Implementation of an Evidence-Based, Tai Ji Quan Fall Prevention Program in Rural West Virginia Churches: A RE-AIM Evaluation

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Dina L. Jones Department of Orthopaedics, Division of Physical Therapy, and Injury Control Research Center, West Virginia University, Morgantown, WV, USA

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Terry Kit Selfe Academic Research Consulting & Services, Health Science Center Libraries, University of Florida, Gainesville, FL, USA

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Sijin Wen Department of Epidemiology and Biostatistics, School of Public Health, West Virginia University, Morgantown, WV, USA

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Jennifer L. Eicher Department of Orthopaedics, West Virginia University, Morgantown, WV, USA

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Sara Wilcox Department of Exercise Science and Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA

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Corrie Mancinelli Division of Physical Therapy, West Virginia University, Morgantown, WV, USA

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This study implemented a 16-week Tai Ji Quan: Moving for Better Balance® intervention for older adults in churches in hard-to-reach, medically underserved, rural communities, and evaluated the process using the RE-AIM Framework. Community-dwelling adults, aged 55 years, or older, were eligible. Data (N = 237) were collected at baseline, 16 weeks, and 32 weeks on falls efficacy, depression, physical/mental health-related quality of life, aerobic activity, gait speed, mobility, balance, and leg strength. Generalized/linear mixed models determined if outcomes improved. Eighteen churches sponsored 16 classes. Church adoption was 94%, instructor adoption was 86%, reach was 90%, and fidelity was good/fair. All outcomes improved except physical health-related quality of life and gait speed. Thirty-six percent of participants, 28% of churches, and 37% of instructors continued Tai Ji Quan: Moving for Better Balance at 32 weeks. Compared with two prior RE-AIM evaluations, adoption and reach rates, improvements in outcomes, and satisfaction were comparable; attendance, program completion, and continuation rates were lower.

More than 25% of older adults fall each year (Moreland et al., 2020) with one-fifth of falls resulting in serious injuries (Alexander et al., 1992; Sterling et al., 2001). Hence, falls are a leading cause of fatal and nonfatal injuries in adults aged 65 years and older in the United States and rural West Virginia (WV) (Burns & Kakara, 2018; Centers for Disease Control and Prevention & National Center for Injury Prevention and Control, 2019a, 2019b; Levi et al., 2015). In 2018, the death rate in WV (93 per 100,000) was significantly higher than the U.S. average (64 per 100,000; Centers for Disease Control and Prevention & National Center for Injury Prevention and Control, 2018). WV also had the third highest increase in fall deaths between 2007 and 2016 (Burns & Kakara, 2018). Fall-related medical costs in the United States were $50 billion in 2015 (Florence et al., 2018) and $357 million in WV in 2014 (Centers for Disease Control and Prevention & National Center for Injury Prevention and Control, 2014). These statistics underscore the need for fall prevention interventions in WV and are concerning given that falls are projected to rise as the size of the older adult population increases (Centers for Disease Control and Prevention & National Center for Injury Prevention and Control, 2020).

Exercise that challenges balance is safe and efficacious for reducing falls in older adults (Sherrington et al., 2019). Tai Ji Quan (TJQ) is one form of exercise that challenges balance. Several systematic reviews have demonstrated that TJQ improves balance and reduces falls (Huang et al., 2017; Leung et al., 2011; Sherrington et al., 2019).

Tai Ji Quan: Moving for Better Balance® (TJQMBB) is an evidence-based program that is efficacious, cost-effective, improves balance, and reduces falls in older adults (Li et al., 2005, 2019). The exercises use TJQ training principles with movements adapted from Yang-style TJQ (Li, 2014). One-hour classes are held twice weekly, for 24 weeks (total 48 hr; Li et al., 2018), which essentially meets the 50-hr dose needed to effectively reduce falls (Sherrington et al., 2008). While TJQMBB has been implemented in some community settings, it has not been widely implemented in more diverse settings, such as hard-to-reach, medically underserved rural communities where fall prevention programs are often not available.

The purpose of this quasi-experimental, one-way, pretest–posttest repeated-measures study was to implement a 16-week TJQMBB intervention for older adults in rural WV churches and evaluate the process using the RE-AIM Framework (Glasgow et al., 1999). We chose churches because they are widespread in WV and may be efficient, effective, and low-cost venues to reach medically underserved, rural older adults with fall prevention programming. We used the RE-AIM Framework to assess factors related to both internal (i.e., did TJQMBB work?) and external (i.e., applicability to other older adults) validity, and to compare our results with two prior TJQMBB RE-AIM evaluations in community settings (Li et al., 2008, 2016).

The objectives of this study were to evaluate TJQMBB’s: (a) reach (enrollment and representativeness), (b) effectiveness (outcomes), (c) adoption (proportion of churches and instructors that delivered TJQMBB), (d) implementation (attendance; program completion; fidelity; adverse events; and participant, church, and instructor satisfaction), and (e) maintenance (participant, church, and instructor TJQMBB continuation). We expected: (a) to reach at least 80% of eligible respondents (Li et al., 2008); (b) statistically significant improvements in participant outcomes (Li et al., 2008); (c) church (Bopp et al., 2007; Li et al., 2008) and instructor (Folta, Lichtenstein, et al., 2015) adoption rates of at least 75%; (d) attendance and completion rates of at least 75% (Li et al., 2008), fidelity rates of at least 75% (Jones & Eicher, 2012), no adverse events, and high participant, church, and instructor satisfaction at 16 weeks (Li et al., 2008); and (e) at least 50% of participants, churches, and instructors continuing TJQMBB at the 16- and 32-week follow-ups (Li et al., 2008). We hypothesized that (a) participant outcomes would significantly improve between baseline and 16 weeks (end of intervention; i.e., the intervention worked), (b) improvements observed at 16 weeks would be maintained at 32 weeks (i.e., significant improvement between baseline and 32 weeks), and (c) that participants with significant improvements at 16 weeks would continue to improve through 32 weeks (i.e., significant improvements from 16 to 32 weeks). The RE-AIM dimensions are presented in chronological order as done in other publications.

Methods

Adoption

In 2010, one third (36%) of WV’s 1.85 million residents adhered to a religion (Association of Statisticians of American Religious Bodies, 2010). Of the 4,413 congregations in WV, the most common religious tradition was Evangelical Protestant (47.2%) followed by Mainline Protestant (44.2%; Association of Statisticians of American Religious Bodies, 2010).

The methods for church and instructor recruitment in this study have been previously described as well as the barriers and facilitators for TJQMBB adoption (Jones et al., 2016). Our goal was to recruit 20 churches and at least 20 instructors from seven, medically underserved rural counties. Four contiguous counties were clustered in the northern-middle part of the state, three contiguous counties were clustered in the most southern part of the state. Churches were eligible if they could (a) secure space for class, (b) host a 16-week class, (c) help identify instructors, (d) help recruit participants, and (e) were interested in continuing TJQMBB after the study. We identified 164 churches that were mailed recruitment packets, with little response (Jones et al., 2016). We switched to snowball sampling, which relied on networking and word-of-mouth, through which we identified 47 additional churches, for a total of 211 targeted churches. The churches were Evangelical Protestant (50.0%), Mainline Protestant (42.8%), other Christian (3.4%), Catholic (2.9%), and non-Christian (1.0%; n = 208) and representative of congregations in WV (Association of Statisticians of American Religious Bodies, 2010).

We documented the number of churches that were invited, joined the study, and started TJQMBB classes. We calculated both study level and population level adoption rates for churches. The study level adoption rate was the proportion of churches with trained instructors that started class, multiplied by 100 (Bopp et al., 2007; Jones et al., 2016) for comparison with two prior TJQMBB RE-AIM evaluations (Li et al., 2008, 2016). The population adoption rate was the proportion of churches that adopted TJQMBB out of the number of targeted churches, multiplied by 100 (Hutto et al., 2021).

Instructors were eligible if they could (a) attend the free, 2-day TJQMBB training with the program developer, (b) lead a 16-week class, (c) help recruit participants, (d) maintain program fidelity, and (e) were interested in continuing TJQMBB after the study. Instructors received a small stipend from the research grant and mileage reimbursement for travel to class sites that were greater than 50 miles roundtrip. Instructors were recruited by the churches and research team via word-of-mouth. We documented the number of instructors that were invited, joined the study, underwent training, and started TJQMBB classes. The instructor adoption rate was the proportion of trained instructors who started class, multiplied by 100 (Folta, Lichtenstein, et al., 2015; Jones et al., 2016).

Reach

This study was approved by our institutional review board (IRB) prior to recruiting any participants. All participants provided written informed consent. Participants were recruited between February and July 2014. Eligible participants were community-dwelling adults aged 55 years or older. We lowered the entry age from 65 to 55 years because smaller churches did not have enough older congregants to fill a class (Jones et al., 2016).

Participants were recruited by the churches, instructors, and research team using flyers, church announcements, word-of-mouth, and press releases sent to newspapers and radio and television stations. People were screened for eligibility by telephone and scheduled for a baseline assessment at the church. We calculated both study level and population level reach rates. We recorded the number of people who inquired about the study, were screened for eligibility, deemed eligible, and enrolled. Study reach was defined as the number of eligible people divided by the number of inquiries about the study, multiplied by 100, for comparison with two prior TJQMBB RE-AIM evaluations (Li et al., 2008, 2016). Population reach was the number of enrollees divided by the estimated number of older adult worshippers (aged 65 years or older) in the adopting churches, multiplied by 100 (Hutto et al., 2021). The number of older adult worshippers was calculated by multiplying the total number of worshippers in the 18 churches by 53%, which was the mean proportion of worshippers aged 65 years and older across the churches. Data were not available for the number of worshippers aged 55–64 years.

Questionnaire data, and height and weight were collected at the baseline assessment to describe the sociodemographic characteristics and fall risk factors of the enrollees. The fall risk factors included chronic medical conditions (Lawlor et al., 2003; Nevitt et al., 1989; Tinetti et al., 1988), fall history in past 12 months (Luukinen et al., 1995; Nevitt et al., 1989), taking four or more medications (i.e., polypharmacy; Campbell et al., 1989; Luukinen et al., 1995; Tinetti et al., 1988), difficulty holding urine (Tromp et al., 2001), restricting activities due to fear of falling (Cigolle et al., 2015; Lach, 2005; Li et al., 2003), using an assistive device for ambulation (Rubenstein, 2006), and body mass index (Mitchell et al., 2014).

The questionnaire contained standardized questions from other fall prevention studies and program materials (Nandy et al., 2004; National Center for Injury Prevention and Control, 2011; Reyes-Ortiz et al., 2006; Tinetti et al., 1988). A question from the 2012 Behavioral Risk Factor Surveillance System determined the number of falls that occurred in the past 12 months (i.e., fall history; Centers for Disease Control and Prevention, 2012). Participants reporting more than one fall in the past 12 months were categorized as frequent fallers (Luukinen et al., 1995; Nevitt et al., 1989). Height and weight were measured with a Seca 213 (Seca North America) portable stadiometer and a calibrated bathroom scale to calculate body mass index, and participants were assigned to obesity categories for comparison with state data.

Data were needed on nonenrolled older adults in the adopting churches to determine representativeness. In the absence of such information, we compared our sociodemographic data with county-level data which were on adults of all ages (U.S. Census Bureau, 2019). Prevalence data on chronic conditions were compared with state-level data in other older adults (West Virginia Department of Health and Human Resources, 2020).

Implementation

Classes were held twice weekly, for 60 min (no breaks), for 16 weeks (32 sessions). A 16-week intervention was used because at least 4 months of TJQ are required to affect fall risk (Li et al., 2005; Wolf et al., 2003), and because the study focus was on implementation, not efficacy. Each session included 5–10 min of preparatory exercises, 40–45 min of core movements, and 5 min of closing exercises (Li et al., 2018). Core movements were selected from (a) an eight-form routine (Li et al., 2005, 2012), (b) 11 mini therapeutic movements (Li et al., 2012), and (c) 10 practice variations (Li, 2014). The forms were choreographed routines with slow deliberate movements (Li, 2014). The mini therapeutic movements integrated TJQ principles with therapeutic balance and mobility exercises and were functional (e.g., reaching, turning, standing up from a chair; Li, 2014). The practice variations kept the exercises challenging (Li, 2014). Instructors documented participant attendance. A completer was defined as someone who attended at least 24 (75%) of the 32 sessions (Li et al., 2008, 2013, 2016). Participants were given a DVD with TJQMBB exercises at the end of the 16-week intervention. The DVD contained warm-up exercises in sitting, standing, and stepping; the eight-form routine both with and without verbal instructions; and standing and stepping exercises.

Each instructor was observed twice by one of three TJQMBB-trained observers, with expertise in exercise or TJQ, to complete the developer’s 25-item fidelity checklist and calculate compliance rates. Observations occurred during the first 6 weeks and the last 4 weeks of class. Compliance was rated with (a) time spent on preparatory exercises, core movements, closing exercises, and total class time; (b) number of sets performed of each form; (c) number of forms performed; (d) performance of two or more mini therapeutic movements; (e) performance of one or more practice variations; (f) use of eight teaching strategies; (g) adherence to 11 core principles; (h) delivery of a well-integrated class; and (i) an efficient teaching pace.

We tracked intervention-related injuries via verbal reports and a questionnaire that participants completed at 8 and 16 weeks. The Principal Investigator (D.L. Jones) conducted standardized interviews via telephone with participants who reported an injury. Any adverse events as defined by IRB protocol (i.e., unanticipated, serious, and attributed to intervention) were reported to the IRB.

Participant and partner (i.e., church representatives, instructors, and community members) satisfaction was assessed at the end of the 16-week intervention. Participants completed a 37-item satisfaction questionnaire adapted from Gillette et al. (Gillette et al., 2015). Partners completed a 22-item questionnaire to evaluate the partnership experience, level of involvement, and degree of benefits relative to challenges (El Ansari, 1999).

Effectiveness

Participants completed questionnaires and performance-based tests at baseline, 16 weeks (end of intervention), and 32 weeks (16 weeks after intervention ended). The outcomes included falls efficacy (i.e., fear of falling), depression, physical and mental health-related quality of life (HRQOL), proportion of participants meeting aerobic physical activity guidelines, gait speed, mobility, balance, and lower extremity strength. The 10-item reliable and valid Falls Efficacy Scale assessed current fear of falling (Tinetti et al., 1990). Participants rated their confidence in performing 10 daily activities without falling. Scores ranged from 10 to 100. Scores greater than 70 indicated fear of falling (i.e., lower falls efficacy). The 15-item Geriatric Depression Scale-Short assessed depressive symptoms in the past week (Yesavage & Sheikh, 1986). Scores ranged from zero to 15. Higher scores indicated a greater likelihood of depression.

The Physical and Mental Component Summary scores of the SF-12 (version 2) determined physical and mental HRQOL over the past 4 weeks (Ware et al., 1996). Norm-based scores were linearly transformed to a mean of 50 and SD of 10. Scores over 50 indicated better physical or mental HRQOL than the general U.S. population. Participants provided the number of times per week and minutes per time they engaged in moderate- and/or vigorous-intensity aerobic activity (National Center for Health Statistics, 2012). The minutes of moderate activity were added to twice the minutes of vigorous activity to obtain the total minutes per week. Participants were classified as inactive (0 min), insufficiently active (1–149 min), or meeting guidelines (150 min or more) based on the total number of minutes of activity per week (U.S. Department of Health and Human Services, 2008).

Participants completed performance-based tests of gait, mobility, balance, and lower extremity strength. Both continuous and categorical outcomes are presented because some of the categorical outcomes identified future fall risk based on established cutoff points. The gait, mobility, and balance tests have high reliability and validity and predict older adult falls (Dite & Temple, 2002; Fritz & Lusardi, 2009; Guimaraes & Isaacs, 1980; Montero-Odasso et al., 2005; Podsiadlo & Richardson, 1991; Studenski et al., 2011). A timed Five-Meter Walk Test at a usual pace determined gait speed (Fritz & Lusardi, 2009; Guimaraes & Isaacs, 1980; Montero-Odasso et al., 2005; Studenski et al., 2011). The length of the course was divided by the number of seconds it took to walk the course to obtain gait speed in meters/second. Higher scores indicated faster gait speed. Participants were at risk for one or more future falls if their gait speed was less than 1.0 m/s.

The timed up-and-go (TUG) assessed mobility (Podsiadlo & Richardson, 1991). Participants were timed as they stood from a chair, walked 3 m at a usual pace, turned, walked back to the chair, and sat down. Lower scores indicated greater mobility. Participants were at risk for one or more future falls if their TUG score was 12 s or more (Lusardi et al., 2017). Balance was assessed with the four-square step test (FSST) where participants were timed as they stepped over two PVC pipes, arranged on the floor in the shape of a cross, while moving in four directions (Dite & Temple, 2002). Lower scores indicated better balance. Participants were at risk for multiple future falls if their FSST score was greater than 15 s (Lusardi et al., 2017).

The five-times sit-to-stand (FTSTS test) measured lower extremity strength by timing how long it took to stand and sit five times from a chair without using armrests (Guralnik et al., 1994, 1995). Lower scores indicated stronger leg strength. Participants who took 12 or more seconds to complete the test were at risk for one or more future falls (Lusardi et al., 2017). The FTSTS has excellent test–retest reliability (Bohannon et al., 2007) and is one of the most evidence-supported functional measures (Lusardi et al., 2017). Although this study was not intended to detect a reduction in falls, we prospectively tracked falls using a daily calendar that participants returned each month by mail, the Behavioral Risk Factor Surveillance System question on fall history (Centers for Disease Control and Prevention, 2012), and verbal reports from participants or instructors.

Maintenance

Maintenance outcomes included TJQMBB continuation by participants, churches, and instructors at the 16- and 32-week follow-ups. Participants reported via questionnaire if they were using the TJQMBB DVD they received at the end of the intervention, and if they were practicing the program at 16 and 32 weeks. Instructors were contacted by email to determine which churches and instructors were offering classes at each time point.

Analysis

This study was not powered to detect a reduction in falls due to its limited scope/budget and because the focus was on implementation, not efficacy. We based our sample size on gait speed because it is a strong predictor of mortality and functional decline in older adults (Fritz & Lusardi, 2009; Studenski et al., 2011). Based on a Type I error rate of 0.05 and a mean ± SD change in gait speed of 1.06 ± 0.23 m/s (Wolf et al., 1996), 192 participants (240 enrolled accounting for 20% attrition) would provide over 80% power to detect a mean difference in gait speed from pre- to postintervention of 0.075 m/s (approximately one third of a SD).

Data on adoption and reach rates, sociodemographic characteristics, fall risk factors, attendance, program completion, injuries, satisfaction, and TJQMBB continuation were summarized descriptively. Comparisons between completers and noncompleters were conducted using chi-square or Mann–Whitney tests. For fidelity, the number of items rated at greater than or equal to 75% (our expected compliance rate) were tallied and divided by the total number of items on the fidelity checklist (25) to provide a compliance rate for each visit.

Descriptive statistics were used to summarize outcomes at baseline, 16 weeks, and 32 weeks. Because the outcome variables included repeated measurements that were correlated within participants, generalized linear mixed models (GLMM) were used for binary and ordinal data that could handle fixed and random effects model parameters, and unbalanced designs, where the number of repeated measurements varied across participants. The GLMM included the fixed effects of time with participants as random effects. The GLMM were used to fit data simultaneously at all time points, with time as a covariate in three levels: (a) baseline as a reference, (b) 16 weeks (end of intervention), and (c) 32 weeks (16 weeks after intervention ended). The regression coefficients assessed changes between 16 weeks and baseline, 32 weeks and baseline, and 32 weeks and 16 weeks. For continuous outcomes, the GLMM analysis was replaced by linear mixed models (i.e., a special case of GLMM). Additional models were run for both continuous and categorical outcomes with time as a continuous variable.

All models were adjusted for the fixed effects of site (northern vs. southern part of state), age at baseline, sex, and completer status (yes/no) (yes = attended at least 24 [75%] of 32 exercise sessions). We included geography as a covariate because there were documented differences in sociodemographic, health characteristics, morbidity, and mortality between the two regions (University of Wisconsin Population Health Institute, School of Medicine and Public Health, 2017; U.S. Census Bureau, 2019; West Virginia Department of Health and Human Resources, 2020). Models were assessed for goodness of fit based on the Akaike information criterion and its significance level. To analyze the effect of exercise dose based on completer status (yes/no), we also reported the p values for continuous outcomes with significant differences between completers and noncompleters, after adjusting for the other variables in the model. The GLMM and linear mixed models were designed to handle missing data and give unbiased estimates of effects. All analyses used Type I error rates of 0.05 and SAS for Windows (version 9.4; SAS Institute, Inc., 2016) or IBM SPSS Statistics for Windows (version 26.0; IBM Corp., 2019).

Results

Adoption

The adoption results have been previously described (Jones et al., 2016). Twenty churches and 28 instructors were recruited between May 2013 and May 2014. The churches were Mainline Protestant (n = 14, 70%), Evangelical Protestant (n = 5, 25%), and multidenominational (n = 1, 5%). Two churches withdrew, and two small churches partnered with two others, which left 18 adopting churches and 16 intervention sites. Two churches chose to hold classes at local senior centers. Fifteen of the 16 churches/senior centers with trained instructors started class for a study adoption rate of 94%. Eighteen of the 211 targeted churches adopted TJQMBB for a population adoption rate of 8.5%.

Six (21.4%) of the 28 instructors withdrew before training (three health, two unknown, and one church withdrew). Twenty-two (78.6%) of the 28 instructors underwent training of which three (13.6%) withdrew afterward (two unknown and one too few participants for a class). Thus, 19 of the 22 trained instructors started class for an adoption rate of 86%.

Reach

Of 294 inquiries, 263 (90%) people were screened for eligibility and all were eligible (Figure 1). Twenty-six (10%) of the 263 people declined to participate (16 unknown, five too busy, three health, and two unavailable). Thus, 237 (90%) of the 263 people enrolled in the study. The study reach was 90% (263 eligible of 294 inquiries). There were an estimated 1,056 worshippers aged 65 years or older in the 18 adopting churches (1,992 worshippers × 53% aged 65 years and older). The population reach was 22.4% (237 enrollees/1,056).

Figure 1
Figure 1

—Study enrollment.

Citation: Journal of Aging and Physical Activity 31, 1; 10.1123/japa.2021-0274

Participants were primarily older, female, non-Hispanic, White, married, and retired (Table 1). Two thirds (66.5%) of participants were Mainline Protestant, 16.7% were Evangelical Protestant, 10.4% were other-Christian, 3.6% were Catholic, 1.4% were non-Christian, and 1.4% had no preference (n = 221). Arthritis was the most frequently reported chronic medical condition. Forty percent of participants reported a fall within the past 12 months. Approximately two thirds of participants reported polypharmacy and/or had difficulty holding urine. Almost 50% of participants were obese.

Table 1

Baseline Sociodemographic and Fall Risk Characteristics of Participants in 16-Week Intervention

CharacteristicsParticipants

(N = 237)
Age (mean ± SD, range)71.5 ± 9.2 (55–98)
Sex, n (% female)192 (81.0)
Ethnicity, n (% Hispanic) (n = 220)5 (2.3)
Race, n (% White)226 (95.4)
Education, n (%) (n = 233)
 Less than high school20 (8.6)
 High school or more213 (91.4)
Annual income, n (%) (n = 208)
 <$50,000153 (73.6)
 ≥$50,00055 (26.4)
Marital status, n (%) (n = 234)
 Single12 (5.1)
 Married146 (62.4)
 Separated or divorced18 (7.7)
 Widowed58 (24.8)
Employment status, n (%) (n = 233)
 Homemaker/retired177 (76.0)
 Working23 (9.9)
 Other33 (14.2)
Chronic medical conditions, n (%)
 Arthritis (n = 229)150 (65.5)
 Cancer (n = 234)52 (22.2)
 Diabetes mellitus (n = 226)55 (24.3)
 Heart attack (n = 229)16 (7.0)
 Parkinson’s (n = 227)2 (0.9)
 Stroke (n = 227)17 (7.5)
Fall in past 12 months, n (%) (n = 232)92 (39.7)
>1 fall in past 12 months, n (%) (n = 232)41 (17.7)
Takes ≥4 medications, n (%) (n = 234)151 (64.5)
Difficulty holding urine, n (%) (n = 234)158 (67.5)
Restricts activities due to fear of falling, n (%) (n = 231)69 (29.9)
Uses assistive device for ambulation, n (%) (n = 232)45 (19.4)
Body mass index (kg/m2) (mean ± SD, range) (n = 227)30.4 ± 6.5 (16.7–62.3)
Obesity, n (%) (n = 214)
 <18.5 kg/m2 (underweight)1 (0.5)
 18.5–24.9 kg/m2 (normal)38 (17.8)
 25.0–29.9 kg/m2 (overweight)75 (35.0)
 ≥30 kg/m2 (obese)100 (46.7)

Implementation

Eighteen churches sponsored 16 TJQMBB classes that were led by 19 instructors, between March and November 2014, at 13 churches and two senior centers in seven, rural WV counties. All sites offered one TJQMBB class except for one site which held two classes. Three sites had more than one instructor and one instructor led classes at two sites. Two-hundred and twenty-three participants started class. The mean ± SD number of participants per class was 14 ± 4.0 (range, 6–23).

Participant attendance was available for 217 participants. Of 32 sessions offered, the mean ± SD number of sessions attended was 19 ± 9 (range, 1–32). Average attendance was 59%. The most common known reasons for missing class were medical appointments (39% of missed classes), travel (36%), family obligations (35%), and health reasons (33%). There were 86 (40%) completers and 131 (60%) noncompleters (n = 217). Noncompleters were more likely than completers to be married (p = .05) with an income of $50,000 or more (p = .02), obese (p = .005), and with lower physical (p = .03) and mental (p = .03) HRQOL.

There were 29 observations of instructors during class (Table 2). Compliance was good at the first visit and classes were mostly well-integrated and taught efficiently. Improvement was needed in the time spent on core movements, ensuring delivery of a 60-min class without breaks, and performing the appropriate number of forms. Twenty (80%) of the 25 rated items on the fidelity checklist met or exceeded our expected compliance rate of 75%.

Table 2

Instructor Compliance With Fidelity During 16-Week Intervention

n (% yes)Visit 1 (Weeks 1–6) (n = 15)Visit 2 (Weeks 13–16) (n = 14)
Appropriate amount of time spent on
 Preparatory exercises (5–10 min)11 (73.3)10 (71.4)
 Core movements (40–45 min)9 (60.0)6 (46.2) (n = 13)
 Closing exercises (5 min)15 (100.0)14 (100.0)
 Total class (60 min without breaks)10 (66.7)9 (64.3)
Appropriate number of sets performed for each form
 Visit 1 (2–4 sets)10 (90.9) (n = 11)N/AP
 Visit 2 (4–5 sets)N/AP9 (64.3)
Appropriate number of forms performed
 Visit 1 (≤4 forms)8 (53.3)N/AP
 Visit 2 (8 forms)N/AP10 (71.4)
Performed ≥2 mini therapeutic movements14 (93.3)14 (100.0)
Performed ≥1 practice variation14 (93.3)14 (100.0)
Teaching strategies
 Provided verbal instructions15 (100.0)N/AP
 Verbal instructions were clear14 (93.3)N/AP
 Demonstrated movements13 (86.7)N/AP
 Demonstrations were clear11 (84.6)N/AP
 Sometimes provided both verbal instructions and demonstrationsN/AP13 (92.9)
 Sometimes provided only demonstrationsN/AP10 (71.4)
 Sometimes provided only verbal instructionsN/AP8 (57.1)
 Sometimes provided no verbal instructions or demonstrationsN/AP7 (50.0)
Adhered to 11 core principles
 Toes gripping floor12 (80.0)11 (78.6)
 Swaying movements around ankles13 (86.7)13 (92.9)
 Initiate movements with a weight shift and trunk turn13 (86.7)11 (78.6)
 Movements driven by the trunk12 (80.0)12 (85.7)
 Lift toes when starting to move12 (80.0)12 (85.7)
 Progress from heel to toes when stepping12 (80.0)12 (85.7)
 Push-off with heel in extended leg12 (80.0)12 (85.7)
 Head movements follow direction of leading hand15 (100.0)12 (85.7)
 Natural breathing15 (100.0)10 (71.4)
 Vary speeds, ranges of motion, and changes in base of support10 (71.4) (n = 13)11 (78.6)
 Included exercises that elicited balance response7 (87.5) (n = 8)13 (92.9)
Well-integrated class (i.e., forms flow smoothly from 1 to the next)13 (86.7)11 (78.6)
Excellent teaching pace (i.e., efficient use of class time)14 (93.3)12 (85.7)
Compliance summary (number of items ≥75%/25 items)20 (80.0)16 (64.0)

Note. N/AP = not appropriate to assess this item at this time point.

At the second visit, compliance was low on the time spent on core movements and total class time, performing the proper number of sets, and on using some of the advanced teaching strategies. Sixteen (64%) of the 25 rated items on the fidelity checklist met or exceeded our expected compliance rate of 75%.

Two (0.9%) participants reported intervention-related injuries (n = 223). One participant “turned” her knee, another “overused” his hip and knee. Neither participant saw a health care provider and both continued in the class. One participant used medication for the injury. No injuries were considered adverse events per our IRB protocol.

Participant and partner satisfaction was high. The participant satisfaction survey was completed by 173 (73%) of the 237 participants. Eighty-seven percent of participants reported that they would take TJQMBB again (n = 170). Less than 2% of participants strongly felt that the exercises were “too hard” (n = 3 of 165, 1.8%) or “too easy” (n = 3 of 160, 1.9%). Eighty-six percent (n = 28) of partners “strongly agreed” that the partnership was worthwhile. Almost 90% reported they were “moderately” or “very involved” in the study. Seventy-one percent believed that the study presented more benefits than challenges.

Effectiveness

Data were collected between March 2014 and March 2015 on 237 participants at baseline, 175 at 16 weeks, and 163 at 32 weeks. There were significant improvements in mean falls efficacy (fear of falling) at 16 weeks that were maintained at 32 weeks (Table 3). There were significant short-term gains in depression and mental HRQOL at 16 weeks but the gains were not maintained at 32 weeks. Participants significantly improved their mobility (TUG) and balance (FSST) from baseline to 16 weeks, and then continued to improve through the 32-week follow-up. It took 32 weeks to observe significant improvements in lower extremity strength (FTSTS). There were no changes in physical HRQOL or gait speed at any of the time points.

Table 3

Continuous Outcome Measures at Baseline, 16 Weeks, and 32 Weeks (Adjusted)a

Mean ± SDBaseline (n = 237)16 weeks (n = 175)Baseline to 16 weeksb32 weeks (n = 163)16–32 weeksBaseline to 32 weeksbChange over timec (p)
Change [95% CI]pChange [95% CI]pChange [95% CI]p
Falls efficacy (10–100)d20.6 ± 21.713.8 ± 7.5−6.87 [−9.6, −4.1]<.00114.5 ± 8.60.8 [−2.1, 3.8].57−6.0 [−8.8, −3.2]<.001<.001
Depression (0–15)e2.1 ± 2.21.7 ± 1.9−0.26 [−0.5, −0.002].0492.0 ± 2.40.2 [−0.1, 0.5].14−0.05 [−0.31, 0.2].68.59
HRQOLf
 Physical42.6 ± 10.743.8 ± 10.40.54 [−0.6, 1.7].3543.5 ± 11.6−0.1 [−1.2, 1.2].9840.55 [−0.6, 1.7].35.35
 Mental52.1 ± 9.154.6 ± 7.51.51 [0.3, 2.7].0153.7 ± 8.7−0.9 [−2.1, 0.4].180.65 [−0.6, 1.9].29.22
Five-meter walk test (m/s)g1.2 ± 0.51.1 ± 0.3−0.01 [−0.05, 0.04].891.2 ± 0.30.05 [−0.01, 0.11].080.05 [−0.01, 0.1].08.05
TUG (s)h12.0 ± 5.411.0 ± 4.7−0.40 [−0.8, −0.1].039.7 ± 4.2−1.1 [−1.5, −0.7]<.001−1.5 [−1.9, −1.1]<.001<.001
FSST (s)i11.6 ± 4.210.3 ± 2.3−0.77 [−1.2, −0.3].00110.1 ± 2.6−0.6 [−1.2, −0.13].02−1.45 [−1.9, −0.94]<.001<.001
FTSTS (s)j15.5 ± 4.714.8 ± 4.7−0.55 [−1.2, 0.1].0913.5 ± 3.9−1.1 [−1.8, −0.4].004−1.64 [−2.3, −0.9]<.001<.001

Note. Boldface type indicates p < .05. HRQOL = health-related quality of life; TUG = timed up-and-go; FSST = four-square step test; FTSTS = five-times sit-to-stand; CI = confidence interval.

aModels adjusted for time (baseline, 16 weeks, and 32 weeks), site (northern vs. southern part of state), age at baseline, sex, and completer status (yes/no) (yes = attended at least 75% of the 32 exercise sessions offered). bChange from baseline, and p value, estimated from mixed model. Mean and SD are based on raw data. cThe p value is for time as a continuous variable from additional mixed models. dHigher score indicated lower falls efficacy (greater fear of falling). eHigher score indicated greater likelihood of depression. fScore greater than 50 indicated better physical or mental HRQOL compared to general U.S. population. gHigher score indicated faster gait speed. hLower score indicated better mobility. iLower score indicated better balance. jLower score indicated stronger lower extremity strength.

The proportion of participants with fear of falling significantly decreased from 6.6% at baseline to 0% at 16 and 32 weeks (Table 4). The proportion of participants meeting the aerobic physical activity guidelines significantly improved from baseline (31.6%) to 16 weeks (43.2%), and was maintained at 32 weeks (38.8%). It took until 32 weeks to observe statistically significant reductions in future fall risk based on gait speed (64% reduction in risk; odds ratio = 0.36; 95% confidence interval [CI] [−0.25, 0.97]); mobility (TUG; 63% reduction in risk; odds ratio = 0.37; 95% CI [−0.34, 1.01]); and lower extremity strength (FTSTS; 70% reduction in risk; odds ratio = 0.30; 95% CI [−0.25, 0.85]). There was no change in fall risk based on balance (FSST). There was no dose–response relationship between continuous outcomes and completer status (yes/no) except that completers were more likely to score higher on physical HRQOL across time than noncompleters (effect 3.55; 95% CI [0.82, 6.28]; p = .02). Of the 193 participants with falls data, 42 (21.8%) reported 56 falls during the 16-week intervention.

Table 4

Categorical Outcome Measures at Baseline, 16 Weeks, and 32 Weeks (Adjusted)a

n (%)Baseline (n = 237)16 weeks (n = 175)Change: Baseline to 16 weeks32 weeks (n = 163)Change: 16–32 weeksChange: Baseline to 32 weeksChange over timec (p)
Log ORb

OR

(SE)
pLog ORb

OR (SE)
pLog ORb

OR

(SE)
p
Falls efficacy > 70d15 (6.6)0 (0.0)N/APe<.0010 (0.0)N/APeN/APeN/APe<.001<.001
Aerobic physical activity (min/week)
 Inactive (0)65 (32.7)29 (18.7)0.21.00327 (17.8)−0.03.710.19.01.009
 Insufficiently active (1–149)71 (35.7)59 (38.1)1.2366 (43.4)0.971.21
 Meeting guidelines (≥150)63 (31.6)67 (43.2)(0.07)59 (38.8)(0.07)(0.07)
Five-meter walk test < 1.0 m/sf86 (37.4)42 (30.0)−0.43

0.65

(0.26)
.0922 (20.4)−0.60

0.54

(0.31)
.06−1.03

0.36

(0.31)
.001.007
TUG ≥ 12 sg74 (32.3)40 (28.4)−0.1

0.90

(0.29)
.8017 (5.7)−0.98

0.37

(0.35)
.01−1.0

0.37

(0.36)
.004.007
FSST > 15 sh20 (10.2)6 (4.9)−0.79

0.45

(0.50)
.124 (4.2)−0.3

0.74

(0.64)
.63−1.0

0.37

(0.59)
.07.04
FTSTS ≥ 12 si161 (80.1)104 (78.2)−0.10

0.90

(0.29)
.6354 (54.5)−1.10

0.33

(0.29)
<.001−1.20

0.30

(0.28)
<.001<.001

Note. Boldface type indicates p < .05. OR = odds ratio; TUG = timed up-and-go; FSST = four-square step test; FTSTS = five-times sit-to-stand.

aModels adjusted for time (baseline, 16 weeks, and 32 weeks), site (northern vs. southern part of state), age at baseline, sex, and completer status (yes/no) (yes = attended at least 75% of the 32 exercise sessions offered). bLog OR, OR (eLogOR), and SE. cThe p value is for time as a continuous variable from additional mixed models. dScore above 70 indicated fear of falling. eNot applicable because the OR is infinity (1/0), p-value is based on the exact binominal test. fGait speed below 1.0 m/s indicated person was at risk for one or more future falls. gScore greater than or equal to 12 s indicated person was at risk for one or more future falls. hScore above 15 s indicated person was at risk for multiple falls. iScore greater than or equal to 12 s indicated person was at risk for one or more future falls.

Maintenance

Seventy-two (41.6%) of 173 participants reported practicing TJQMBB on their own outside of class at 16 weeks. At 32 weeks, 59 (36%) of 162 participants reported practicing TJQMBB and 35 (22.0%) of 159 participants reported using the TJQMBB DVD.

The instructors decided whether to continue TJQMBB at the end of the intervention (16 weeks). Six (31.6%) of the 19 instructors continued six classes for four (22.2%) of the 18 adopting churches. At 32 weeks, seven (37%) of the 19 instructors continued six classes for five (28%) of the 18 adopting churches. The reasons instructors did not continue class were health-related issues (n = 4), unknown (n = 3), time commitment (n = 2), wanted more training (n = 1), wanted to offer private lessons (n = 1), and wanted to continue but participants did not at that time of year (n = 1). Instructors who continued TJQMBB held class only once per week.

Discussion

This study implemented the evidence-based TJQMBB program in rural WV churches. Study adoption and reach were high, population adoption and reach were lower, instructor adoption was good, fidelity was good to fair, there were no major injuries and no IRB-reportable adverse events, and participant and partner satisfaction were high. There were significant improvements in fear of falling, depression, mental HRQOL, physical activity, mobility, and balance; delayed improvement in lower extremity strength; and a reduction in future fall risk. We exceeded our expectations in all areas except for attendance, program completion, compliance at the second fidelity visit, and TJQMBB continuation. Compared with two other RE-AIM evaluations of TJQMBB (Table 5; Li et al., 2008, 2016), our study adoption and reach rates, improvements in participant outcomes (Li et al., 2005, 2008, 2016), and participant and partner satisfaction were comparable; attendance, program completion, and continuation rates were lower (Li et al., 2008, 2016).

Table 5

Comparison of Study Results With Prior TJQMBB RE-AIM Evaluations (Li et al., 2008, 2016)

RE-AIM dimensionsGoalCurrent studyPrior evaluation

(Li et al., 2008)
Prior evaluation

(Li et al., 2016)
Reach
 Study reach80%90%87%90%
EffectivenessSignificantly improved outcomesSignificantly improved
 Fear of fallingYesYesa (Li et al., 2005)Not reported
 DepressionYesNot reportedNot reported
 Physical HRQOLNoYesNot reported
 Mental HRQOLYesYesNot reported
 Physical activityYesNot reportedNot reported
 Gait speedNoYesaYesa
 MobilityYesYesYes
 BalanceYesYesaYesa
 Lower extremity strengthYesYesYes
Adoptionb
 Study adoption (sites)≥75%94%100%89%
 Instructors≥75%86%Not reportedNot reported
Implementation
 Attendance (mean)≥75%59%80%75% (median)
 Completion rate≥75%40%75%77%
 FidelityNot reportedWell maintainedc
  Visit 1≥75%80%Not applicableNot applicable
  Visit 2≥75%64%Not applicableNot applicable
 Adverse eventsNoneNoneNot reportedNone
 Participant satisfactionHighHighHighHigh
 Partner satisfactionHighHighHighNot reported
Maintenance
 Continuation of TJQMBBd
  Participants≥50%42% at 16 weeks, 36% at 32 weeks92%80%
  Churches≥50%22% at 16 weeks, 28% at 32 weeks83%55%
  Instructors≥50%32% at 16 weeks, 37% at 32 weeksNot reportedUnable to determinee

Note. HRQOL = health-related quality of life; TJQMBB = Tai Ji Quan: Moving for Better Balance.

aDifferent tests were used to measure the outcome than in the current study. bWe defined study adoption as the proportion of churches with trained instructors who started class, and the proportion of trained instructors who started class. The previous evaluation defined adoption as the percentage of sites approached that agreed to participate. cAll instructors delivered program per the protocol and annual participation rate of at least 75% was achieved. dMaintenance was measured at 16 and 32 weeks in current study and at 12 (sites) and 24 weeks (participants) in Li et al. (2008), and at 6 months after the 48-week intervention for sites and participants in Li et al. (2016). eInstructors continued teaching classes at 55% of the sites. The total number of instructors was not reported.

Churches are one of the few institutions found in every rural area and can serve a major role in facilitating the adoption of evidence-based health programs. The church is a central part of older, rural adults’ lives and religion has a positive effect on health outcomes, both factors that strengthen the role of churches in promoting health (Arcury et al., 2000; Chida et al., 2009; Cornwell et al., 2008; Coruh et al., 2005). Our study adoption rate was high (94%) and exceeded that in a study by Bopp et al. (Bopp et al., 2007), which reported church adoption rates of 80% (Year 1) and 52% (Year 2) in a physical activity intervention. Our population adoption rate was lower than the study rate because the population base was used as the denominator (i.e., all churches that we attempted to reach), which is a more accurate reflection of the potential public health impact of an intervention (Wilcox et al., 2018). Our population adoption rate (8.5%) was similar to a statewide initiative in South Carolina churches (11.7%; Hutto et al., 2021), but lower than their countywide initiative (42%; Wilcox et al., 2018), in the Faith, Activity, and Nutrition (FAN) study. We previously reported on the challenges in recruiting rural churches (e.g., limited staff/resources, competing priorities) yet, with additional time and travel funds, we were able to recruit the necessary number of churches (Jones et al., 2016).

Our instructor adoption rate was good (86%) and comparable with a study by Folta, Lichtenstein, et al. (2015) where 83% of trained leaders began an evidence-based intervention on heart disease risk factors through an Extension Service. Finding rural instructors was challenging (Jones et al., 2016). We preferred to train two or more instructors per church, as suggested by Bopp et al. (2007) but it was hard in some areas to find one, let alone two instructors.

Our study reach of 90% was high and most likely due to the study’s broad inclusion criteria. Our population reach (22.4%) was similar to the previously mentioned statewide initiative of FAN in South Carolina (20%; Hutto et al., 2021) but again lower than their countywide initiative (42%; Wilcox et al., 2018). Our population adoption and reach rates may have been lower than the FAN countywide study because they hired a well-known local person to recruit churches, and the county coalition they collaborated with had previously worked with churches (Wilcox et al., 2018).

Participants were representative of adults in their respective counties with regard to race and ethnicity (U.S. Census Bureau, 2019). The participants were more educated and had a higher proportion of females than other adults in their counties (U.S. Census Bureau, 2019). In addition, participants had higher rates of obesity, similar rates of diabetes mellitus and arthritis, and lower rates of cancer than other older adults in WV (West Virginia Department of Health and Human Resources, 2020). For the most part, our participants appeared representative of other older adults at the county and state level. Overall, our study reached older adults with high fall risk in need of fall prevention interventions as evidenced by their older age, female sex, and high prevalence of other fall risk factors including chronic medical conditions, previous falls, polypharmacy, and urinary incontinence.

Participant retention is difficult in fall prevention programs (Ory et al., 2015). Our attendance and completion rates were lower than expected, but comparable with a 12-week dissemination study of TJQMBB in three states (Ory et al., 2015). It appeared that “life got in the way” in our study and participants missed sessions due to health, family, and travel. These reasons were similar to those encountered in other fall prevention programs, including those with group exercise (Child et al., 2012). Although attendance was low, satisfaction with the program was high. It is possible that participants liked the program but missed sessions due to these “life” issues and exercise became less of a priority. Furthermore, this type of exercise was new for almost all participants. Participants may also have considered the 16-week intervention as too long. Interventions of 20 weeks or longer have been associated with lower adherence (McPhate et al., 2013). Attendance was most likely not related to the difficulty level of the program as only a few participants felt the exercises were too easy or too hard.

Our completion rate was lower than expected. In one community-based TJQ study (Shah et al., 2015), better physical and mental health predicted adherence, which was consistent with our study where noncompleters had lower physical and mental HRQOL than completers. Noncompleters were also more obese which has been associated with lower exercise adherence (Picorelli et al., 2014).

Despite lower than expected attendance and completion rates, participants still experienced significant improvements in outcomes. Participants in the Ory et al. (2015) study, with a low (50%) completion rate, also significantly improved their mobility and self-rated health. The lack of a dose–response relationship in our study in all but one of the outcomes indicated that participants improved even if they attended fewer than 75% of the classes.

Instructor fidelity was good during the first observation but fair during the second observation. All instructors were new to TJQ. As the program progressed, so did the difficulty of the exercises. Instructors had to perform more complex movements and incorporate advanced teaching strategies concurrently. Practicing advanced movements takes time, especially for novice instructors. The developer recommended a refresher training 1 month after the initial training but the study budget and timeline did not allow for this extra training. Thus, undergoing standardized instructor training may not have been enough for novice instructors to implement the advanced TJQMBB exercises as intended. Programs planning classes may wish to budget for refresher trainings and observational visits to enhance fidelity.

Participants demonstrated improvements in most outcome measures, and gains in falls efficacy, physical activity, mobility, and balance were maintained or improved at 32 weeks. Improvements in mental HRQOL and depression were short-term. Perhaps the gains in mental health were not evident at 32 weeks because there was a loss of socialization, when the intervention ended at 16 weeks, which may have been a secondary benefit of the program. There was also no change in mean gait speed even though TJQMBB studies have consistently demonstrated improvements in walking speed with the 50-foot walk test (Li et al., 2003, 2005, 2008, 2014). The lack of improvement may have been because participants’ mean gait speed at baseline was already in the normal range and there was little room for improvement (Bohannon, 1997; Fritz & Lusardi, 2009).

There was a delayed improvement in lower extremity strength that was not apparent until 16 weeks after the intervention ended (at 32 weeks). Previous TJQMBB studies demonstrated gains in lower extremity strength at 24 weeks using the FTSTS test; however, those interventions were longer (between 24 and 48 weeks; Li et al., 2013, 2016). Perhaps, 16 weeks was too early to expect changes in strength given that our mean baseline FTSTS scores were lower than in other TJQMBB studies (Li et al., 2013, 2016), and lower than age-specific normative data (Bohannon, 2006). Instructor fidelity was also lower for the advanced movements in the later part of the program and thus, the intensity of those exercises may not have been high enough to improve strength.

Continuation of TJQMBB in participants, churches, and instructors was lower than expected. We did not distribute the program DVD to participants until the end of the study as we did not want it to be a substitute for attending class. Distributing the DVD at the end of the intervention may have been too late for participants to transition to and stay motivated with this form of exercise instruction. There is evidence; however, that participants continued to engage in some form of physical activity including that their mobility and balance scores continued to improve after the intervention ended, and that improvements in the proportion of participants meeting the aerobic activity guidelines were maintained between 16 and 32 weeks.

Continuing TJQMBB was challenging for the churches and instructors. In the FAN study, implementation was greater when churches had active leader involvement, at least one physical activity champion, and were open to new ideas (Wilcox et al., 2021). We struggled with securing clergy support which is necessary in faith-based partnerships (Hippolyte et al., 2013; Jones et al., 2016). Perhaps, continuation of TJQMBB would have been greater if buy-in from clergy had been bigger at the beginning of the study. Once clergy approved the program, the instructors became the representatives for the church.

In our study, churches lacked the infrastructure, staff/volunteers, and resources (i.e., instructor compensation) to offer continued programming. In addition, some churches told us that they had greater priorities in their communities, including increased rates of unemployment, substance abuse, and crime. Continuation of classes mostly depended on whether instructors had time to do so. The fact that all instructors who continued TJQMBB did so only once per week, which was inconsistent with the TJQMBB evidence (Li et al., 2005), indicated that time may have been an issue, as it has been in other studies (Folta, Seguin, et al., 2015). Another obstacle was a lack of funding to compensate instructors. Instructors could charge a small fee for classes; however, many felt that this would unduly burden their participants. Perhaps overrecruiting instructors (more than two per site; Bopp et al., 2007; Jones et al., 2016), identifying a local champion, and offering programs in churches with denominations that have state-level organizations with greater resources may be several ways to overcome these barriers.

There were several strengths to this study, primarily, that we were able to intervene in hard-to-reach, medically underserved, rural older adults. Furthermore, the evaluation addressed more than just effectiveness. In particular, we included an objective assessment of fidelity which is only measured 9% of the time in church-based health interventions (Yeary et al., 2012).

There were three limitations to this study. First, the study did not include a control group and was not powered to detect a reduction in falls because the focus was on implementation in a new setting and not on efficacy. Second, certain data were not available for our adoption and reach analyses. Data were not available on churches that did not adopt TQMBB, or the people who did not enroll in the study at the adopting churches. We had data on the proportion of worshippers over age 65 at the adopting churches, but not on those over age 55, and therefore, our population reach rate may be slightly overestimated. There was also a lack of county and state data for comparisons specifically in older adults. Finally, it was beyond the scope and funding of our research grant to collect cost data to implement the TJQMBB program; however, the positive net benefit and return on investment of TJQMBB has been reported (Carande-Kulis et al., 2015).

This study used a population-based approach to primary fall prevention by implementing an evidence-based intervention in a new setting. The TJQMBB program was well-received and participants had significant improvements in outcomes and reductions in risk for future falls. This intervention reached a representative sample of older adults in need of fall prevention programming. Future studies should continue to broaden the reach of TJQMBB by investigating the implementation process in other diverse settings, and examining alternative delivery modes for the program (e.g., virtual delivery).

Acknowledgments

This work was supported by grant number: 1R49CE002109 from the Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, to the West Virginia University Injury Control Research Center. The contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention. ClinicalTrials.gov Registration: NCT01961037.

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