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Use of Protection Motivation Theory, Affect, and Barriers to Understand and Predict Adherence to Outpatient Rehabilitation

EJ Grindley, EdD, is Instructor, Department of Health, Physical Education, Recreation and Dance, University of Idaho, PO Box 2401, University of Idaho, Moscow, ID 83844 (USA)
SJ Zizzi, EdD, is Sport and Exercise Psychology Program Coordinator and Associate Professor, Department of Sport Studies, West Virginia University, Morgantown, West Virginia
AM Nasypany, EdD, ATC, is Athletic Training Program Director and Clinical Coordinator, University of Idaho

Address all correspondence to Dr Grindley at: egrindle{at}uidaho.edu

Submitted March 9, 2007; Accepted July 30, 2008

	Abstract

 
Background and Purpose: Protection motivation theory (PMT) has been used in more than 20 different health-related fields to study intentions and behavior, albeit primarily outside the area of injury rehabilitation. In order to examine and predict patient adherence behavior, this study was carried out to explore the use of PMT as a screening tool in a general sample of people with orthopedic conditions.

Subjects and Methods: New patients who were more than 18 years old and who were prescribed 4 to 8 weeks of physical therapy treatment (n=229) were administered a screening tool (Sports Injury Rehabilitation Beliefs Scale, Positive and Negative Affect Schedule, and a barriers checklist) prior to treatment. Participants’ adherence was assessed with several attendance measures and an in-clinic assessment of behavior. Statistical analyses included correlation, chi-square, multiple regression, and discriminant function analyses.

Results: A variety of relationships among affect, barriers, and PMT components were evident. In-clinic behavior and attendance were influenced by affect, whereas dropout status was predicted by affect, severity, self-efficacy, and age.

Discussion and Conclusion: The screening tool used in this study may assist in identifying patients who are at risk for poor adherence and provide valuable information to enhance provider-patient relationships and foster patient adherence. However, it is recommended that more research be conducted to further understand the impact of variables on patient adherence and that the screening tool be enhanced to increase its predictive ability.

	Introduction

Top Abstract Introduction Method Results Discussion Conclusion Appendix. References

 
Adherence has been defined by Michenbaum and Turk as an "active, voluntary collaborative involvement of the patient in a mutually acceptable course of behavior to produce a desired preventative or therapeutic result."^1(p20) It is generally believed that poor adherence is a factor related to the failure of rehabilitation programs and that there are personal, social, and economic consequences of this behavior.^2–6 More specifically, the failure of a patient to attend therapy can interfere with the rehabilitation process. In turn, this situation can lead to poor therapeutic outcomes and poor patient satisfaction. From a business perspective, a facility's efficiency can be hindered and financial aspects can be affected. An effort to help patients be adherent should be part of the high-quality service provided by any health care facility as well as a shrewd business move. Such an effort is a vast and multifaceted task. As yet, no single theory has emerged to comprehensively guide all research, and no "solution" has been found. However, researchers have discovered several key factors and have favored theories related to cognitive appraisal and preventative health behavior.

Protection motivation theory (PMT)⁷ is one such preventative health behavior theory that has been used in more than 20 different health-related fields to study intentions and behavior.⁸ This theory shares many features with the health belief model, yet it is more comprehensive and is "... sufficiently broad to apply to any situation involving threat. ..."^9(p158) Protection motivation theory considers that behavior and attitudes can be changed through a cognitive mediating process^9,10 following fear-arousing stimuli.⁷ As Rogers⁷ stated, threat and coping appraisals are made as the magnitude of the noxious event, the probability of the event occurring, and the belief in the efficacy of a protective response are considered. Only if the event is perceived as noxious and likely to occur and the coping response is seen as effective in preventing the future event will protection motivation occur.⁷ Protection motivation has been described by Rogers as "an intervening variable that ... arouses, sustains, and directs activity."^7(p98)

In orthopedic rehabilitation situations, fear-arousing stimuli can originate from experiences of pain, loss of mobility, or a physician's diagnosis and prescription for rehabilitation. The amount of threat appraisal generated depends on the belief that the present discomfort or disability will persist, will worsen, or could lead to further health complications. The amount of coping appraisal depends on an individual's belief in the ability to successfully follow prescribed health behaviors (eg, attend sessions, follow directions, and complete exercises) and the belief in the ability of the treatment to provide assistance (eg, belief in the physical therapist's competence and belief in the prescribed modalities). Furthermore, unique costs related to the rehabilitation context (eg, amount of time it will take, pain that may be experienced, and financial costs) are also considered in the PMT model.

These appraisals undergo a cost-benefit analysis, which produces a degree of protection motivation. In turn, this protection motivation can generate a change in intentions or behavior: adaptive coping (eg, following prescribed treatment to gain health benefits) or maladaptive coping (eg, not adopting recommended action). Compared with other health behavior theories, PMT seems to be well suited to the behavioral context of rehabilitation because the primary goal of starting or sustaining rehabilitation behavior is triggered by an injury or diagnosis (fear-arousing stimuli).

Protection motivation theory has rarely been used in orthopedic rehabilitation situations and, in such instances, has only been used with athletes. Taylor and May¹¹ and Brewer and colleagues¹² used the Sports Injury Rehabilitation Beliefs Scale (SIRBS),¹¹ which measures several PMT factors: severity (how severe the injury or illness is), susceptibility (the extent of vulnerability to having health problems from not taking action), self-efficacy (belief in the ability to undergo rehabilitation), and treatment efficacy (belief that attending therapy will help). Brewer and colleagues¹² reported that the SIRBS explained 43% of the variance in adherence scores in a sample of athletes undergoing rehabilitation after anterior cruciate ligament reconstruction. These studies have provided initial insights into the use of PMT and the SIRBS in rehabilitation situations.

Affect is described in Merriam-Webster OnLine as "a set of observable manifestations of a subjectively experienced emotion"¹³ and is a term that encompasses both moods and emotions. Affect may play a role in the cognitive mediating process in PMT by influencing the amount or type of protection motivation generated. Numerous moods and emotions, such as anxiety, shock, anger, denial, frustration, and depression, are frequently reported in relation to emotional responses to injury^14–16 and disability.¹⁷ Such moods and emotions can be a normal part of the process of adjustment and adaptation that occurs following an injury, illness, or disability. Wiese-Bjornstal et al,¹⁶ Kubler-Ross,¹⁸ Tunick et al,¹⁹ and Livneh and Antonak²⁰ provide examples of the frameworks used to understand response and adaptation to loss, injury, illness, or disability for different populations. The tenet of each of these frameworks is that individuals may experience several emotions and moods as they adjust to their situations. Changes in affect, in particular, the presence of negative affect (NA), may be part of psychological healing; however, research has also found such psychological disturbances to be related to nonadherence, prolonged or problematic rehabilitation, or both.^21–24 Further investigation into psychological changes may enhance the understanding of cognitive-affective elements that influence and predict adherence.

Perceived barriers to adherence have also been studied. Forkan et al²⁵ noted that barriers, and not motivators, predicted adherence to physical therapists’ recommendations following discharge. If barriers are not overcome, then the desired behavior may cease, resulting in nonadherence even if motivation is present. In the coping appraisal components of PMT, barriers may be evidenced as response costs (eg, "I believe in my ability to do my exercises but it may cause me discomfort and take time."), which can reduce patients’ perceived efficacy for themselves or the treatment protocol. Vasey²⁶ and Slujis et al²⁷ noted that problems with taking time off from work, being too tired, exercises being painful, and family commitments were common reasons that patients gave to explain their nonadherence to physical therapy. Furthermore, perceived lack of time has been noted as one of the most frequently reported barriers^27,28 and one that has been used as an excuse even "... despite adequate time being available."^28(p95) Therefore, perceived barriers may be another variable that can be used to assist in the understanding of cognitive processes in PMT and provide information to help treat patients on a more individual level.

One aim of this study was to explore the utility of PMT in guiding research related to predicting the adherence behavior of patients in a general orthopedic rehabilitation facility. A screening tool devised specifically for this study included the SIRBS, the Positive and Negative Affect Schedule (PANAS), and a barriers checklist, a relatively brief questionnaire that could easily fit into a facility's procedures with minimum disruption to the quality and efficiency of patient care. A second aim of this study was to examine the utility of the screening tool in the prediction and further understanding of adherence behavior in this specific population of patients. Three hypotheses were tested: (1) the screening tool would predict a physical therapist's reported ratings of a patient's clinic-based adherence (patient's intensity in completing clinic-based rehabilitation exercises, frequency with which the patient followed instructions in the clinic, and patient's receptivity to changes in the rehabilitation program at the clinic); (2) the screening tool would predict attendance behavior (number of no-shows, number of cancellations, and an attendance ratio); and (3) the screening tool would predict adherence group membership (whether a patient would drop out of the rehabilitation program or be adherent by continuing to work toward the completion of the rehabilitation goals at the clinic).

	Method

Top Abstract Introduction Method Results Discussion Conclusion Appendix. References

 
Participants

Patients who entered a rehabilitation and fitness facility and registered for physical rehabilitation treatment, who were more than 18 years of age, and who were prescribed 4 to 8 weeks of treatment were recruited for this study (n=229). Only those who were prescribed rehabilitation treatment of this duration were included to obtain a more homogeneous sample. It was believed that patients who were prescribed less than 4 weeks of treatment would have relatively minor injuries (eg, minor muscle strain, fitting of orthotics, 2 or 3 visits, and then release to a home exercise program [HEP]) and that those who were prescribed greater than 8 weeks of treatment would have very severe injuries (eg, chronic pathologies) and, thus, would experience different rehabilitation demands, such as time until discharge and time spent following the prescribed treatment. In addition, 4 to 8 weeks was the most commonly prescribed treatment duration at the clinic; therefore, the sample reflected the majority of the clinic's population.

Measures

Screening tool.
The screening tool was devised specifically for this study to address elements of PMT, affect, and barriers. The screening tool consisted of 3 different instruments: the SIRBS,¹¹ the PANAS,²⁹ and a barriers checklist (Appendix).

The SIRBS is a 19-item instrument on which responses are made with a 7-point scale with the anchors "very strongly disagree" and "very strongly agree." The items assess some of the components of PMT: perceived susceptibility (vulnerability) (items 1–5), perceived treatment efficacy (response efficacy) (items 6–9), perceived self-efficacy (items 10–13), rehabilitation value (item 14), and perceived severity (items 15–19).¹¹ Cronbach alpha values have been reported to be .79–.91 for self-efficacy, .83–.85 for treatment efficacy, .83–.84 for susceptibility, and .52–.63 for severity.^10,11 In accordance with the suggestion of Brewer and colleagues,¹² item 19 was removed prior to analysis for the pilot sample (n=163) and the study sample (n=229), resulting in Cronbach alpha values of .88 to .91 for self-efficacy, .77 to .86 for treatment efficacy, .86 to .89 for susceptibility, and .80 to .82 for severity. In addition, minor changes in wording and spelling were made so that the instrument would be applicable to a US sample; for example, "rehabilitation programme" was changed to "rehabilitation program" and then abbreviated as "RP."

The PANAS is used to assess NA (10 items) and positive affect (PA) (10 items). Responses on the PANAS are recorded with a 5-point scale. With the prompt of "past few weeks," Cronbach alpha coefficients have ranged from .87 to .91 for NA and from .85 to .90 for PA.^29–31 In the present study, NA and PA items yielded alpha coefficients of .89 and .92, respectively.

The barriers checklist was designed specifically for this study. Items on the barriers checklist were compiled by the authors using suggestions from adherence research as well as personal experiences working in exercise adherence settings. Feedback on the relevance and completeness of the items was provided by 23 rehabilitation professionals. Final items for the pilot study totaled 12; participants responded to the items using a 5-point Likert-type scale based on frequency. Following the pilot study, the barriers checklist was revised to 7 items. These items were those that yielded the highest mean scores. Because of low variances reported for each item and skewed responses in pilot data, the scale was adjusted from an interval to a nominal frequency of the occurrence of barriers (ie, "yes" or "no").

The response burden for participants was considered to be low because all item responses were made with a 2-, 5-, or 7-point scale, the approximate time for completion was 3 to 5 minutes, and the screening tool was completed at new patient check-in, when there is usually a brief waiting period while new patient information is entered into the computer system. In addition, it was believed that the screening tool was efficient because it captured a variety of data from 3 different instruments, with minimal disruption to the normal efficiency of the facility and patient care.

Adherence behavior.
An attendance ratio (number of attended appointments/number of scheduled appointments) has been calculated in a variety of studies.^12,21,28 Although general attendance is important, the use of an attendance ratio may give the impression that a patient who attends 3 scheduled appointments per week but who stops attending 6 weeks prior to the end of the prescribed treatment and before discharge is "adherent." In the present study, attendance behavior was recorded as number of visits, number of no-shows, and number of cancellations. From these data, 3 nonindependent adherence behavior groups were created: no-shows and non–no-shows, cancellations and no cancellations, and dropouts (DO) and non-dropouts (NDO). It was believed that all classifications had clinical relevance. No-shows and cancellations can affect the efficiency (time and money) of a facility and have the potential to interfere with the progression of patients’ treatments. Dropout status was believed to be of importance because patients who dropped out were at risk for negative physical effects, such as poor range of motion, poor muscle strength (force-generating capacity), altered neuromuscular control, and increased chance of a compensatory injury or reinjury.

An assignment to the no-show or cancellation group was given for one or more no-shows or cancellations, respectively. Patients who cancelled and rescheduled an appointment were not classified in the cancellation group. Dropout rates are common in exercise settings, educational institutions, and medical trials, yet a dropout rate was not found in research for physical therapy patients; therefore, the authors devised a clinically relevant method for determining DO assignments. One trained clinician, using the physical therapist's progress and discharge notes for each patient, ascertained dropout status. A DO assignment was made if a patient self-discharged from treatment and was not deemed to be progressing toward the recovery goals. This classification was used to differentiate patients whose nonadherence (eg, stopped attending) would likely adversely affect their rehabilitation outcome (eg, likely to experience negative physical effects from noncompletion) from those whose nonadherence would not likely cause future impairment (eg, patient was functional, not all goals were met, patient would have been discharged by the physical therapist within a few sessions). In all cases, the DO or NDO status was easily discernible.

The Sport Injury Rehabilitation Adherence Scale (SIRAS)³² was used to measure physical therapists’ perceptions of patients’ clinic-based adherence. The 3-item scale asks about the health care provider's perception of "... the intensity with which this patient has completed rehabilitation exercises" and asks the questions, "How frequently has this patient followed your instructions and advice?" and "How receptive has this patient been to changes in the rehabilitation program?" Responses range from 1 to 5, with scores reflecting "minimum–maximum effort," "never–always," and "very unreceptive–very receptive." Cronbach alpha coefficients have ranged from .81 to 1.0,^21,33–35 suggesting good internal consistency. The response burden for participating physical therapists was considered to be low because the scale consisted of 3 items that required responses on a 5-point scale and the approximate time for completion was 10 to 15 seconds.

Procedure

Ethical guidelines were followed throughout the study. A cover letter and screening tool were given to all patients during check-in at a rehabilitation facility over a 3-month period. Only patients wishing to participate in the study completed the screening tool as part of the facility's registration procedures (N=305). Once completed, the screening tool was coded with a 6-digit clinical identification number and detached from the clinic's paper work by the facility's check-in administrative assistants. During the registration period, new patient data were gathered in accordance with the facility's normal procedures. Such data included age, sex, date of injury, insurance type, and location of injury. These data were entered into the facility's billing system by the administrative assistants along with the 6-digit clinical identification number. All participants gave written informed consent.

From this sample of convenience, only patients who were more than 18 years old and who had been prescribed 4 to 8 weeks of treatment were included in the analyses (n=229). Three age groupings were used: 18 to 25, 26 to 55, and 55 or more years. These life stages were believed to encompass different physical and psychosocial challenges and motivations (eg, attending college, work commitments, and caring for family members) that might influence adherence behavior. It was believed that any age group differences might provide insight into adherence behavior and, thus, influence potential treatment and psychosocial interventions. The treating physical therapist completed the SIRAS at every sixth session, a naturally occurring point at which to assess rehabilitation efforts because of the clinic's reassessment protocol. Next, 4 weeks passed before attendance data and participant demographic information were gathered by administrative assistants using the facility's computerized billing system. Also at this time, dropout status was ascertained through the inspection of progress notes by a trained professional (the third author). All data were entered into a statistical database and analyzed by the authors.

Data Analysis

Data were analyzed with SPSS 14.0.^* Descriptive statistics were determined for appropriate demographic variables. Correlation coefficients were calculated, and chi-square analyses were performed to study the relationships among variables. To investigate the ability of the screening tool to predict SIRAS scores, we constructed a multiple regression model. Only the first SIRAS score was analyzed because of low numbers for all other data points and, because of the sample size, the regression model was constructed with 4 separate stepwise regressions. In addition, adjusted alpha levels of .10 to enter and .20 to remove were used to maximize power and to allow the factors to enter more easily. The dependent variable was the SIRAS score (sixth session physical therapist assessment of adherence), and the independent variables were the 3 measures in the screening tool and age. The independent variables were entered in relation to their hypothesized effect: SIRBS subscales, PA and NA, total barriers, and age. Only variables that were significant at each step of building the model were carried into the next step and then into the final models.

To investigate the ability of the screening tool to predict attendance behavior (number of no-shows, number of cancellations, and the attendance ratio), we created 3 separate multiple regression best models. Each comprised 4 separate stepwise regressions with alpha levels of .10 to enter and .20 to remove. The dependent variables were the number of no-shows, the number of cancellations, and the attendance ratio calculations. The independent variables were the SIRBS subscales, PA and NA, total barriers, and age. These were entered in relation to their hypothesized effect. Only variables that were significant at each step of building the model were carried into the next step and then into the final models.

To investigate the ability of the screening tool to predict adherence group membership (DO or NDO), we conducted a discriminant function analysis containing 4 steps to create a best model. The dependent variable was the DO or NDO classification. The independent variables were the SIRBS subscales, PA and NA, total barriers, and age. These were entered in relation to their hypothesized effect.

	Results

Top Abstract Introduction Method Results Discussion Conclusion Appendix. References

 
Sample Demographics

Participants (149 women and 80 men) had a mean age of 44.67 years (SD=14.58) and were found to be demographically similar to the facility's entire patient population with regard to sex, injury site, insurance, and attendance behavior. Perfect attendance was seen with 46.7% of the sample (n=107), and 75 participants (32.8%) dropped out of therapy. Tables 1 and 2 show participant demographic information and a summary of attendance behavior, respectively.

The PA items with the highest mean scores on a 5-point scale were "alert" (=3.55, SD=1.07) and "determined" (=3.55, SD=1.09), whereas the NA items with the highest mean scores were "distressed" (=2.46, SD=1.27), "irritable" (=2.4, SD=1.14), and "upset" (=2.29, SD=1.24). The most commonly noted barriers were "scheduling problems" (n=49, 21.4%), "not having enough time" (n=42, 18.3%), and "fear of pain or further discomfort" (n=36, 15.7%). The item with the highest mean score on the SIRBS with a 7-point scale was "being fully recovered is important to me" (= 6.74, SD=0.71).

Total barriers were negatively correlated with self-efficacy (r=–.380, P=.001) and treatment efficacy (r= –.273, P=.001) but positively correlated with NA (r=.342, P=.001). Negative affect also was correlated with perceived severity (r=.317, P=.001), with higher NA scores being related to higher perceived severity of the injury. Additional correlations among screening variables and adherence measures are shown in Table 3.

Predicting Patients’ Attendance Behavior

The final model accounting for the greatest variance in the number of no-shows consisted of NA and age (R²=.04; adjusted R²=.03; F=3.57; df=2,196; P=.03). Approximately 4% of the variance in the number of no-shows was accounted for by NA and age. The final model accounting for the greatest variance in the number of cancellations consisted of NA (R²=.04; adjusted R²=.03; F=7.97; df=1,197; P=.005). Approximately 4% of the variance in the number of cancellations was accounted for by NA. The final model accounting for the greatest variance in the calculated attendance ratio (attended/scheduled) consisted of NA (R²=.02; adjusted R²=.02; F=4.92; df=1,197; P=.028). Approximately 2% of the variance in the attendance ratio was accounted for by NA.

Predicting Adherence Group Membership

The discriminant function analysis revealed that predictors differentiated between DO and NDO (=.89, ²=16.04, df=5, n=144, P=.007). On the basis of the relationships observed, the discriminant function comprised NA, PA, severity, self-efficacy, and age. Correlation coefficients obtained with the discriminant function analysis were –.76 for NA, .69 for PA, –.40 for severity, .39 for self-efficacy, and .34 for age. The final model correctly classified 63.9% of the cases as DO or NDO and was calculated to be able to correctly predict 60.4% of cases in a new sample, with a kappa value of .25 (a kappa value of 0 reflects chance).

	Discussion

Top Abstract Introduction Method Results Discussion Conclusion Appendix. References

 
Use of PMT for Prediction

Other studies that have used PMT concepts^12,36 have generally shown an increase in coping appraisal (treatment efficacy and self-efficacy) in relation to behaviors measured. In the present study, an increase in only one of the coping appraisal components (self-efficacy) differentiated between participants who were more adherent (NDO) and those who were less adherent (DO). Furthermore, higher self-efficacy was related to higher treatment efficacy and, thus, a general belief in an individual's own ability to meet the demands of rehabilitation and the effectiveness of therapy; lower self-efficacy was related to a larger number of total barriers (response costs). Although it is not clear which variable initiates these relationships, it is possible that various perceptions can be altered to enhance overall coping appraisal. Ensuring that the nature of treatment and concerns about treatment are discussed in a meaningful way with patients, in terms that they understand, may be key in increasing treatment efficacy. Such interactions may encompass understanding each patient's motivation (eg, to return to work, to play with grandchildren, or to be independent), intelligence level (eg, high or low cognitive functioning), learning style (eg, visual, auditory, or kinesthetic), and even career (eg, manual labor or customer service) and changing the discussion, examples, and metaphors used in talking about treatment to meet the patient's needs. In addition, incorporating components for building self-efficacy into interactions may have a positive influence on adherence behavior. To increase self-efficacy, it is recommended that goals be set to ensure early successes, that patients monitor both physical and emotional achievements, and that feedback specifying which behaviors should be repeated is provided.

In the present study, dropout behavior also was differentiated by threat appraisal, with higher perceived severity being related to dropping out of treatment. This result is contrary to those of some studies in other medical fields that reported a relationship between higher threat appraisal and increased adherence.³⁷ In the present study, participants’ threat appraisal may have been related to their current noxious experience of poor mobility, limited range of motion, pain, or a combination of these factors rather than to the long-term consequences of not completing their treatment programs. This context is different from that of many other medical conditions, in which patients may not physically or mentally experience a noxious event until the development of symptoms that may take a number of years to become apparent, if at all (eg, development of cancer or contraction of a sexually transmitted disease).

First, patients going through orthopedic rehabilitation may not fully understand the negative consequences that nonadherence to their treatment programs may have, such as future discomfort, poor mobility, or reinjury. Second, once the noxious experience of poor mobility, limited range of motion, pain, or a combination of these factors has decreased and only the long-term threat of poor rehabilitation outcomes remains, less protection motivation may be generated. With less protection motivation, especially for longer rehabilitations, other life events requiring attention and effort may take precedence over treatment. In such situations, barriers such as time and support can arise and may lead to patients’ dropping out before treatment is completed. Finally, pain and discomfort from actually participating in early treatment may be perceived as a separate health threat that generates protection motivation in the form of nonadherence.

In all instances, physical therapists may be able to adjust these perceptions through education such as types of pain, reasons for icing, and the need to continue to attend treatment when patients are not close to treatment goals even if they feel better. In addition, ensuring that patients’ goals and motivations are included in discussions can be beneficial. For example, "That heel prop thing hurts, but by doing this, it means that all the muscles will work properly. If we don’t get full extension, it may be difficult to move about properly, and that would make that dancing you mentioned hard to do."

Because we wanted to administer the screening tool at a time most conducive to the normal efficiency of the facility, it was administered prior to a patient's first visit with a therapist. This strategy assumed that the onset of the injury and the referral to a physical therapist from a physician were sufficient environmental stimuli to evoke the cognitive processes in PMT. This strategy was also believed to mirror how such a screening tool may actually be used in practice. However, in both previous studies with the SIRBS, administration occurred after a patient's initial visit. Because these dynamics need to be further understood, it is suggested that protection motivation be measured at several points throughout rehabilitation. Doing so will allow the exploration of changes that occur from a baseline and could lead to further understanding of appraisals, intentions, and behaviors over the course of treatment. In turn, such understanding will shed further light on the utility of PMT in an orthopedic rehabilitation setting.

Affect

The levels of NA and PA in the present study were similar to those reported for a nonclinical (mental health) sample.³⁸ More specifically, DO demonstrated more NA and less PA than NDO and also differed from the large general public sample. Affect also played a role in differentiating DO and NDO. Although it should be remembered that both NA and PA were combined with severity, self-efficacy, and age and predicted only slightly better than chance, the results of the present study offer some insight into the role of affect in rehabilitation adherence. More specifically, the results offer some support to previous research that has discussed the influence of emotions and moods following injury^{3,14,16,22,39} as well as research that has noted poor adherence or coping for patients who experience psychological distress.^{21,23,24,40,41} The type of psychological distress has been suggested to vary depending on the relationship between NA and PA, with high levels of NA accompanied by low levels of PA being more indicative of depression but high levels of NA alone being suggestive of anxiety.³⁸ This information suggests that depression rather than anxiety may have had some influence on dropout behavior in the present study.

It is possible then that a measure of affect could assist in identifying patients with levels that may negatively influence their rehabilitation. Once identified, physical therapists could address results during their patient interactions. Alternately, patients who exhibit higher levels of distress can be referred to a sport and exercise psychology professional who has more training and time to work with the patient specifically on particular issues (eg, setting daily goals, developing individual relaxation plans to assist with nervousness about treatment, enhancing time-management strategies to accommodate treatment), whereas patients demonstrating levels of clinical concern (eg, signs of depression, anxiety, adjustment disorder) should be directed to a licensed mental health professional. To discern among the 3 options presented, the raw score and percentile chart devised by Crawford and Henry³⁸ could be used. Addressing affect could assist in enhancing patient care and increase in-clinic adherence behavior or decrease DO, or both. The screening tool used in the present study indicated that affect accounted for only 5% of variance. Although 5% is a very small amount of variance to be accounted for by affect, it may equate to many patients over time, their rehabilitation and satisfaction, and several thousand dollars per year for a facility. Therefore, it is recommended that this measure as well as other measures continue to be studied in a variety of facilities.

Age

Participants who were 26 to 55 years of age reported the most back and neck injuries, were more likely to report "fear of pain or further discomfort," and were more likely to drop out. This age group included numerous participants who were employed, taking care of their families, or both. In addition, decreased physical activity and poor posture and ergonomics found for this age group often lead to back and neck discomfort. Although the exact relationships among these variables are unclear at this time, it is recommended that consideration be given to patients who have the aforementioned criteria. However, more importantly, it should be remembered that individual perceptions of injury and personal situations (eg, work commitments, family commitments, financial constraints, and affect) will have more of an influence on perceived barriers and adherence behavior than will the specific age of a patient or the injury site alone. Therefore, treatments and interactions should match the patient and not just pathologies.

Barriers

The results for the entire sample suggested a moderate positive correlation between total barriers and NA and a small negative relationship with PA. Although these relationships are logical, the manner in which they work in PMT is not clear. It is possible that barriers are appraised as response costs which, if high, may decrease coping. This effect, in turn, could influence the amount of protection motivation evoked and the type of outcome behavior. It then would be important to pay attention to patients’ perceived barriers, because these barriers could be an obstacle to positive action being taken. To assist in barrier reduction, physical therapists must listen and acknowledge the barrier (eg, "On a scale of 1–10, it is a 6 for doing your HEP. What stops it from being more than a 6 is that you forget when you are busy."). Physical therapists then could ask patients to generate their own solutions (eg, "So, how can we help you to remember or to fit it into your day better?"). Asking these questions, instead of relying purely on home exercise prescription, may improve patient self-efficacy as well as patient-therapist rapport for future appointments.

Limitations

The limitations of the present study include the use of one rehabilitation facility and a sample of convenience; therefore, caution should be taken when making inferences to the rehabilitation population. The present study measured adherence to clinic attendance as well as in-clinic behavior but did not address adherence to the home physical therapy program. Home exercise programs are an integral part of most physical therapy regimens. Caution then should be taken when considering the results of the present study because not all aspects of adherence were measured. This means that a patient may be adherent to appointments and complete all rehabilitation activities at the appointments but may not be following the HEP, a fact that could influence behavior at appointments as well as therapeutic outcomes. In addition, the predictive ability of the screening tool for HEP adherence and the relationships among adherence to home exercise, clinic attendance, and in-clinic behavior have not been studied. The present study also used in the screening tool an instrument (the SIRBS) that has been used in only 2 other published studies, which examined athletes. Thus, a limitation is that this instrument has no published reliability or validity for patients receiving physical therapy intervention.

	Conclusion

Top Abstract Introduction Method Results Discussion Conclusion Appendix. References

 
The present study provides some support for the use of PMT in guiding adherence research in an orthopedic rehabilitation setting, yet further investigation is needed. In addition, the study sheds light on the utility of a screening tool to aid in the identification of patients who may be at risk for dropping out of treatment. Although the screening tool incorporated 3 separate measures, was relatively easy to fit into the facility's procedures, and had a low response burden, the analysis of data revealed predominantly weak relationships and low predictive ability. Future research is recommended to further explore the concepts examined in the present study to fully understand the relationships and their impact on patient adherence behaviors. Furthermore, the screening tool requires further attention to increase its predictive ability, making it a more effective tool for facilities to use to assist in adherence issues.

The present study did provide some initial insight into dropout behavior, specifically raising awareness of NA, barriers, self-efficacy, and perceived severity. Although the level of statistical significance in the present study was low, it is believed that being aware of and addressing these components can have numerous positive effects, such as building rapport, increasing patients’ perceptions of empathy, increasing patients’ perceptions of control, increasing patients’ coping appraisal (self-efficacy and response costs), and enhancing mutual cooperation in seeking solutions, as recommended by Slujis et al.²⁷

It is likely that the most effective method for addressing these components (with the exception of the need to refer a patient to a mental health professional) without disruption of the course of therapy would be for physical therapists or a sport and exercise psychology professional to integrate any discussion or intervention directly into the patient's treatment time (eg, talking about how they are doing and what barriers they face and generating solutions while performing exercises or icing). This may be a time- and cost-efficient way to address the 32.8% DO issue as well as assisting in reducing no-shows and cancellations. In turn, such efforts could positively influence patients’ rehabilitation, satisfaction with service, and therapists’ satisfaction, which could influence facility efficiency and increase profit margins.

	Appendix.

Top Abstract Introduction Method Results Discussion Conclusion Appendix. References

 

View larger version (22K): [in this window] [in a new window]   Appendix. Screening Tool Items: Sports Injury Rehabilitation Beliefs Scale (SIRBS), Positive and Negative Affect Schedule (PANAS), and Barriers Checklist

	Footnotes

 
All authors provided concept/idea/research design and consultation (including review of manuscript before submission). Dr Grindley and Dr Nasypany provided writing and data collection. Dr Grindley and Dr Zizzi provided data analysis. Dr Grindley provided project management.

Facility and West Virginia University review board approval was obtained prior to the start of this study.

The authors thank HealthWorks Rehabilitation and Fitness, Morgantown, West Virginia, for continued input and support of this research.

An oral presentation of this research was given at the Annual Conference of the Association for the Advancement of Applied Sport Psychology 2005; Vancouver, British Columbia, Canada; and a poster presentation of this research was given at the 11th World Congress of the International Society of Sport Psychology; August 15–19, 2005; Sydney, New South Wales, Australia.

^* SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

	References

Top Abstract Introduction Method Results Discussion Conclusion Appendix. References

 

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				C. A Thorstensson Invited Commentary Physical Therapy, December 1, 2008; 88(12): 1541 - 1543. [Full Text] [PDF]

				E. J Grindley, S. J Zizzi, and A. M Nasypany Author Response Physical Therapy, December 1, 2008; 88(12): 1543 - 1544. [Full Text] [PDF]

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