フィットネスクラブの新規会員における早期退会リスクを推定するモデルの開発

Yuta Nemoto*, Nobumasa Kikuga, Susumu Sawada, Munehiro Matsushita, Yuko Gando, Natsumi Watanabe, Yuko Hashimoto, Yoshio Nakata, Noritoshi Fukushima, Shigeru Inoue

*この研究の対応する著者

研究成果: Article査読

抄録

Approximately 40%–65% of new fitness club (FC) members cancel their membership within 6 months. To prevent such cancellations, it is essential to identify members at high risk of doing so. This study developed a model to predict the probability of discontinuing FC membership among new members. We conducted a cohort study and enrolled participants from 17 FCs in Japan. We asked 5,421 individuals who became members from March 29, 2015 to April 5, 2016 to participate in the study; 2,934 completed the baseline survey, which was conducted when the participants became FC members. We followed up the participants until September 30, 2016. We excluded 883 participants with missing values and 69 participants under aged 18 years; thus, our analysis covered 1,982 individuals. We conducted the random survival forest to develop the prediction model. The mean follow-up period was 296.3 (standard deviation, 127.3) days; 488 participants (24.6%) cancelled their membership during the follow-up. The prediction model comprised 8 predictors: age; month of joining FC; years of education; being under medical follow-up; reasons for joining FC (health improvement, relaxation); and perceived benefits from exercise (maintaining good body weight, recognition of one’s ability by other). The discrimination and calibration were acceptable (C statistic: 0.692, continuous ranked probability score: 0.134). Our findings suggest that the prediction model could assess the valid probability for early FC cancellation among new members; however, a validation study will be needed.

寄稿の翻訳タイトルDevelopment of a model to predict the probability of discontinuing fitness club membership among new members
本文言語Japanese
ページ(範囲)431-441
ページ数11
ジャーナルjapanese journal of physical fitness and sports medicine
71
5
DOI
出版ステータスPublished - 2022

Keywords

  • Calibration
  • cohort study
  • Discrimination
  • Random survival forest
  • TRIPOD

ASJC Scopus subject areas

  • 整形外科およびスポーツ医学
  • 理学療法、スポーツ療法とリハビリテーション

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