Lower extremity injuries are common among the physically active population and account for more than 50% of collegiate and recreational athletes' injuries.1–3 Individuals who sustain these injuries may develop long-term consequences such as functional impairments, decreased health-related quality of life, and osteoarthritis.4,5 Exercise-related injury prevention programs (ERIPPs) have been developed to prevent these injuries from occurring. Several studies have found ERIPPs to be effective for reducing lower extremity injuries.6,7 However, one of the major limitations of ERIPP effectiveness is participant compliance to complete the prescribed exercises.8
It is unclear why ERIPP compliance is low within physically active populations. One possible reason why compliance issues are not fully understood is the lack of theoretical models in research related to ERIPP participation. A systematic review revealed that only 11% of research studies related to ERIPP participation included theoretical models.9 However, theoretical models have been used to better understand participation in other preventative health behaviors such as mammography screenings, vaccine uptake, and bicycle helmet use.10–12 Applying theoretical models such as the Health Belief Model (HBM) and Theory of Planned Behavior (TPB) may aid in elucidating why compliance of ERIPP participation is low from the end-user's perspective. The HBM and TPB have been used to predict participation in other preventative health behaviors.11,12 Using these theoretical models within the scale development for new survey instruments to examine the behavioral determinants of ERIPP participation may provide insight into the underlying reasons for the historically low compliance with these programs.
The HBM contains six constructs thought to directly predict participation in a preventative health behavior.13 The first construct of perceived susceptibility is the individual's beliefs regarding the perceived risk for sustaining a lower extremity injury. The second construct is perceived severity or the individual's beliefs regarding the potential consequences of sustaining a lower extremity injury. The third construct is perceived benefits, which describes the individual's perceptions of the benefits from participating in an ERIPP. The fourth construct is perceived barriers, which is defined as the perceived obstacles that may prevent an individual from participating in an ERIPP. The fifth construct is cues to action or reminders for the individual to participate in an ERIPP. The final construct is self-efficacy, which describes the individual's beliefs about his or her ability to participate in an ERIPP. The amalgamation of these constructs is thought to provide an indication of participation in a preventative health behavior.
The TPB contains three constructs that are thought to indirectly predict participation in a preventative health behavior through intention to participate.14 The first construct is attitude, which is defined as the individual's overall evaluation of the preventative health behavior. The second construct is subjective norm, which is the individual's beliefs about what other important individuals in his or her life would think about the preventative health behavior. The final construct is perceived behavioral control, which is the individual's beliefs about his or her ability to participate in the preventative health behavior despite any barriers he or she may face. The three constructs are thought to predict participation in a preventative health behavior through intention to participate.
Although there are several parallels and differences between the theoretical constructs of the HBM and TPB, both theories have demonstrated usefulness in defining the behavioral determinants regarding participation in various health behaviors in an array of populations.10–12 Therefore, the TPB and HBM may provide insight into the reasons for low compliance associated with ERIPPs in physically active populations. Information gained on the behavioral determinants of ERIPP participation through the use of scales may be used to tailor a specific intervention to improve adoption and use of ERIPPs. The clinician could use a scale to assess the behavioral determinants that were most associated with the intention to participate in an ERIPP. Based on this information, clinicians could create interventions that target specific behavioral determinants. For example, White et al.15 found that subjective norms and attitudes were most associated with the intention to participate in an ERIPP among female netball players. This information could be used to develop educational interventions that would be delivered to participants in conjunction with the ERIPP. For this situation, attitudes could be addressed by promoting the ERIPP as a sport-relevant activity with benefits associated with reduced injury risk and performance enhancement. Additionally, educational interventions could be created to address the attitudes of individuals (eg, parents and coaches) who may have an influence in the athlete's decision to participate in an ERIPP. It is possible that assessing the behavioral determinants of ERIPP participation using scales first and creating a promotion and implementation plan second may lead to improvements in adoption and compliance rates. However, there are no current scales directly created using the HBM and TPB to measure behavioral determinants of ERIPP participation.
The purposes of this study were to design and pilot test the HBM Scale (HBMS) and TPB Scale (TPBS) associated with ERIPP participation and examine the validity of the scales. We hypothesized the HBMS and TPBS would have adequate internal consistencies. Behavioral determinants of ERIPP participation evaluated through the HBMS and TPBS would be significantly correlated to physical and mental function measured using the modified Disablement of the Physically Active Scale (mDPA) and exercise-self efficacy measured through the Exercise Self-Efficacy Scale (ESES). Additionally, anxiety and depression related to health measured through the Hospital Anxiety and Depression Scale (HADS) would be significantly correlated to the subscales of the HBMS and TPBS. These correlations would aid in establishing validity for the HBMS and TPBS.
The design of this study was a single cross-sectional survey. The scales were developed using the HBM and TPB to better understand perceptions of ERIPPs. Additional previously validated scales (mDPA,16 HADS,17 and ESES18) were used to establish validity for the HBMS and TPBS. All scales were administered electronically using Qualtrics (LLC, Provo, UT).
Forty-nine physically active adults volunteered to participate in this study (15 male and 34 female; age: 22.33 ± 3.04 years; height: 64.97 ± 9.51 cm; mass: 156.29 ± 27.90 kg). All participants were moderately or vigorously physically active for a minimum of 90 minutes per week. The classification of physically active was confirmed with a question regarding the level of participation in physical activity within the demographic questionnaire. Participants were also asked to categorize their level of physical activity and the sample included collegiate athletes (n = 5), recreational athletes (n = 17), individuals who exercise for fitness (n = 24), and other (n = 3).
Participants were recruited by flyers and word of mouth at a large public university during the fall semester of the 2016–2017 academic year. Researchers also attended classes in the exercise science and physical therapy departments to recruit participants. Potential participants e-mailed the primary investigator (EHG) if they had an interest in participating in the survey. A link to access the surveys was then e-mailed to the potential participant. The study was approved by the institutional review board and informed consent was granted by following the survey link and answering “yes” to proceed with the survey. Once the survey was initiated, participants completed a demographic questionnaire and the HBMS, TPBS, mDPA,16 HADS,17 and ESES.18
HBMS. Champion's HBMS was originally developed to predict participation in mammography or breast cancer screenings.10 The scale was adapted to accommodate several languages and used to predict participation in other preventative health behaviors.19–22 For the purposes of this study, the items within the scale were transformed to address participation in an ERIPP. For example, one of the susceptibility questions included in the scale, “It is extremely likely that I will get breast cancer,”10 was changed to “It is likely I will sustain a lower extremity injury.” The remainder of the scale was transformed to make the scale pertinent to lower extremity injury prevention. The response choices for the participants were on a 5-point Likert scale ranging from strongly agree (2) to strongly disagree (−2). There were a total of 41 items in the HBMS across six different subscales. The total score ranges for each subscale vary because they depend on the number of statements within each subscale. Scores are interpreted as falling within either the positive, neutral, or negative range. Table 1 shows the number of statements within each subscale. Responses were totaled for each subscale for analyses.
Internal Consistencies of Statements Within the HBMS and TPBS
TPBS. Questionnaires regarding the TPB are constructed using the procedures outlined by Ajzen.23 The direct measure items for the constructs of the TPB and intention to participate were developed using the structure provided in the instructions on how to develop a TPB scale. An example question constructed to evaluate attitude was, “My participation in an injury prevention program would be beneficial.” There were 22 items in the direct measures portion of the scale. The breakdown of numbers of statements within each subscale is in Table 1. Responses to the statements were on a 5-point Likert scale ranging from strongly agree (2) to strongly disagree (−2). The total score ranges for each subscale vary depending on the number of statements within each subscale. Scores are interpreted as falling within either the positive, neutral, or negative range. To ensure that all aspects related to attitudes, perceived behavioral control, perceived subjective norms, and intention to participate in an ERIPP were assessed, nine open-ended salient beliefs questions were added to the initial scale (Table 2). Individuals were given space to type in their response to each salient belief question. The responses were then coded by three researchers who were athletic trainers with previous experience performing qualitative analysis. One of the coders was involved in the initial scale development but the other two were not. Initially, 10 randomly selected responses were assigned to each coder and the coders created a code book independently. Then the coders met to confirm the code book and the remaining responses were randomly assigned to the coders. Frequency counts of each code book response were calculated. In cases where more than 25% of the participants provided the same response, the response was transformed into a statement to add into the future TPBS. In some cases, the statement was the same as an existing scale item and a new item was not added.
Salient Beliefs Questions from the Theory of Planned Behavior Scale
mDPA. The DPA is a generic patient-reported outcome measure assessing quality of life in respect to physical activity. The mDPA was established using two subscales providing a physical summary component (DPA-PSC) and a mental summary component (DPA-MSC).16 The DPA-PSC contains 12 statements and the DPA-MSC contains 4 statements. Participants respond to each statement with a descriptor ranging from no problem (0) to severe (4). The responses for each component are added to create a physical summary component score and mental summary component score. The scores for the physical summary component range from 0 to 48. Higher scores are associated with increased functional impairments associated with participation in physical activity. The scores for the mental summary component range from 0 to 16, with higher scores being associated with increased mental impairments associated with participating in a physical activity. The mDPA has excellent internal consistencies within the two subscales, ranging from 0.8 to 0.94.16 Additionally, construct validity was established by the mDPA scores being strongly correlated to the original DPA.16 The mDPA was used in this study to determine whether physical and mental function would influence behavioral determinants of ERIPP participation measured through the HBMS and TPBS.
HADS. The HADS is used to measure anxiety and depression related to health. The two components of this scale are anxiety and depression.17 The anxiety and depression subscale each contain seven statements. The participant responds according to a scale provided, which ranges from 0 to 3. The total score for each subscale is derived from adding the responses for each statement within the subscale. A score ranging from 0 to 7 is defined as normal, 8 to 10 is borderline abnormal, and 11 to 21 is abnormal. The psychometric properties of the HADS have been established previously. The HADS-Anxiety had an internal consistency of 0.89 and the HADS-Depression had an internal consistency of 0.86.24 The HADS was used in this study to determine whether anxiety and depression related to health may influence the behavioral determinants of ERIPP participation.
ESES. The ESES was used to measure an individual's beliefs about his or her ability to participate in physical activity.18 The ESES contains 10 statements relating to confidence in participating in exercise or physical activity. Participants rate their confidence in participating in physical activity by responding to statements on a scale ranging from not true at all (1) to exactly true (4). Responses for each item are added to create a total score for the scale. Total scores range from 10 to 40. Higher scores are associated with having a greater confidence in participating in physical activity, whereas lower scores are associated with decreased confidence in participating in physical activity. The internal consistencies were excellent and ranged from 0.87 to 0.93.18 Construct validity was established by the correlation between scores on the ESES and Generalized Self-Efficacy Scale.18 The ESES was used in this study to determine whether self-efficacy related to physical activity influenced behavioral determinants of ERIPP participation.
Means and standard deviations were calculated for the subscales of the HBMS and TPBS, DPA-PSC, DPA-MSC, HADS-Anxiety, HADS-Depression, and ESES. The internal consistencies for each construct of the HBMS and TPBS were calculated using Cronbach's alpha (SPSS version 22, SPSS, Inc., Chicago, IL) and used to determine whether items should be removed from the scales. If the internal consistency (Cronbach's alpha) improved by more than 0.05 by removal of a statement, then the statement was removed.
Validity was assessed through a series of analyses involving the total scores from the individual subscales of the HBMS (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy) and TPBS (attitudes, perceived subjective norms, perceived behavioral control, and intention), total scale scores from the DPA-PSC, DPA-MSC, HADS-Anxiety, HADS-Depression, and ESES, and the total score from the questions examining intention to participate in the TPBS. First, preliminary construct validity of the HBMS and TPBS subscales were examined through correlational analyses with the DPA-PSC, DPA-MSC, HADS-Anxiety, HADS-Depression, and ESES. Second, a series of correlational analyses between the HBMS and TPBS subscales were executed to examine redundancy between the scales. Finally, the correlations between each HBMS and TPBS subscale and intention to participate were examined to determine how the subscales were associated with intention to participate in an ERIPP. Spearman correlations were used for all correlation analyses. Alpha was set at a P value of .05 or less for all correlational analyses.
The means and standard deviations for total scores of all subscales are listed in Table 3. Statements within the perceived benefits of the HBMS (1 item), perceived barriers of the HBMS (1 item), perceived subjective norms of the TPBS (1 item), and intention of the TPBS (1 item) were removed to improve internal consistency. The original and final internal consistencies of each subscale can be found in Table 1. All other internal consistencies of the items within the subscales did not improve when an item was removed; therefore all other statements were retained. The final internal consistencies ranged from 0.60 to 0.90. The HBMS susceptibility, HBMS benefits, HBMS barriers, HBMS cues to action, HBMS self-efficacy, TPBS perceived subjective norm, and TPBS perceived behavioral control had adequate internal consistency. However, the HBMS perceived severity, TPBS attitudes, and TPBS intention had inadequate internal consistencies. The final version of the HBMS (39 items) can be found in Table 4. Two items were identified during the coding process due to the high frequency of responses from the salient beliefs questions to be added to the future TPBS. One statement was created regarding a perceived benefit of participating in an ERIPP: “My participating in an injury prevention program would improve my knowledge of lower extremity injuries and injury prevention programs.” Additionally, a statement was created regarding a perceived barrier of participating in an ERIPP: “My participating in an injury prevention program would be dependent on the location of the program.” The final version of the TPBS (22 items) is listed in Table 5.
Total Scores for Subscales
Final Health Belief Model Scale
Final Theory of Planned Behavior Scale
The DPA-PSC was positively and significantly correlated with HBMS benefits (r = 0.47, P = .001), TPBS subjective norms (r = 0.36, P = .01), and intention to participate (r = 0.44, P = .002). Additionally, the DPA-PSC was significantly and negatively correlated with HBMS barriers (r = −0.30, P = .04). The ESES was positively and significantly correlated with the HBMS cues to action (r = 0.47, P = .001), and TPBS attitudes (r = 0.32, P = .03). However, the DPA-MSC, HADS-Anxiety, and HADS-Depression were not significantly correlated with any of the subscales of the HBMS or TPBS (P > .05). The correlation coefficients between the HBMS and TPBS subscales and the DPA-PSC, DPA-MSC, HADS-Depression, HADS-Anxiety, and ESES are listed in Table 6.
Correlations Between Health Belief Model Scale and Theory of Planned Behavior Scale Subscales and DPAS, HADS, and ESES
The HBMS perceived susceptibility and perceived severity subscales were not significantly correlated with any of the subscales of the TPBS. All other subscales were correlated with at least one other subscale. The correlations between the HBMS and TPBS subscales are listed in Table 7.
Correlations Between the HBMS and TPBS Subscales
The HBMS subscales including benefits, self-efficacy, and cues to action and the TPBS subscales including attitudes, subjective norms, and perceived behavioral control were positively and significantly correlated with intention to participate in an ERIPP (r = 0.29 to 0.59). The HBMS barriers was negatively and significantly correlated with intention to participate (r = −0.41).
The primary finding of this preliminary study was that the HBMS and TPBS are viable instruments to assess behavioral determinants of intention to participate in an ERIPP. The internal consistencies of the items within each HBMS and TPBS subscale ranged from 0.60 to 0.90. The internal consistencies within the HBMS severity, TPBS attitudes, and TPBS intention need to be improved. Additionally, participants identified two areas within the salient beliefs questions including a perceived benefit of improving knowledge and a perceived barrier of the location of the ERIPP that were added to the final instrument. The internal consistency of the subscales these statements were added to be investigated further. Interestingly, significant inter-subscale correlations were identified across nearly all HBMS and TPBS subscales; however, none involved the HBMS perceived susceptibility and perceived severity subscales. The DPA-PSC was the only additional scale that was significantly positively correlated with a subscale from the HBMS, TPBS, and intention to participate in an ERIPP. Future studies should continue to investigate the relationship between the DPA-PSC and HBMS and TPBS.
Although most of the subscales had adequate internal consistencies, a few subscales within the HBMS and TPBS did not. The HBMS severity, TPBS attitudes, and TPBS intention to participate internal consistencies fell below 0.70. It is possible that expanding the number of participants and the breadth of response range via broader samples of active individuals within the study will improve the internal consistencies. The internal consistency of the subscales is important because the measure ensures that the statements of the subscale are assessing the construct they are associated with. To use the HBMS and TPBS effectively, it is important that all subscales have adequate internal consistency.
Most of the subscales of the HBMS correlated to those of the TPBS, but others did not. Perceived susceptibility and severity from the HBMS did not significantly correlate with any of the subscales within the TPBS. This lack of correlation may indicate that these subscales of the HBMS bring a unique perspective outside of the subscales of the TPBS. Additionally, these results may indicate that the population in this study requires further education regarding this aspect. Furthermore, many of the significant relationships between the HBMS and TPBS subscales were of moderate strength (r = 0.3 to 0.75). This indicates that there is some explained variance across subscales; however, the strength of these correlations does not suggest there is excessive redundancy. Therefore, using both the HBMS and TPBS to assess behavioral determinants of ERIPP participation is warranted.
The DPA-PSC was the only additional scale to correlate to a subscale of the HBMS, TPBS, and intention to participate in an ERIPP. This indicates that physical function may influence the subscales of the HBMS and TPBS, which would also influence intention to participate. Therefore, an individual with a history of a lower extremity injury who is still experiencing some physical limitations may have different behavioral determinants of ERIPP participation than an individual without any physical limitations. There is a possibility that intervention strategies may need to be tailored to individuals with different levels of physical limitations. Interestingly, the ESES was significantly correlated with HBMS cues to action and TPBS attitudes, but none of the other subscales. It is possible that participating in exercise and being confident in that ability influences the different cues that remind an individual to participate in an ERIPP. Participating in physical activity on a regular basis may in itself be a cue to remind an individual that preventing injuries and participating in an ERIPP are important. Individuals who are confident in their ability to participate in physical activity may have better attitudes regarding participation in ERIPPs when compared to those who are not confident in participating in physical activity. Although there was a correlation between confidence in participating in physical activity and two of the subscales, there was no correlation with intention to participate. Additionally, these results indicate that depression, anxiety, and exercise related to self-efficacy may not influence an individual's intention to participate in an ERIPP. The DPA-PSC correlated with the most subscales from the HBMS and TPBS, whereas the DPAMSC, HADS-Depression, and HADS-Anxiety did not correlate with any of the subscales from the HBMS or TPBS. There is a possibility that the more mental aspects associated with the DPA-MSC, HADS-Anxiety, and HADS-Depression do not inform the behavioral determinants of ERIPP participation, whereas the physical function aspect plays a much larger role.
Previous literature has investigated the behavioral determinants of ERIPP participation within physically active individuals.25,26 The scales used to evaluate the behavioral determinants have been guided by theoretical models. Using theory to inform the development of the scales used to assess behavioral determinants of ERIPP participation may give clinicians a more robust depiction of how to maximize compliance by understanding their perceptions of this health behavior, especially if future interventions are also based on these theories. A previous study investigated the use of a homogenous educational interventions to improve both attitudes toward ERIPP participation and compliance with the programs.27 The educational interventions used in this study was not able to significantly improve attitudes toward ERIPP participation or compliance rates. It is possible that using the HBMS and TPBS developed in this study to first assess the behavioral determinants of ERIPP participation and then inform the development of educational interventions could lead to improved adoption and compliance. The subscales that were correlated the most to intention to participate could be targeted using an intervention.
To increase compliance, the scales must be used to inform implementation strategies. For example, Martinez et al.26 determined the most important behavioral determinant of ERIPP participation for female high school athletes was the potential to reduce the risk factors associated with injury. Therefore, the perceived benefits of the ERIPP were most important to the users in this instance. Clinicians could use this information to develop an educational intervention including the benefits of the ERIPP and specifically highlight the potential to reduce the risk for lower extremity musculoskeletal injuries. The educational information could be delivered to the users prior to participating in the ERIPP to facilitate adoption of and compliance with the program. Several informational reminders could be distributed periodically over time to gain continued compliance. The implementation strategies that can be used to leverage ERIPP adoption and compliance will likely differ for various groups of users based on their perceptions and attitudes toward ERIPPs. Therefore, creating scales to assess the behavioral determinants of ERIPP participation is vitally important to developing an implementation strategy.
This study focused on the preliminary development of the HBMS and TPBS. As a result of the preliminary nature of this research, there were several limitations associated with this study that will be addressed through further development of the HBMS and TPBS prior to integration into clinical practice. First, the number of participants included in this study was limited, which allowed us to perform preliminary scale development but did not allow for the evaluation of factor structure. Further research should evaluate the use of the scales within a larger population and the scales should be subjected to more advanced statistical procedures to confirm factor structure and identify clinically meaningful cut-scores. The number of participants within each physical activity group in this study did not permit a comparison across subgroups of physically active adults. Future studies should compare behavioral determinants of ERIPP participation across different levels of physical activity participation. If behavioral determinants of ERIPP participation differ among groups, there is a possibility that interventions may need to be tailored for individuals within different physical activity groups. To determine whether interventions employed to improve behavioral determinants of ERIPP participation are effective, minimal detectable change and clinically meaningful change for the HBMS and TPBS must be evaluated. Therefore, several aspects of the psychometric properties and the use of these instruments require additional investigation.
Implications for Clinical Practice
The initial development of the HBMS and TPBS indicates they may be promising instruments to assess the behavioral determinants of ERIPP participation within the physically active population. The preliminary information gained from these scales may provide more insight into adoption and compliance challenges for implementing ERIPPs in clinical settings. Additionally, the information gained from the scales may be used to inform interventions to improve compliance of ERIPPs. These scales may aid clinicians in gaining a better picture of the attitudes and perceptions of the intended user of an ERIPP and developing effective interventions based on the information gained.
- Frost AM, Dompier TP, Langel JA, Klatt TH. Descriptive epidemiology of injuries and illnesses at a university wellness and recreation center: 1987–2006. Paper presented at: Research in the Capitol. ; 2007. ; Des Moines, IA. .
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Internal Consistencies of Statements Within the HBMS and TPBS
|Subscale||Initial Number of Statements||Initial Internal Consistency||Final Number of Statements||Final Internal Consistency|
|HBMS Cues to Action||9||0.70||9||0.70|
|TPBS Perceived Subjective Norm||6||0.83||5||0.90|
|TPBS Perceived Behavioral Control||5||0.72||5||0.72|
Salient Beliefs Questions from the Theory of Planned Behavior Scale
What do you see as the advantages of participating in an injury prevention program?
What do you see as the disadvantages of participating in an injury prevention program?
What else comes to mind when you think about participating in an injury prevention program?
List the individuals or groups who would approve or think you should participate in an injury prevention program.
List the individuals who would disapprove or think you should not participate in an injury prevention program.
List the individuals who are most likely to participate in an injury prevention program.
List the individuals who are least likely to participate in an injury prevention program.
List any factors or circumstances that would make it easy to participate in an injury prevention program.
List any factors that would make it difficult or prevent you from participating in an injury prevention program.
Total Scores for Subscales
|Subscale||Mean ± SD|
|HBMS Susceptibility||−1.18 ± 4.96|
|HBMS Severity||−3.39 ± 5.06|
|HBMS Benefits||4.86 ± 3.00|
|HBMS Barriers||−3.67 ± 3.99|
|HBMS Cues to Action||7.96 ± 4.91|
|HBMS Self-Efficacy||5.31 ± 5.83|
|TPBS Attitudes||4.33 ± 3.01|
|TPBS Perceived Subjective Norm||6.79 ± 3.11|
|TPBS Perceived Behavioral Control||7.26 ± 2.28|
|TPBS Intention||4.40 ± 2.24|
|DPA-PSC||11.10 ± 10.52|
|DPA-MSC||4.50 ± 4.16|
|HADS-Anxiety||7.85 ± 3.34|
|HADS-Depression||3.26 ± 2.53|
|ESES||33.91 ± 4.21|
Final Health Belief Model Scale
| It is extremely likely I will sustain a lower extremity injury.|
| I feel I will get a lower extremity injury in the future.|
| There is a good possibility I will get a lower extremity injury within the next 10 years.|
| My chances of sustaining a lower extremity injury are great.|
| I am more likely than other athletes to get a lower extremity injury.|
| The thought of a lower extremity injury scares me.|
| When I think about lower extremity injuries, my heart beats faster.|
| I am afraid to think about lower extremity injuries.|
| Problems I would experience as a result of a lower extremity injury would last a long time.|
| A lower extremity injury would threaten a relationship with my boyfriend/girlfriend, teammates, or parents.|
| A lower extremity injury would affect my academic performance.|
| If I had a lower extremity injury, my whole life would change.|
| If I sustained a lower extremity injury, I would suffer consequences from it for up to 5 years.|
| When I do injury prevention programs I feel good about myself.|
| Participation in an injury prevention program will improve my athletic performance.|
| Completing an injury prevention program will decrease my risk of lower extremity injury.|
| If I complete an injury prevention program during the next year, I will decrease my chances of sustaining a lower extremity injury.|
| If I complete an injury prevention program regularly, I will decrease my chances of requiring surgery if a lower extremity injury does occur.|
| I feel funny doing injury prevention programs.|
| Participating in an injury prevention program will be embarrassing to me.|
| Participating in an injury prevention program will take too much time.|
| Participating in an injury prevention program will be unpleasant or painful.|
| I don't have the equipment to do an injury prevention program.|
|Cues to Action|
| I want to discover health problems early.|
| Maintaining good health is extremely important to me.|
| I search for new information to improve my health.|
| I feel it is important to carry out activities which will improve my health.|
| I eat well balanced meals.|
| I have regular health check-ups even if I am not sick.|
| I seek out ways to prevent illnesses and/or injuries.|
| My coach has recommended participating in an injury prevention program.|
| A health care professional (physician, athletic trainer, physical therapist) has recommended I participate in an injury prevention program.|
| I know how to perform an injury prevention program.|
| I am confident I can perform an injury prevention program correctly.|
| I have performed an injury prevention program.|
| I would feel confident in performing an injury prevention program if given educational materials on the program.|
| I would feel confident in performing an injury prevention program if it was led by my coach.|
| I would feel confident in performing an injury prevention program if it was led by an athletic trainer.|
| I would feel confident in performing an injury prevention program if it was led by a strength and conditioning coach.|
Final Theory of Planned Behavior Scale
| My participating in an injury prevention program would be beneficial.|
| My participating in an injury prevention program would be pleasant.|
| My participating in an injury prevention program would decrease my chances of having a lower extremity injury.|
| My participating in an injury prevention program would improve my athletic performance.|
| My participating in an injury prevention program would improve my knowledge of lower extremity injuries and injury prevention programs.|
| My participating in an injury prevention program would take too much time.|
| My participating in an injury prevention program would cost too much.|
| My participating in an injury prevention program would be dependent on the location of the program.|
|Perceived Subjective Norms|
| Most people who are important to me approve of me participating in an injury prevention program.|
| My health care providers (doctor/athletic trainer/physical therapist) would approve of my participation in an injury prevention program.|
| My coach/strength coach would approve of my participation in an injury prevention program.|
| My parents would approve of my participation in an injury prevention program.|
| My teammates/friends would approve of my participation in an injury prevention program.|
|Perceived Behavioral Control|
| I am confident that I can participate in an injury prevention program.|
| My participation in an injury prevention program is up to me.|
| If my entire team was participating in an injury prevention program, I would be more likely to participate.|
| If there were evidence injury prevention programs improved athletic performance, I would be more likely to participate.|
| If I had access to an injury prevention program, I would be more likely to participate.|
| I intend to participate in an injury prevention program.|
| If my team was participating in an injury prevention program, I would participate, too.|
| If I was given an injury prevention program to perform at home, I would participate.|
| If a health care provider led an injury prevention program session, I would attend.|
Correlations Between Health Belief Model Scale and Theory of Planned Behavior Scale Subscales and DPAS, HADS, and ESES
|Subscale||DPA Physical||DPA Mental||HADS-Anxiety||HADS-Depression||ESES|
|HBMS Cues to Action||0.113||−0.058||−0.029||−0.164||0.471a|
|TPBS Subjective Norms||0.359a||0.042||0.042||−0.063||0.178|
|TPBS Perceived Behavioral Control||0.073||0.178||0.168||0.082||0.198|
Correlations Between the HBMS and TPBS Subscales
|Subscale||HBMS Susceptibility||HBMS Severity||HBMS Benefits||HBMS Barriers||HBMS Cues to Action||HBMS Self-Efficacy||TPBS Attitudes||TPBS Subjective Norms||TPBS Perceived Behavioral Control|
|HBMS Cues to Action||−0.054||−0.160||0.243||−0.355a|
|TPBS Subjective Norms||0.026||0.011||0.568a||−0.580a||0.295a||0.323||0.605a|
|TPBS Perceived Behavioral Control||−0.128||−0.109||0.407a||−0.427a||0.241||0.302a||0.350a||0.655a|