Effects of analogy and explicit instructional strategies on affective responses during lifting tasks among novice exercisers

Vol.:(0123456789) Sport Sciences for Health https://doi.org/10.1007/s11332-025-01393-y RESEARCH Effects ofanalogy andexplicit instructional strategies onaffective responses duringlifting tasks amongnovice exercisers AngelCarnero‑Diaz1,2· JavierPecci1· AdrianaKaplánová3 Received: 18 August 2024 / Accepted: 25 March 2025 © The Author(s) 2025 Abstract The instruction given before a lifting task could modulate the affective responses of the participants in a training program. This study aimed to analyze the effects of two types of instruction—analogy and explicit—on the affective responses of novice exercisers during lifting tasks. Twenty-one subjects participated in the present study. A crossover design was employed, in which all participants experienced both instructional conditions in a randomized within-subjects approach. Instruction was provided before performing each lifting task. On day 1, familiarization was done about questionnaires and tasks. On days 2 and 3, participants performed the lifting tasks under their assigned instructional condition, with counterbalanced order. Affective responses such as preferences, self-efficacy, and feeling scale were assessed after the lifting task. Participants equally preferred analogy and explicit instruction. Nonetheless, in those participants who preferred analogy instruction, the force applied was reduced. Self-efficacy improved with both instructions (p < 0.001), while the feeling scale showed no significant effects (p = 0.157). In conclusion, both instructions enhanced self-efficacy, but only analogy instruction reduced force production. Providing instruction during exercise enhances the overall experience, particularly for novice participants, by offering guidance and increasing confidence. Keywords Self-efficacy· Feeling scale· Explicit learning· Analogy· Coaching· Feedback Introduction The increasing prevalence of sedentary behavior in the contemporary population has proposed substantial challenges in public health. Skeletal muscles act as a key endocrine organ [1], and the lack of its stimulation through vigorous activities not only deprives them of beneficial adaptations but is also linked to aging and poor health [2]. This context is particularly relevant today due to the growing incidence of mental health disorders such as anxiety and depression [3]. The connection between exercise and overall health, especially mental health, goes beyond functional adaptations due to its capacity to modulate emotions and affective responses during practice [4]. From a decision-making perspective, avoiding exercise may seem rational due to the immediate costs in time, energy, and effort [5]. However, negative affective responses during exercise, such as fatigue and discomfort [6], can further discourage participation, despite long-term benefits [7]. This tension between short-term effort and long-term gains directly impacts exercise adherence (Fig.1). Although exercise induces short-term mood improvements (e.g., endorphin release) [8], meaningful physiological changes, such as fat loss and muscle gain, take weeks to develop. Understanding these challenges is key to designing interventions that enhance positive affective responses and long-term adherence. Several efforts have been made to find the optimal intensity for generating positive affective responses [9, 10], although a specific percentage of intensity has not yet been determined [11]. Besides, it has been studied how to overcome the main barrier of lack of time, but no results have been found that shed light on the best way to improve [12]. Some studies have attempted to relate exercise intensity to affective * Adriana Kaplánová adriana.kaplano[email protected] 1 Department ofPhysical Education andSport, University ofSeville, Seville, Spain 2 Universidad Pablo de Olavide, Seville, Spain 3 Department ofSport Science inEducology andHumanities, Faculty ofPhysical Education andSports, Comenius University inBratislava, Bratislava, Slovakia Sport Sciences for Health responses such as enjoyment preferences (PRF), selfefficacy (SE), feeling scale (FS), or autonomy [4, 13]. It is well known that positive feelings during training promote improvements in conflict resolution during learning [4]. However, other variables in exercise programs can modulate affective responses and adherence, such as the type of instruction (augmented feedback) or self-controlled practice. Some studies have analyzed the influence of attentional focus derived from instruction, but these interventions have focused on the dichotomy between task-associated focus or dissociated focus, overlooking the influence of different associated instructions [14]. It seems that instruction acts as augmented feedback [15] facilitating performance knowledge through environmental information [16] and providing greater benefits in learning and autonomy [13]. However, environment-oriented instruction, traditionally known as an external focus, is not useful in all tasks due to movement speed [17] or lack of information in the environment [18], such as lifting a load from the ground. In that case, our brain generates, even when attending to an instruction focused on the environment, processing as if it were attending to an instruction focused on movement control, which results in lower learning rates [19, 20]. In these cases, analogy instruction (ANA) is an alternative, when instruction environment-centered is not possible to assist the task. ANA facilitates movement execution by promoting implicit learning, reducing conscious control, and preventing disruptions in motor fluency [21]. Previous studies have shown that ANA enhances motor performance in dynamic tasks by decreasing cognitive load and promoting automaticity [22], as well as in everyday situations to promote learning in natural contexts [23]. Conversely, explicit learning (EXP) requires the participant to consciously attend to movement execution, which can improve precision but may lead to higher cognitive demands and performance breakdown under pressure [24, 25]. Moreover, there is a body of evidence indicating motor performance deterioration when attention is focused on movement control rather than its effect on the environment, especially in some sectors of the population [26]. These distinctions highlight the need to tailor instructional strategies based on the learner’s skill level and task complexity, ensuring optimal motor learning and performance. In addition, not instructing a person can lead to bad habits related to attention and suboptimal responses due to self-instruction [27]. Despite this, some people seem to prefer this type of attention (i.e., focused on movement control) [28]. In other contexts such as pain pedagogy, the literature is stable in stating that participants should be educated and receive short lectures on key concepts related to physiology or cognitive aspects [29]. This fact can be taken into account to educate exercise participants on the importance of following the instructions given by the professional, or not letting their thoughts drift during the tasks [30]. Nonetheless, if they are experts in a skill, the occupation of working memory is so low that the performance is not negatively affected. On the other hand, in novices with fewer resources available [31] attending to an instruction focused on movement control or allowing the person to self-generate such instructions may negatively affect performance as well as affective responses because novice exercisers have no increased information (augmented feedback) to know that the exercise is safe and well performed [32]. Therefore, encouraging practice with better affective responses reduces the fear of not being in control of the task and decreases the amount of effort, resulting in a better performance on the task [33, 34]. In addition, the Fig. 1 The diagram depicts the process of not instructing optimally. Failure to provide augmented feedback provokes negative responses and allows hedonistic decision-making to modulate exercise adherence Sport Sciences for Health practice itself reduces the mental effort derived from it, since it facilitates the automatic control of the subcortical pathways [35]. This means that if the person can exercise regularly, it promotes autonomy and adherence. The conceptual pathway model is delineated in Fig.2. Intrinsic motivation emerges as the crucial factor for a positive experience of training, influencing both acute affective responses and long-term participation [16, 34]. Enhancing intrinsic motivation involves not only addressing the unattractiveness of exercise in the short term but also promoting positive affective responses during the training session, thereby facilitating long-term autonomy and competence [36]. Our hypothesis supports the idea that instruction and/or feedback act as key modulators of exercise responses. Instructions that facilitate an optimal relationship between the organism and the task are those that appear to be most encouraging to autonomy and self-feedback. To the best of our knowledge, no previous studies have studied the effect of different types of instruction (i.e., explicit for the control of the movement and based on analogy learning) on acute affective responses. Therefore, this study aimed to analyze the influence of different types of instruction on measured affective responses, in the hope of modulating exercise behavior and improving adherence to physical activity. Materials andmethods Design This is a randomized blinded clinical trial. This work received ethical approval according to the Pablo Olavide University ethics committee (code: 23/6-8) and registered in clinical trials ANZCTR (code: 386738). Participants 16 males (age = 21.94 ± 3.21) and 5 females (age = 22.15 ± 1.36) were included for this study. All participants were queried regarding their involvement in formal physical exercise or fitness training. This inquiry aimed to mitigate potential complications arising from participants deviating from experimental instructions due to the application of previously acquired strategies during lifting tasks [37]. Therefore, the population under consideration is characterized as novice, since it has not received formal instruction in physical exercise or conditioning programs. Individuals who self-reported such a status were excluded from the study. Additional exclusion criteria encompassed a history of injuries that would make it impossible to make submaximal efforts, as well as impairments in vestibular, visual, or balance functions, cardiovascular diseases, or any neurological disorders [38] using a standardized questionnaire before inclusion in the study. Participants were recruited through social networks and advertisements for participation. Those who met the requirements were randomly and blinded using a randomizer software (https:// www. random. org/). The required sample size was predetermined using the G*Power statistical program (version 3.1.9.4; Dusseldorf, Germany) with the following variables: ANOVA repeated measures (within factors) based on α = 0.05, power (1 − β) = 0.95, and effect size of f = 0.24. Our power analyses revealed a required sample size of n = 20. Before commencing their participation in the study, all participants completed the Physical Activity Readiness Questionnaire (PAR-Q), to assess their eligibility. In Fig. 2 Process resulting from proper instruction. The diagram depicts the process of instructing optimally. Providing augmented feedback promotes positives responses and not allows hedonistic decision-making to modulate exercise adherence Sport Sciences for Health addition, participants provided informed consent. The process of participants was reported following the Consolidated Standards of Reporting Trials (CONSORT) guidelines [39] displaying those 20 participants completed all assessments. Only one participant left the intervention due to personal complications to attend the evaluation sessions (Fig.3). Procedures Before the start of the intervention, participants were recommended not to perform high-intensity activities 48h before the evaluation sessions. On day 1, the familiarization day, anthropometric data including height and weight were measured using a mechanical telescopic measuring rod (SECA® model 206, Hamburg, Germany) and a myoelectrical impedance analysis monitor (Tanita® MC980MA PLUS model, Arlington Heights, Illinois). This session aimed to familiarize participants with measuring instruments such as the rating of perceived exertion (RPE), PRF, FS, SE, declarative knowledge (DK), and dynamic and isometric tasks. Participants received coaching on a warm-up protocol involving mobility exercises, hip hinge and good morning exercises, three dynamic lifts, and three isometric pulls at 5/10, 7/10, and 9/10 of maximum RPE. Regarding instructions [40], participants were informed that they would receive instruction, and their goal was to utilize only this information during tasks [41]. Subsequently, participants performed three dynamic 25kg load lifts (i.e., deadlift) and three 3-s isometric pulls in the bottom position [42]. Before each isometric pull, participants were reminded of the condition instruction, as in high-intensity tasks, the ability to change intention is reduced [43]. The rest time between tasks was 5min. On day 2, participants were divided into two groups, who engaged in lifting tasks under two different experimental conditions: baseline or control (CNT), and one experimental condition (ANA or EXP). The control condition was executed at the beginning of the intervention in all instances. Always after making a condition task, the participant was asked about DK. The other two types of instructions were counterbalanced at least 2days apart across all participants to control for possible order effects. Participants were reminded of the Fig. 3 CONSORT flow diagram outlining the enrollment, allocation, and analysis of participants in the study. The diagram illustrates the number of participants assessed for eligibility, those excluded, randomized into the intervention and control groups, as well as the follow-up and analysis outcomes for each group Sport Sciences for Health instruction at the beginning of the dynamic task and before the isometric pull. On day 3, the same procedure was followed counterbalancing the experimental conditions between the groups, with participants performing dynamic and static tasks under the instruction not used on day 2. The same variables were measured. After completing the task under all instructions, participants filled out questionnaires related to instruction PRF, SE for following instructions, and the FS regarding the difficulty of remembering instructions. Experimental conditions Each participant had to do dynamic and isometric lifts under 3 experimental conditions as previously stated. In CNT, assistants just encourage saying “Try to stand up” and not directing attention anywhere, avoiding characteristics of ANA or EXP learning. Experimental conditions (ANA and EXP) were created to try to reorganize motor control, improving the % of muscular activity and force production of lower limbs, which better assist than back or upper body muscle to functional activities enhancing ergonomic, perceived effort or pain [44]. Back injuries are a common source of longterm disability in working areas, and many issues occur usually during lifting tasks [45]. EXP was used to instruct participants to direct their attention to producing force with their lower limb muscles. ANA was used to put the first participant in an “experimental condition” where have to try to stand up against an invincible load on their back in a smith machine. After that, participants were instructed to “try to make the same that in condition before”. This experimental condition was created because ANA needs some characteristics to be carried out properly: first, participants need to be familiarized with the task [46]. Second, despite verbal ANA being very common in the scientific literature, it is better performed through real experience. The main reason is that in this movement (i.e., deadlift) it is not so easy to apply an instruction that directs participant attention to their environment, allowing the participant to adopt an external focus (EF) of attention, which appears to be the optimal way to instruct [26] (Fig.4). All instructions expressly proposed by the attendees are presented in Table1. Preferences (PRF) The measurement of PRF was carried out following the protocol proposed by Wulf [47]. PRF was recorded asking the participants for preferred instruction. Therefore, when a participant finishes the set of experimental conditions, it is asked about what kind of condition is the best in his/her opinion. Feeling scale (FS) The feeling scale (FS) is a widely validated measure of affective valence, originally developed by Hardy and Rejeski [48] and commonly used to assess pleasure or displeasure in response to a specific task [49]. In this study, FS was used to monitor participants’ affective responses to performing a task following a specific instruction. Participants rated their feelings on an 11-point Likert scale, ranging from + 5 (very good) to − 5 (very bad), with 0 representing a neutral state. In addition, its validity in Spanish-speaking populations has been confirmed [50]. Self‑efficacy (SE) SE was assessed using a questionnaire adapted and validated for Spanish-speaking populations [51], based on Bandura’s self-efficacy questionnaire, a well-established tool for evaluating an individual’s confidence in successfully performing a task [33]. In this study, SE was measured to Fig. 4 Familiarization task using analogy-based instruction Sport Sciences for Health assess participants’ confidence in performing the exercise correctly under each type of instruction and its potential impact on autonomy in future tasks. Participants rated their confidence on a scale from 0% (not confident at all) to 100%. Declarative knowledge (DK) The measurement of DK was carried out following the protocol created by van Abswoude [52]. When the task was finished, they were asked what they were thinking about during the uprising. To reduce differences caused by the number of rules, the number of rules was minimized during EXP [53, 54]. Statistical analyses anddependent variables The data are shown as mean ± the standard deviation (SD). The study utilized a 2 (analogy and explicit) × 1 within-subjects design to evaluate outcomes such as force production adjusted for body weight, feeling scale or selfefficacy. Clusters were created according to the preference of the subject (i.e., analogy, explicit or control instruction) and the preference of the subjects was reported as a percentage of the total. Initially, the Shapiro–Wilk test was employed to check the normal distribution of the continuous variables. Following this, a comparison of the differences across the control, ANA, and EXP conditions in each cluster was conducted using a 3-level (control, ANA, and EXP) repeated measures ANOVA. If a significant interaction was detected, differences between each pair of conditions (control vs ANA, ANA vs EXP, and control vs EXP) were assessed using the Tukey post-hoc test. The eta-partial square (η2p) value was determined to quantify the effect size. A significance threshold was set at an alpha level of 0.05. All statistical analyses were performed using the Jamovi software (The Jamovi project, version 2.3.18). Results Instruction preferences Among the included participants (n = 20), 10 (50%) subjects preferred ANA instruction, while 10 (50%) subjects preferred EXP instruction. Nonetheless, none (0%) subjects preferred the control condition. Force production inpreference clusters The effects of instruction on force production based on the preference (ANOVA repeated measures) are presented in Table1. Mauchly’s test indicated that the assumption of sphericity was not violated for those subjects who preferred ANA (χ2(df) = 0.564, p = 0.101). However, Mauchly’s test indicated that the assumption of sphericity was violated (χ2(df) = 0.272, p = 0.005) for those subjects preferring EXP. Therefore, Greenhouse–Geisser correction was applied (ε = 0.579) for this outcome and cluster. Feeling scale The effects of instruction on feeling scale are presented in Table2. Mauchly’s test indicated that the assumption of sphericity was not violated for this outcome (χ2(df) = 0.857, p = 0.250). Self‑efficacy The effects of instruction on self-efficacy are presented in Table3. Mauchly’s test indicated that the assumption of sphericity was not violated for those subjects who preferred ANA (χ2(df) = 0.564, p = 0.101). Mauchly’s test indicated Table 1 Analogy, explicit and control instruction protocols Explicit Analogy Control “Avoid using your arm to pull” “Use the strength of your legs” Simulate the task before lifting “Attempt to rise up” Table 2 Effect of instruction in the different analyzed clusters ANA analogy, EXP explicit Comparison p value η2pSignificant differences Instruction effect (ANOVA) p = 0.157 0.093 No Tukey’s post-hoc tests p > 0.05 No Table 3 Effects of instruction on self-efficacy ANA analogy, EXP explicit Comparison p value η2pSignificant differences Effect of instruction on self-efficacy p < 0.001 0.329 Yes ANA vs EXP p = 0.927 No ANA vs Control p = 0.002 Yes EXP vs Control p = 0.013 Yes Sport Sciences for Health that the assumption of sphericity was not violated for those subjects who preferred ANA (χ2(df) = 0.756, p = 0.081). Discussion The main finding of this study was that both analogy (ANA) and explicit (EXP) instruction promoted better affective responses compared to the control condition (CNT) during lifting tasks. However, no significant differences were observed between ANA and EXP, suggesting that both strategies similarly modulate affective responses in novice exercisers. The absence of significant differences between ANA and EXP aligns with previous research on motor learning. While explicit instruction provides detailed movement cues that can enhance performance, it also increases cognitive load, particularly in novices [55]. Conversely, analogy instruction facilitates implicit learning by reducing attentional demands and promoting automaticity [56]. However, in relatively simple tasks or when instructional complexity is minimized thorough reducing number of rules, both strategies may yield comparable affective and motor outcomes [57]. This may explain the similar responses observed in our study. No significant differences were found between EXP and ANA, with both instructional strategies being preferred over the CNT group. This finding aligns with previous research, which presents a controversy regarding attentional focus preferences. While some studies suggest that individuals tend to favor instructions related to internal focus, others provide evidence supporting a preference for external focus strategies [28, 47]. A possible explanation for the greater preference for ANA and EXP over CNT is that novice exercisers typically seek high levels of declarative knowledge (DK) to feel confident that they are performing the task correctly [58]. Similarly, a sub-analysis of force production based on instructional preferences showed no significant variations between these conditions. However, the control condition (CNT) resulted in higher force levels. This could be explained by the fact that, when participants self-regulate their movement without external guidance, they rely on pre-existing movement patterns that may maximize force output but not necessarily optimize movement efficiency [59]. For the feeling scale (FS), no significant differences were observed between conditions, indicating that novice exercisers did not perceive one type of instruction as more beneficial in terms of affective responses. This is consistent with prior research suggesting that individuals process information differently and may not have a universal preference for instructional style. This is consistent with the findings discussed in the section on preferences. Self-efficacy (SE) was the variable that showed the most significant differences among conditions, with ANA leading to the highest SE scores, followed by EXP, both of which were superior to CNT. This finding highlights the impact of instructional strategies on perceived competence and psychological responses during exercise. Higher levels of self-efficacy have been associated with increased autonomy [60] and better affective responses, as individuals who feel more confident in their abilities tend to experience less anxiety or uncertainty about task execution [61]. Conversely, when individuals doubt whether they are performing a task correctly, cognitive processes may be negatively affected, leading to adverse emotional responses such as fear [62]. In addition, a lack of autonomy in task execution has been identified as one of the main barriers to exercise adherence [63, 64]. Interestingly, despite the CNT condition resulting in the highest force production levels, it also yielded the lowest SE scores. This suggests that while self-regulated movement strategies may facilitate force output, the absence of structured instruction may lead to reduced confidence in task execution. Given that motivation and adherence are strongly influenced by perceived competence, structured instruction appears essential for long-term engagement, particularly in novice or special populations. In these cases, achieving positive affective responses should take priority over merely increasing force production. According to self-determination theory, autonomy plays a central role in modulating motivation, which is one of the key pillars of adherence [16]. The significant difference in self-efficacy between ANA and EXP aligns with prior research on instructional strategies and perceived competence. Explicit instruction, by providing detailed movement cues, may enhance the perception of control and reduce uncertainty. In contrast, analogy instruction fosters a more intuitive learning process, potentially influencing self-efficacy in a distinct manner. These findings underscore the importance of tailoring instructional strategies to optimize both motor performance and psychological engagement, particularly in novice exercisers. One of the main problems in this field of study is that professionals rarely educate people on the importance of following instruction since they only pay little attention to the relevance of instructions. Therefore, the advantages and consequences of one type of instruction over another should also be explained, as well as providing value in following instruction so that the self-talk generated by the person is oriented in the correct way [15]. It is common that in the absence of instruction, people tend to repeat movements without any intentions. In addition, self-talk generated by the person when not instructed, negatively affects training results [20]. Previous research qualitatively studied different Sport Sciences for Health aspects of self-talk, remarking that 95% of the participants use it during exercise and that in a significant number, this self-talk is focused on “controlling the correct technique” of the exercise [25]. In this line, self-talk can generate regulation processes, thoughts, and affective responses [65]. Therefore, thanks to increased feedback produced due to instructions before lifting, we can modify attention and not fall into self-talk and its consequences [66]. This study is the first, to our knowledge, to highlight the importance of attending to the affective responses promoted by the instruction given by professionals exercise instruction or during ergonomics workshops related to occupational postural hygiene. Here, the need to rethink exercise programming is called for. Although it is known that the elements that cause physical exercise adaptations are training variables, it is necessary to pay attention to the type of instruction, as well as the importance of following it by the participant of an exercise program to modulate the adaptations and the possibility of promoting adherence to exercise. A practical application derived from this study is the need to educate the novice on the importance of attending exclusively to what the professional guides in the first steps of his/her training, allowing other types of instruction with the progress of his development, thanks to the automatic processing learned. In this way, the participant will attend to the relevant aspects that promote their autonomy, discarding information that is not very relevant or that is detrimental to learning or task performance at the moment when they are more dependent. In this way, by promoting these positive affective responses, it is more likely that in daily decisionmaking, the participant will not succumb to hedonism and will endure their participation in the long term. Future studies should assess other potential interesting variables such as those related to electroencephalography, which would allow us to rely on objective tests to contrast the hypotheses given by scientific evidence and to see the real physiological changes in the cerebral cortex. Conclusion Instruction needs to be provided as it promotes self-efficacy in participants who are novices in a training program. This study demonstrated that ANA instruction as well as EXP instruction promoted positive affective responses over no instruction along with the variables of effort dosage. In addition, this study showed that participants preferred instruction over not giving it before a lifting task. Nonetheless, coaches should be aware of a possible loss of force production in the task, especially if the subject preferred implicit (e.g., analogy) learning strategies. Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1007/ s1133202501393-y. Acknowledgements The authors express their gratitude to all the participants who generously contributed their time to complete this study. This study was finished during the residency period in Bratislava (Slovakia) of A.C.D. Therefore, the authors thanks to Faculty of Physical Education and Sport in COMENIUS UNIVERSITY BRATISLAVA for favoring the research residency to A.C.D. in Comenius University Bratislava. Author contributions Ángel Carnero-Díaz: conceptualization; data curation; formal analysis; investigation; methodology; project administration; software; supervision; visualization; roles/writing— original draft; and writing—review and editing. Javier Pecci: data curation; formal analysis; methodology; software; visualization; roles/ writing—original draft; and writing—review and editing. Adriana Kaplánová: visualization, conceptualization; roles/writing—original draft; and writing—review and editing. Funding Open access funding provided by The Ministry of Education, Science, Research and Sport of the Slovak Republic in cooperation with Centre for Scientific and Technical Information of the Slovak Republic. Funding was provided by VEGA (Grant number: 1/0786/21). Data availability No datasets were generated or analyzed during the current study. Declarations Conflict of interest The authors declare that they have no conflict of interests. Ethical approval This work received ethical approval according to the Pablo Olavide University ethics committee (code: 23/6-8) and registered in clinical trials ANZCTR (code: 386738). Human and animal rights and informed consent This study was conducted in accordance with the Declaration of Helsinki. All the participants provided informed consent to participate and agreed to the publication of their data. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. 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