匈牙利青少年运动员运动坚持性随机对照前后测数据集发布

DATA REPORT article

Front. Psychol., 08 October 2026

Sec. Sport Psychology

Volume 17 - 2026 | https://doi.org/10.3389/fpsyg.2026.1921608

1 Introduction

Sport participation is widely recognized as an important contributor to physical health, psychological wellbeing, and social development (). However, maintaining long-term engagement in sport remains challenging, with participation differing by gender (; ) and typically declining across adolescence and early adulthood (; ). These trends underline the need to better understand the factors that promote sustained engagement in sport.

Sport persistence represents a complex psychological and behavioral construct that extends beyond the frequency of participation and reflects a qualitative commitment to long-term sporting activity (). It encompasses athletes' capacity to maintain effort despite setbacks such as injuries, performance plateaus, failures, or other challenges, while also effectively utilizing positive experiences to sustain development. Consequently, sport persistence can be considered an indicator of effective and enduring sport participation rather than mere attendance. Despite its theoretical importance, empirical research has primarily focused on sport motivation, commitment, or participation, leaving sport persistence relatively underexplored ().

Previous studies have also demonstrated consistent gender differences in sport persistence (,; ). These differences are likely shaped by socialization processes, gender-specific expectations, and variations in motivational development. Boys and girls may internalize achievement goals and competitive experiences differently, potentially influencing both grit and sport orientation (). Consequently, these psychological constructs may partially explain how gender differences emerge in long-term commitment to sport.

Although the determinants of sport motivation and commitment have been widely investigated, relatively little attention has been devoted to sport persistence as a distinct construct, and evidence-based interventions specifically targeting its development remain scarce. Building on our previous research (,; ; ; ), the present study contributes to this emerging field by examining sport persistence within a comprehensive psychological framework and evaluating an intervention designed to strengthen athletes' long-term commitment to sport.

The dataset is particularly relevant because it goes beyond one focal outcome. In addition to sport persistence, it includes measures that can support secondary analyses of motivational regulation, anxiety, coping-related functioning, subjective wellbeing, future orientation, and repetitive negative thinking. This breadth makes the dataset suitable not only for intervention evaluation but also for psychometric studies, cross-construct association testing, subgroup comparisons, attrition analyses, and methodological work on multi-scale athlete datasets. The present article therefore does not report the findings of a single hypothesis-driven study; instead, it documents the origin, structure, quality indicators, and reuse potential of the dataset.

The intervention context is also an important part of the dataset. The sport persistence training programme was developed as a multidimensional psychological workbook and delivery framework intended to support long-term commitment, mental resilience, and performance-related self-regulation. The intervention materials cover self-assessment, anxiety and coping, self-management and time management, communication, attachment, and social support. Because these materials are explicitly linked to the data collection design, they provide important context for interpreting change scores, format-specific exposure, and the practical meaning of the variables captured in the dataset.

2 Methods

2.1 Study design

The dataset was generated in a randomized controlled trial involving athletes aged 14–25 years in Hungary. Recruitment was carried out between September 2025 and November 2025, the intervention period ran from October to December 2025, and post-intervention follow-up assessments were completed between November 2025 and January 2026. Eligibility screening initially covered 300 individuals. The design used a pre-test/post-test questionnaire battery and three study conditions: a hybrid training format, an online self-administered training format, and a no-training control group. This timeline and structure should be reported explicitly because they determine how the repository files can be interpreted for longitudinal, between-group, and format-sensitive reuse.

Participants were recruited through sports clubs and secondary schools. Inclusion criteria were clearly defined: participants had to be 14–25 years old, engage in sport at least three times per week, practice either an individual or team sport, and be enrolled in secondary or higher education. Exclusion rules applied where valid completion of the measures or intervention was not possible, where baseline or post-intervention participation was missing, where primary questionnaire data were incomplete, or where parental/guardian permission was not available for minors under the approved protocol. For dataset users, these criteria are important because they define the analytic population and limit generalization primarily to actively training student-athletes rather than the broader youth population.

Random allocation followed a simple computer-generated procedure with a 2:1 intervention-to-control ratio. Participants were randomly allocated using a computer-generated randomization sequence. Participants were informed of their allocation after randomization because delivery of the intervention differed between study arms. After eligibility screening, 281 participants were randomized. Of these, 188 were assigned to the intervention arm and 93 to the control arm. Within the intervention arm, 86 participants entered the hybrid format and 102 the online format. Follow-up attrition occurred in both main arms, mainly because post-intervention tasks were not completed. The final analysis-ready sample consisted of 208 complete cases: 139 in the intervention arm, including 60 hybrid and 79 online participants, and 69 in the control arm. Because the dataset supports both intention-sensitive design description and completer-based secondary analysis, the repository documentation should clearly distinguish screened, randomized, allocated, follow-up, and analysis-ready cases (Figure 1).

Figure 1

Anonymization relied on participant-generated codes that linked repeated measurements without storing identifiers in the research database itself. According to the study documentation, the separate file used for verification purposes was stored independently, password-protected, and accessible only to the principal investigator. For a public dataset release, only the de-identified analytical files and metadata are openly available. The OSF repository includes the anonymized dataset, a complete codebook, dataset documentation, and the intervention workbook materials. The codebook describes the variable names, coding schemes, participant identifiers, measurement waves, group allocation variables, missing-value coding, and scoring procedures required for data reuse.

2.2 Procedure

The intervention materials are an essential interpretive layer of the dataset. The workbook is organized into six blocks: self-assessment; anxiety, resilience, and wellbeing; self-management and time management; communication skills; attachment; and social support. The workbook also contains practical exercises such as success journaling, reframing negative automatic thoughts, Pomodoro-based time structuring, tactical communication signals, motivational keyword mapping, and social support network mapping. In addition, the usage instructions encourage stepwise completion, journaling, collaboration with coaches or teammates where relevant, and repeated revisiting of the material. These features matter because the dataset does not merely record exposure to an intervention label; it records participation in a structured psychological training environment with recognizable content domains (Table 1).

Table 1

Block	Objective	Sample task
Block 1: self-assessment	To help athletes become aware of their areas for improvement and limitations, while also recognizing their personal values.	Success Journal: write down 2–3 important sporting achievements and note which of your strengths (e.g., perseverance, discipline) helped you accomplish them. Then reread them to remind yourself of what you are good at.
Block 2: anxiety, resilience, and wellbeing	To help athletes understand the role these three components play in sporting success and to provide them with tools for overcoming anxiety.	Write down the negative automatic thoughts that contribute to your anxiety, then rephrase them so that they no longer feel threatening.
Block 3: self-management and time management	Athletes face diverse daily demands; therefore, balancing training, competitions, studies or work, and recovery requires conscious planning. Self-management supports the maintenance of discipline and motivation, while effective time management reduces the risk of burnout and performance fluctuations caused by overload.	Try the Pomodoro Technique during a study session: work with full focus for 25 min, then take a 5-min break. Observe how much more effectively you work using this method.
Block 4: development of communication skills	Effective, open, and assertive communication fundamentally influences the athlete–coach relationship, team cohesion, and performance, while also helping to prevent and manage conflicts.	Create shared tactical signals (e.g., hand gestures), practice using them during training, and observe how much easier communication becomes.
Block 5: attachment	To foster healthy bonds with both the athlete's social environment and sporting activity.	Write down keywords that describe you as an athlete and motivate you. Then identify which words appear most frequently—these reflect your strengths and your motivation toward sport.
Block 6: social support	An athletic career is full of challenges, during which adequate social support plays a crucial role in maintaining psychological wellbeing and commitment.	List the people who make up your support network and note what kind of help you receive from each of them. This will help you see who you can rely on and for what type of support.

The modules of the sport persistence training programme, their objectives and sample tasks.

The questionnaire package covered socio-demographic, sport-specific, health-related, and psychological domains. The comprehensive study also utilized additional measurement tools that are not the subject of this study: a sports- and health-specific questionnaire, the perception of success questionnaire (PSQ, ), the Sport Anxiety Scale-2 (SAS-2, ), the Connor-Davidson Resilience Scale (), the WHO wellbeing inventory (WBI-5, ), Self in the Future Scale (), and the Ruminative Response Scale (RRS, ).

The dataset should be accompanied by clear variable-level documentation. At minimum, the repository package should identify each scale, its item count, response format, reverse-coded items where applicable, subscale composition, score range, and whether a variable belongs to baseline, post-intervention, or derived difference-score files. If multiple files are deposited, it is advisable to separate raw de-identified item-level data, scored scale-level data, and documentation files. Because Frontiers requires datasets to be reusable and interpretable by readers beyond the original study team, the documentation of scoring decisions and filters is not optional background information but a central part of the publication.

3 Descriptive overview and basic analysis of the data

The descriptive profile of the complete-case sample indicates broad heterogeneity within an active youth athlete population. Among the 208 analyzed participants, the gender distribution was relatively balanced, with 112 males and 96 females. Most participants were enrolled in secondary education, and a smaller but substantial subgroup was in higher education. The sample included athletes from a range of settlement types, although county towns and small towns were most common. In sport participation terms, the sample was highly active: most trained several times a week or more often, most were involved in team sports, many were linked to sports clubs, and the majority identified as competitive rather than purely recreational athletes. A notable proportion also reported prior sports injury, which increases the potential for secondary analyses on injury history and persistence-related functioning.

The participant-flow information is itself analytically useful. Screening, exclusion, randomization, intervention-format allocation, and follow-up loss were all documented. This means the dataset can support not only substantive analyses but also methodological work on retention, missingness, and intervention completion in athlete populations. Importantly, the analytic dataset is completer-based rather than based on imputed follow-up data. For secondary users, this makes it especially important to distinguish design-level counts from complete-case analysis files and to consider possible attrition-related bias in any downstream modeling.

Basic psychometric indicators suggest that the focal scales have generally strong internal consistency within this dataset. In the manuscript tables, the focal instruments show Cronbach's alpha values ranging from 0.76 to 0.97 and McDonald's omega values ranging from 0.77 to 0.97 across the two measurement waves. Sport persistence shows particularly high reliability, while the sport orientation subscales and grit subscales also demonstrate usable to strong internal consistency. These values make the dataset well suited for score-based secondary analysis, while the presence of multiple related constructs also supports factor-analytic, invariance-oriented, or network-based work, provided that users rely on the deposited item-level documentation.

A further strength of the dataset is its mixed intervention structure. Because the intervention arm was split into hybrid and online formats, and because the control arm remained untreated during the study period, the dataset can support several forms of secondary categorization: intervention vs. control comparisons, hybrid vs. online comparisons, and dose- or exposure-sensitive work if future documentation of completion intensity is linked to the public data package. Even when no confirmatory hypothesis testing is undertaken in the Data Report itself, these structural features increase the long-term value of the dataset for open secondary research.

Baseline descriptive statistics and between-group comparisons are presented in Tables 2, 3. Overall, the three study groups showed comparable baseline values on several psychological measures, including task orientation, sport persistence, perseverance of effort, wellbeing, future control, and concentration disruption, with no statistically significant differences observed. However, significant baseline differences were identified for several variables, including consistency of interest, resilience, positive future orientation, time management, future uncertainty, lack of self-efficacy, both rumination dimensions, and the somatic anxiety and negative thoughts subscales of sport anxiety. Effect sizes ranged from negligible to large (ε² < 0.001–0.423), indicating that while some constructs were well balanced across groups, others exhibited meaningful baseline variability.

Table 2

Variable	Hybrid (n = 60) M ±SD	Online (n = 79) M ±SD	Control (n = 69) M ±SD
PSQ—task orientation	24.98 ± 6.15	25.43 ± 6.19	26.55 ± 4.15
PSQ—ego orientation	20.65 ± 6.32	18.61 ± 7.12	18.42 ± 6.30
SOQ—win orientation	21.30 ± 6.58	19.80 ± 7.20	19.65 ± 6.08
SOQ—goal orientation	14.68 ± 3.78	14.14 ± 3.95	13.93 ± 3.14
SOQ—competitiveness	11.27 ± 2.89	11.11 ± 3.05	11.23 ± 2.82
Sport persistence (SPQ)	49.25 ± 13.03	51.48 ± 13.81	51.67 ± 11.08
Grit—consistency of interest	12.43 ± 4.18	14.08 ± 3.74	11.17 ± 3.71
Grit—perseverance of effort	14.62 ± 3.85	14.63 ± 3.99	15.07 ± 3.26
Resilience^*	33.11 ± 5.20	29.59 ± 8.04	8.88 ± 13.70
Wellbeing (WHO-5)	12.73 ± 5.40	13.19 ± 4.46	12.42 ± 4.55
Self in the future—positive future	13.37 ± 5.05	14.67 ± 4.67	12.64 ± 4.87
Self in the future—future control	13.03 ± 4.42	13.18 ± 3.72	12.42 ± 3.12
Self in the future—time management	12.05 ± 3.67	12.35 ± 3.70	9.97 ± 3.49
Self in the future—future uncertainty	14.47 ± 4.89	14.96 ± 5.11	11.35 ± 5.98
Self in the future—lack of self-efficacy	14.43 ± 3.89	15.11 ± 3.80	11.97 ± 3.11
Rumination—reflection^*	7.74 ± 4.17	7.08 ± 4.20	1.83 ± 3.12
Rumination—brooding^*	6.53 ± 3.56	7.18 ± 4.42	2.14 ± 3.61
Sport anxiety—somatic anxiety	9.75 ± 3.98	8.82 ± 3.73	12.30 ± 4.49
Sport anxiety—negative thoughts	12.53 ± 4.41	11.38 ± 4.74	15.59 ± 4.09
Sport anxiety—concentration disruption	9.55 ± 3.96	8.56 ± 3.43	9.42 ± 3.23

Descriptive statistics of the study groups at baseline (pre-test).

^*means significant difference.

Table 3

Variable	χ²	df	p	ε²
PSQ—task orientation	0.855	2	0.652	0.004
PSQ—ego orientation	4.653	2	0.098	0.022
SOQ—win orientation	2.884	2	0.237	0.014
SOQ—goal orientation	3.111	2	0.211	0.015
SOQ—competitiveness	0.086	2	0.958	< 0.001
Sport persistence (SPQ)	2.399	2	0.301	0.012
Grit—consistency of interest	19.025	2	< 0.001	0.092
Grit—perseverance of effort	0.374	2	0.830	0.002
Resilience	70.266	2	< 0.001	0.423
Wellbeing (WHO-5)	1.252	2	0.535	0.006
Self in the future—positive future	6.767	2	0.034	0.033
Self in the future—future control	3.518	2	0.172	0.017
Self in the future—time management	15.449	2	< 0.001	0.075
Self in the future—future uncertainty	15.262	2	< 0.001	0.074
Self in the future—lack of self-efficacy	26.956	2	< 0.001	0.130
Rumination—Reflection	60.736	2	< 0.001	0.366
Rumination—Brooding	49.911	2	< 0.001	0.301
Sport anxiety—somatic anxiety	23.718	2	< 0.001	0.115
Sport anxiety—negative thoughts	30.659	2	< 0.001	0.148
Sport anxiety—concentration disruption	3.682	2	0.159	0.018

Baseline (pre-test) differences between the three study groups (Kruskal–Wallis test).

An attrition analysis was also conducted to compare participants who completed both measurement waves with those lost to follow-up. Baseline descriptive statistics and between-group comparisons are presented in Appendix Tables A1, A2. No statistically significant differences were observed between completers and non-completers on any of the baseline psychological measures (all p > 0.05). Moreover, effect sizes were uniformly negligible (ε² ≤ 0.006), indicating that loss to follow-up was not systematically associated with the assessed baseline characteristics. These findings suggest that attrition was unlikely to introduce substantial bias into the final analytical sample and support the suitability of the complete-case dataset for secondary analyses.

4 How readers may interpret and reuse the dataset

The dataset is best interpreted as a structured youth-athlete intervention dataset with repeated psychological measurement and documented intervention delivery format. It should not be treated as a general population dataset, nor as a representative sample of all Hungarian athletes. Instead, it is most appropriate for questions concerning actively training student-athletes in adolescence and early adulthood. Its strongest reuse potential lies in psychometrics, intervention-methodology studies, attrition analyses, subgroup modeling, scale co-development work, and secondary theory testing on the relationships among persistence, motivation, anxiety, resilience, and wellbeing.

Because the source material involves human participants, reuse guidance should also specify anonymization boundaries. The public release should exclude direct or indirectly identifying information and should document any variables that were removed, generalized, or collapsed in order to preserve participant confidentiality. If any portion of the raw material cannot legally or ethically be shared, that limitation should be stated with precision. However, for a Data Report article, the openly reusable version must still be sufficient to justify the claim that a fixed public dataset has been deposited. In practical terms, this means that a request-only repository entry is not enough for this article type; a shareable anonymized release is needed.

Statements

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://osf.io/h2zpg.

Ethics statement

The studies involving humans were approved by The United Ethical Review Committee for Research in Psychology (EPKEB) approved this study (2025–073). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants' legal guardians/next of kin.

Author contributions

KK: Writing – original draft, Formal analysis, Funding acquisition, Project administration, Conceptualization, Methodology, Writing – review & editing, Investigation.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This paper was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences (BO/000686/23/2).

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author KK declared that they were an editorial board member of Frontiers, at the time of submission This had no impact on the peer review process and the final decision.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2026.1921608/full#supplementary-material

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Keywords

Hungary, intervention, pre-post testing, sport persistence, sport training

Citation

Kovács KE (2026) The sport persistence training dataset: a randomized controlled pre–post dataset on sport persistence and related psychological resources among young athletes in Hungary. Front. Psychol. 17:1921608. doi: 10.3389/fpsyg.2026.1921608

Received

27 June 2026

Revised

10 July 2026

Accepted

08 September 2026

Published

08 October 2026

Volume

17 - 2026

Updates

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Karolina Eszter Kovács, karolina92.kovacs@gmail.com; kovacs.karolina@arts.unideb.hu

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.