The MoveMind randomized controlled trial, described in a protocol paper published in Frontiers in Physiology by researchers at São Paulo State University (UNESP) and collaborators including experts from King’s College London, Deakin University, and the University of British Columbia, will enroll 150 adults aged 18 to 59 with a confirmed diagnosis of major depressive disorder. Participants will be randomized in equal numbers into three groups: a high-volume resistance training group performing four sets of 10 to 12 repetitions at their repetition maximum, a low-volume group performing just two sets at the same intensity, and a non-exercise control group placed on a waiting list. Both training groups will exercise three non-consecutive days per week for eight weeks, targeting all the major muscle groups through eleven exercises ranging from leg presses to bench presses and rows.

The scientific logic behind the comparison is more nuanced than simply asking whether more exercise is better. Total training volume, calculated as the sum of repetitions performed multiplied by the load lifted, is a key driver of muscle hypertrophy and of the acute metabolic stress a session produces. Higher volumes flood the working muscles with greater accumulations of metabolites such as lactate, inorganic phosphate, and hydrogen ions. Intriguingly, lactate itself has been linked to brain-derived neurotrophic factor, or BDNF, a protein proposed as a crucial mediator of exercise-induced neuroplasticity. Researchers led by Fabrício Eduardo Rossi hypothesize that high-volume training may therefore exert its antidepressant effects primarily through neurobiological pathways, by elevating BDNF and insulin-like growth factor 1, boosting the anti-inflammatory cytokine IL-10, and reducing pro-inflammatory markers including TNF-α, IL-6, IL-1β, C-reactive protein, cortisol, and insulin.

Low-volume training, by contrast, may work through an entirely different route: the mind rather than the molecules. Sessions that take less time and impose less perceived burden are expected to strengthen exercise self-efficacy and intrinsic motivation, the psychological factors that most strongly predict whether people keep showing up to the gym. This distinction matters enormously for depression specifically, because the disorder itself erodes motivation and energy, and higher baseline symptom severity has been linked to higher dropout rates from exercise interventions. Meta-analytic data report dropout rates around 17 percent in exercise trials for depression, and dropout in turn threatens both the effectiveness of treatment and the validity of research findings. If two sets can deliver the mood benefits of four sets while being easier to sustain, the clinical implications could be transformative for exercise prescription in psychiatry.

The trial’s measurement plan reflects this dual mechanistic hypothesis. The primary outcome, depressive symptom severity, will be assessed by a blinded psychiatrist using the Montgomery–Åsberg Depression Rating Scale, a ten-item clinical interview scored from 0 to 60, at baseline, immediately after the eight-week intervention, and again at a three-month follow-up. Treatment response will be defined as at least a 50 percent improvement from baseline, with remission thresholds set between 8 and 14 points on the scale. Secondary outcomes capture the hypothesized mechanisms: blood samples collected fasting at rest, always between 6:30 and 7:00 a.m. to control for circadian rhythms and timed to menstrual cycle phase, will be analyzed by enzyme-linked immunosorbent assay for the full panel of inflammatory and metabolic biomarkers. Psychological measures will include validated Portuguese-language instruments for self-efficacy, affective responses during exercise, and motivation, with the Feeling Scale administered both before warm-up and immediately after each session, and even on non-training days.

Methodological rigor extends throughout the protocol. Participants undergo a two-week familiarization phase during which load prediction procedures estimate their 10 to 12 repetition maximum for each exercise, ensuring that training intensity is standardized between groups so that volume remains the only experimental variable. Randomization is conducted in a 1:1:1 ratio by a researcher with no participant contact, using sequentially numbered opaque sealed envelopes for allocation concealment, and participants are pair-matched on initial depressive symptoms and biological sex. Although participants and trainers cannot be blinded to assignment, the psychiatrists, assessors, and laboratory analysts remain strictly blinded. Training sessions are supervised with a 1:1 participant-to-instructor ratio, perceived exertion is monitored on the OMNI-Resistance Exercise Scale with a target range of 6 to 8 out of 10, and loads are progressed whenever a participant can exceed twelve repetitions with good technique. All statistical analyses, including the primary intention-to-treat linear mixed-effects models, will be performed by a statistician blinded to group allocation.

The trial also reaches beyond mood and biomarkers into lifestyle territory that intersects with depression biology. Tertiary outcomes include dietary intake and ultra-processed food consumption assessed through 24-hour dietary recalls analyzed with the QuestNova system, body composition measured by dual-energy X-ray absorptiometry, muscular strength estimated through a velocity-based protocol using a linear transducer in the hexagonal bar squat, and sleep quality measured by the Pittsburgh Sleep Quality Index. These additions acknowledge that depression travels with unfavorable dietary patterns, weight gain, and disturbed sleep, all of which feed the low-grade inflammation and metabolic dysfunction increasingly implicated in the disorder’s pathophysiology. Medication use will be carefully tracked and converted to fluoxetine-equivalent doses, and menstrual cycle phase, diet quality, illness duration, and number of depressive episodes will all be included as covariates in adjusted models.

Perhaps the most ambitious component is the mediation analysis. Using structural equation modeling and latent growth curve mediation frameworks, the researchers will test whether changes in biomarkers or psychological variables statistically explain the reductions in depressive symptoms within each training group. Subgroup analyses will compare responders and non-responders, and exploratory analyses will probe whether men and women, or younger and older participants, respond differently to the two volumes. The sample size, set conservatively at 50 participants per group after accounting for expected attrition, was powered on the basis of an earlier trial in older adults that found large antidepressant effects for both high- and low-intensity weight training compared with usual care. Notably, that trial examined intensity rather than volume, and its effect sizes far exceed those in more recent meta-analyses, which cluster around standardized mean differences of 0.49 to 0.66, underscoring why a carefully powered, directly comparative modern trial is needed.

The team is candid about limitations: participants and supervisors cannot be blinded, the control group is a passive waiting list rather than an attention-matched active condition, no biological sampling will occur at follow-up, and the eight-week intervention plus three-month follow-up cannot speak to long-term sustainability. Yet the strengths are considerable, including the gold-standard randomized design, the mechanistic depth, the extensive covariate control, and the direct head-to-head comparison of training volumes that no prior study has performed in this population. The trial is registered in the Brazilian Registry of Clinical Trials under identifier RBR-9tn4ncp, conducted under the Declaration of Helsinki with ethics approval from UNESP, and follows the SPIRIT 2025 reporting checklist for trial protocols.

If the MoveMind investigators’ hypotheses hold, the payoff would be a more personalized and practical form of exercise prescription for depression: longer, more metabolically demanding workouts for patients most likely to benefit from neurobiological adaptation, and shorter, less daunting sessions for those whose success hinges on confidence and adherence. In a condition where the disease itself sabotages the very behaviors that treat it, identifying the minimal effective dose of resistance training could remove one of the largest barriers between millions of patients and a therapy that costs nothing but effort. The results, expected after the eight-week interventions and follow-up assessments conclude, may finally tell psychiatrists not just whether to prescribe the barbell, but precisely how much weight, and how many sets, the prescription should carry.

Subject of Research: Effects of resistance training volume on depressive symptoms and underlying mechanisms in major depressive disorder

Article Title: Resistance training volume for major depressive disorder: the MoveMind randomized controlled trial protocol

Article References: Resistance training volume for major depressive disorder: the MoveMind randomized controlled trial protocol. (n.d.). https://doi.org/10.3389/fphys.2026.1943543

Image Credits: AI Generated

DOI: 10.3389/fphys.2026.1943543

Keywords: major depressive disorder, resistance training, training volume, BDNF, inflammation, randomized controlled trial, exercise adherence, self-efficacy, mental health, exercise prescription, biomarkers, neuroplasticity

The research team, led by Koshiro Inoue of Health Sciences University of Hokkaido, took advantage of a natural experiment hiding in the Japanese racing calendar. They surveyed finishers at the Tsukuba Marathon in November 2022 and 2023, and at the Hokkaido Marathon in August 2023. According to data from the Japan Meteorological Agency, the mean air temperatures during those races were 6.5, 20.6, and 28.2 degrees Celsius respectively, with estimated wet-bulb globe temperatures of 11.2, 22.2, and 31.5 degrees. In the classification scheme of earlier endurance research, those conditions correspond roughly to natural, moderate heat, and extreme heat environments, giving the scientists three distinct thermal snapshots of the same 42.195-kilometre distance.

In total, 1,938 male runners provided complete datasets, well above the minimum of 1,022 required by the team’s a priori power analysis. Each participant completed an online questionnaire before racing, reporting personal best marathon time over the preceding one to three years, age, years of running experience, height and weight, and detailed training habits over the previous three months, including weekly running distance, the longest single run, and weekly running frequency. Official net finish times were then retrieved from race websites. Crucially, the runners’ profiles differed between events: those who chose the hot Hokkaido race tended to have slower personal bests, higher body mass index, longer running careers, lower weekly mileage, and less frequent training than their counterparts at the cooler Tsukuba events, a pattern the researchers had to account for statistically.

The analytical centrepiece was a hierarchical multiple regression with interaction terms, a technique that allows scientists to ask not just whether a variable predicts finish time, but whether its predictive power changes across conditions. The baseline model, containing only the runner characteristics, explained about 71 percent of the variance in finish time. Adding the race event, which served as a proxy for temperature, boosted explained variance by a striking 10.7 percent, and the regression coefficients revealed a stepwise slowing from the coolest to the hottest race. Average finish times climbed from 223 minutes in the cool Tsukuba race of 2023, to 234 minutes in the milder 2022 edition, to 281 minutes in the August heat of Hokkaido.

But the headline finding lay in the third model, where temperature significantly moderated the relationships between finish time and four specific variables: personal best time, age, running experience, and body mass index. The associations between training volume, longest run, or training frequency and finish time, by contrast, remained stable across all three thermal conditions. In other words, heat selectively rewires the importance of who the runner is, while leaving the benefits of what the runner does largely intact.

Some of the individual interactions were genuinely counterintuitive. The link between personal best and finish time, strongly positive in both cool races, became significantly flatter in the extreme heat of Hokkaido. That pattern supports the minority view in the literature, advanced by economists Gasparetto and Nesseler, that faster runners suffer proportionally greater declines in hot conditions, perhaps because they run at higher intensities and push closer to their physiological limits, while slower runners, spending longer on the course, were already expected to fare worse. The new data suggest that under extreme heat, the usual hierarchy of ability is compressed, and a fast runner may lose more time to the mercury than a slower one.

Age told a more predictable but sobering story. Older runners were slower at every temperature, but the age-related penalty grew significantly steeper in the two warmer races. This aligns with physiological evidence that thermoregulation, particularly sweating and skin blood flow responses, declines with age, and with large-scale analyses of the New York City Marathon showing that heat amplifies age-related slowing in men between 30 and 64. Body mass index followed a similar trajectory: at the optimal cool temperature it bore no significant relationship to finish time, but its influence emerged and strengthened progressively as temperatures rose, consistent with the known advantages of smaller body size for heat dissipation during distance running and with epidemiological links between higher BMI and exertional heat illness risk.

Perhaps the most curious result concerned running experience. Years of training had no bearing on finish time in the cool race, was associated with slower times in the moderate heat of 2022, and, remarkably, predicted faster finishes in the extreme heat of Hokkaido. The authors suggest that long-accumulated adaptations and racing savvy may become decisive assets precisely when conditions are harshest, making veteran experience a potential key to surviving summer marathons. Meanwhile, the training variables behaved as conventional wisdom expects: greater weekly distance and higher training frequency were reliably associated with faster finishes, and, importantly, those benefits were conferred independently of temperature, implying that the performance payoff of training volume survives even as the thermometer climbs.

The study’s authors are careful about its limits. Participants were predominantly Japanese male recreational runners who volunteered for the survey, the hot condition rested on a single August race at one venue, and self-reported measures of height, weight, and training are known to carry small biases. Course differences between events cannot be fully excluded either. Still, the statistical framework was robust, the sample comfortably exceeded power requirements, and the central conclusion is hard to escape: temperature is not merely another variable in the marathon equation but a structural determinant that alters the weight of the other predictors.

The practical implications arrive at an opportune moment. Climate analyses suggest that opportunities to race in the optimal 3 to 11 degree Celsius range for recreational runners are shrinking, with the probability of ideal conditions at the Tokyo Marathon projected to fall over the coming decades. As more amateur runners face warmer start lines, the new findings point to concrete targets: body mass index, a modifiable factor, becomes a more meaningful lever in the heat, while experience can be deliberately banked. Age, irreversible, demands respect and adjusted expectations. For coaches and runners drafting training plans for the hot races of the future, the message is that the old prediction formulas, built in temperate conditions, may need a thermal correction.

Subject of Research: How air temperature modulates the physiological and training determinants of marathon finish time in male recreational runners

Article Title: Temperature‐driven modulation of factors influencing full‐Marathon time in male recreational runners

Article References: Inoue, K., Yamaguchi, A., Nabekura, Y., Ishihara, T., & Fukuie, T. (2026). Temperature‐driven modulation of factors influencing full‐Marathon time in male recreational runners. Physiological Reports, 14(17), Article e71096. https://doi.org/10.14814/phy2.71096

Image Credits: AI Generated

DOI: 10.14814/phy2.71096

Keywords: marathon, heat stress, thermoregulation, recreational runners, body mass index, running performance, aging athletes, training volume, wet-bulb globe temperature, climate change, exercise physiology, hierarchical regression