The effects of a home-based physical activity intervention on cardiorespiratory fitness in breast cancer survivors; a randomised controlled trial

Lahart, Ian; Carmichael, Amtul R.; Nevill, Alan M.; Kitas, George D.; Metsios, George S.

doi:10.1080/02640414.2017.1356025

Cited by 31 publications

(24 citation statements)

References 48 publications

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“…Lahart et al . [29] conducted a six-month randomized controlled trial of a home-based physical activity intervention involving 32 breast cancer survivors. Magnitude-based inference analyses revealed at least small beneficial effects on absolute and relative VȮ 2 max (cardiorespiratory fitness), and total and moderate physical activity in the intervention compared to the usual care group.…”

Section: Resultsmentioning

confidence: 99%

A review of home-based physical activity interventions for breast cancer survivors

et al. 2019

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As breast cancer relative survival continues to increase, many breast cancer patients face many issues, including recurrence of cancer and cancer-related side effects that impact several aspects of their quality of life. With breast cancer patients living longer, there is more of a concern for negative breast cancer outcomes. Although physical activity is an affordable and relatively convenient way to improve breast cancer outcomes, only about one-third of breast cancer survivors engage in the recommended level of physical activity. This article reviews articles published to date to examine whether home-based physical activity interventions are effective in improving physical activity and other outcomes among breast cancer survivors who have completed primary therapy for the disease. The present review is based upon bibliographic searches in PubMed and CINAHL and relevant search terms. Articles published in English from 1980 through February 28, 2019 were identified. A total of 360 article citations were identified in PubMed and non-duplicates in CINAHL. After screening the abstracts or full texts of these articles and reviewing the references of previous review articles, 20 studies that met the eligibility criteria. Three of the studies were pre-/post-test trials and 17 were randomized controlled trials. home-based exercise programs are effective in improving physical activity among breast cancer survivors who have completed primary therapy for the disease. Home-based exercise programs such as walking programs offer a convenient and affordable option for women who wish to increase their physical activity and maintain a healthy lifestyle.

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Section: Resultsmentioning

confidence: 99%

A review of home-based physical activity interventions for breast cancer survivors

et al. 2019

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Section: Resultsmentioning

confidence: 99%

“…N per group for studies with >1 group (n = 111) a 10 [8,15] Total N for single group studies (n = 121) 14 [10,24] Number of dependent variables 7 [5,12] Number Some authors explicitly set a minimum evidence threshold above which effects were declared "implementable", "substantial", or "practically meaningful." Others implicitly set this threshold by only choosing to highlight and draw conclusions based on effects that met a given evidentiary threshold, such as "likely" or "possible.…”

Section: Measure Median [Iqr] or N(%)mentioning

confidence: 99%

“…Others implicitly set a minimum threshold by only highlighting and drawing conclusions based on effects above a certain bar. For example, Lahart et al [24] write in their abstract: "Magnitude-based inference analyses revealed likely at least small beneficial effects (effect sizes�.20) on absolute and relative VO 2 max (d = .44 and .40, respectively), and total and moderate PA (d = .73 and .59, respectively) in the intervention compared to the usual care group. We found no likely beneficial improvements in any other outcome" (emphasis added).…”

Section: Plos Onementioning

confidence: 99%

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Systematic review of the use of “magnitude-based inference” in sports science and medicine

et al. 2020

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Magnitude-based inference (MBI) is a controversial statistical method that has been used in hundreds of papers in sports science despite criticism from statisticians. To better understand how this method has been applied in practice, we systematically reviewed 232 papers that used MBI. We extracted data on study design, sample size, and choice of MBI settings and parameters. Median sample size was 10 per group (interquartile range, IQR: 8-15) for multi-group studies and 14 (IQR: 10-24) for single-group studies; few studies reported a priori sample size calculations (15%). Authors predominantly applied MBI's default settings and chose "mechanistic/non-clinical" rather than "clinical" MBI even when testing clinical interventions (only 16 studies out of 232 used clinical MBI). Using these data, we can estimate the Type I error rates for the typical MBI study. Authors frequently made dichotomous claims about effects based on the MBI criterion of a "likely" effect and sometimes based on the MBI criterion of a "possible" effect. When the sample size is n = 8 to 15 per group, these inferences have Type I error rates of 12%-22% and 22%-45%, respectively. High Type I error rates were compounded by multiple testing: Authors reported results from a median of 30 tests related to outcomes; and few studies specified a primary outcome (14%). We conclude that MBI has promoted small studies, promulgated a "black box" approach to statistics, and led to numerous papers where the conclusions are not supported by the data. Amidst debates over the role of p-values and significance testing in science, MBI also provides an important natural experiment: we find no evidence that moving researchers away from p-values or null hypothesis significance testing makes them less prone to dichotomization or over-interpretation of findings.

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“…Only 15% of studies reported any a priori power analysis. In cases where authors reported sample size calculations based on the MBI calculators, they often reported very low sample size requirements, such as 5, 6, or 7 total participants [22][23][24]. We also note that many authors seemed to erroneously believe that use of MBI circumvents the need for an adequate sample size [25][26][27][28][29] In these cases, authors wrote a version of the following statements: "When the positive and negative values were both >5%, the inference was classified as unclear" or, equivalently, "If the 90% confidence interval overlapped the thresholds for the smallest worthwhile positive and negative effects, effects were classified as unclear"; this means they used 1ℎ =5% and treated both directions equivalently, consistent with non-clinical MBI.…”

Section: Resultsmentioning

confidence: 99%

Systematic Review of the use of “Magnitude-Based Inference” in Sports Science and Medicine

Lohse¹,

Sainani²,

Taylor³

et al. 2020

Preprint

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Magnitude-based inference (MBI) is a controversial statistical method that has been used in hundreds of papers in sports science despite criticism from statisticians. To better understand how this method has been applied in practice, we systematically reviewed 232 papers that used MBI. We extracted data on study design, sample size, and choice of MBI settings and parameters. Median sample size was 10 per group (interquartile range, IQR: 8 – 15) for multi-group studies and 14 (IQR: 10 – 24) for single-group studies; few studies reported a priori sample size calculations (15%). Authors predominantly applied MBI’s default settings and chose “mechanistic/non-clinical” rather than “clinical” MBI even when testing clinical interventions (only 14 studies out of 232 used clinical MBI). Using these data, we can estimate the Type I error rates for the typical MBI study. Authors frequently made dichotomous claims about effects based on the MBI criterion of a “likely” effect and sometimes based on the MBI criterion of a “possible” effect. When the sample size is n=8 to 15 per group, these inferences have Type I error rates of 12%-22% and 22%-45%, respectively. High Type I error rates were compounded by multiple testing: Authors reported results from a median of 30 tests related to outcomes; and few studies specified a primary outcome (14%). We conclude that MBI has promoted small studies, promulgated a “black box” approach to statistics, and led to numerous papers where the conclusions are not supported by the data. Amidst debates over the role of p-values and significance testing in science, MBI also provides an important natural experiment: we find no evidence that moving researchers away from p-values or null hypothesis significance testing makes them less prone to dichotomization or over-interpretation of findings.

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The effects of a home-based physical activity intervention on cardiorespiratory fitness in breast cancer survivors; a randomised controlled trial

Cited by 31 publications

References 48 publications

A review of home-based physical activity interventions for breast cancer survivors

A review of home-based physical activity interventions for breast cancer survivors

Systematic review of the use of “magnitude-based inference” in sports science and medicine

Systematic Review of the use of “Magnitude-Based Inference” in Sports Science and Medicine

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