Modern health worries,subjective somatic symptoms,somatosensory amplification,and health anxiety in adolescents

Abstract

The cross-sectional study aimed at the psychometric evaluation of the Modern Health Worries Scale in adolescents and the exploration of the relationship among modern health worries, somatosensory amplification, health anxiety, and somatic symptoms. A total of 480 secondary school students (aged between 14 and 19 years) completed a set of questionnaires. Four-factor structure of the scale was confirmed by confirmatory factor analysis. Modern health worries were connected to somatosensory amplification and health anxiety, and somatosensory amplification and health anxiety were partial mediators of the connection between modern health worries and somatic symptoms. Perceived vulnerability (conceptualized as somatosensory amplification and health anxiety) appears to build a “social-cognitive-emotional bridge” between symptoms and modern health worries.

Keywords

adolescence anxiety physical symptoms psychological distress well-being

Introduction

Although “worry” is the central definitional feature of generalized anxiety disorder, its definition and nature are not fully understood. Worry, as opposed to the somatic and emotional aspects of anxiety, is conceptualized as a thought process; therefore, it belongs to the cognitive domain (Borkovec and Inz, 1990). As the phenomenon has a crucial impact on behavior and psychological well-being, content of worries is at least more important than their extent, particularly in the field of health psychology (Moser et al., 2007). Health-related worries are usually connected to elevated (and often biased) risk perception (Moser et al., 2007; Senay et al., 2012); thus, worries triggered by specific situations (e.g. pregnancy, perceived proneness to cancer, having adolescent children) need specific interventions and also specific measures (Green et al., 2003; Moser et al., 2007; Sturm et al., 2008). Worries about health-related threats or harmful “side-effects” of new technologies and other features of modern life (modern health worries (MHWs)) have been reported for many decades; however, the public concern has substantially increased recently (Petrie et al., 2001). Typical representatives of MHWs are concerns about negative effects of chemical and biological agents (e.g. toxins in household products, drug-resistant bacteria), of various kinds of environmental pollution (e.g. noise pollution, traffic fumes), of tainted food (e.g. additives, pesticides, hormones in food), or of electromagnetic radiation (e.g. high tension power lines, mobile phone towers). These worries, exaggerated and maintained by stories published in mass media (Petrie et al., 2001) appear to be quite frequent among adults and are closely connected to various health-related aspects of life. For example, MHWs were related to worse self-evaluated health status (Filipkowski et al., 2010; Petrie et al., 2001; Rief et al., 2012), to more frequent use of health-care services (Andersen and Jensen, 2012; Filipkowski et al., 2010; Furnham, 2007), to a preference of organic and functional food (Chen, 2011; Devcich et al., 2007), and to more subjective somatic symptoms (Bailer et al., 2008; Köteles et al., 2011b; Petrieet al., 2001; Rief et al., 2012). Interestingly, research on this field exclusively focuses on adults, although the impact of the above-mentioned problems (particularly those of subjective symptoms) on psychological well-being of adolescents is well known. We do not even have data on the existence of the phenomenon and on the applicability of the MHW scale (MHWS) in this group, not to mention the magnitude of various MHWs among adolescents or their role in the development of subjective symptoms.

Subjective somatic symptoms are common in adolescence, though the frequency, duration, intensity, and their disabling effects vary among individuals. The most common ones are headache, abdominal pain (Dul et al., 2011), and fatigue (Jellesma et al., 2006). Persistent or bothersome symptoms interfere with psychological (Jellesma et al., 2006) and day-to-day functioning (Huguet and Miró, 2008). Minor and transient symptoms are supposed to be concomitants of normal pubertal development, as well as increased attention to the body and increased bodily awareness (Taylor et al., 1996). Enhanced body-focus becomes problematic only if normal bodily sensations become associated with negative feelings (negative affect, anxiety) and become attributed to potentially illness-related somatic processes (somatosensory amplification—tendency to experience a somatic sensation as intense, noxious, and disturbing) (Barsky et al., 1990). Based on the symptom perception hypothesis (Watson and Pennebaker, 1989), negative affect or any general dimension of distress (e.g. trait anxiety, health anxiety) may cause attentional and interpretational bias to bodily sensations, and increased body-focus and the concomitant hypervigilance lead to the perception and reporting of more symptoms. Similarly, external influences focusing attention on (possibly pathological) body processes and personal vulnerability may also play an important role in development of symptoms.

MHWs were found to be connected to somatosensory amplification in previous studies on various adult samples (Köteles et al., 2011b, 2012; Köteles and Simor, 2013a). Health anxiety (i.e. the fear of having a serious illness) was also related to MHWs even after controlling for somatosensory amplification in a cross-sectional study (Köteles and Simor, 2013b). According to these findings, MHWs can be seen as indicators of sensitization for health-related concerns. As somatic symptoms have a considerable impact on everyday functioning of adolescents and MHWs are closely associated with symptoms, better understanding of MHW-related processes in this group might have important practical and theoretical implications.

The first goal of the present study was the psychometric investigation of the MHWS on data obtained from adolescents. Although there might be differences between adolescents’ and adults’ MHWs (in other words: we have no data on the construct validity of the MHWS in adolescents), we decided to use the original version of the scale as this way results obtained from adolescent and adult samples remain directly comparable with each other. The study had a descriptive aspect: as in the absence of empirical data, we did not want to formulate hypotheses, we aimed to assess and to quantify adolescents’ MHWs and to compare them to adults’ MHWs. Moreover, it was hypothesized that MHWs are connected to subjective somatic symptoms as well as to somatosensory amplification and health anxiety. Finally, the connection between MHWs and somatic symptoms was expected to be mediated by somatosensory amplification and health anxiety.

Methods

Participants

Participants were students from three Hungarian secondary schools. Students were divided into two age groups (14–16 years: n = 204, mean age = 15.6 ± 0.58 years, 31.4% male; 17–19 years: n = 276, mean age = 17.7 ± 0.73 years, 39.9% male). Students filled out the paper-based questionnaires anonymously in groups in their classrooms, the whole procedure took approximately 35–40 minutes. Students received no educational or other reward for their participation. The study procedure was approved by the Ethical Committee of the Eötvös Loránd University, Budapest, Hungary.

Questionnaires

MHWS (Petrie et al., 2001) is a 25-item scale that measures people’s concerns of modernity affecting their health. Items (e.g. amalgam dental fillings, air pollution, or radiation from cell phones) are rated on a 5-point Likert scale ranging from 1 (“no concern”) to 5 (“extreme concern”). Higher scores reflect greater concerns. The scale is divided into four subscales (Environmental pollution, Toxic interventions, Tainted food, and Radiation) and is characterized by a stable factor structure and good internal reliability (Kaptein et al., 2005; Köteles et al., 2011b; Petrie et al., 2001). In the present study, internal consistency of the scale was 0.93 and 0.94 for the younger and the older student sample, respectively. Cronbach’s α values for subscale 1–3 were above 0.85 in both samples, while they were substantially lower but still acceptable for the Radiation subscale (0.60 and 0.71, respectively).

Trait Anxiety Inventory (STAI-T; Spielberger et al., 1970) is a widely used and reliable 20-item questionnaire that measures the general level of anxiety on a 4-point scale. Higher scores reflect higher levels of dispositional anxiety. In the present study, Cronbach’s α values of the Hungarian version (Sipos et al., 1994) were 0.87 and 0.89 in the two samples, respectively.

Patient Health Questionnaire Somatic Symptom Severity Scale (PHQ-15; Kroenke et al., 2002) is a 15-item scale designed to measure the prevalence of the most common body symptoms (e.g. headache, nausea) experienced in the last 4 weeks on a 3-point Likert scale from 1 (“not bothered at all”) to 3 (“bothered a lot”). Higher scores refer to more symptoms. The Hungarian version had good psychometric properties in previous studies (Köteles et al., 2009, 2011b). Its Cronbach’s α coefficients were 0.80 and 0.79 for the two samples in the present study, respectively.

Somatosensory Amplification Scale (SSAS; Barsky et al., 1990) is a scale that refers to a tendency to experience a somatic sensation as intense, noxious, and disturbing. It consists of 10 self-rated statements that are rated on a 5-point scale. Anchor points of the scale were 1 (“not at all”) and 5 (“extremely”); higher scores refer to higher amplification tendency. The Hungarian version proved to be valid and psychometrically sound (Köteles et al., 2009). Its internal reliability was 0.68 and 0.66 in the two groups of the present study.

Short Health Anxiety Inventory (SHAI; Salkovskis et al., 2002) contains 18 items that assess health anxiety independently of actual physical health status on a 4-point scale. Higher scores reflect higher levels of health-related anxiety. The SHAI has two subscales (Illness Likelihood and Illness Severity), which were replicated in the Hungarian version (Köteles et al., 2011a). Only the total score (sum of the scores of the subscales) was used in the present study. Cronbach’s α coefficients were 0.85 and 0.81 for the two samples, respectively.

Statistical analysis

The data were analyzed using SPSS version 15.0 software. Questionnaire total scores were calculated as sums of item scores. To make scores of the total MHWS and the subscales of different length comparable, mean scores instead of sums were calculated and then multiplied by 20, achieving a theoretical range of 20–100 in each case. Participants’ gender and group affiliation were coded into binary variables (0 = male, 1 = female and 0 = younger students, 1 = older students, respectively). Socioeconomic status (SES) of students was estimated as mean of parents’ educational qualification. Factor structure of the MHWS in the two student groups was checked by confirmatory factor analysis (CFA) using the MPlus program (v6.01). Due to the serious deviation from normal distribution, responses to each item were treated as ordinal variables, and the robust weighted least square (WLSMV) estimation method was used. Model fit was assessed with a chi-square (χ²) value, a widely used absolute fit index (root mean square error of approximation (RMSEA)) that compares the observed data with the theoretical model and with incremental fit indices that compare the observed data with a baseline model (Tucker–Lewis Index (TLI), comparative fit index (CFI)). Satisfactory degree of fit requires that CFI and TLI are greater than 0.95. An RMSEA value below 0.05 indicates excellent fit, a value <0.08 indicates adequate fit, and a value >0.10 signifies poor fit.

Students were divided into two age groups (14–16 years and 17–19 years), and scores obtained from these groups were compared to the scores of university students (n = 262, mean age = 21.24 ± 2.72 years, 37% male) and patients visiting their general practitioners (n = 249, mean age = 46.79 ± 17.89 years, 33.3% male) reported in two previous studies (Köteles et al., 2011b, 2012). Group-level differences among total MHWS scores as well as among subscale scores were investigated by one-way analyses of variance (ANOVAs) and post hoc analyses using Bonferroni correction. Differences in SHAI, STAI-T, SSAS, and PHQ-15 scores between the younger and the older student groups were checked with independent sample t-tests. Associations among variables were examined by Pearson correlations. To investigate the individual effects of the variables on the MHWS, a multiple linear regression analysis was applied with the MHWS score as a dependent variable. Variables were entered in three steps using the ENTER method. In Step 1, sociodemographic control variables (gender, group affiliation, and SES) were entered, followed by (Step 2) control variables assessing negative affect and subjective symptoms (STAI and PHQ-15), and finally (Step 3) somatosensory amplification and health anxiety scores. To test mediation effects between MHWs and somatic symptoms, two Sobel tests were conducted using SSAS and SHAI scores as mediating variables (M). In these tests, a linear regression analysis with MHWS score as independent variable and M as dependent variable and another analysis with MHWS and M scores as independent variables and PHQ-15 score as dependent variable were carried out. To calculate the Sobel statistic, MHWS’ regression coefficient from the first equation and M’s regression coefficient from the second equation were used in both cases.

Results

CFA

Data of the two samples fit well to the hypothesized four-factor model (χ² = 1299; $χ_{younger}^{2}$ = 650.980; $χ_{older}^{2}$ = 648.516), df = 600, p < 0.001; TLI = 0.958; CFI = 0.956; RMSEA = 0.067). All factor loadings were above 0.55, typically in the range of 0.7–0.85.

MHWS total and subscale scores

Descriptive statistics of the four groups (younger and older high school students, university students, and patients) are summarized in Table 1. According to the results of the ANOVAs, significant differences among groups were found in the total score as well as in all subscale scores (MHWS: F(3, 987) = 38.201; Environmental pollution: F(3, 987) = 15.163; Toxic interventions: F(3, 987) = 50.436; Tainted food: F(3, 987) = 24.487; Radiation: F(3, 987) = 43.856; p < 0.001 for all cases). Inspection of means and 95 percent confidence intervals indicates an increasing tendency from younger students to university students and patients in every case (see Figure 1 for details), while the overall pattern remained unchanged (i.e. adolescents, similar to adults, scored higher on the Toxic interventions and Tainted food subscales than on the other two).

Table 1.

Descriptive statistics (means and SDs) of the MHWS and the subscales for the four groups.

Group	MHW total score	Environmental pollution	Toxic interventions	Tainted food	Radiation
14–16 years	42.63 ± 13.84	40.04 ± 14.33	47.88 ± 18.54	49.43 ± 21.03	30.29 ± 12.97
17–19 years	46.04 ± 14.74	42.17 ± 15.32	52.46 ± 18.20	53.96 ± 22.17	34.15 ± 15.05
University students	51.34 ± 13.76	45.22 ± 13.79	62.94 ± 17.22	58.32 ± 20.99	38.91 ± 17.35
Patients	56.15 ± 16.26	48.91 ± 16.95	65.80 ± 19.35	65.73 ± 21.31	47.47 ± 21.59

SD: standard deviation; MHWS: Modern Health Worries Scale.

Correlates of MHWs

According to the results of the t-tests, no significant differences between the SSAS, STAI-T, SHAI, and PHQ-15 scores of the two groups were found. MHWS scores showed weak to medium correlations (r = 0.24–0.45; p < 0.001 for all cases) with SSAS, SHAI, and PHQ-15 scores, and weak correlations (r = 0.19–0.23; p < 0.001 for all cases) with STAI-T scores.¹

In the first equation of the regression analysis, adolescents’ gender and group affiliation were significantly associated with MHWs: females and older adolescents reported more MHWs than males and younger students. In the second step of the analysis, somatic symptoms also showed a significant relationship to MHWs. In the final step, the contribution of somatic symptoms and gender lost its significance, while both somatosensory amplification (β = 0.271, p < 0.001) and health anxiety (β = 0.219, p < 0.001) remained significantly related to MHWs. The final regression equation explained 21.0 percent of the total variance (see Table 2 for details).

Table 2.

Results of the multiple linear regression analysis (dependent variable: MHW).

	Step 1: R² = 0.05***		Step 2: R² = 0.103***		Step 3: R² = 0.21***
	B ± SE	β	B ± SE	β	B ± SE	β
Gender	5.312 ± 1.374	0.177***	3.310 ± 1.403	0.110*	1.710 ± 1.337	0.057^NS
Group	3.944 ± 1.310	0.135**	3.531 ± 1.279	0.121**	3.577 ± 1.206	0.123**
SES	−0.450 ± 0.431	−0.048^NS	−0.307 ± 0.420	−0.033^NS	−0.697 ± 0.399	−0.074^NS
STAI-T			0.143 ± 0.078	0.089^NS	−0.107 ± 0.080	−0.067^NS
PHQ-15			0.549 ± 0.141	0.189***	0.186 ± 0.140	0.064^NS
SSAS					0.671 ± 0.122	0.271***
SHAI					0.456 ± 0.103	0.219***

MHW: modern health worries; SES: socioeconomic status; SSAS: Somatosensory Amplification Scale; STAI-T: Trait Anxiety Inventory; SHAI: Short Health Anxiety Inventory; PHQ-15: Patient Health Questionnaire Somatic Symptom Severity Scale; NS: not significant.

p < 0.05, **p < 0.01, ***p < 0.001.

As for the mediation analyses, in the case of somatosensory amplification, the Sobel test revealed a partial mediation effect (Sobel test statistic: 5.793 ± 0.0076, p < 0.001), that is, the effect of MHWS on PHQ-15 remained significant after entering SSAS into the equation (regression coefficients: MHWS → SSAS: 0.152; SSAS → PHQ-15: 0.289; MHWS → PHQ-15 (residual effect): 0.089; p < 0.001 for all cases). The results of the second Sobel test testing the mediating effect of health anxiety were quite similar (Sobel test statistic: 5.795 ± 0.0076, p < 0.001): MHWS → SHAI: 0.163; SHAI → PHQ-15: 0.270; MHWS → PHQ-15 (residual effect): 0.089, p < 0.001 for all cases.

Discussion

The most important findings of the study were as follows: (1) the factor structure of the MHWS was confirmed using the samples of younger and older secondary school students, (2) students’ MHW scores were lower than scores of university students and patients, (3) somatosensory amplification and health anxiety were independently associated with MHWs even after controlling for participants’ age, gender, SES, trait anxiety, and subjective somatic symptoms, and (4) both somatosensory amplification and health anxiety were mediators of the connection between MHWs and somatic symptoms.

According to the psychometric results, the MHWS appears to be a reliable tool to assess MHWs among adolescents. In terms of both internal consistency and factor structure, the MHWS showed practically the same characteristics as in adult samples in previous studies (Bailer et al., 2008; Kaptein et al., 2005; Köteles et al., 2011b; Petrie et al., 2001), which indicates that these worries are similarly structured in the mind of adolescents and adults. Moreover, the relationship between MHWs and other investigated constructs (health anxiety, trait anxiety, somatic symptoms, and somatosensory amplification) was similar to results obtained from adult samples (Köteles et al., 2011b, 2012; Köteles and Simor, 2013a, 2013b), which also supports the applicability of the scale among adolescents. This impression gains further support from the fact that the magnitude of worries is similarly distributed among the four subscales in the adolescent and adult samples; food-related problems and toxic chemicals trigger more concerns than environmental pollution or electromagnetic radiation.

Age-related changes in MHW scores (adolescents scored lower than adults, younger adolescents scored lower than older adolescents, and group affiliation showed a positive connection to MHWs in the regression analysis) might be interpreted as a consequence of cognitive development (e.g. a growing need to understand how the body functions), a feeling of enhanced emotional vulnerability, and increasing openness to external information. The increasing number and severity of subjective somatic symptoms experienced in adolescence and the accompanying emotions (e.g. fear of a serious disease) may be strong motives to identify possible causes and to avoid supposed harmful influences.

Subjective somatic symptoms were associated with MHWs in the correlational analysis as well as in the second step of the regression analysis. Following the entering of somatosensory amplification and health anxiety, however, the association vanished indicating that the latter two are more closely connected to MHWs than somatic symptoms. Moreover, health anxiety and somatosensory amplification were independently associated with MHWs in the regression analysis, and both of them partially mediated the connection between MHWs and somatic symptoms. Taking these findings as a whole, perceived vulnerability appears to build a “social-cognitive-emotional bridge” between symptoms and MHWs— at least from a cross-sectional point of view.

A further concern would be how this bridge is created. The majority of studies exploring these connections were cross-sectional; therefore, little is known about causal relationships. As for the relationship between somatic symptoms and MHWs, two mechanisms were proposed. First, the connection between the two phenomena is only perceived (i.e. mistaken attribution; Köteles and Simor, 2013a); people try to find causes of everyday symptoms, and agents related to modern technologies appear to be appropriate candidates as they are widely present and their harmful effects are often emphasized. Second, MHWs increase body-focus and negative affect that leads to the perception of more symptoms as it was described by the symptom perception model (Filipkowski et al., 2010). The latter mechanism was not confirmed by a recent 2-month longitudinal study; university students’ somatic symptoms were predicted by somatosensory amplification, and MHW scores were predicted by somatic symptoms, but somatosensory amplification was not predicted by MHWs (Köteles and Simor, 2013a). This finding supports the attribution hypothesis: MHWs do not trigger a symptom-seeking process but might help to explain already existing symptoms. However, the consequences of one single study are far from conclusive, and as the existence of circular relationships are also possible, a longitudinal design might not be the best way to answer these questions. Moreover, based on the concept of cognitive perseveration (Brosschot et al., 2006), only repeated or chronic activation of the cognitive representation of a stressor can affect health. Therefore, not only the magnitude of modern health worries but also their duration should be taken into account to reveal the relationship and mechanisms between MHWs and symptoms.

The most important shortcoming of the present study concerns the characteristics of the sample. As it was not representative, the results can only be generalized with cautions. Although the MHWS appeared to be a reliable tool in the present study, further—preferably qualitative—research is needed to confirm its construct validity among adolescents. Moreover, cross-sectional data were obtained on which conclusions on causal relationships among variables cannot be appropriately drawn. Beyond the measured constructs, there are other variables that could be associated with MHWs, symptoms, or both: for example, depression (Rief et al., 2012). A better research strategy would be the application of a developmental perspective, that is, tracking similarities or differences in the development of MHWs and subjective symptoms from childhood. Further studies on adolescent and even younger samples may shed more light on the pattern and the causal relationships among the constructs studied in the research. A more detailed understanding of the MHW phenomenon can help us determine and design possible practical interventions.

Footnotes

Declaration of conflicting interests

The authors declare that there is no conflict of interest.

Funding

This research was supported by the Hungarian National Scientific Research Fund (OTKA K 76880) and by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences (for Gyöngyi Kökönyei).

Notes

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