https:\/\/doi.org\/10.1113\/JP285762.","journal-title":"J Physiol"},{"issue":"4","key":"2131_CR6","doi-asserted-by":"publisher","first-page":"1326","DOI":"10.1152\/jappl.1999.87.4.1326","volume":"87","author":"M Esbjornsson-Liljedahl","year":"1999","unstructured":"Esbjornsson-Liljedahl M, Sundberg CJ, Norman B, Jansson E. Metabolic response in type I and type II muscle fibers during a 30-s cycle sprint in men and women. J Appl Physiol (1985). 1999;87(4):1326\u201332. https:\/\/doi.org\/10.1152\/jappl.1999.87.4.1326.","journal-title":"J Appl Physiol (1985)"},{"issue":"1","key":"2131_CR7","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1152\/japplphysiol.00053.2021","volume":"131","author":"O Horwath","year":"2021","unstructured":"Horwath O, Envall H, Roja J, Emanuelsson EB, Sanz G, Ekblom B, et al. Variability in vastus lateralis fiber type distribution, fiber size, and myonuclear content along and between the legs. J Appl Physiol (1985). 2021;131(1):158\u201373. https:\/\/doi.org\/10.1152\/japplphysiol.00053.2021.","journal-title":"J Appl Physiol (1985)"},{"issue":"4\u20135","key":"2131_CR8","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1007\/s00421-002-0622-4","volume":"87","author":"R Beneke","year":"2002","unstructured":"Beneke R, Pollmann C, Bleif I, Leithauser RM, Hutler M. How anaerobic is the Wingate anaerobic test for humans? Eur J Appl Physiol. 2002;87(4\u20135):388\u201392. https:\/\/doi.org\/10.1007\/s00421-002-0622-4.","journal-title":"Eur J Appl Physiol"},{"issue":"2","key":"2131_CR9","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1123\/IJSPP.2013-0006","volume":"9","author":"P Davis","year":"2014","unstructured":"Davis P, Leithauser RM, Beneke R. The energetics of semicontact 3 \u00d7 2-min amateur boxing. Int J Sports Physiol Perform. 2014;9(2):233\u20139. https:\/\/doi.org\/10.1123\/IJSPP.2013-0006.","journal-title":"Int J Sports Physiol Perform"},{"issue":"3","key":"2131_CR10","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1055\/s-0042-117722","volume":"38","author":"F Milioni","year":"2017","unstructured":"Milioni F, Zagatto AM, Barbieri RA, Andrade VL, Dos Santos JW, Gobatto CA, et al. Energy systems contribution in the running-based anaerobic sprint test. Int J Sports Med. 2017;38(3):226\u201332. https:\/\/doi.org\/10.1055\/s-0042-117722.","journal-title":"Int J Sports Med"},{"issue":"5","key":"2131_CR11","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1007\/s00421-009-1172-9","volume":"107","author":"MF de Campos","year":"2009","unstructured":"de Campos MF, de Moraes Bertuzzi RC, Grangeiro PM, Franchini E. Energy systems contributions in 2,000 m race simulation: a comparison among rowing ergometers and water. Eur J Appl Physiol. 2009;107(5):615\u20139. https:\/\/doi.org\/10.1007\/s00421-009-1172-9.","journal-title":"Eur J Appl Physiol"},{"key":"2131_CR12","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1159\/000421672","volume":"70","author":"M Elia","year":"1992","unstructured":"Elia M, Livesey G. Energy expenditure and fuel selection in biological systems: the theory and practice of calculations based on indirect calorimetry and tracer methods. World Rev Nutr Diet. 1992;70:68\u2013131. https:\/\/doi.org\/10.1159\/000421672.","journal-title":"World Rev Nutr Diet"},{"issue":"2","key":"2131_CR13","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1123\/ijspp.2018-0935","volume":"14","author":"FM Impellizzeri","year":"2019","unstructured":"Impellizzeri FM, Marcora SM, Coutts AJ. Internal and external training load: 15 years on. Int J Sports Physiol Perform. 2019;14(2):270\u20133. https:\/\/doi.org\/10.1123\/ijspp.2018-0935.","journal-title":"Int J Sports Physiol Perform"},{"issue":"Suppl. 2","key":"2131_CR14","doi-asserted-by":"publisher","first-page":"S29","DOI":"10.1123\/ijspp.2016-0403","volume":"12","author":"I Mujika","year":"2017","unstructured":"Mujika I. Quantification of training and competition loads in endurance sports: methods and applications. Int J Sports Physiol Perform. 2017;12(Suppl. 2):S29-217. https:\/\/doi.org\/10.1123\/ijspp.2016-0403.","journal-title":"Int J Sports Physiol Perform"},{"issue":"4","key":"2131_CR15","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1123\/ijspp.2017-0722","volume":"14","author":"T van Erp","year":"2019","unstructured":"van Erp T, Foster C, de Koning JJ. Relationship between various training-load measures in elite cyclists during training, road races, and time trials. Int J Sports Physiol Perform. 2019;14(4):493\u2013500.","journal-title":"Int J Sports Physiol Perform"},{"issue":"5","key":"2131_CR16","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1123\/ijspp.2020-0599","volume":"16","author":"C Foster","year":"2021","unstructured":"Foster C, Boullosa D, McGuigan M, Fusco A, Cortis C, Arney BE, et al. 25 Years of session rating of perceived exertion: historical perspective and development. Int J Sports Physiol Perform. 2021;16(5):612\u201321. https:\/\/doi.org\/10.1123\/ijspp.2020-0599.","journal-title":"Int J Sports Physiol Perform"},{"issue":"5","key":"2131_CR17","doi-asserted-by":"publisher","first-page":"872","DOI":"10.1249\/01.MSS.0000064999.82036.B4","volume":"35","author":"A Lucia","year":"2003","unstructured":"Lucia A, Hoyos J, Santalla A, Earnest C, Chicharro JL. Tour de France versus Vuelta a Espana: which is harder? Med Sci Sports Exerc. 2003;35(5):872\u20138. https:\/\/doi.org\/10.1249\/01.MSS.0000064999.82036.B4.","journal-title":"Med Sci Sports Exerc"},{"key":"2131_CR18","volume-title":"Training and racing with a power meter","author":"H Allen","year":"2019","unstructured":"Allen H, Coggan AR, McGregor S. Training and racing with a power meter. Boulder: VeloPress; 2019."},{"issue":"3","key":"2131_CR19","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1123\/ijspp.2022-0157","volume":"18","author":"KM Vermeire","year":"2023","unstructured":"Vermeire KM, Caen K, Bourgois JG, Boone J. Training load and acute performance decrements following different training sessions. Int J Sports Physiol Perform. 2023;18(3):284\u201392. https:\/\/doi.org\/10.1123\/ijspp.2022-0157.","journal-title":"Int J Sports Physiol Perform"},{"issue":"10","key":"2131_CR20","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1123\/ijspp.2018-0877","volume":"14","author":"T van Erp","year":"2019","unstructured":"van Erp T, Hoozemans M, Foster C, de Koning JJ. The influence of exercise intensity on the association between kilojoules spent and various training loads in professional cycling. Int J Sports Physiol Perform. 2019;14(10):1395\u2013400.","journal-title":"Int J Sports Physiol Perform"},{"key":"2131_CR21","first-page":"1031","volume":"48","author":"JA Rothschild","year":"2022","unstructured":"Rothschild JA, Morton JP, Stewart T, Kilding AE, Plews DJ. The quantification of daily carbohydrate periodization among endurance athletes during 12 weeks of self-selected training: presentation of a novel Carbohydrate Periodization Index. medRxiv. 2022;48:1031.","journal-title":"medRxiv"},{"issue":"7624","key":"2131_CR22","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1136\/bmj.39335.541782.AD","volume":"335","author":"E von Elm","year":"2007","unstructured":"von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007;335(7624):806\u20138. https:\/\/doi.org\/10.1136\/bmj.39335.541782.AD.","journal-title":"BMJ"},{"key":"2131_CR23","doi-asserted-by":"publisher","DOI":"10.1136\/bmj-2023-078378","volume":"385","author":"GS Collins","year":"2024","unstructured":"Collins GS, Moons KGM, Dhiman P, Riley RD, Beam AL, Van Calster B, et al. TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods. BMJ. 2024;385: e078378. https:\/\/doi.org\/10.1136\/bmj-2023-078378.","journal-title":"BMJ"},{"key":"2131_CR24","volume-title":"Borg's perceived exertion and pain scales","author":"G Borg","year":"1998","unstructured":"Borg G. Borg\u2019s perceived exertion and pain scales. Champaign: Human Kinetics; 1998."},{"issue":"2","key":"2131_CR25","doi-asserted-by":"publisher","first-page":"33","DOI":"10.3390\/jfmk6020033","volume":"6","author":"CG Ballmann","year":"2021","unstructured":"Ballmann CG. The influence of music preference on exercise responses and performance: a review. J Funct Morphol Kinesiol. 2021;6(2):33. https:\/\/doi.org\/10.3390\/jfmk6020033.","journal-title":"J Funct Morphol Kinesiol"},{"issue":"3","key":"2131_CR26","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1123\/ijspp.2015-0273","volume":"11","author":"M Fanchini","year":"2016","unstructured":"Fanchini M, Ferraresi I, Modena R, Schena F, Coutts AJ, Impellizzeri FM. Use of CR100 Scale for session rating of perceived exertion in soccer and its interchangeability with the CR10. Int J Sports Physiol Perform. 2016;11(3):388\u201392. https:\/\/doi.org\/10.1123\/ijspp.2015-0273.","journal-title":"Int J Sports Physiol Perform"},{"issue":"3","key":"2131_CR27","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1080\/17461391.2020.1748117","volume":"21","author":"V Cerezuela-Espejo","year":"2021","unstructured":"Cerezuela-Espejo V, Hernandez-Belmonte A, Courel-Ibanez J, Conesa-Ros E, Mora-Rodriguez R, Pallares JG. Are we ready to measure running power? Repeatability and concurrent validity of five commercial technologies. Eur J Sport Sci. 2021;21(3):341\u201350. https:\/\/doi.org\/10.1080\/17461391.2020.1748117.","journal-title":"Eur J Sport Sci"},{"key":"2131_CR28","unstructured":"Maturana FM. whippr: tools for manipulating gas exchange data. R package version 0.1.2 ed2022."},{"issue":"4","key":"2131_CR29","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1093\/ajcn\/47.4.608","volume":"47","author":"G Livesey","year":"1988","unstructured":"Livesey G, Elia M. Estimation of energy expenditure, net carbohydrate utilization, and net fat oxidation and synthesis by indirect calorimetry: evaluation of errors with special reference to the detailed composition of fuels. Am J Clin Nutr. 1988;47(4):608\u201328. https:\/\/doi.org\/10.1093\/ajcn\/47.4.608.","journal-title":"Am J Clin Nutr"},{"issue":"17","key":"2131_CR30","doi-asserted-by":"publisher","first-page":"7189","DOI":"10.1074\/jbc.M116.774471","volume":"292","author":"SA Mookerjee","year":"2017","unstructured":"Mookerjee SA, Gerencser AA, Nicholls DG, Brand MD. Quantifying intracellular rates of glycolytic and oxidative ATP production and consumption using extracellular flux measurements. J Biol Chem. 2017;292(17):7189\u2013207. https:\/\/doi.org\/10.1074\/jbc.M116.774471.","journal-title":"J Biol Chem"},{"issue":"9","key":"2131_CR31","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.1123\/ijspp.2020-0662","volume":"16","author":"KM Vermeire","year":"2021","unstructured":"Vermeire KM, Van de Casteele F, Gosseries M, Bourgois JG, Ghijs M, Boone J. The influence of different training load quantification methods on the fitness-fatigue model. Int J Sports Physiol Perform. 2021;16(9):1261\u20139. https:\/\/doi.org\/10.1123\/ijspp.2020-0662.","journal-title":"Int J Sports Physiol Perform"},{"key":"2131_CR32","doi-asserted-by":"publisher","first-page":"456","DOI":"10.3389\/fpsyg.2017.00456","volume":"8","author":"JZ Bakdash","year":"2017","unstructured":"Bakdash JZ, Marusich LR. Repeated measures correlation. Front Psychol. 2017;8:456. https:\/\/doi.org\/10.3389\/fpsyg.2017.00456.","journal-title":"Front Psychol"},{"key":"2131_CR33","first-page":"36","volume":"19","author":"W Hopkins","year":"2015","unstructured":"Hopkins W. Spreadsheets for analysis of validity and reliability. Sportscience. 2015;19:36\u201342.","journal-title":"Sportscience"},{"key":"2131_CR34","doi-asserted-by":"publisher","first-page":"2775","DOI":"10.1007\/s40279-022-01727-7","volume":"52","author":"J Rothschild","year":"2022","unstructured":"Rothschild J, Kilding AE, Stewart T, Plews DJ. Factors influencing substrate oxidation during submaximal cycling: a modelling analysis. Sports Med. 2022;52:2775\u201395.","journal-title":"Sports Med"},{"key":"2131_CR35","doi-asserted-by":"publisher","DOI":"10.1037\/met0000620","author":"D McNeish","year":"2023","unstructured":"McNeish D. A practical guide to selecting and blending approaches for clustered data: Clustered errors, multilevel models, and fixed-effect models. Psychol Methods. 2023. https:\/\/doi.org\/10.1037\/met0000620.","journal-title":"Psychol Methods"},{"issue":"1","key":"2131_CR36","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1111\/j.0006-341x.2001.00120.x","volume":"57","author":"W Pan","year":"2001","unstructured":"Pan W. Akaike\u2019s information criterion in generalized estimating equations. Biometrics. 2001;57(1):120\u20135. https:\/\/doi.org\/10.1111\/j.0006-341x.2001.00120.x.","journal-title":"Biometrics"},{"issue":"12","key":"2131_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v034.i12","volume":"34","author":"V Calcagno","year":"2010","unstructured":"Calcagno V, de Mazancourt C. glmulti: an R package for easy automated model selection with (generalized) linear models. J Stat Softw. 2010;34(12):1\u201329.","journal-title":"J Stat Softw"},{"issue":"15","key":"2131_CR38","doi-asserted-by":"publisher","first-page":"3301","DOI":"10.1093\/bioinformatics\/bti499","volume":"21","author":"AM Molinaro","year":"2005","unstructured":"Molinaro AM, Simon R, Pfeiffer RM. Prediction error estimation: a comparison of resampling methods. Bioinformatics. 2005;21(15):3301\u20137. https:\/\/doi.org\/10.1093\/bioinformatics\/bti499.","journal-title":"Bioinformatics"},{"key":"2131_CR39","doi-asserted-by":"publisher","DOI":"10.1136\/bmj-2023-074819","volume":"384","author":"GS Collins","year":"2024","unstructured":"Collins GS, Dhiman P, Ma J, Schlussel MM, Archer L, Van Calster B, et al. Evaluation of clinical prediction models (part 1): from development to external validation. BMJ. 2024;384: e074819. https:\/\/doi.org\/10.1136\/bmj-2023-074819.","journal-title":"BMJ"},{"issue":"1","key":"2131_CR40","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1186\/s12874-022-01801-8","volume":"22","author":"MAE Binuya","year":"2022","unstructured":"Binuya MAE, Engelhardt EG, Schats W, Schmidt MK, Steyerberg EW. Methodological guidance for the evaluation and updating of clinical prediction models: a systematic review. BMC Med Res Methodol. 2022;22(1):316. https:\/\/doi.org\/10.1186\/s12874-022-01801-8.","journal-title":"BMC Med Res Methodol"},{"key":"2131_CR41","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.m441","volume":"368","author":"RD Riley","year":"2020","unstructured":"Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, et al. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020;368: m441. https:\/\/doi.org\/10.1136\/bmj.m441.","journal-title":"BMJ"},{"issue":"7","key":"2131_CR42","doi-asserted-by":"publisher","first-page":"1262","DOI":"10.1002\/sim.7993","volume":"38","author":"RD Riley","year":"2019","unstructured":"Riley RD, Snell KIE, Ensor J, Burke DL, Harrell FE Jr, Moons KGM, et al. Minimum sample size for developing a multivariable prediction model. Part I: continuous outcomes. Stat Med. 2019;38(7):1262\u201375. https:\/\/doi.org\/10.1002\/sim.7993.","journal-title":"Stat Med"},{"issue":"1","key":"2131_CR43","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1002\/sim.8766","volume":"40","author":"L Archer","year":"2021","unstructured":"Archer L, Snell KIE, Ensor J, Hudda MT, Collins GS, Riley RD. Minimum sample size for external validation of a clinical prediction model with a continuous outcome. Stat Med. 2021;40(1):133\u201346. https:\/\/doi.org\/10.1002\/sim.8766.","journal-title":"Stat Med"},{"key":"2131_CR44","doi-asserted-by":"publisher","DOI":"10.51224\/SRXIV.16","author":"FM Impellizzeri","year":"2021","unstructured":"Impellizzeri FM, Jeffries AC, Weisman A, Coutts AJ, McCall A, McLaren SJ, et al. A clarification of the (mis) use of the term \u2018load\u2019in sport and exercise science: why it is appropriate and scientific. SportRxiv. 2021. https:\/\/doi.org\/10.51224\/SRXIV.16.","journal-title":"SportRxiv"},{"issue":"11","key":"2131_CR45","doi-asserted-by":"publisher","first-page":"812","DOI":"10.1016\/j.tem.2020.08.003","volume":"31","author":"LV Andreato","year":"2020","unstructured":"Andreato LV. High-intensity interval training: methodological considerations for interpreting results and conducting research. Trends Endocrinol Metab. 2020;31(11):812\u20137. https:\/\/doi.org\/10.1016\/j.tem.2020.08.003.","journal-title":"Trends Endocrinol Metab"},{"issue":"6","key":"2131_CR46","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1016\/j.jsams.2024.03.005","volume":"27","author":"M Mateo-March","year":"2024","unstructured":"Mateo-March M, Leo P, Muriel X, Javaloyes A, Mujika I, Barranco-Gil D, et al. Is all work the same? Performance after accumulated work of differing intensities in male professional cyclists. J Sci Med Sport. 2024;27(6):430\u20134.","journal-title":"J Sci Med Sport"},{"issue":"7","key":"2131_CR47","doi-asserted-by":"publisher","first-page":"2039","DOI":"10.1007\/s00421-021-04676-7","volume":"121","author":"FM Maturana","year":"2021","unstructured":"Maturana FM, Schellhorn P, Erz G, Burgstahler C, Widmann M, Munz B, et al. Individual cardiovascular responsiveness to work-matched exercise within the moderate- and severe-intensity domains. Eur J Appl Physiol. 2021;121(7):2039\u201359. https:\/\/doi.org\/10.1007\/s00421-021-04676-7.","journal-title":"Eur J Appl Physiol"},{"issue":"5","key":"2131_CR48","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.1007\/s40279-018-0867-7","volume":"48","author":"SG Impey","year":"2018","unstructured":"Impey SG, Hearris MA, Hammond KM, Bartlett JD, Louis J, Close GL, et al. Fuel for the work required: a theoretical framework for carbohydrate periodization and the glycogen threshold hypothesis. Sports Med. 2018;48(5):1031\u201348.","journal-title":"Sports Med"},{"issue":"6","key":"2131_CR49","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1007\/s40279-021-01610-x","volume":"52","author":"JA Rothschild","year":"2022","unstructured":"Rothschild JA, Islam H, Bishop DJ, Kilding AE, Stewart T, Plews DJ. Factors influencing AMPK activation during cycling exercise: a pooled analysis and meta-regression. Sports Med. 2022;52(6):1273\u201394. https:\/\/doi.org\/10.1007\/s40279-021-01610-x.","journal-title":"Sports Med"},{"issue":"4","key":"2131_CR50","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1249\/mss.0b013e3180304570","volume":"39","author":"J Helgerud","year":"2007","unstructured":"Helgerud J, Hoydal K, Wang E, Karlsen T, Berg P, Bjerkaas M, et al. Aerobic high-intensity intervals improve VO2max more than moderate training. Med Sci Sports Exerc. 2007;39(4):665\u201371. https:\/\/doi.org\/10.1249\/mss.0b013e3180304570.","journal-title":"Med Sci Sports Exerc"},{"issue":"7","key":"2131_CR51","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.1249\/MSS.0b013e31816c4839","volume":"40","author":"SE Gormley","year":"2008","unstructured":"Gormley SE, Swain DP, High R, Spina RJ, Dowling EA, Kotipalli US, et al. Effect of intensity of aerobic training on VO2max. Med Sci Sports Exerc. 2008;40(7):1336\u201343. https:\/\/doi.org\/10.1249\/MSS.0b013e31816c4839.","journal-title":"Med Sci Sports Exerc"},{"issue":"1","key":"2131_CR52","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1186\/s40798-023-00579-3","volume":"9","author":"M Reuter","year":"2023","unstructured":"Reuter M, Rosenberger F, Barz A, Venhorst A, Blanz L, Hecksteden A, et al. Does higher intensity increase the rate of responders to endurance training when total energy expenditure remains constant? A randomized controlled trial. Sports Med Open. 2023;9(1):35.","journal-title":"Sports Med Open"},{"issue":"1","key":"2131_CR53","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1002\/cphy.c110007","volume":"2","author":"GA Brooks","year":"2012","unstructured":"Brooks GA. Bioenergetics of exercising humans. Compr Physiol. 2012;2(1):537\u201362. https:\/\/doi.org\/10.1002\/cphy.c110007.","journal-title":"Compr Physiol"},{"issue":"Pt 3","key":"2131_CR54","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1113\/jphysiol.2002.018820","volume":"541","author":"MJ Watt","year":"2002","unstructured":"Watt MJ, Heigenhauser GJ, Dyck DJ, Spriet LL. Intramuscular triacylglycerol, glycogen and acetyl group metabolism during 4 h of moderate exercise in man. J Physiol. 2002;541(Pt 3):969\u201378. https:\/\/doi.org\/10.1113\/jphysiol.2002.018820.","journal-title":"J Physiol"},{"issue":"1","key":"2131_CR55","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1152\/jappl.1995.78.1.288","volume":"78","author":"M Hargreaves","year":"1995","unstructured":"Hargreaves M, McConell G, Proietto J. Influence of muscle glycogen on glycogenolysis and glucose uptake during exercise in humans. J Appl Physiol (1985). 1995;78(1):288\u201392. https:\/\/doi.org\/10.1152\/jappl.1995.78.1.288.","journal-title":"J Appl Physiol (1985)"},{"issue":"4","key":"2131_CR56","doi-asserted-by":"publisher","first-page":"887","DOI":"10.1152\/japplphysiol.00353.2022","volume":"134","author":"PK Gill","year":"2023","unstructured":"Gill PK, Kipp S, Beck ON, Kram R. It is time to abandon single-value oxygen uptake energy equivalents. J Appl Physiol (1985). 2023;134(4):887\u201390. https:\/\/doi.org\/10.1152\/japplphysiol.00353.2022.","journal-title":"J Appl Physiol (1985)"},{"issue":"5","key":"2131_CR57","doi-asserted-by":"publisher","first-page":"E1202","DOI":"10.1152\/ajpendo.2000.279.5.E1202","volume":"279","author":"Z-P Chen","year":"2000","unstructured":"Chen Z-P, McConell GK, Michell BJ, Snow RJ, Canny BJ, Kemp BE. AMPK signaling in contracting human skeletal muscle: acetyl-CoA carboxylase and NO synthase phosphorylation. Am J Physiol Endocrinol Metab. 2000;279(5):E1202\u20136.","journal-title":"Am J Physiol Endocrinol Metab"},{"issue":"Pt 3","key":"2131_CR58","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1113\/jphysiol.2006.120972","volume":"577","author":"JB Birk","year":"2006","unstructured":"Birk JB, Wojtaszewski JF. Predominant alpha2\/beta2\/gamma3 AMPK activation during exercise in human skeletal muscle. J Physiol. 2006;577(Pt 3):1021\u201332. https:\/\/doi.org\/10.1113\/jphysiol.2006.120972.","journal-title":"J Physiol"},{"issue":"3","key":"2131_CR59","doi-asserted-by":"publisher","first-page":"E566","DOI":"10.1152\/ajpendo.00023.2006","volume":"291","author":"RS Lee-Young","year":"2006","unstructured":"Lee-Young RS, Palmer MJ, Linden KC, LePlastrier K, Canny BJ, Hargreaves M, et al. Carbohydrate ingestion does not alter skeletal muscle AMPK signaling during exercise in humans. Am J Physiol Endocrinol Metab. 2006;291(3):E566\u201373.","journal-title":"Am J Physiol Endocrinol Metab"},{"issue":"19","key":"2131_CR60","doi-asserted-by":"publisher","first-page":"4271","DOI":"10.1113\/JP280247","volume":"598","author":"R Jensen","year":"2020","unstructured":"Jensen R, Ortenblad N, Stausholm MH, Skjaerbaek MC, Larsen DN, Hansen M, et al. Heterogeneity in subcellular muscle glycogen utilisation during exercise impacts endurance capacity in men. J Physiol. 2020;598(19):4271\u201392. https:\/\/doi.org\/10.1113\/JP280247.","journal-title":"J Physiol"},{"key":"2131_CR61","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.jclinepi.2015.04.005","volume":"69","author":"EW Steyerberg","year":"2016","unstructured":"Steyerberg EW, Harrell FE Jr. Prediction models need appropriate internal, internal-external, and external validation. J Clin Epidemiol. 2016;69:245\u20137. https:\/\/doi.org\/10.1016\/j.jclinepi.2015.04.005.","journal-title":"J Clin Epidemiol"},{"issue":"2","key":"2131_CR62","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1123\/ijsnem.2020-0216","volume":"31","author":"RG Stables","year":"2021","unstructured":"Stables RG, Kasper AM, Sparks SA, Morton JP, Close GL. An assessment of the validity of the remote food photography method (termed Snap-N-Send) in experienced and inexperienced sport nutritionists. Int J Sport Nutr Exerc Metab. 2021;31(2):125\u201334. https:\/\/doi.org\/10.1123\/ijsnem.2020-0216.","journal-title":"Int J Sport Nutr Exerc Metab"},{"issue":"9","key":"2131_CR63","doi-asserted-by":"publisher","first-page":"5511","DOI":"10.3390\/app13095511","volume":"13","author":"J Olaya-Cuartero","year":"2023","unstructured":"Olaya-Cuartero J, Pueo B, Penichet-Tomas A, Villalon-Gasch L. Does power output at critical power intensity interchange between cycling and running? Appl Sci. 2023;13(9):5511.","journal-title":"Appl Sci"},{"issue":"2","key":"2131_CR64","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1007\/s40279-021-01581-z","volume":"52","author":"DA Keir","year":"2022","unstructured":"Keir DA, Iannetta D, Mattioni Maturana F, Kowalchuk JM, Murias JM. Identification of non-invasive exercise thresholds: methods, strategies, and an online App. Sports Med. 2022;52(2):237\u201355. https:\/\/doi.org\/10.1007\/s40279-021-01581-z.","journal-title":"Sports Med"},{"issue":"4","key":"2131_CR65","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1139\/h00-024","volume":"25","author":"MA Tarnopolsky","year":"2000","unstructured":"Tarnopolsky MA. Gender differences in substrate metabolism during endurance exercise. Can J Appl Physiol. 2000;25(4):312\u201327. https:\/\/doi.org\/10.1139\/h00-024.","journal-title":"Can J Appl Physiol"},{"issue":"2","key":"2131_CR66","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1123\/ijsnem.17.2.189","volume":"17","author":"RT McLay","year":"2007","unstructured":"McLay RT, Thomson CD, Williams SM, Rehrer NJ. Carbohydrate loading and female endurance athletes: effect of menstrual-cycle phase. Int J Sport Nutr Exerc Metab. 2007;17(2):189\u2013205. https:\/\/doi.org\/10.1123\/ijsnem.17.2.189.","journal-title":"Int J Sport Nutr Exerc Metab"},{"issue":"6","key":"2131_CR67","doi-asserted-by":"publisher","first-page":"1284","DOI":"10.1152\/japplphysiol.00346.2023","volume":"135","author":"AC D'Souza","year":"2023","unstructured":"D\u2019Souza AC, Wageh M, Williams JS, Colenso-Semple LM, McCarthy DG, McKay AKA, et al. Menstrual cycle hormones and oral contraceptives: a multimethod systems physiology-based review of their impact on key aspects of female physiology. J Appl Physiol (1985). 2023;135(6):1284\u201399. https:\/\/doi.org\/10.1152\/japplphysiol.00346.2023.","journal-title":"J Appl Physiol (1985)"},{"issue":"3","key":"2131_CR68","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1123\/ijsn.4.3.299","volume":"4","author":"AC Hackney","year":"1994","unstructured":"Hackney AC, McCracken-Compton MA, Ainsworth B. Substrate responses to submaximal exercise in the midfollicular and midluteal phases of the menstrual cycle. Int J Sport Nutr. 1994;4(3):299\u2013308. https:\/\/doi.org\/10.1123\/ijsn.4.3.299.","journal-title":"Int J Sport Nutr"},{"issue":"9S","key":"2131_CR69","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1249\/01.mss.0000876480.87986.45","volume":"54","author":"M Wageh","year":"2022","unstructured":"Wageh M, Williams JS, McCarthy DG, Tarnopolsky MA, MacDonald MJ, Gibala MJ, et al. Hormonal cycling and substrate oxidation at rest and during exercise: a systematic review and meta-analysis: 473. Med Sci Sports Exerc. 2022;54(9S):115.","journal-title":"Med Sci Sports Exerc"},{"issue":"4","key":"2131_CR70","doi-asserted-by":"publisher","first-page":"1291","DOI":"10.3390\/nu13041291","volume":"13","author":"JA Rothschild","year":"2021","unstructured":"Rothschild JA, Kilding AE, Broome SC, Stewart T, Cronin JB, Plews DJ. Pre-exercise carbohydrate or protein ingestion influences substrate oxidation but not performance or hunger compared with cycling in the fasted state. Nutrients. 2021;13(4):1291. https:\/\/doi.org\/10.3390\/nu13041291.","journal-title":"Nutrients"},{"issue":"7","key":"2131_CR71","doi-asserted-by":"publisher","first-page":"1047","DOI":"10.1123\/ijspp.2019-0402","volume":"15","author":"D Barranco-Gil","year":"2020","unstructured":"Barranco-Gil D, Gil-Cabrera J, Valenzuela PL, Alejo LB, Montalvo-Perez A, Talavera E, et al. Functional threshold power: relationship with respiratory compensation point and effects of various warm-up protocols. Int J Sports Physiol Perform. 2020;15(7):1047\u201351. https:\/\/doi.org\/10.1123\/ijspp.2019-0402.","journal-title":"Int J Sports Physiol Perform"},{"issue":"5","key":"2131_CR72","first-page":"626","volume":"62","author":"S Sitko","year":"2021","unstructured":"Sitko S, Cirer-Sastre R, Corbi F, L\u00f3pez-Laval I. Relationship between functional threshold power, ventilatory threshold and respiratory compensation point in road cycling. J Sports Med Phys Fitness. 2021;62(5):626\u201332.","journal-title":"J Sports Med Phys Fitness"},{"issue":"13","key":"2131_CR73","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1055\/a-2079-1363","volume":"44","author":"S Sitko","year":"2023","unstructured":"Sitko S, Cirer-Sastre R, Lopez-Laval I. An update of the Allen & Coggan Equation to predict 60-min power output in cyclists of different performance levels. Int J Sports Med. 2023;44(13):983\u20137. https:\/\/doi.org\/10.1055\/a-2079-1363.","journal-title":"Int J Sports Med"},{"issue":"23","key":"2131_CR74","doi-asserted-by":"publisher","first-page":"2578","DOI":"10.1080\/02640414.2023.2176045","volume":"40","author":"S Wong","year":"2022","unstructured":"Wong S, Burnley M, Mauger A, Fenghua S, Hopker J. Functional threshold power is not a valid marker of the maximal metabolic steady state. J Sport Sci. 2022;40(23):2578\u201384.","journal-title":"J Sport Sci"},{"key":"2131_CR75","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1123\/ijspp.2018-0539","volume":"14","author":"O Jeffries","year":"2019","unstructured":"Jeffries O, Waldron M, Patterson SD, Galna B. An analysis of variability in power output during indoor and outdoor cycling time trials. Int J Sports Physiol Perform. 2019;14:1273\u20139. https:\/\/doi.org\/10.1123\/ijspp.2018-0539.","journal-title":"Int J Sports Physiol Perform"},{"issue":"8","key":"2131_CR76","doi-asserted-by":"publisher","first-page":"2324","DOI":"10.1519\/JSC.0000000000000384","volume":"28","author":"ME Mieras","year":"2014","unstructured":"Mieras ME, Heesch MW, Slivka DR. Physiological and psychological responses to outdoor vs. laboratory cycling. J Strength Cond Res. 2014;28(8):2324\u20139. https:\/\/doi.org\/10.1519\/JSC.0000000000000384.","journal-title":"J Strength Cond Res"}],"container-title":["Sports Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40279-024-02131-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40279-024-02131-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40279-024-02131-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T17:16:59Z","timestamp":1744305419000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40279-024-02131-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,1]]},"references-count":76,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["2131"],"URL":"https:\/\/doi.org\/10.1007\/s40279-024-02131-z","relation":{},"ISSN":["0112-1642","1179-2035"],"issn-type":[{"value":"0112-1642","type":"print"},{"value":"1179-2035","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,1]]},"assertion":[{"value":"3 October 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 November 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No sources of funding were used to assist in the preparation of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Funding"}},{"value":"Jeffrey A. Rothschild is on the scientific advisory board of Applied Behavior Systems Ltd. Stuart Hofmeyr, Shaun J. McLaren, and Ed Maunder have no conflicts of interest that are directly relevant to the content of this study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}},{"value":"Study protocols and materials were approved by the Auckland University of Technology Ethics Committee (23\/143 and 23\/258).","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"Written informed consent was obtained prior to participating. Participant information sheets were provided prior to scheduling the first session.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to Participate"}},{"value":"Not applicable.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}},{"value":"Data are available at .","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Availability of Data and Material"}},{"value":"Data and R code are available at .","order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Code Availability"}},{"value":"JAR, SJM, and EM conceptualized and designed the study. JAR and SH performed the data collection. JAR performed the analyses and wrote the first draft of the manuscript. All authors edited and revised the manuscript and approved the final version of the manuscript.","order":9,"name":"Ethics","group":{"name":"EthicsHeading","label":"Authors\u2019 Contributions"}}]}}