An appraisal of the SD _IR as an estimate of true individual differences in training responsiveness in parallel‐arm exercise randomized controlled trials

Abstract

Calculating the standard deviation of individual responses (SD IR ) is recommended for estimating the magnitude of individual differences in training responsiveness in parallel‐arm exercise randomized controlled trials (RCTs). The purpose of this review article is to discuss potential limitations of parallel‐arm exercise RCTs that may confound/complicate the interpretation of the SD IR . To provide context for this discussion, we define the sources of variation that contribute to variability in the observed responses to exercise training and review the assumptions that underlie the interpretation of SD IR as a reflection of true individual differences in training responsiveness. This review also contains two novel analyses: (1) we demonstrate differences in variability in changes in diet and physical activity habits across an intervention period in both exercise and control groups, and (2) we examined participant dropout data from six RCTs and found that significantly ( P < 0.001) more participants in control groups (12.8%) dropped out due to dissatisfaction with group assignment compared to exercise groups (3.4%). These novel analyses raise the possibility that the magnitude of within‐subject variability may not be equal between exercise and control groups. Overall, this review highlights that potential limitations of parallel‐arm exercise RCTs can violate the underlying assumptions of the SD IR and suggests that these limitations should be considered when interpreting the SD IR as an estimate of true individual differences in training responsiveness.

Dose–Response Matters! – A Perspective on the Exercise Prescription in Exercise–Cognition Research

“…In order to account for this interindividual heterogeneity, the concept of (i) “responder” [also referred as “individuals with high sensitivity” (Booth and Laye, 2010)] and (ii) “non-responder” [also referred as “individuals with low-sensitivity” (Booth and Laye, 2010), limited responders (Burley et al, 2018), or “individuals which did not respond” (Pickering and Kiely, 2018b)] was introduced, however, with varying definitions (Booth and Laye, 2010; Buford and Pahor, 2012; Scharhag-Rosenberger et al, 2012; Buford et al, 2013; Mann et al, 2014). While the definition and methods to classify responders and non-responders are currently discussed in the literature (Atkinson and Batterham, 2015; Hecksteden et al, 2015, 2018; Bonafiglia et al, 2018, 2019a,b; Swinton et al, 2018; Atkinson et al, 2019; Dankel and Loenneke, 2019), it is relatively accepted that (i) not all outcome variables are affected equally by the responsiveness state (e.g., be a responder or non-responder) (Sparks, 2017; Pickering and Kiely, 2018b, 2019b; Toigo, 2019), (ii) measurement errors are inevitable in repeated measurements and are caused, for instance, by random biological fluctuations that do not represent a meaningful change in the outcome variable (Atkinson and Nevill, 1998; Scharhag-Rosenberger et al, 2012; Atkinson and Batterham, 2015; Williamson et al, 2017; Pickering and Kiely, 2019a), and (iii) some responses are likely to be transient, causing uncertainty regarding the time course of the responsiveness state (Pickering and Kiely, 2018b). Hence, the following working definitions can be proposed (see Table 1).…”

Heterogeneity and incidence of non-response for changes in cardiorespiratory fitness following time-efficient sprint interval exercise training

“…Firstly, and most importantly, whilst the large sample size is a strength of this study, this is a pooled dataset from six independent studies and there were minor differences in training protocols, testing procedures, and the duration of the control intervention (4-weeks for n=14 and 6-weeks for n=26) between some of the studies (described in full in the methods). It is possible that these differences may affect the validity of the SDIR estimate, which assumes that all sources of variability are equal between the exercise and control groups except that the exercise group underwent exercise training (Atkinson and Batterham, 2015;Bonafiglia et al, 2019). However, two pieces of information can help to mitigate these concerns.…”

“…Individual variability in the training-induced change in VO2max in response to REHIT has been alluded to (Metcalfe et al, 2016), but not definitively demonstrated using an adequate sample size, or appropriate experimental and statistical methods. The inclusion of data from no-exercise control group is particularly important when assessing individual responses to exercise training in order to account for the variance caused by technical error, day-to-day biological and random within-subjects variability (Atkinson and Batterham, 2015;Bonafiglia et al, 2019). Thus, the aim of this study was firstly to establish whether true individual variability in changes in VO2max in response to REHIT exists and, if so, to characterise the heterogeneity of response and incidence of nonresponders to this extremely low-volume and time-efficient exercise intervention.…”

Can non-responders be ‘rescued’ by increasing exercise intensity? A quasi-experimental trial of individual responses among humans living with pre-diabetes or type 2 diabetes mellitus in Canada

“…Research staff will emphasise that each participant receives the same dose of exercise (time and energy expenditure), as differences throughout the intervention group can have negative repercussions on the SD IR . 24 Accordingly, enrolment will be discontinued if a participant is unable to achieve the required time allotment for three consecutive weeks, or for a total of 4 weeks during either phase 1 or phase 2. If a participant is absent from the trial for a full week (due to illness, vacation, family emergency, etc), an additional week will be added at the end of the trial for that participant for each week missed.…”