Changing the behavior of patients with periodontitis

There is a great need in dentistry for effective interventions to improve patients adherence to oral hygiene instructions, particularly to improve the long-term treatment success in periodontal patients, and a wide range of psychological models and theories provide an important framework for increasing the authors' understanding.

Abstract

Success in periodontal treatment is highly dependent upon the ability and willingness of the patient to maintain good oral hygiene. This is achieved through a combination of personal care and seeking professional help. Assistance provided by dental professionals includes removing deposits of plaque or calcified bacterial material (calculus) that may prevent effective self-care, as well as dealing with any associated secondary aetiological factors, such as smoking or dietary control (19, 51). However, even with professional help, poor oral hygiene can lead to treatment failure in the longer term (10, 46, 61, 67, 71). Furthermore, Turner et al. (87) concluded that periodontal outcomes can be improved in chronic periodontitis patients by the sole use of oral hygiene. Improving patients’ adherence to oral hygiene instructions requires changing patients’ behavior in terms of brushing, flossing and the use of additional oral hygiene techniques. There is a great need in dentistry for effective interventions to improve patients’ adherence to oral hygiene instructions (92), particularly to improve the long-term treatment success in periodontal patients (8). However, this is potentially challenging, as the behaviors that require adherence to oral hygiene in patients with periodontal disease display many characteristics that have been shown to predict low adherence (35, 54). Specifically, the effects of behavior change are only manifest after several weeks, thus it does not provide immediate relief of symptoms. Furthermore, flossing and brushing may exacerbate symptoms initially, and the patient might experience bleeding and pain. Inflammatory periodontal diseases require patients to make permanent lifestyle changes, because they are chronic conditions. Johansson et al. (39) assessed adherence in a sample of 44 patients with moderate periodontitis, and found that less than half reported still using interdental cleaning aides at the end of 3 years. Similarly, Strack et al. (80) assessed adherence to oral hygiene through patient interviews. This study reported that 30 days after receiving the oral hygiene instructions provided within the clinic, half of the patients (51%) were ‘highly compliant’, while 38% were ‘moderately compliant’ and 11% completely failed to adhere to the instructions. There are a wide range of psychological models and theories that provide an important framework for increasing our understanding of the determinants of adherence to recommendations concerning health behaviors. Social cognition models in particular have been repeatedly applied to predict and explain behavior changes such as screening attendance, dieting and oral hygiene behavior (21). ‘Social cognitions’ are beliefs, thoughts and attitudes concerning behaviors that are believed to be related to whether or not a person undertakes a particular behavior. All these models share the common assumption that an individual’s behavior is best understood by examining their attitudes and beliefs. The following models will be reviewed in relation to oral hygiene behaviors: health belief model. protection motivation theory. locus of control. social learning theory. theory of planned behavior. implementation intentions. stages of change model (or trans-theoretical model). For each model, an outline of the constructs involved in the model and their relationships will be given. This will be followed by a review of research exploring the relationship between the theory and health-related behaviors, including oral health-related behaviors where possible. Finally, intervention studies based on targeting the cognitions in the model will be discussed for each model. Overall, the application of social cognition models to behavior change interventions is still in its infancy, and so there are relatively few published intervention studies. A Cochrane review of interventions to enhance oral hygiene-related behaviors in patients with periodontal disease based on social cognition models identified only four studies (64). The earliest version of the health belief model comprised two core dimensions: threat perception and behavioral evaluation. Threat perception encompassed two key beliefs, perceived susceptibility to the disease (a person’s subjective perception of the risk of contracting the disease) and perceived severity (a person’s subjective evaluation of the impact of the disease or consequences of the illness). Behavioral evaluation also consisted of two distinct sets of beliefs, perceived benefits (the subjective evaluation of the effectiveness of various actions available in reducing the threat) and perceived barriers (which describe a person’s anticipated negative aspects of a particular behavior). According to this model, the combination of high levels of susceptibility and severity increases motivation to act, whereas perceptions of benefits (fewer barriers) provide the preferred path of action. In 1977, the concept of a ‘cue to action’ was added to account for any stimuli that might trigger behavior. These cues can be internal, such as experiencing symptoms, or external, for example reading a health information leaflet or receiving a reminder from the doctor (15). This model is summarized in Fig. 1. The health belief model. Source: (2). Janz & Becker (38) assessed the predictive validity of the four fundamental variables in the health belief model for a variety of health-related behaviors. The results were presented within three behavioral categories: preventive behaviors (where the primary purpose is to prevent a disease that the individual does not currently have; examples of such behaviors include inoculation, screening attendance and self-examination), sick-role behavior (behaviors designed to ameliorate the effects of existing disease, such as diet, adherence to medication regimen and exercise), and clinic utilization (which included preventive and acute visits). In studies assessing preventive behavior, ‘susceptibility’, ‘benefits’ and ‘barriers’ were most consistently associated with behavior, whereas the ‘severity’ construct seemed to be a much poorer predictor, producing significant results in only around one third of the studies. Turning to sick-role behaviors, the ‘severity’ construct becomes a much better predictor of behavior, producing the second highest significance ratio. The best predictor across all studies assessing sick-role behavior was the ‘barriers’ construct, which was significantly correlated with behavior in all of the studies that examined this relationship. Although ‘benefits’ was also consistently associated with behavioral outcomes, perceived susceptibility was a much weaker predictor for this type of behavior. The reviewers point out that this construct may have little relevance for people who are already diagnosed with an illness. Summarizing the three studies assessing clinic utilization proved more difficult as each one assessed a different type of clinic utilization. Nonetheless, the ‘benefits’ construct seemed to produce the most consistent results across those studies. In order to assess the relative predictive validity of each of the four theoretical constructs, Janz & Becker (38) calculated the ratio of positive and statistically significant findings for each construct to the total number of studies in which the construct was tested. Across all 29 studies included in the review, the ‘barriers’ construct was the best predictor of behavior, as it was positively and significantly correlated with behavior in 91% of the studies, followed by ‘benefits’ (81%), ‘susceptibility’ (77%) and ‘severity’ (59%). Harrison et al. (34) attempted to estimate the strength of relationships between health belief model variables and health-related behaviors across studies in a meta-analytic review that broadly followed the inclusion criteria of the original review by Janz & Becker (38). A total of 51 studies matched their inclusion criteria, 20 of which were included in the original review by Janz & Becker (38). This number was further reduced to 16 when studies that did not assess the reliability of the measures were excluded. Those 16 studies assessed a range of behavioral outcome variables, such as vaccination, doctor visits, self-examination, diet and pill taking. Seventeen effect sizes were calculated from the 16 studies, as one study analyzed two samples separately. Significant positive relationships between health belief model dimensions and behavioral outcomes were found. The results of this review indicate that a maximum of 10% of the variance of behavior can be accounted for by any of the four dimensions. However, as the authors point out, the combined effect of all four dimensions may be smaller or larger than the sum of all four individual dimensions (34). Evidence of the ability of the health belief model constructs to predict adherence in patients with periodontal disease is equivocal. Three studies in this area have been published, all of which included measures of clinical status as proxy measures of adherence, rather than assessing oral hygiene behaviors directly. Kühner & Raetzke (42) examined the validity of the health belief model in 96 periodontal patients. Participants received a complete periodontal examination at their first visit to the clinic, and completed a measure assessing components of the health belief model. Following this visit, all participants received a diagnosis and oral hygiene instructions together with information about the relationship between oral hygiene and periodontal disease. Participants were assessed with respect to plaque control at the following visits and received feedback on their performance. The treatment performed at each visit varied according to patients’ needs, but the total number of visits was limited to a total of four visits per patient. Changes in oral hygiene behavior were assessed through changes in bleeding on probing. Compliance was significantly correlated with four out of five items exploring ‘motivation’, two out of three items exploring ‘seriousness’ and two out of three assessing ‘benefits’, but none of the items exploring ‘susceptibility’, ‘barriers’ or ‘dentist–patient relationship’. A further integrated-predictive variable was calculated, which assessed the combined predictive power of all significant variables. The results showed that the combination of these variables explained around a third of the variance in oral hygiene behavior. Barker (14) used the health belief model as the basis for a study of the role of patients’ health beliefs in compliance with preventive dental advice amongst 43 adult patients attending a secondary care dental service. Patients were seen twice, 1 month apart. Compliance was defined as any reduction in plaque or bleeding scores at the second visit. The perceived ‘benefits’ of treatment showed a significant correlation with compliance, and a combination of ‘susceptibility’ and ‘benefits’ beliefs was also found to be significantly related to compliance. Rayant & Sheiham (62) used the gingival index (48) and the plaque index (48) as indicators of adherence in patients with periodontal disease. None of the factors in the health belief model were significantly associated with the periodontal status of these patients. These three studies together suggest that the health belief model plays a small role in predicting the oral hygiene-related behavior of individuals with periodontal disease. Perhaps the most important variable is beliefs about the ‘benefits’ of oral hygiene. This has obvious implications for patient education. Rogers (66) originally formulated the protection motivation theory in an attempt to provide a theoretical framework that could help explain empirical data from previous studies on ‘fear appeals’ (behavior change communications based on creating fear within the target audience). This research was based on the fear-drive model, which proposes that fear is a driving force that motivates changes in behavior in order to avoid negative consequences. Research by Hovland et al. (37) suggested that a fear appeal contains three main stimulus variables: (i) the noxiousness of an event, (ii) the probability of occurrence if no protective behavior is adopted or existing behavior is not modified, and (iii) the efficacy of a recommended coping response in reducing or eliminating the noxious event. Rogers (66) included these variables in the original formulation of the model, but further proposed that each stimulus variable initiates a corresponding cognitive response that motivates the individual to protect themselves from the threat (hence protection motivation theory). Rogers later expanded his theory in order to incorporate additional cognitive mediators, such as self-efficacy, response efficacy and perceptions of the rewards of mal-adaptive responses. This newer version of the model was organized into two parallel cognitive processes, threat appraisal and coping appraisal (see Fig. 2). Protection motivation theory. Source: (66). Threat appraisal focuses on the source of the threat and is the product of a cognitive response resulting from a persuasive communication identifying an event or illness as harmful and likely to occur, along with the belief that the recommended behavior is effective in preventing this negative event. As a result, the individual will be motivated to take action to protect themselves from the threat if the illness (in this case periodontal disease) is appraised as having negative consequences, being likely to occur and if the behavior (oral hygiene) can prevent the disease. Coping appraisal focuses on the perceived coping resources available to the individual. If a person believes the recommended behavior is effective in reducing the threat (response efficacy) and also feels able to perform the recommended action (self-efficacy), then he or she is more likely to engage in the recommended behavior. An early narrative review of studies applying the model (58) reported that, with regard to threat appraisal, ‘severity’ was found to be a good predictor of a range of behaviors, whereas ‘vulnerability’ was predictive of the intention to engage in a behavior. Within the coping appraisal process, response efficacy was found to be a good predictor of changes in intentions, while perceptions of self-efficacy predicted changes in preventive practices. In 2000, two meta-analytic reviews were published (28, 55) that provided a more quantitative understanding of the model variables. Floyd et al. (28) reviewed a total of 65 studies. Out of the 65 studies, 16 focused on only one of the variables of the model, whereas 49 studied multiple components of the theory. Sixteen of the 49 studies assessed intention and behavior, 22 only measured behavior, and 11 of the studies used intention to engage in the behavior as their only dependent variable. All studies were rated on nine points assessing their methodological quality, and each was given a score from 1 (poor) to 5 (excellent). The mean score for all studies combined was 4.2, indicating that on the whole the studies were of high quality. The heterogeneous effect sizes for this review ranged from 0.39 to 0.88, which represents small to medium effects. On the whole, effect sizes for coping appraisal variables were slightly larger than those for threat appraisal variables. The largest effect size for a single variable in this review was for self-efficacy. In general, coping variables showed slightly stronger relationships with adaptive responses compared to threat variables, but the effect sizes for both coping and threat variables were still in the moderate range. This pattern of results was largely confirmed in the review by Milne et al. (55), which contained a smaller number of studies due to more rigorous inclusion criteria. A total of 27 studies comprising 29 independent samples and a total of 7694 participants were included. Nineteen of the studies employed a cross-sectional study design, of which 11 measured intention only, five measured concurrent behavior only, and three measured both intention and concurrent behavior. Seven studies were longitudinal, six of which included measures of both intention and subsequent behavior, and one measured subsequent behavior but not intention. One longitudinal study measured intention, concurrent behavior and subsequent behavior. Most of the cross-sectional studies (14 of the 19) used samples from students. General population samples were used in seven studies, while another seven studies targeted specific groups. The relationship between the variables of the protection motivation theory and health-related intention is most consistently explained by coping variables. Although all of the model variables were significantly correlated with intention, the association between coping variables and intention was much stronger than the association between threat variables and intention. To conclude, the protection motivation theory has informed a considerable amount of empirical research, and has repeatedly been shown to be significantly correlated with both intention and behavior, both in cross-sectional and longitudinal studies. However, to date, there are no published studies in which the protection motivation theory has been applied to oral hygiene. The main conclusion that can be drawn in relation to oral hygiene behaviors is probably the importance of self-efficacy beliefs in behavior change. This finding is replicated in research from other models. The term locus of control was introduced to describe a relatively stable set of beliefs held by a person about the perceived causes of events and situations. Locus of control was first postulated in relation to social learning models of behavior, which postulate that behavior is a function of (i) the extent to which the individual believes the behavior will lead to a particular reward, and (ii) the extent to which the reward is valued. Rotter (68) also believed that social learning theory (see below) could be applied at a more general level, and that a distinction could be made between individuals with an internal locus of control (those who believe events are a consequence of their own actions) and individuals with an external locus of control (those who feel that events are unrelated to their own actions and steered by external factors instead). Rotter (68) developed the internal–external scale, which is the standard measure for assessing the generalized locus of control beliefs. Wallston et al. (90) later developed the health locus of control scale, which is a health-specific measure of the same construct. Both these measures were based on the assumption that locus of control is a uni-dimensional construct, and consequently people were dichotomized into ‘externals’ or ‘internals’. Hundreds of studies followed that compared the two, and, on the whole, an internal locus of control seemed to be beneficial to health, as internal individuals were more likely to engage in health-promoting behaviors compared to external individuals (83). This uni-dimensional conceptualization of the construct was later deemed inadequate, and a new approach for assessing locus of control was put forward. Levenson (45) developed the ‘I, P and C scale’, which differentiated between two types of external control beliefs. According to Levenson (45), external individuals could be further divided into those who feel events are influenced by powerful others, and those who believe events are contingent upon chance, luck or fate. Thus, according to this scale, people have one of the following three orientations: ‘internal’, ‘powerful others’ or ‘chance’. Based on Levenson’s psychometric and theoretical expansion of the concept, Wallston et al. (90) developed the multi-dimensional health locus of control scale, which is now the most widely used measure of locus of control as applied to health behaviors. In general, research has shown that the predictive ability of the locus of control construct increases as the behavior to which it refers is specified more exactly (44). There are a small number of studies that have explored the relationship between locus of control and oral hygiene behaviors. Two large-scale studies of the relationship between measures of dentally related locus of control and oral hygiene behavior and knowledge found only weak or insignificant relationships between these variables. Harris et al. (33) found that locus of control was not significantly associated with dental knowledge or dental care practices in 200 adults without periodontal disease. Among 7770 health adolescents, Regis et al. (63) found low correlations between locus of control and toothbrushing frequency. A number of studies have found a relationship between measures of locus of control and indices of periodontal disease. Kneckt et al. (40) found a significant relationship between dental locus of control and a plaque index amongst diabetic patients. There was no relationship between plaque and a diabetes-related locus of control measure, demonstrating the importance of behavior-specific measures. Galgut et al. (29) investigated the relationship between the multi-dimensional health locus of control and the response of a group of 60 office workers to a plaque control programme. A significant correlation was found between the external multi-dimensional health locus of control dimension of ‘powerful others’ and improvements in some of the clinical criteria; a similar result was found for the ‘internal’ dimension of the multi-dimensional health locus of control. In contrast, there was minimal correlation between the external ‘chance’ dimension of the multi-dimensional health locus of control and the clinical results. Wolfe et al. (94) assessed the relationship between oral hygiene behavior and locus of control (internal/external), self-efficacy and a further construct named ‘oral health beliefs’, which, according to the authors, focused ‘on the role of thought in the regulation of behavior’. The sample consisted of 99 male veterans. As the outcome measure, Wolfe et al. (94) used the plaque index (48). Only external locus of control was significantly correlated with oral hygiene behavior. Given the introduction of the multi-dimensional locus of control scales around 15 years prior to their study, the authors’ use of the earlier, uni-dimensional scale is somewhat surprising. Although it provided support for use of the locus of control construct in the study of oral hygiene behaviors, this study unfortunately failed to provide any information as to which type of external locus of control beliefs were correlated with behavior. A later study by Borkowska et al. (16) failed to find any relationship between locus of control and oral hygiene behavior. This study examined the relationship between locus of control, health value, adherence intent, psychological mood and oral hygiene behavior in a longitudinal study with a repeated-measures design. Oral hygiene was assessed through bleeding on probing, plaque score and probing depth. Both psychological and clinical measurements were taken at time 1 and time 2. At time 2, the only psychological variable (measured at time 1) significantly correlated with the clinical outcome measures was ‘adherence intent’, which was significantly negatively correlated with plaque score and bleeding score. The adherence intent scale consisted of four items that appeared to tap into several different theoretical constructs, such as intention (‘I intend to follow the dentist’s instructions’), self-efficacy (‘I expect that it will be easy for me to follow the dentist’s advice) and outcome expectancy (‘I’m not sure the dentist’s treatment will be worth the trouble it will take me’). Similarly, Odman et al. (56) found that locus of control showed no relationship with improvement in plaque scores or oral hygiene behavior following a 3-month oral hygiene instruction intervention in patients with moderate periodontal disease. In conclusion, it appears that locus of control is correlated with clinical indices, but is not a strong predictor of oral health-related behavior. This may in part be due to the weaknesses of the various measures used, but it is also possible that an external locus of control is associated with seeking professional support for periodontal disease and in turn with improved plaque indices. Alternatively, it is possible that locus of control is susceptible to change following treatment, At least four studies have demonstrated changes in locus of control (from ‘external’ to ‘internal’) following standard periodontal treatment in patients with periodontal disease (11, 12, 75, 95). Bandura’s social learning theory (13) postulates that behavior is learned through self-monitoring, skill training, modelling and visualization. According to this theory, behavior is mainly determined by incentives (personal values that an individual attaches to an outcome) and by the following three types of expectancies: situation outcome, action outcome and perceived self-efficacy. Situation outcome expectancies represent beliefs about the consequences of not engaging in a behavior. These include, among others, beliefs about the perceived threat of an illness. Action outcome expectancies are beliefs about whether or not the behavior will lead to the desired outcome. For example, the belief that flossing reduces the risk of periodontal disease is an action outcome expectancy. Self-efficacy describes the person’s subjective evaluation about the ease or difficulty with which he or she can undertake a given behavior. For example, a patient might feel that it would be easy or difficult to floss their teeth as recommended by the health professional. This theory further specifies a clear causal ordering among the three types of expectancies. Generally, action outcome expectancies are thought to mediate the effect of situation outcome expectancies on behavior, and are thought to determine behavior through their influence upon goals and intentions to engage in the behavior (74). As with most other social cognition models, social learning theory also includes a motivational variable, which is thought to be the most immediate determinant of behavior. In this case, the variable is called goal formation, which represents self-incentives and information about what to do. This goal formation in turn is influenced by a person’s sense of control, their expectancies about outcomes and socio-structural factors. According to this theory, behavior is a product of personal goals, outcome expectancies and self-efficacy beliefs. This model is summarized in Fig. 3. Social learning theory. Source: (49). Although all the above variables are part of the social cognitive theory, the construct of self-efficacy has quickly assumed the greatest importance in this theory. Many applications of this theory have solely focused on self-efficacy beliefs. Furthermore, this construct has been integrated into other social cognition models, and has often been used as a construct analogous to perceived behavioral control in the theory of planned behavior. Self-efficacy beliefs have been shown to predict sexual risk behaviors (76), physical exercise (24, 82), dieting behavior (70, 77), self-examination behaviors (7, 20) and adherence to medication regimens (81). A smaller number of studies that assessed these behaviors also included goals (41) or outcome expectancies (72). Self-efficacy has also been shown to be an effective target in behavior change interventions. Luszczynska et al. (50) found that an intervention aimed at enhancing self-efficacy beliefs produced a significant change in vegetable consumption at a 6-month follow-up. For oral hygiene-related behaviors, Little et al. (47) adopted a social learning theory perspective when devising a group-based intervention for 107 patients aged 50–70 years with moderate to severe periodontal disease. All were members of a dental care programme run by a research organization. The control group received the usual dental care including periodontal maintenance therapy, and the intervention group additionally attended a series of five 90-minute group sessions. The group sessions provided feedback on bleeding on probing for each participant (provided by a dental hygienist), and participants in the experimental intervention group were also encouraged to define their problem in behavioral terms, set weekly targets and introduce cues to behavior change. The presence or absence of plaque was recorded using an adaptation of the Poshadley–Haley plaque index (57), and gingival bleeding was recorded using the Loe and Silness gingival index (48) but dichotomized into categories of ‘no bleeding’ and ‘bleeding’. Pocket depth and attachment loss were measured using a Florida probe. Self-reported toothbrushing and flossing were recorded, and patients were observed and rated on their skill in flossing and brushing. Measurements were taken at baseline and 4 months after baseline. Significant differences were found between the intervention and control groups for all measures, with the intervention group showing more favourable scores in all cases. Within a social learning framework, Weinstein et al. (93) also conducted a small trial of 20 patients (11 women, 9 men) aged between 32 and 50 years and described as presenting with, ‘periodontal problems for which long term behavioral maintenance of oral hygiene routines were necessary as judged by a periodontist’. No further data regarding the clinical condition of patients were provided. The active intervention was based upon the principles of ‘operant and classical conditioning’. Equal numbers of participants (five per group) were assigned to one of four groups (two control groups and two experimental groups). The two control groups received instructions