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The greater amount of repetitions performed per set is related to increased difficulty to accurately gauge RIR further from failure.

Practitioners should note that as repetitions increase, gauging effort may become less accurate.

There was a significant moderate correlation between 1RM and ACV decline from 30 to 90% 1RM (r = 0.48, p = 0.01).

Strength coaches can use this correlation to better understand how strength levels affect velocity decline during training.

There was a significant moderate correlation between relative back squat strength and ACV decline from 30 to 90% 1RM (r = 0.56, p= < 0.01).

Strength coaches can utilize this correlation to tailor training programs based on relative strength levels.

Lifters with greater absolute and relative strength will experience a larger decrease in ACV between 30 and 90% of their 1RM.

Stronger lifters may need to adjust their training intensity based on expected velocity declines.

Powerlifters trained an average of 4.25 times per week, performing competition-style lifts at specific frequencies: squat 1.64 times, bench press 2.48 times, and deadlift 1.37 times per week.

Trainers should consider the average training frequency and specific lift focus when designing programs for powerlifters.

Programming decisions for competition lifts were influenced by athlete characteristics such as gender, age, and training status.

Coaches should consider individual athlete characteristics when designing training programs for powerlifters.

Small between group effect sizes were observed comparing 4-6 vs. 7-9+ RPE and 7-9 vs. 7-9+ RPE.

While differences exist, they are minimal, suggesting similar effectiveness across RPE levels.

The absolute RIRDIFF was significantly greater when predicting 4RIR (0.993 ± 0.106) versus 1RIR (0.765 ± 0.080).

Practitioners should note that predicting RIR varies significantly based on the number of repetitions intended.

Raw RIRDIFF was significantly higher in weeks 1-4 compared to weeks 5-6 (all p ≤ 0.005).

Trainers may need to adjust RIR predictions as training progresses.

Subjects tended to overpredict RIR in lower repetition sets and underpredict RIR in higher repetition sets.

Practitioners should be aware that athletes may misjudge their effort based on the number of repetitions they are performing.

Trained men can predict RIR close to failure within less than 1 repetition of error under various conditions.

Athletes can accurately gauge their remaining repetitions close to failure, which can inform training intensity.

Non-nutrient factors of the diet may influence appetite and energy intake as much as macronutrient composition.

Practitioners should explore non-nutrient factors when addressing appetite and energy intake.

High GI meals are associated with lower satiety at peak glycemia compared to low GI meals.

High GI foods may lead to increased hunger shortly after consumption, which could affect dietary choices.

High GI meals result in greater late postprandial hunger compared to low GI meals.

Practitioners should be aware that high GI meals may lead to increased hunger later, potentially influencing overall caloric intake.

A high glycemic index (GI) meal elicits increased hunger and late postprandial activation of brain areas linked to food cravings.

Practitioners should be aware that high GI meals can increase hunger and cravings, potentially leading to overeating.

A high GI meal may promote overeating due to insulin dose deviations caused by hyperglycemia or hypoglycemia.

Practitioners should consider the impact of GI on insulin management to prevent overeating.

94% of participants significantly improved their scores on the validated Mindful Eating Questionnaire (P=.001).

Practitioners can consider using mindful eating technologies to enhance awareness and improve eating behaviors.

Participants with food and nutrition insecurity had more symptoms of depression and anxiety compared to participants with food and nutrition security (p<0.05).

Practitioners should consider mental health support for those facing food and nutrition insecurity.

Total repetition count for squat performance was lower at day 10 compared to day 8 within the 1.8g.kg-1.d-1 protein group.

Practitioners should monitor performance over consecutive training days, especially with lower protein intake.

One of two synergist muscles consistently demonstrated higher activity levels during the exercises.

Understanding which muscles are more active can help in designing targeted training programs.

The course focused on psychological dangers associated with avoiding carbohydrates.

Incorporating psychological support in dietary programs can enhance effectiveness.

Psychological capabilities and reflective motivation have direct effects on the frequency of resistance training participation among GLP-1 medication users.

Practitioners should focus on enhancing psychological capabilities and motivation to improve resistance training frequency in GLP-1 users.

Psychological capabilities directly or indirectly influence all resistance training participation characteristics among GLP-1 medication users.

Enhancing psychological capabilities is crucial for improving overall resistance training participation.

Early change in eating-related self-regulation is a stronger predictor of longer-term change in eating-related self-efficacy than the reverse.

Focusing on enhancing self-regulation may be crucial for improving self-efficacy in obesity treatment.