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. 2024 May 9;19(5):e0302892. doi: 10.1371/journal.pone.0302892

Comparing preferences to evaluations of barrier self-efficacy for two strength training programs in US older adults

Jordan D Kurth 1,2,*, Christopher N Sciamanna 1,2, Cheyenne Herrell 1,2, Matthew Moeller 1,2, Jonathan G Stine 3
Editor: Sohel Ahmed4
PMCID: PMC11081341  PMID: 38722856

Abstract

Background/Objectives

Engagement in regular physical activity is one of the best strategies for older adults to remain healthy. Unfortunately, only 35% of older adults meet guidelines for muscle strengthening activities. Eliciting participant preferences is one possible way to improve physical activity engagement. However, other sources of participant input to improve uptake and maintenance remain uninvestigated. This study compared preferences to self-efficacy ratings for two strength training programs.

Methods

We conducted a national cross-sectional survey of 611 US adults over age 65. We compared two participant evaluations (the preferred program and the program for which they had higher barrier self-efficacy) of two hypothetical strength training programs (45 minutes performed three times per week (traditional) and 5 minutes performed daily (brief)).

Results

Most participants (68%) preferred the brief strength training program. The difference in self-efficacy ratings was an average of 1.2 (SD = 0.92). One in five participants preferred a strength training program for which they had less self-efficacy; nearly all of these participants (92%) preferred the traditional strength training program but had more self-efficacy for the brief strength training program.

Conclusion

Older adults reported preferring and having more self-efficacy for a brief compared to a traditional strength training program. Differences in self-efficacy ratings between the two strength training programs were large. Preferences were often not congruent with ratings of self-efficacy.

Significance/Implications

Preferences for strength training programming may not always reflect the program most likely to be maintained. Future investigations should evaluate differences in behavioral uptake, maintenance, and outcomes from two comparative strength training interventions using preferences and self-efficacy.

Introduction

Engagement in regular physical activity (PA) is one of the best strategies for adults over the age of 65 to preserve mobility, reduce falls risk, and remain both physically and mentally healthy [1–5]. Unfortunately, 31% of U.S. older adults report performing zero physical activity in their leisure time, and only 23% report meeting both the Centers for Disease Control and Prevention guidelines for aerobic activity (150 minutes of moderate-to-vigorous physical activity per week) and the recommendations for muscle strengthening activities (two days per week) [6]. Thus, a need exists to enhance current physical activity promotion efforts among older adults.

One possible physical activity promotion effort is to align characteristics (e.g., duration, frequency, mode of physical activity, reward structure) of physical activity programs with the preferences of the participants. There have been numerous examples of physical activity preference identification, particularly in community-dwelling older adults and clinical populations, such as those with chronic joint pain [7–10]. Despite the intuitive appeal of this approach, there is limited evidence to support its influence on increasing regular physical activity engagement [11–13]. Additionally, preferences are often operationally defined as “a predisposition to like a particular type of or context for physical activity more than others and to choose it when given the opportunity [emphasis added]” [14]. This definition, and much of the evidence that does exist surrounding the influence of preference alignment in physical activities, often evaluates self-selection [12,13] instead of preference alignment [11]. While the connection between allowing an individual to self-select program characteristics and improved affective response is well-established [15,16], this is of limited value when attempting to design a large, prescribed, scalable physical activity program. What we do know about expressed preferences generally suggests that they evolve across social and environmental contexts, and in some cases may be difficult to articulate prior to a relevant experience [17]. Additionally, they may be susceptible to repeated exposure to or familiarity with the stimuli being presented [18–20], thereby calling into question their utility in informing program design, particularly with relatively low-active populations that are frequently targeted.

The goal of most physical activity programming is long-term engagement in the behavior, or maintenance, as repeated performance is required to reap the benefits associated with physical activity. Identifying factors associated with maintenance of regular physical activity–and in fact even defining the phenomenon of “maintenance” itself–remains an active pursuit of both research and clinical practice [21]. However, of what is known, self-efficacy (SE; the level of confidence in one’s capability to engage in the behavior) is to-date perhaps the single most well-established predictor of physical activity engagement and maintenance according to systematic reviews and meta-analyses [22–25]. As such, designing programs that maximize known predictors of long-term physical activity engagement such as self-efficacy may promote long-term behavior performance. One novel method by which this might be accomplished is to use the evaluation of program characteristics rated using a known predictor of physical activity maintenance (i.e., self-efficacy) in place of the traditional rating of preference [26].

Therefore, this study aimed to compare two hypothetical evaluations: [1] preferred strength training program (5-minute daily program vs. 45-minute program performed 3 times per week) and [2] barrier self-efficacy for each respective program in a population of adults over the age of 65 years. We hypothesized that most participants would prefer the shorter, more frequent training program, and have higher self-efficacy for that same program. We also hypothesized that most participants would report preferring a program for which they had higher self-efficacy.

Materials and methods

This institutional review board exempted study (Penn State University IRB# STUDY00022306) used an anonymous online cross-sectional survey to inform the design of strength training programs in adults over 65 years of age with varying levels of health status and comorbidities. Throughout this manuscript, the reporting of data are in-line with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational cross-sectional studies [27]. The survey was conducted using a commercial survey company (Qualtrics). Qualtrics uses a network of survey participants from many suppliers with a range of recruitment methodologies from across the US. Participants are sourced from different methods depending on the supplier, including advertisements and promotions on smartphones, referrals from membership lists, social networks, mobile games, banner advertisements, mail-based recruitment campaigns and others [28,29]. The survey was estimated to take 5–10 minutes to complete and all participants were compensated. To ensure data quality, surveys included [1] attention checks (i.e., factual questions with correct answers) and [2] speeding checks (i.e., eliminating responses from those who completed the online survey in less than one-third the median duration of survey completion).

Participants

Participants were required to be at least 65 years of age, located in the United States, and fluent in the English language. Additional target demographic quotas were placed on recruitment to ensure a sample representative of the population over 65 years of age in the US. Target demographic quotas were placed on sex (50% male/50% female) and race/ethnicity (55% non-White Hispanic, 15% African American, 15% Asian American, 15% Alaskan Native/Native Hawaiian; 10% Hispanic). A target minimum of 556 participants (278 per preferred program) were planned to be enrolled in order to be able to detect a small (Cohen’s d = 0.2) difference at 90% power at an α = 0.05 within each preference group. Data collection occurred between April 3, 2023 and May 31, 2023. The need for consent was waived by the institutional review board, as data was collected anonymously.

Instruments and measures

Demographic information

Smoking status was assessed using a single item adapted from the Behavioral Risk Factor Surveillance System (BRFSS), “Do you use a tobacco product every day?” [30]. Medical history was assessed using questions (also from BRFSS) assessing presence or absence of: diabetes, high cholesterol, heart disease, osteoporosis, hypertension, stroke, and arthritis, as well as the frequency of strength training [30]. Demographic and anthropometric characteristics, such as age, gender, race, ethnicity, height, and weight were assessed, and body mass index (BMI) was calculated using the standard formula.

Strength training program preference

Strength training program preference was assessed by asking the following, “We are designing a strength training program for people over 65 to use at home, to improve their physical function, ability to walk and to reduce falls. Assuming that all programs include similar types of exercises, which would you prefer?” Participants were given two strength training program options from which to choose: “5 minutes, every day” or “45 minutes, 3 times per week”. The order of these answer options was randomized for each participant.

Strength training program self-efficacy

Self-efficacy for each strength training program was assessed using a 5-item, 5-point Likert scale (Not at all confident to Extremely confident) [31] to respond to the prompt “Regardless of your previous selection, please answer the following regarding a strength training program performed [45 minutes, 3 days per week OR 5 minutes, every day]. How confident are you that you could complete this program under each of the following conditions over the next 12 months? I could exercise for [45 minutes, 3 times per week OR 5 minutes, each day…]”. The order of the presentation of each program’s scale was also randomized for each participant. The five items evaluated by each participant were: “when I am tired.”, “when I am in a bad mood.”, “when I feel I do not have the time.”, “when I am on vacation.”, and “during bad weather (i.e., raining or snowing).”.

Analysis

Participants were grouped by their expressed strength training program preference. Additionally, two mean self-efficacy scores, one for the 5-minute daily program and one for the 45-minute program performed three days per week, were then calculated for each participant. These two scores were then compared; where applicable, the program for which participants reported higher SE was identified as the program for which the participant had the most self-efficacy. The distribution of these two variables (program preference and higher/lower/equal self-efficacy) were then cross-tabulated for comparison.

Results

Participant profile

A total of 1,162 of the participants that were screened met inclusion criteria. Data from participants that did not complete the survey (n = 438) were excluded from the final sample. Additionally, participants whose demographic quotas were filled before they completed their survey (n = 95), that completed the survey too quickly (less than half of the median complete time; n = 9), that failed the attention check (n = 5), or that were identified as bots using embedded survey fields (n = 4) were removed. Therefore, the final sample size included 611 participants (Fig 1). A demographic summary of the 611 participants that completed the survey is provided in Table 1. Of note, the mean participant age was 72 years. Approximately half of participants were female. Racial and ethnic distributions were representative of the US population over the age of 65 [32].

Fig 1. Participant flow diagram.

Fig 1

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Table 1. Participant characteristics.

Total (N = 611)
Mean(SD) or n(%)
Age, years 72.4 (5.1)
Sex, female, n 294 (48.1)
Race, White, n 341 (55.8)
Race, Black, n 102 (16.7)
Ethnicity, Hispanic, n 62 (10.2)
Body Mass Index, kg/m2 27.7 (7.0)
Strength Training, days/week 1.4 (2.1)
Daily Tobacco Use, n 64 (10.5)
Diabetes, n 152 (25.2)
High Cholesterol, n 338 (56.5)
Heart Disease, n 787 (14.6)
Osteoporosis, n 100 (17.0)
Hypertension, n 375 (62.1)
Stroke, n 40 (6.6)
Arthritis, n 295 (49.4)
Prefer 5-min, daily program, n 380 (68.4)
Higher SE for 5-min, daily program, n 490 (80.2)
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Note. SE = self-efficacy.

Description of strength training program preference and self-efficacy

Most participants (68%) expressed preference for the 5-minute daily strength training program over the 45-minute program completed three times per week. Even more participants (80%) reported having more self-efficacy for the 5-minute, daily program compared to the 45-minute program completed three days per week. The mean absolute difference in program self-efficacy rating was 1.2 (SD = 0.92; Cohen’s d = 1.3).

Congruence of strength training program preference and self-efficacy rating

Most participants’ (402/611; 66%) expressed strength training program preference was congruent with the program for which they had the most self-efficacy. However, more than 1 in 5 participants (130/611; 21.3%) expressed a strength training program preference that was incongruent with the program for which they reported higher self-efficacy. Nearly all (370/418; 89%) participants who reported preferring the 5-minute daily program also had higher self-efficacy for that same program, whereas only 17% of participants (32/193) who reported preferring the 45-minute program completed 3 days per week also had higher self-efficacy for the 45-minute program. Approximately 13% (79/611) participants reported the same self-efficacy for both programs, reporting nearly equal preferences for each (n = 41 vs. n = 38; Table 2).

Table 2. Cross-tabulation of preference and higher self-efficacy rating.


 Self-Efficacy Rating Higher for 45-minute, 3 Times per Week Self-Efficacy Rating Higher for 5-minute, Daily Self-Efficacy Rating Equal for Both Programs
Prefer 45-minute, 3 Times per Week Program 32 (5.2%) 120 (19.6%) 41 (6.7%)
Prefer 5-minute, Daily Program 10 (1.6%) 370 (60.6%) 38 (6.2%)
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Note. Percentages are relative to the total sample (N = 611).

Discussion

In this study, consistent with our hypothesis, more than 2 in 3 adults over the age of 65 expressed a preference for a 5-minute daily strength training program compared to a 45-minute program completed three times per week. Also consistent with our hypothesis, more than 80% of participants reported higher self-efficacy for the 5-minute program. Two in three participants preferred the program for which they had higher self-efficacy. However, more than four out of every five participants that preferred the 45-minute program had higher self-efficacy for the 5-minute program.

The present study suggests that elicited preferences are often not congruent with ratings of self-efficacy. The impact of this discrepancy between preference selection and higher self-efficacy ratings on long-term behavior remains unknown. Given that most participants who preferred the 45-minute program had higher self-efficacy for the 5-minute program, and that the 45-minute program structure is the most commonly offered, the potential impact of designing self-efficacy driven programs could be large. What is known is that the literature supporting the positive effects of self-efficacy [22–25] is much stronger than the literature supporting the effects of preference selection [11–13].

Additionally, preferences are known to not necessarily arise directly from cognitions [20]. In other words, they are rife with influence from irrelevant and/or counterproductive sources–such as emotional states and repeated exposure to or familiarity with the stimuli being presented [18–20]. Standard physical activity programs are typically 45–60 minutes performed three days per week. This is one possible factor that may have led some participants to report preferring the 45-minute program despite having higher self-efficacy for the 5-minute program. While self-efficacy is not immune to emotional influence [33], that emotional influence is theoretically more directly relevant to the activity in question. For those reasons, soliciting evaluations of possible program options on known predictors of the target behavior (in this case self-efficacy for physical activity maintenance) instead of preference may lead to more effective decision-making by intervention designers targeting physical activity maintenance.

This is a preliminary investigation into asking for program evaluations using a known predictor of the target behavior (in this case, barrier self-efficacy for physical activity) instead of preference. This study is not intended to suggest that a 5-minute daily strength training workout is the best strength training format for older adults or that it is better than a 45-minute program completed three times per week. Further exploration into alternative/additional program details, the number of options presented, and how those programs are described is required. Most importantly, investigation also needs to be done to evaluate differences in actual behavioral uptake, maintenance, and outcomes that arise from two comparative interventions: one designed using participant preferences and one designed using a known predictor of maintenance.

This study has several limitations. First, only two program options were evaluated; information about any alternative program options that may be preferable or elicit higher self-efficacy evaluations is not available. Second, the relevance of the difference in self-efficacy, though large (Cohen’s d = 1.3), is unclear. While one program was often rated higher than the other and dichotomized as the program for which self-efficacy was higher, the magnitude of that difference varied by participant. Finally, the impact of preference and self-efficacy evaluations was not evaluated by assessing actual behavior uptake, maintenance, or outcomes. It remains unclear if there is a behavioral or outcome-based difference between preference and self-efficacy-designed programs.

This study also has multiple strengths. Sampling quotas allowed for a demographically-representative sample of the US population over the age of 65 years based on the characteristics of sex, race, and ethnicity–overcoming a well-documented limitation of exercise promotion research historically [34]. Additionally, data was collected using a digital, anonymous survey, thereby reducing–though not eliminating–self-selection bias common in physical activity research. Additionally the presentation of the self-efficacy questions and preference answer options were presented randomly to eliminate order effects.

Conclusion

In this novel study directly comparing preferences and self-efficacy, adults over the age of 65 years reported preferring a 5-minute daily strength training program compared to a 45-minute program performed three times per week. Most participants also reported higher self-efficacy for that program. However, 1 in 5 older adults preferred a program for which they had lower self-efficacy than the alternative; nearly all of these participants preferred the 45-minute program but had lower self-efficacy for it. This evidence suggests that expressed preferences for physical activity programming may not always reflect the program most likely to be maintained. Soliciting evaluations of possible program options on known predictors of the target behavior (in this case self-efficacy for physical activity maintenance) instead of preference may lead to more effective decision-making by intervention designers targeting physical activity maintenance.

Supporting information

S1 Checklist. STROBE statement—checklist of items that should be included in reports of cross-sectional studies.

(DOCX)

pone.0302892.s001.docx (32.3KB, docx)

Data Availability

Data associated with this study is available via Penn State Data Commons at https://doi.org/10.26208/Q1KB-AW67.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Sohel Ahmed

13 Mar 2024

PONE-D-24-04115Comparing Preferences to Evaluations of Barrier Self-Efficacy for Two Strength Training Programs in US Older AdultsPLOS ONE

Dear Dr. Kurth,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Additional Editor Comments:

• Why is this study really important? The Centers for Disease Control and Prevention say that adults aged 65 and up need to do at least 150 minutes of moderate-intensity exercise or 75 minutes of vigorous-intensity activity each week. This could be broken down into 30 minutes of activity each day, five days a week. So why do you say that people should only work out for 35 minutes a week?

• What is the implication of this study for clinical practices?

• How do you calculate the appropriate sample size for this study? What was the sampling method you used? How did the study become a national representative survey?

• As this study is an online survey, how do you calculate the potential response rate?

• A third party conducted this survey; how can you reduce unresponsive bias?

• A lot of people might not be able to use the internet or fill out an online survey because they are not tech-savvy enough. How will they be a part of the study? How can you say that the survey is representative of the whole country?

• Inclusion and exclusion criteria should be more specific

• This survey is focusing on the efficiency of 5 minutes and 45 minutes of strength training for US older adults; why not 10/15/20 and 45 minutes?

• Discuss the generalizability of the study findings

• This study should acknowledge the potential bias of the study.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for inviting me to review this paper. This paper is well written and very interesting and important for the readers. However, there are some minor changes required to improve quality of this paper.

Introduction

The introduction section should be elaborated by reflecting the significance and novelty of the study.

Methodology

What were the exclusion criteria? Who did the survey?

The statistical analysis section should reflect all the tests used.

Discussion

In discussion section, focus more on potential implications of your study's findings and add future research direction based on current findings.

Conclusion

Clearly state the contributions of your study to the field and highlight any novel aspects of your research. Future work should be mentioned in discussion section.

Language and Writing Style

The manuscript requires careful proofreading to eliminate grammatical errors and improve sentence structure. Clarity and precision in language will significantly enhance the manuscript's readability and overall impact.

I appreciate your attention to these matters and look forward to reviewing the revised version of your manuscript.

Reviewer #2: The study addresses an important public health issue of physical activity among older adults. As a whole, it is a well-structured manuscript. However, the main issue of the manuscript is the lack of detail in the methods section, which needs to be corrected.

A point of ambiguity throughout the text is the procedure for choosing the type of strength training, the kinds of contractions, the duration of contractions, and its specifics. In the case of older adults, the choice of resistance exercise has unique details that are not mentioned anywhere in the study. Was the exercise instruction also provided online? How can the authors ensure that the participants correctly learned and executed the exercise? The study does not provide information on how the strength training programs were presented to the participants, which could influence their preferences and self-efficacy ratings.

The study does not provide details on how the survey questions and the 5-point Likert scale were developed or validated. This information is crucial to assess the reliability and validity of the findings.

In general, the methods section lacks clarity, and many details are missing. The methods should be written in a way that allows the audience to replicate the study, but the necessary details are not presented.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Sahar Boozari

**********

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Attachment

Submitted filename: reviwer comment.docx

pone.0302892.s002.docx (12.6KB, docx)
PLoS One. 2024 May 9;19(5):e0302892. doi: 10.1371/journal.pone.0302892.r002

Author response to Decision Letter 0

19 Mar 2024

Editor Comments

Why is this study really important? The Centers for Disease Control and Prevention say that adults aged 65 and up need to do at least 150 minutes of moderate-intensity exercise or 75 minutes of vigorous-intensity activity each week. This could be broken down into 30 minutes of activity each day, five days a week. So why do you say that people should only work out for 35 minutes a week?

Thank you for raising this point. This is the recommended amount of exercise; however, less than 3 in 10 older adults are able to reach this amount. More than 3 in 10 do absolutely zero exercise. We do not suggest in this manuscript that people should only exercise for 35 minutes per week – however, increasing exercise from 0 minutes per week to any non-zero amount per week is in line with the lay recommendation to “move more, sit less”. This point is illustrated in the quotes below:

Introduction:

“Unfortunately, 31% of U.S. older adults report performing zero physical activity in their leisure time, and only 23% report meeting both the Centers for Disease Control and Prevention guidelines for aerobic activity (150 minutes of moderate-to-vigorous physical activity per week) and the recommendations for muscle strengthening activities (two days per week)(6). Thus, a need exists to enhance current physical activity promotion efforts among older adults.”

Discussion:

“This study is not intended to suggest that a 5-minute daily strength training workout is the best strength training format for older adults or that it is better than a 45-minute program completed three times per week.”

What is the implication of this study for clinical practices?

Thank you for raising this question. This study is meant to inform the design of exercise interventions. To the extent that clinical practice is involved in exercise program design, this study implies that patients may not always prefer the program they are most confident they can stick with. This point is illustrated in the quote below:

Discussion:

“For those reasons, soliciting evaluations of possible program options on known predictors of the target behavior (in this case self-efficacy for physical activity maintenance) instead of preference may lead to more effective decision-making by intervention designers targeting physical activity maintenance.”

How do you calculate the appropriate sample size for this study? What was the sampling method you used? How did the study become a national representative survey?

The following information has been added regarding sample size calculation in the Materials and Methods section:

“A target minimum of 556 participants (278 per preferred program) were planned to be enrolled in order to be able to detect a small (Cohen’s d = 0.2) difference at 90% power at an α = 0.05 within each preference group.”

Qualtrics Survey Software conducted the distribution of the survey, as indicated in this quote from the Materials and Methods section:

“The survey was conducted using a commercial survey company (Qualtrics). Qualtrics uses a network of survey participants from many suppliers with a range of recruitment methodologies from across the US. Participants are sourced from different methods depending on the supplier, including advertisements and promotions on smartphones, referrals from membership lists, social networks, mobile games, banner advertisements, mail-based recruitment campaigns and others (28,29).”

Quota sampling was employed in order to ensure a nationally-representative sample based on the criteria of sex, race, and ethnicity of people over 65 years of age in the United States. This is illustrated by the quote from the Materials and Methods section below:

“Additional target demographic quotas were placed on recruitment to ensure a sample representative of the population over 65 years of age in the US. Target demographic quotas were placed on sex (50% male/50% female) and race/ethnicity (55% non-White Hispanic, 15% African American, 15% Asian American, 15% Alaskan Native/Native Hawaiian; 10% Hispanic).”

As this study is an online survey, how do you calculate the potential response rate?

Thank you for asking for this clarification. It is not possible to quantify the number of people who had the potential to respond to the survey (i.e., those that received invitation from Qualtrics, but did not click the link to start the survey). However, Qualtrics software collects information about all responses that were started, even those not finished, so we do have information about the completion rate of the survey, as below from the Results section:

“A total of 1,162 of the participants that were screened met inclusion criteria. Data from participants that did not complete the survey (n = 438) were excluded from the final sample. Additionally, participants whose demographic quotas were filled before they completed their survey (n = 95), that completed the survey too quickly (less than half of the median complete time; n = 9), that failed the attention check (n = 5), or that were identified as bots using embedded survey fields (n = 4) were removed. Therefore, the final sample size included 611 participants (Figure 1).”

A third party conducted this survey; how can you reduce unresponsive bias?

Thank you for highlighting this. The third party uses business with whom participants already have an existing relationship to deliver the survey. The survey was estimated to take 5-10 minutes. All participants were compensated. All of these factors mitigate nonresponse bias. This information has been added to the Materials and Methods section, as quoted below:

“The survey was conducted using a commercial survey company (Qualtrics). Qualtrics uses a network of survey participants from many suppliers with a range of recruitment methodologies from across the US. Participants are sourced from different methods depending on the supplier, including advertisements and promotions on smartphones, referrals from membership lists, social networks, mobile games, banner advertisements, mail-based recruitment campaigns and others (28,29). The survey was estimated to take 5-10 minutes to complete and all participants were compensated.”

A lot of people might not be able to use the internet or fill out an online survey because they are not tech-savvy enough. How will they be a part of the study? How can you say that the survey is representative of the whole country?

Thank you for raising this point. This survey was only accessible online. As mentioned above, the survey is representative of the whole country based only the criteria of age, race, and ethnicity.

Notably, according to Pew Research Center in 2021, 75% of US adults over 65 years of age have internet access. (1)

1. Perrin A, Atske S. 7% of Americans don’t use the internet. Who are they? [Internet]. Pew Research Center. [cited 2023 Jun 13]. Available from: https://www.pewresearch.org/short-reads/2021/04/02/7-of-americans-dont-use-the-internet-who-are-they/

Inclusion and exclusion criteria should be more specific

The only inclusion/exclusion criteria are below, as provided in the Materials and Methods section:

“Participants were required to be at least 65 years of age, located in the United States, and fluent in the English language.”

This survey is focusing on the efficiency of 5 minutes and 45 minutes of strength training for US older adults; why not 10/15/20 and 45 minutes?

Thank you for highlighting this. There are infinitely many possible lengths of strength training sessions and frequencies that are possible to test. Given the rise in popularity of brief workouts, a 5-minute option was selected to draw a clear distinction between what is typically offered for older adults (i.e., 30-45 mins). Notably, this is mentioned as a limitation, as illustrated in the two quotes below from the discussion section:

“This study is not intended to suggest that a 5-minute daily strength training workout is the best strength training format for older adults or that it is better than a 45-minute program completed three times per week. Further exploration into alternative/additional program details, the number of options presented, and how those programs are described is required.”

“This study has several limitations. First, only two program options were evaluated; information about any alternative program options that may be preferable or elicit higher self-efficacy evaluations is not available.”

Discuss the generalizability of the study findings

This study is generalizable insofar as a cross-sectional survey has the capability to be. It is an evaluation of preferences and self-efficacy for two strength training programs in a sample that is nationally-representative of the sex, race, and ethnicity of the US population over the age of 65. Important next steps have been suggested in the Discussion section, as quoted below:

“This is a preliminary investigation into asking for program evaluations using a known predictor of the target behavior (in this case, barrier self-efficacy for physical activity) instead of preference. This study is not intended to suggest that a 5-minute daily strength training workout is the best strength training format for older adults or that it is better than a 45-minute program completed three times per week. Further exploration into alternative/additional program details, the number of options presented, and how those programs are described is required. Most importantly, investigation also needs to be done to evaluate differences in actual behavioral uptake, maintenance, and outcomes that arise from two comparative interventions: one designed using participant preferences and one designed using a known predictor of maintenance.”

This study should acknowledge the potential bias of the study.

Potential biases are discussed in a limitations paragraph, found in the Discussion section, as below:

“This study has several limitations. First, only two program options were evaluated; information about any alternative program options that may be preferable or elicit higher self-efficacy evaluations is not available. Second, the relevance of the difference in self-efficacy, though large (Cohen’s d = 1.3), is unclear. While one program was often rated higher than the other and dichotomized as the program for which self-efficacy was higher, the magnitude of that difference varied by participant. Finally, the impact of preference and self-efficacy evaluations was not evaluated by assessing actual behavior uptake, maintenance, or outcomes. It remains unclear if there is a behavioral or outcome-based difference between preference and self-efficacy-designed programs.”

Reviewer #1 Comments

Thank you for inviting me to review this paper. This paper is well written and very interesting and important for the readers. However, there are some minor changes required to improve quality of this paper.

Introduction

The introduction section should be elaborated by reflecting the significance and novelty of the study.

Thank you for this suggestion. The following section of the Introduction has been edited to address this feedback:

“The goal of most physical activity programming is long-term engagement in the behavior, or maintenance, as repeated performance is required to reap the benefits associated with physical activity. Identifying factors associated with maintenance of regular physical activity – and in fact even defining the phenomenon of “maintenance” itself – remains an active pursuit of both research and clinical practice (21). However, of what is known, self-efficacy (SE; the level of confidence in one’s capability to engage in the behavior) is to-date perhaps the single most well-established predictor of physical activity engagement and maintenance according to systematic reviews and meta-analyses (22–25). As such, designing programs that maximize known predictors of long-term physical activity engagement such as self-efficacy may promote long-term behavior performance. One novel method by which this might be accomplished is to use the evaluation of program characteristics rated using a known predictor of physical activity maintenance (i.e., self-efficacy) in place of the traditional a rating of preference (26).”

Methodology

What were the exclusion criteria? Who did the survey?

The statistical analysis section should reflect all the tests used.

Thank you for requesting this clarification. The criteria for inclusion are state in the Materials and Methods section, as below:

“Participants were required to be at least 65 years of age, located in the United States, and fluent in the English language.”

Participant description is available in the Results section, as below, and also in Table 1:

“A demographic summary of the 611 participants that completed the survey is provided in Table 1. Of note, the mean participant age was 72 years. Approximately half of participants were female. Racial and ethnic distributions were representative of the US population over the age of 65 (32).”

The statistical tests used are identified in the Materials and Methods section, as below:

“Participants were grouped by their expressed strength training program preference. Additionally, two mean self-efficacy scores, one for the 5-minute daily program and one for the 45-minute program performed three days per week, were then calculated for each participant. These two scores were then compared; where applicable, the program for which participants reported higher SE was identified as the program for which the participant had the most self-efficacy. The distribution of these two variables (program preference and higher/lower/equal self-efficacy) were then cross-tabulated for comparison.”

Discussion

In discussion section, focus more on potential implications of your study's findings and add future research direction based on current findings.

Potential implications have been mentioned in the Discussion section, as below:

“…soliciting evaluations of possible program options on known predictors of the target behavior (in this case self-efficacy for physical activity maintenance) instead of preference may lead to more effective decision-making by intervention designers targeting physical activity maintenance.

Future directions are suggested in the Discussion section as below:

“Further exploration into alternative/additional program details, the number of options presented, and how those programs are described is required. Most importantly, investigation also needs to be done to evaluate differences in actual behavioral uptake, maintenance, and outcomes that arise from two comparative interventions: one designed using participant preferences and one designed using a known predictor of maintenance.”

Conclusion

Clearly state the contributions of your study to the field and highlight any novel aspects of your research. Future work should be mentioned in discussion section.

Thank you for this suggestion. Future directions have been removed from the Conclusion section. Implications have been added as below:

“In this novel study directly comparing preferences and self-efficacy, adults over the age of 65 years reported preferring a 5-minute daily strength training program compared to a 45-minute program performed three times per week. Most participants also reported higher self-efficacy for that program. However, 1 in 5 older adults preferred a program for which they had lower self-efficacy than the alternative; nearly all of these participants preferred the 45-minute program but had lower self-efficacy for it. This evidence suggests that expressed preferences for physical activity programming may not always reflect the program most likely to be maintained. Soliciting evaluations of possible program options on known predictors of the target behavior (in this case self-efficacy for physical activity maintenance) instead of preference may lead to more effective decision-making by intervention designers targeting physical activity maintenance.”

Language and Writing Style

The manuscript requires careful proofreading to eliminate grammatical errors and improve sentence structure. Clarity and precision in language will s

Attachment

Submitted filename: ResponsetoReviewers_20240314.docx

pone.0302892.s003.docx (26.5KB, docx)

Decision Letter 1

Sohel Ahmed

16 Apr 2024

Comparing preferences to evaluations of barrier self-efficacy for two strength training programs in US older adults

PONE-D-24-04115R1

Dear Dr. Jordan D Kurth

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Sohel Ahmed, BPT, MPT, MDMR

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Sahar Boozari

**********

Acceptance letter

Sohel Ahmed

26 Apr 2024

PONE-D-24-04115R1

PLOS ONE

Dear Dr. Kurth,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

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on behalf of

Dr. Sohel Ahmed

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Checklist. STROBE statement—checklist of items that should be included in reports of cross-sectional studies.

    (DOCX)

    pone.0302892.s001.docx (32.3KB, docx)
    Attachment

    Submitted filename: reviwer comment.docx

    pone.0302892.s002.docx (12.6KB, docx)
    Attachment

    Submitted filename: ResponsetoReviewers_20240314.docx

    pone.0302892.s003.docx (26.5KB, docx)

    Data Availability Statement

    Data associated with this study is available via Penn State Data Commons at https://doi.org/10.26208/Q1KB-AW67.

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