Relationship between Physical Activity and Health Outcomes in Persons with Psychotic Disorders after Participation in a 2-Year Individualized Lifestyle Intervention

Abstract

People with psychotic disorders have a significantly increased risk of physical diseases and excessive mortality rates. The aim of the study was to investigate relationships between changes in physical activity, levels of salutogenic health, and glycated hemoglobin among people with psychotic disorders after participation in an individualized lifestyle intervention. The results from analyses showed that self-reported increased physical activity was positively associated with the level of salutogenic health and negatively associated with the level of HbA1c on an individual level. The results indicate that coordinated, individualized, holistic and health-promoting nursing care is crucial to enabling enhanced lifestyle within this vulnerable target group.

Introduction

Persons with psychotic disorders, such as schizophrenia, have an increased risk of serious health problems with physical multimorbidity and mortality (Kugathasan et al., 2019), as well as reduced life expectancy of 15–20 years compared to the general population (Nordentoft et al., 2013). A higher risk of Type 2 diabetes has been highlighted among people with schizophrenia, and identification and treatment of diabetes is deficient in this group (Ward & Druss, 2015). Nearly one in 10 persons diagnosed with severe mental illness, such as schizophrenia, bipolar disorder, or major depressive disorder, have Type 2 diabetes, and the relative risk in this target group has shown to be almost two-fold compared to the general population (Vancampfort et al., 2016).

Worldwide, Type 2 diabetes is the most common type of diabetes, accounting for approximately 90% of all diabetes cases due to increasingly unhealthy lifestyles, and people with Type 2 diabetes have an increased risk of developing several serious physical health complications such as kidney disease, health failure, retinopathy, and neuropathy (IDF - International Diabetes Federation, 2017). Type 2 diabetes is associated with increased risk of major cardiovascular disease (CVD) outcomes (Larsson et al., 2018), and people with severe mental illness have a significantly increased risk of CVD and CVD‐related mortality, highlighted in a large-scale meta-analysis (Correll et al., 2017). Lifestyle-related factors in the overall population, such as physical inactivity, are some of the leading risk factors for mortality worldwide, and the fourth contributor to mortality worldwide in high-income countries after tobacco use, high blood pressure, and overweight/obesity (World Health Organization, 2009). In the general adult population, long-lasting sedentary time has shown to be associated with health problems, such as increased risk of diabetes, CVD, and early death (Biswas et al., 2015).

In the current study, the term psychotic disorders are used to describe the inclusion criteria among study participants, which include long-term psychotic conditions such as schizophrenia and schizophrenia-like disorders related to Schizophrenia Disorder DSM-5 295.90 (F20.9). In Sweden, the main cause of early death among people with psychotic disorders has shown to be CVD, and the increased risk of CVD-related death among this group occurs 10 years earlier, compared with the general population (Westman et al., 2018). It has been stated that reasons for poorer health among people with psychotic disorders are complex (Liu et al., 2017). Regardless of the existing variety of studies with a growing recognition of these increased risks and risk factors for persons with psychotic disorders, physical diseases, excessive years of life lost (Laursen et al., 2019), and excess mortality rates (Lee et al., 2018) still exist.

Unhealthy lifestyles, such as low amount of physical activity and sedentary leisure time are more common among people with psychotic disorders in comparison with the general population (Stubbs et al., 2016a). Less involvement in physical activity (Stubbs et al., 2016a; 2016b), depressive symptoms, and older age in this population has shown to be associated with less vigorous physical activity (Stubbs et al., 2016a), leading to overweight and obesity, and over the longer-term, risk of developing of Type 2 diabetes. Physical health risks of obesity and overweight (McDaid & Smyth, 2015) are also related to side-effects of psychotropic medication, used as treatment for people with psychotic disorders, associated with an increased risk of several physical diseases (De Hert et al., 2011), including diabetes (Correll et al., 2015). A meta-analysis of effects of a lifestyle intervention on weight management and reducing cardiometabolic risk has showed to be effective among people with psychotic disorders (Bruins et al., 2014). On the contrary, it has also been argued that there is no convincing evidence that interventions targeting changing physical activity or sedentary leisure time in this population are effective (Ashdown-Franks et al., 2018).

The European Psychiatric Association’s (EPA) guidance on physical activity has recommended physical activity as an adjunctive treatment for persons with psychotic disorders in order to improve symptoms, cognition, quality of life, and physical health (Stubbs et al., 2018). It has been established that for people with schizophrenia, participation in sports activity contributes to a range of positive effects on the health and wellbeing (Soundy et al., 2015), and provides substantial mental health benefits (Hodgson et al., 2011). A broad spectrum of psychosocial benefits has been found by participation in a sporting activity, such as its positive impact on a sense of meaning, purpose, belonging, identity, and achievement, as well reduction in social isolation and an increase in social confidence, autonomy, and independence (Soundy et al., 2015).

However, people with psychotic disorders themselves have described multifaceted hindrances to physical activity, such as tiredness related to side-effects of medication, and symptoms related to illness and disease (Hodgson et al., 2011), such as depressive mood, anxiety, overweight and obesity, pain, loneliness, difficulties in social situations as well as lack of financial resources (Rastad et al., 2014). Moreover, the importance of being supported by mental health professionals has been underlined (Firth et al., 2016; Hodgson et al., 2011).

As a motivating factor for physical activity, people with psychotic disorders have pointed out the possibility to improve their own health such as losing weight, obtaining better overall mood, and decreasing stress (Firth et al., 2016). This target group faces complex obstacles to maintaining a healthy lifestyle, but the motivational processes related to physical activity and exercise are the same as in the general population (Farholm & Sørensen, 2016). Encounters with people with psychotic disorders require a person-centered approach to be able to consider the individual needs and preferences when aiming to support participation in physical activity (Soundy et al., 2014).

In the general population, regular physical exercise has shown to reduce the risk of several diseases such as CVD and Type 2 diabetes and early all-cause mortality (Warburton et al., 2010). Also, participation in sports has been shown to be beneficial to psychosocial and social health (Eime et al., 2013). Correspondingly, positive associations have been found between physical activity levels and health-related quality of life in the general population (Bize et al., 2007). Physical exercise has been shown to contribute to improvements regarding clinical symptoms, global functioning, and quality of life among people diagnosed with schizophrenia (Dauwan et al., 2016). Nevertheless, low rates of physical activity and high rates of sedentary leisure time are common in this population (Stubbs et al., 2016a). Furthermore, it is well known that the use of antipsychotic medications is associated with an increased risk of several physical diseases (Correll et al., 2015) such as metabolic syndrome and Type 2 diabetes (Suvisaari et al., 2016). Despite several bio-psychosocial health benefits of physical activity among people with psychotic disorders (Soundy et al., 2014), mental health nurses traditionally have paid relatively little attention to interventions intended to increase physical activity among people with mental illness (Happell et al., 2011), and mental health nurses still consider it unclear who is responsible for promotion of health lifestyle interventions for people with psychotic disorders (Lundström et al., 2020).

The need for implementation of lifestyle interventions has been established due to increased risk of physical diseases and excess mortality in this population (Correll et al., 2017; Vancampfort et al., 2016; Westman et al., 2018), and makes it important to investigate the health effect of individualized lifestyle intervention in the context of psychiatric outpatient services. There is also a need to establish best practice assessment and monitoring procedures within exercise interventions in severe mental illness (McMahen et al., 2022). Glycated hemoglobin (HbA1c) can be used as a diagnostic test for assessing glycemic control in persons with diabetes, and as a screening test for persons at high risk of diabetes. The blood count reflects average plasma glucose over the previous 8 to 12 wk (World Health Organization, 2011).

The association between sense of coherence and all-cause mortality in the general adult population has been shown (Piiroinen et al., 2020). The salutogenic perspective highlights sources that lead to health rather than causes of disease, and the salutogenic perspective is a central factor in health promotion to achieve person-centered care, and accordingly, the sense of coherence scale is frequently used in nursing research (Ekman et al., 2021; Sundberg et al. 2022). WHO's definition of health, the salutogenic theories of Antonovsky, and holistic health-related theories frame salutogenic health (Bringsén et al., 2009). To our knowledge, no previous study has examined the relationship between self-reported changes in physical activity, levels of self-rated salutogenic health and glycated hemoglobin (HbA1c) among people with psychotic disorders. Therefore, the aim of the study was to investigate the relationships between changes in physical activity and levels of salutogenic Health Indicator Scale (SHIS) and HbA1c among people with psychotic disorders after participation in a 2-year individualized lifestyle intervention in psychiatric outpatient services.

Method

Design and setting

The current study is a part of a larger lifestyle research project carried out in psychiatric outpatient services specialized to deliver care and treatment for people with psychotic disorders, and other long-term psychotic conditions such as schizophrenia disorder (F20.9), according to DSM-5 295.90. The complete longitudinal quasi-experimental lifestyle intervention study for people with psychotic disorders was undertaken in southern Sweden between March 2013 and January 2017, and each individual participant participated in the intervention for 2 years. The project was performed in cooperation with the municipalities that provided social support and service in the accommodation (Blomqvist et al., 2019).

Participants

Participants (n = 54) were recruited from three different psychiatric outpatient services specialized to provide care and treatment for people with psychotic disorders, such as schizophrenia and other long-term psychotic conditions, in one region in Sweden. People diagnosed with psychotic disorders who met the inclusion criteria (1) were under ongoing treatment at one of the included psychiatric outpatient services, (2) were between 18 and 65 years of age, (3) had participated in at least one face-to-face counseling session related to individual lifestyle factors, and (4) had received some follow-up care after baseline. Two people who were 66 years old and expressed a desire to participate, and, with the exception of their age, met the study’s other inclusion criteria of receiving outpatient treatment for psychotic disorders such as schizophrenia, were also included. The exclusion criterion was current admission for inpatient care. The participants were recruited by a mental health nurse working in the psychiatric outpatient services who didn´t have any caring contact with participants. The participants gave their written consent after they had received both written and oral information about the study. This consisted of information about the aim of the study, how it was to be carried out, and ethical considerations concerning confidentiality, voluntary participation, and that they could withdraw at any time without any negative consequences.

The individualized lifestyle intervention

The individualized intervention was tailored to suit the psychiatric outpatient services specialized for caring and treating people with psychotic disorders. The intervention was aimed at promoting health and targeting lifestyle habits, such as physical activity, a healthy diet, smoking cessation, and reduce harmful use of alcohol among the patients. Moreover, it was designed to be delivered in partnership between the psychiatric outpatient services and municipal housing support. Before the intervention began, all the healthcare professionals in the included psychiatric outpatient services and in the municipal housing support teams were invited for a 2-day educational session and discussions led by the research group. A detailed manual describing the intervention and information material concerning lifestyle changes, physical activity, and nursing documentation were provided. Individual and group-based supervision and administrational support were also provided to nurses, when needed, during the whole intervention. All intervention efforts were individualized in the sense that all the areas of the intervention were processed, but the focus on the efforts was adapted to the needs and wishes of the respective participant, and each participant was able to freely choose the design and scope of their participation in terms of increasing physical activity, transforming to a healthier diet, smoking cessation, or reducing harmful use of alcohol.

Components of the intervention

First, the participants had opportunity to take part in four individual health counseling sessions with the participant’s contact nurse or equivalent. The aim of the health counseling sessions was to increase the patient’s knowledge of lifestyle factors and health and to promote health through tailored support. The counseling sessions lasted about 60 min, and were held every 2 weeks, and were delivered using the MI approach (Miller & Rollnick, 2013). The clinical measurements, results from the blood samples, goal setting, and future plans were discussed with the participants. If necessary, a physician and the primary health care services were contacted, or a referral was sent to the patient’s primary care center. If needed, the final counseling session resulted in a coordinated individual plan (The National Board of Health and Welfare, 2018a) together with the participant, social services, and with the participant’s housing support team or next of kin, in accordance with participant’s preferred lifestyle intervention such as ‘physical activity on prescription’ or dietary advice. ‘Physical activity on prescription’ is a working method for promoting physical activity, as a recommendation to increase physical activity. A systematic review of ‘physical activity on prescription’ suggests positive results from three of the five RCTs, and from the cohort study, and this model of ‘physical activity on prescription’ may increase levels of physical activity among adults and should be considered part of regular healthcare (Onerup et al., 2019). All authorized healthcare professionals in Sweden are able to write an individually tailored prescription based on the existing recommendations for physical activity. The recommendation for physical activity was for a total of at least 150 min a week, and the level of intensity should at least be moderate (Public Health Agency of Sweden, 2019). The dietary advice delivered was in accordance with the guidelines of the Swedish National Food Agency and included: (a) eating plenty of vegetables, fruit, and berries, regular intake of fish, use of liquid vegetable oils, and whole grains; (b) choosing food labeled with the Keyhole that is recommended by Swedish National Food Agency, which, when shopping for food helps to find the healthier options in the store—food with less sugar and salt, more whole grains and fiber, and healthier fats; and (c) using the plate model, which is an educational way of showing how food can be distributed on the plate to increase the amount of vegetables and have a good balance in the meal and food circle when constructing the daily meal. The food circle consists of seven food groups and serves to help to choose food that provides a good variety of nutrients and energy (National Food Agency, Sweden, n.d.). Help with tobacco cessation (Holm Ivarsson, 2015) and alcohol prevention were offered in conjunction with individualized counseling sessions by the MI approach in accordance with Swedish guidelines (The National Board of Health and Welfare, 2018b) and were recommended (Miller & Rollnick, 2013).

The next component included six educational group-based sessions, and the sessions lasted about 120 min including a coffee break. The sessions were provided every 2 weeks but only after individual health counseling sessions. The counseling about physical activity and healthy diet was delivered with a health promotion empowerment approach based on mutual alliance and openness (Jormfeldt et al., 2012). These group-based sessions used the course material “A Healthier Life”; a modified version of Eli Lilly Sweden (2005). The cookbook Healthy Nordic Food (Adamsson & Reumark, 2010) was offered to support participants in cooking at home, and a pedometer was offered as a tool for self-monitoring the number of steps taken each day. Two or three nurses co-led and supervised these sessions, together with one of the staff members from the municipal housing support teams. Encouragement to involve significant others, such as next-of-kin or a contact person from the municipal housing support team, was made in order to encourage the participant to implement and support the desired lifestyle change in his/her daily home environment. A website on the internet was used to motivate and maintain achieved lifestyle changes.

Data collection

The variables physical activity, salutogenic health and glycated hemoglobin (HbA1c) were used as outcome measures since they could be expected to play a role in the relationship to lifestyle intervention to be delivered. The data was collected between 2013 and 2017.

Questionnaires

The National Public Health Survey and Salutogenic Health Indicator Scale (SHIS) questionnaires were distributed and collected by the participants’ contact nurse/study nurse during participants’ regular appointment at the psychiatric outpatient services. The questionnaires were answered by the participants, either at home and, if needed, with assistance from a contact person from a housing support team or by the contact nurse at psychiatric outpatient services. The National Public Health Survey (Public Health Agency of Sweden (Folkhalsomyndigheten), 2009) was used to measure changes in physical activity. This self-reported survey is coordinated nationally by the Public Health Agency of Sweden. The responses concerning behavior changes in physical activity were measured using a survey question related to physical activity: How much time do you spend on moderately-exertive activities that make you warm during a normal week? The answers to this question were estimated on a five-point Likert scale, where ‘1’ demonstrated 5 hours a week or more, and ‘5’ represented not at all.

Salutogenic Health Indicator Scale (SHIS) is a validated general health assessment applied to measure subjective health indicators from a salutogenic and holistic perspective

(Bringsén et al., 2009; Lindert et al., 2015). The 12 items in the questionnaire emphasize self-rated states of health and deal with mental, social, and physical well-being, activities, and functioning, as well as personal situations (Linton et al., 2016). SHIS is assessed on a 6-point Likert scale with higher scores indicating better salutogenic health with a range from 12 to 72 points.

Glycated hemoglobin (HbA1c)

HbA1c value can be used as an indicative test for diabetes, and it states average plasma glucose over the previous eight to 12 wk (Florkowski, 2013; World Health Organization, 2011). According to Swedish Diabetes Association (n.d.), the HbA1c value of a person under 50 years without diabetes is normally in the range of 27–42 mmol/mol. For persons over 50 years, 31–46 mmol/mol is considered normal. Values of HbA1c were collected at regional healthcare services, analyzed and calculated by laboratory professionals according to routine methods at hospital laboratories, and for the study collected from electronic patient records.

Data analysis

To examine if within-person changes in physical activity between baseline (month 0), and the end of the study (month 24) were associated with the level of SHIS and HbA1c at the end of the study, latent change score (LCS) models were estimated (McArdle & Nesselroade, 2014). Given the small sample size, all outcomes were analyzed in separate models. The LCS analyses were estimated in Mplus 8.0. In the LCS model, a latent change score represents the absolute change between the construct measured at month 0 and month 24. In the model, the change in physical activity was specified to predict the level of SHIS and HbA1c at the end of the study. To control for the baseline levels of SHIS and HbA1c, the constructs measured at month 24 were regressed on the constructs measured at month 0 (baseline).

In the analyses, model convergence was assessed with the potential scale reduction factor (PSRF), and a PSRF around 1 was considered evidence of convergence (Kaplan & Depaoli, 2012). Bayesian models using Markov chain Monte Carlo (MCMC) simulation procedures with a Gibbs sampler were used. More specifically, a fixed number of 150,000 iterations was specified for each of the four MCMC chains (the first half is used as the burn-in phase, which is the default in Mplus). Model convergence was assessed using both statistical criteria (i.e. PSRF <1.1) and visual inspection of trace plots to ensure that multiple chains converged toward a similar target distribution. Model fit of the estimated models was assessed using the posterior predictive p (PPp) value, and the 95% confidence interval (CI). A well-fitting model should have a PPp value around 0.50 in combination with a symmetric 95% CI centering on zero.

For each parameter, a CI was calculated. In contrast to the frequentist confidence interval, the CI allows researchers to calculate an interval that indicates the probability (e.g. 95%) that the parameter of interest lies between the two values given the observed data. This is an intuitive and meaningful interpretation that is easier to communicate than the frequentist confidence interval, because it provides the probability that a certain parameter lies between two numbers (van de Schoot et al., 2014). If the 95% CI does not include zero, the null hypothesis is rejected as improbable, and the parameter estimate is considered credible (Kaplan & Depaoli, 2012).

Priors (i.e. mean and variance) for the structural parameter estimate (i.e. the path between the change score in physical activity and the outcome variables) were obtained from a recently-published intervention study (Jakobsen et al., 2017). Because different priors can potentially influence the relation between variables (Zyphur & Oswald, 2015), a sensitivity analysis was performed. In the sensitivity analysis, three models with different variance priors were compared. In the first model, we used a highly precise prior for the variance (i.e. 0.001), in the second model we used moderate precise prior for the variance (i.e. 0.01), while in the third comparison model, we used a prior with low precision (i.e. 0.1). For parameter estimates see Table 1.

Table 1. Comparison of standardized weights of parameter estimates using different priors.

	Prior Mean (variance)	Model A	Model B	Model C
HbA1c
Change PA HbA1c (month 24)	−.19	−.01 [−.02, −.004]	−.01 [−.02, .00]	−.01 [−.04, .02]
HbA1c (month 0) HbA1c (month 24)		.68 [.50, .79]	.69 [.50, .79]	.69 [.50, .79]
PPp		.379	.380	.383
95% CI		−.12.93, 16.19	−12.93, 16.18	−12.94, 16.18
DIC		451	451	451
SHIS
Change PA SHIS (month 24)	.19	.09 [.04, .17]	.07 [−.01, .20]	.01 [−.24, .24]
SHIS (month 0) SHIS (month 24)		.67 [.35, .82]	.67 [.35, .82]	.67 [.34, .82]
PPp		.446	.449	.464
95% CI		−13.01, 14.06	−13.07, 14.08	−13.15, 13.94
DIC		216	216	216

Note: Model A = Highly precise priors were set for the expected parameter estimates variances (i.e. .001); Model B = Moderate precise priors were set for the expected parameter estimates variances (i.e. .01); Model C = Low precise priors were set for the expected parameter estimates variances (i.e. .10); PPp = Posterior Predictive P-value; CI = Confidence Interval; DIC = Deviance Information Criterion.

Independent t-tests were performed to test whether there was systematic missingness in any of the variables between the participants with full data and the participants with missing values.

Ethical considerations

The study was approved by the Regional Ethical Review Board in Lund, Sweden (Dnr: 2012/267) and has been performed in accordance with ethical standards (WMA Declaration of Helsinki, 2013). The participants gave their written consent after they had received both written and oral information about the study, its confidentiality, voluntary participation, and that they could withdraw at any time without any negative consequences to their ongoing care and treatment contacts in services.

Results

The study consisted of participants (n = 54) who were between 23 to 66 years old with a mean age of 46 years. Of all participants 35 (65%) were male and 19 (35%) were female. Most of the participants had a disability pension (70%), and just as many lived alone. Data were considered to be missing at random because there were no statistically-significant differences in any of the variables between the two groups.

All three models estimated for both outcome variables (i.e. SHIS and HbA1c) evaluated in the sensitivity analysis demonstrated a good data–model fit (PPp values ≈0.38–0.46) and the DIC values were also very similar the models in both analyses. In both analyses, the parameter estimates in all three models were in the same direction with small-to-moderate differences in magnitude and width of the CI (for estimates see Table 1). In both analyses, Model A showed less uncertainty regarding the parameter estimate (as indicated by a narrower CI) than Models B and C. In the light of these results, we chose to focus our presentation and discussion of the results for both outcomes variables on the models with high precise priors.

Regarding SHIS the selected model showed a good data-model fit (PPp = 0.446, 95% CI = [–13.01, 14.06]). Standardized estimates for the factor loadings ranged between 0.48 and 0.70. No credible change was found in physical activity between the baseline and the end of the intervention (Δ = 0.23, [–0.03, 0.49]), but the estimate for the variance in change indicated heterogeneity in the sample (Ψ = 0.20, [0.05, 0.57]). Still, a credible positive effect on SHIS was shown to be related to increased physical activity, indicating that an increase in reported physical activity was related to higher levels of SHIS at the end of the study (β = 0.09 [0.04, 0.17]). For HbA1c, the selected model showed a good data–model fit (PPp = .379, 95% CI = [–12.93, 16.19]). No credible change at a group level was shown regarding physical activity between the baseline measures and measures taken at the end of the intervention (Δ = 0.23, [–.02, 0.49]), but the estimate for the variance in change indicated heterogeneity in the sample (Ψ = 0.22, [0.06, 0.60]). At an individual level, a credible negative relationship between change in physical activity and HbA1c was found, indicating that an increase in reported physical activity was related to lower levels of HbA1c at the end of the study (β = −0.01 [–0.02, −0.004]).

Discussion

The results show that an increase in self-reported physical activity was positively associated with the level of self-reported salutogenic health and negatively associated with level of HbA1c. The results are supported by previous research, as it has been documented that regular exercise and physical activity improve both the physical and mental health of people with psychotic disorders such as schizophrenia (Gorczynski & Faulkner, 2010). Moreover, previous research has shown that exercise therapy can reduce symptoms of schizophrenia, depression, need of care, and increase cardiovascular fitness (Scheewe et al., 2013). In contrast, the review of Pearsall et al. (2014) found a modest increase in levels of exercise activity of exercise programs but no clear change for symptoms of mental health, body mass index, and body weight.

For individuals with psychotic disorders, it is especially important, given the evidence of poor health and health risk such as CVD (Correll et al., 2017) and diabetes (Suvisaari et al., 2016; Vancampfort et al., 2016), that mental health services deliver lifestyle interventions (Happell et al., 2011; Suvisaari et al., 2016). The result of the current study encourages consideration that implementation of lifestyle interventions focusing on physical activity for people with psychotic disorders in the context of psychiatric outpatient services may be valuable.

It has been recognized previously that participation in sporting activities contributes to many positive effects on the health and wellbeing of people with schizophrenia (Soundy et al., 2015) and offers substantial mental health benefits (Hodgson et al., 2011). A broad spectrum of psychosocial benefits has been found from participation in a sporting activity, such as its positive impact on a sense of meaning, purpose, belonging, identity, and achievement, as well reduction in social isolation and an increase in social confidence, autonomy, and independence (Soundy et al., 2015). It has been shown that the individual needs and perceptions of health promotion should be considered when supporting people with psychotic disorders to increase their levels of physical activity (Mishu et al., 2019). Consequently, the importance of strengthening the person’s self-efficacy and supporting their positive experiences of lifestyle changes has been highlighted (Lundström et al., 2017). A person-centered care approach (Håkansson Eklund et al., 2019) is considered as suitable to adopt in clinical practice when promoting healthier lifestyles among people with psychotic disorders, together with motivational interviewing approach (Martins & McNeil, 2009; Miller & Rollnick, 2013). The Swedish model for physical activity by prescription is individually tailored for the patient, and all licensed healthcare professionals may prescribe physical activity (Public Health Agency of Sweden (Folkhälsomyndigheten), 2012). In regular primary healthcare, a significant increase in the self-reported physical activity level has been reported after 6 and 12 months, following physical activity prescription with an ongoing non-significant trend at 24 months, as well as a clear improvement in quality of life during that period (Rödjer et al., 2016).

The need for increased monitoring and management of metabolic abnormalities is important in clinical mental health practice due to already-existing metabolic abnormalities in the early phases of schizophrenia (Horsdal et al., 2017; Nyboe et al., 2015), and, therefore, promoting a healthy lifestyle should be part of psychiatric and metal health care and rehabilitation (De Hert et al. 2009; Nyboe et al., 2015). Of note, physical activity interventions for people with psychotic disorders have also shown to reduce objectively-measured levels of sedentary behavior (Williams et al., 2019). Despite the growing awareness of the positive effects of increased physical activity for persons with psychotic disorders, there is still a lack of clarity on to how to motivate patients to structurally engage in physical activity (Farholm & Sørensen, 2016). Increasing autonomous motivation for suitable physical activities can prove favorable, as a positive relationship between autonomous motivation and physical activity as well as physical health-related quality of life has been reported (Farholm et al., 2017) and, moreover, autonomous motivation is significantly related to greater participation in physical activities among people with psychotic disorders (Vancampfort et al., 2013; 2014). Therefore, it has been recommended that mental health nurses actively explore patients’ intrinsic motives for physical activity. Furthermore, supporting autonomy has showed to be linked to the quality of motivation and positive health behavior (Ng et al., 2012).

However, the lack of confidence among health care providers in promoting physical activity and integrating physical activity into daily clinical practice has been highlighted as a barrier, implying a need for changes in working habits and organization of tasks in mental health services (Glowacki et al., 2019). Creating a need-supportive environment encouraging the possibility of physical activity has been demonstrated, which, in the context of mental health services, requires cooperation with other caregivers, such as social support and supported accommodation provided by municipalities (Farholm et al., 2017). Healthcare professionals working in mental health services have described that a common barrier to the promotion of physical activity is the belief that people with mental health difficulties do not overcome obstacles to engage in physical activity engagement (Glowacki et al., 2019). Thus, health promotion focus need to be integrated into all levels of mental health care, into the relationship with each patient, embedded in a joint vision within the working unit, and incorporated into decisions made at the management level (Lundström et al., 2020). A person with severe mental illness needs to be encountered as a unique and whole human being, as opposed to solely being viewed as a mental health patient, by all the involved care providers in cooperation if healthy living is to be truly enabled (Blomqvist et al., 2018; Rosenbaum et al., 2021).

Due to solid evidence regarding the risk of physical diseases such as Type 2 diabetes (Vancampfort et al., 2016) and CVD (Correll et al., 2017), health promotion is needed in this caring context. Nevertheless, when mental health nurses have frequent therapeutic relationships with their patients, they also have substantial opportunities to provide and integrate physical activity as a routine element in the care and treatment provision (Happell et al., 2011), although they might require more knowledge, training, and organizational support in delivering health promotion interventions (Blythe & White, 2012; Way et al., 2018).

This study is not without limitations, which refer partly to the complex nature of the lifestyle intervention when conducted as part of regular clinical practice such as heavy workload and staff turnover among nurses. However, a real-world and practice-oriented approach study design may increase the external validity of the results and its applicability. Moreover, the small sample size affects generalizability of the results, and is emblematic of the major challenges in recruitment and data collection. Self-reported questionnaires may entail a risk of social desirability bias (Adams et al., 2005).

Conclusion

This 2-year individualized lifestyle intervention study among persons with psychotic disorders, such as schizophrenia, found no credible change in physical activity between the baseline and the end of the intervention at group level, but an increase in reported physical activity was related to higher levels of salutogenic health (SHIS) and lower levels of HbA1c on an individual level. The results indicate that coordinated, individualized, holistic, and health-promoting nursing care is crucial to enabling enhanced lifestyles, healthy living, and overall health among persons diagnosed with psychotic disorders such as schizophrenia.

Implications

Due to the growing awareness of the fact that persons with psychotic disorders face serious physical health risks and excessive years of life lost, it is vitally important to undertake the changes necessary to implement a person-centered and holistic mental health nursing approach to successfully promote overall health in this population. Integration of the promotion of healthy living in terms of physical activity, and healthy diet, as well as reduced consumption of alcohol and tobacco, within the context of mental health care services delivery in cooperation with municipalities is central. The significant role of the mental health nurse as coordinator of individualized, holistic, and health-promoting care needs to be highlighted to establish a kind of care that enables enhanced lifestyle and healthy living within this vulnerable target group. Further research regarding how nurses could better support patents’ individual health needs, and research to explore innovative interventions in mental health nursing to encourage patient motivation is warranted.

Authorships statement

All authors meet the criteria according to the latest guidelines of the International Committee of Medical Journal Editors and are in agreement with this manuscript.

Author contribution and declaration of interest

All the authors have contributed to the study in terms of its design and the interpretation of the results. The manuscript was drafted by the first author and critical revisions for significant intellectual content were made by all the authors in its completion. The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Acknowledgements

The authors are most grateful to the participants for taking part in the study and Region Halland, Sweden for funding. We also thank Professor Gunnar Johansson for his contribution in the design phase of the larger research project.

Disclosure statement

The authors confirm that this article content has no conflict of interest.

Additional information

Funding

This work was supported by Region Halland, Sweden.