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Record W4385196947 · doi:10.3389/fspor.2023.1256235

Editorial: Sport and psychosocial health/well-being after the COVID-19 lockdown - Volume II

2023· editorial· en· W4385196947 on OpenAlexaboutno aff
Amy Chan Hyung Kim, James Du, Rochelle Eime

Bibliographic record

VenueFrontiers in Sports and Active Living · 2023
Typeeditorial
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Psychosocial2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Volume (thermodynamics)Front (military)PsychologyPolitical scienceMedicineGeographyVirologyPsychiatryMeteorologyPhysics

Abstract

fetched live from OpenAlex

Similarly, but by using a nonexperimental design, Hu and colleagues (2023) examined the relationship between home-based High-Intensity Interval Training (HIIT) dance and depression during the COVID-19 pandemic in China while examining the moderating effects of personal perception including perceived susceptibility, severity, benefits, and self-efficacy among quarantined residents in China. The findings showed that more often the quarantined residents participated in home-based HIIT dance, the less likely they were to suffer from depression during the lockdown. While perceived susceptivity did not play a significant role as a moderator on this preventive relationship between HIIT dance frequency and depression, higher perceived severity and perceived benefits tended to strengthen the association. Moreover, if the quarantine residents had a clear sense that they could effectively participate in home-based HIIT dance, it inclined to prevent their experience of depression more greatly.Jungwirth and colleagues (2022) examined the impact of the COVID-19 crisis on individual physical activity patterns and life satisfaction among recreational golfers. The participants recruited from German speaking countries reported that, in indoor settings, the frequency of fitness center use was decreased by 42.12% while the frequency of home training was increased by 14.18% (independent training) and 23.48% (with online instructions). Notably, life satisfaction had decreased significantly after the COVID-19 pandemic among the respondents compared to before the COVID-19 pandemic.The remaining three articles explored the different patterns or situational factors of physical activity behavior during the COVID-19 pandemic. Kim et al. (2023) examined how the degree of conflict (i.e., conflict due to prejudice, conflict due to competition, conflict due to prior expectations, conflict due to not observing etiquette) and coping strategies (i.e., avoidance behavior, resolution behavior) varies depending on spatial proximity that occurs in indoor and outdoor settings. The results from 508 Korean adults disclosed that conflict due to prejudice was higher in indoor sport activities such as Pilates, yoga, and gym workouts. Conflicts due to competition were relatively low in these activities though in that these activities were only available via reservation or appointments in order to limit the number of people within a certain size of indoor spaces during the pandemic in South Korea. The results also indicated that indoor golf showed higher level of conflict from competition and conflict due to not observing etiquette in indoor golf settings compared to outdoor golf settings. Outdoor activities such as jogging and hiking showed higher conflicts due to prior expectations and prejudice. The results implied that, during the time under nonpharmaceutical restrictions, physical activity participants may feel different conflicts and adopt coping strategies depending on the type of activities and environmental contexts. The policymakers and leisure service providers need to consider different conflicts and coping strategies among leisure participants when they run different programs under various restrictions that may resulted from major events such as the COVID-19 pandemic. Kovacevic et al. (2022) investigated the changes in adolescents' physical activity behaviors and cognitions associated with COVID-19 using the Multi-Process Action Control (M-PAC) framework. The findings from a total of 588 grade 11 students in Ontario, Canada presented that participants were 67% less likely to participate in organized physical activities during the pandemic compared to before the pandemic. When it comes to physical activity cognitions, physical activity intention, identity, and habit significantly decreased over time while behavioral regulation was increased. Considering that many restrictions result in disruptions to typical behaviors, adolescents had to implement new skills and plans to be physically active. The findings implied the need of more support on helping adolescents regulate their behaviors through various skills such as self-monitoring, goal setting, and coping strategies.In the end, volume II extended knowledge in how physical activity, exercise, and sport play roles in one's mental health during the COVID-19 pandemic as well as how one's active lifestyle has been affected by the recent pandemic. In summary the pandemic impacted individuals' sport and physical activity behaviors which in turn negatively impacted a range of health outcomes. The crucial message from this issue is that one's active lifestyle should be promoted effectively to cope one's mental health issues that can be resulted from the COVID-19 pandemic. Also, as the pandemic restrictions are lifted and we have the opportunity to return to playing sport and being physically active, the impact of the pandemic and associated restrictions are likely to continue to impact our sport and physical activity behaviors. This in turn will impact individuals' health and wellbeing and the long-term effects of the COVID-19 on one's active lifestyle should continue to be examined.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.030
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0060.002
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0040.002
Science and technology studies0.0030.003
Scholarly communication0.0070.004
Open science0.0060.001
Research integrity0.0140.013
Insufficient payload (model declined to judge)0.0300.012

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.294
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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