A randomized comparative effectiveness study of Healthy Directions 2--a multiple risk behavior intervention for primary care

The effect of a single visit to a health coach on perceived health in 50-year old residents in a high-income country - a randomised controlled trial

OBJECTIVE

To evaluate the one-year-effect of a single visit to a health coach on perceived health and exercise level in 50-year-old citizens.

DESIGN

One factor design randomised controlled trial.

SETTING

Participants were randomly selected from the Swedish Population Register.

SUBJECTS

50-year-old residents of the town of Alingsås, Sweden (n = 105).

INTERVENTION

The intervention group (n = 52) received a single one-hour visit to a health coach. The control group (n = 53) received no intervention.

MAIN OUTCOME MEASURES

Change over 12 months in the SF-36 dimensions physical functioning, role-physical, bodily pain, general health, vitality, social functioning, role-emotional, mental health, physical component summary and mental component summary. Reported health transition at follow-up. Change in exercise level.

RESULTS

The control group changed their perceived health more favourable than the intervention group in the following dimensions of the SF-36; general health (p = 0.0055-0.025), role-emotional (p = 0.034-0.040) and mental component summary (p = 0.033-0.073).

CONCLUSION

A single visit to a health coach does not improve perceived health or exercise-level in 50-year-old citizens. On the contrary it may make perceived health worse.Key pointsResearch on health coaching has emerged in the last 20 years, but is diverse and the characteristics of a successful health coaching intervention are still unknown.There is a lack of randomised controlled trials evaluating long-term effectiveness of health coaching.This randomised controlled trial concludes that a single visit to a health coach does not improve, but rather impairs, perceived health in 50-year olds.

Strategies to improve smoking cessation rates in primary care

BACKGROUND

Primary care is an important setting in which to treat tobacco addiction. However, the rates at which providers address smoking cessation and the success of that support vary. Strategies can be implemented to improve and increase the delivery of smoking cessation support (e.g. through provider training), and to increase the amount and breadth of support given to people who smoke (e.g. through additional counseling or tailored printed materials).

OBJECTIVES

To assess the effectiveness of strategies intended to increase the success of smoking cessation interventions in primary care settings. To assess whether any effect that these interventions have on smoking cessation may be due to increased implementation by healthcare providers.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and trial registries to 10 September 2020.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and cluster-RCTs (cRCTs) carried out in primary care, including non-pregnant adults. Studies investigated a strategy or strategies to improve the implementation or success of smoking cessation treatment in primary care. These strategies could include interventions designed to increase or enhance the quality of existing support, or smoking cessation interventions offered in addition to standard care (adjunctive interventions). Intervention strategies had to be tested in addition to and in comparison with standard care, or in addition to other active intervention strategies if the effect of an individual strategy could be isolated. Standard care typically incorporates physician-delivered brief behavioral support, and an offer of smoking cessation medication, but differs across studies. Studies had to measure smoking abstinence at six months' follow-up or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Our primary outcome - smoking abstinence - was measured using the most rigorous intention-to-treat definition available. We also extracted outcome data for quit attempts, and the following markers of healthcare provider performance: asking about smoking status; advising on cessation; assessment of participant readiness to quit; assisting with cessation; arranging follow-up for smoking participants. Where more than one study investigated the same strategy or set of strategies, and measured the same outcome, we conducted meta-analyses using Mantel-Haenszel random-effects methods to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs).

MAIN RESULTS

We included 81 RCTs and cRCTs, involving 112,159 participants. Fourteen were rated at low risk of bias, 44 at high risk, and the remainder at unclear risk. We identified moderate-certainty evidence, limited by inconsistency, that the provision of adjunctive counseling by a health professional other than the physician (RR 1.31, 95% CI 1.10 to 1.55; I2 = 44%; 22 studies, 18,150 participants), and provision of cost-free medications (RR 1.36, 95% CI 1.05 to 1.76; I2 = 63%; 10 studies,7560 participants) increased smoking quit rates in primary care. There was also moderate-certainty evidence, limited by risk of bias, that the addition of tailored print materials to standard smoking cessation treatment increased the number of people who had successfully stopped smoking at six months' follow-up or more (RR 1.29, 95% CI 1.04 to 1.59; I2 = 37%; 6 studies, 15,978 participants). There was no clear evidence that providing participants who smoked with biomedical risk feedback increased their likelihood of quitting (RR 1.07, 95% CI 0.81 to 1.41; I2 = 40%; 7 studies, 3491 participants), or that provider smoking cessation training (RR 1.10, 95% CI 0.85 to 1.41; I2 = 66%; 7 studies, 13,685 participants) or provider incentives (RR 1.14, 95% CI 0.97 to 1.34; I2 = 0%; 2 studies, 2454 participants) increased smoking abstinence rates. However, in assessing the former two strategies we judged the evidence to be of low certainty and in assessing the latter strategies it was of very low certainty. We downgraded the evidence due to imprecision, inconsistency and risk of bias across these comparisons. There was some indication that provider training increased the delivery of smoking cessation support, along with the provision of adjunctive counseling and cost-free medications. However, our secondary outcomes were not measured consistently, and in many cases analyses were subject to substantial statistical heterogeneity, imprecision, or both, making it difficult to draw conclusions. Thirty-four studies investigated multicomponent interventions to improve smoking cessation rates. There was substantial variation in the combinations of strategies tested, and the resulting individual study effect estimates, precluding meta-analyses in most cases. Meta-analyses provided some evidence that adjunctive counseling combined with either cost-free medications or provider training enhanced quit rates when compared with standard care alone. However, analyses were limited by small numbers of events, high statistical heterogeneity, and studies at high risk of bias. Analyses looking at the effects of combining provider training with flow sheets to aid physician decision-making, and with outreach facilitation, found no clear evidence that these combinations increased quit rates; however, analyses were limited by imprecision, and there was some indication that these approaches did improve some forms of provider implementation.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that providing adjunctive counseling by an allied health professional, cost-free smoking cessation medications, and tailored printed materials as part of smoking cessation support in primary care can increase the number of people who achieve smoking cessation. There is no clear evidence that providing participants with biomedical risk feedback, or primary care providers with training or incentives to provide smoking cessation support enhance quit rates. However, we rated this evidence as of low or very low certainty, and so conclusions are likely to change as further evidence becomes available. Most of the studies in this review evaluated smoking cessation interventions that had already been extensively tested in the general population. Further studies should assess strategies designed to optimize the delivery of those interventions already known to be effective within the primary care setting. Such studies should be cluster-randomized to account for the implications of implementation in this particular setting. Due to substantial variation between studies in this review, identifying optimal characteristics of multicomponent interventions to improve the delivery of smoking cessation treatment was challenging. Future research could use component network meta-analysis to investigate this further.

Self-reported changes in physical activity, sedentary behavior, and screen time among informal caregivers during the COVID-19 pandemic

BACKGROUND

Informal caregivers providing unpaid assistance may be vulnerable to changes in health behaviors due to modifications in caregiving during the COVID-19 pandemic. Therefore, this cross-sectional study explored self-reported changes in physical activity (PA), sedentary behavior, and screen time among informal caregivers providing care for older adults aged 50+ during the pandemic.

METHODS

Study participants were recruited via Amazon's Mechanical Turk and reported their perceived changes (increased a lot, increased a little, remained the same, decreased a little, decreased a lot) in moderate-intensity PA (MPA), vigorous-intensity PA (VPA), sedentary behavior, and screen time (weekday and weekend) during the pandemic. For analytic purposes, response categories were categorized into three-level ordinal variables-increased (increased a lot, increased a little), no change (remained the same), decreased (decreased a little, decreased a lot). Multinomial logistic regression models assessed the likelihood of changes (vs. no change) in  MPA,  VPA, sedentary behavior, and screen time (weekday, weekend) based on caregiving and demographic characteristics.

RESULTS

In total, 2574 individuals accessed the study link, 464 of whom did not meet eligibility requirements. In addition, people who completed 80% or less of the survey (n = 1171) and/or duplicate IP addresse (n = 104) were excluded, resulting in an analytic sample of n = 835. The sample was 69% male, had a mean age of 34 (SD = 9.7), and 48% reported increased VPA, while 55% reported increased MPA. The majority also reported increased sedentary behavior, as well as increased screen time. Respondents living with their care recipient were more likely to report increased weekday screen time (Odds Ratio [OR] = 1.55, 95% CI 1.11-2.16) and sedentary behavior (OR = 1.80, 95% CI 1.28-2.53) than respondents not living with the care recipient. Those living with their care recipient were also more likely to reported increased MPA (OR = 1.64, 95% CI 1.16-2.32), and VPA (OR = 1.53, 95% CI 1.09-2.15), but also more likely to report a decrease in VPA (OR = 1.75, 95% CI 1.14-2.70).

CONCLUSION

The majority of respondents reported that their MPA, VPA PA, sedentary behavior, and screen time had changed during the pandemic. Living with the care recipient was associated with both positive and negative changes in behavior. Future research can explore factors associated with these reported changes in behavior.

Multiple Unhealthy Behaviors Share Equivalent Profiles of Readiness for Change in Patients with Type 2 Diabetes

Few studies have considered more than one behavior, despite the tendency towards multiple behaviors, and there are none that have focused on a Latino population. We determined the concurrence of four unhealthy behaviors related to glycemic control and identified common cognitive factors at advanced stages of readiness for change in patients with type 2 diabetes treated in primary care. A cross-sectional study was carried out during August–December 2018 in northeastern Mexico. We consecutively included patients between 20 and 70 years who were without medical contraindication, physical impediment against exercise, pregnancy and edentulism, among other selection criteria (n = 407). Stages of behavior were measured according to the Transtheoretical Model. Pros, cons, self-efficacy, susceptibility, and severity data were collected by interview. Statistical analysis consisted of descriptive statistics and multiple logistic regression. A total of 36.7% exhibited more than one unhealthy behavior in precontemplation or contemplation (no interest or some interest in changing consumption of refined sugars and saturated fats, exercise, or oral hygiene behavior). Cons (p < 0.05) and self-efficacy (p < 0.001) were common to all four unhealthy behaviors, independent of potential confounders. Studies like ours facilitate the recognition of individuals with multiple unhealthy behaviors who share equivalent profiles of readiness for change before implementing public health programs.

The effects of nurse-led health coaching on health-related quality of life and clinical health outcomes among frequent attenders: A quasi-experimental study

OBJECTIVE

To evaluate the effects of the nurse-led health coaching on health-related quality of life and clinical health outcomes among frequent attenders in primary healthcare.

METHODS

A quasi-experimental study design. A total of 110 patients were enrolled in the study. The experimental group (n = 52) received nurse-led health coaching and the control group (n = 58) received the usual care at primary health care centres in Finland. The data were collected before the intervention and 12 months via a questionnaire of health-related quality of life and clinical health outcomes as measured by health-coaching nurses.

RESULTS

This study found frequent attenders have low health-related quality of life. The nurse-led health coaching showed no differences in health-related quality of life between the experimental and control groups. However, the nurse-led health coaching had statistically significant effects on the blood pressure and health-related quality of life among the experimental participants, especially in emotional role limitation and energy.

CONCLUSIONS

This study suggests that nurse-led health coaching may lead to an improvement in the health-related quality of life and blood pressure among frequent attenders.

PRACTICE IMPLICATIONS

The health-coaching sessions with own health-coaching nurses and action plans support the frequent attenders´ health promotion goals and implementation.

Enhancing behavioral change among lung cancer survivors participating in a lifestyle risk reduction intervention: a qualitative study

PURPOSE

Early detection and improved treatment have increased lung cancer survival. Lung cancer survivors have more symptom distress and lower function compared with other cancer survivors; however, few interventions are available to improve health-related quality of life (HR-QOL). Lifestyle risk reduction interventions have improved HR-QOL in other cancer survivors. The purpose of this study was to explore lung cancer survivor perspectives on making behavioral changes in the context of a lifestyle risk reduction intervention.

METHODS

Twenty-two lung cancer survivors participated in interviews after completing the Healthy Directions (HD) intervention. Interviews were audiotaped, transcribed, and analyzed using inductive content analysis. Demographic and clinical characteristics were gathered through a survey and analyzed using descriptive statistics.

RESULTS

Five main themes were identified: (1) the diagnosis was a motivator for behavior change, (2) participants had to deal with disease consequences, (3) the coach provided guidance, (4) strategies for change were initiated, and (5) social support sustained behavioral changes. Other important subthemes were the coach helped interpret symptoms, which supported self-efficacy and goal setting, and survivors employed self-monitoring behaviors. Several participants found the recommended goals for physical activity were difficult and were discouraged if unable to attain the goal. Findings underscore the need for individualized prescriptions of physical activity, especially for sedentary survivors.

CONCLUSIONS

Lung cancer survivors described the benefits of coaching to enhance their engagement in behavioral change. Additional research is needed to validate the benefit of the HD intervention to improve HR-QOL among this vulnerable and understudied group of cancer survivors.

Long-term effectiveness of health coaching in rehabilitation and prevention: A systematic review

OBJECTIVE

This systematic review aims to evaluate the long-term effectiveness of health coaching interventions in rehabilitation and prevention.

METHODS

Databases and a manual search were used to identify randomized controlled trials (RCTs) in English through to June 2015. Studies were included if: (1) the target population were people of employment age, (2) the intervention addressed either people suffering from a diagnosed disease or healthy people, (3) the intervention included health coaching to influence health-related outcomes and/or processes and (4) the study had a follow-up of at least 24 weeks after the end of the intervention period.

RESULTS

Out of 90 RCTs, 14 studies were selected using the inclusion criteria: seven were designed for the rehabilitative setting and seven for the preventive setting. Three studies of each setting found statistically significant long-term effectiveness.

CONCLUSIONS

The high number of studies evaluating health coaching underlines the relevance of this approach. Despite the increasing popularity of health coaching, a research gap exists in regard to its long-term effectiveness.

PRACTICE IMPLICATIONS

It is of utmost importance to consider the sustainability already during planning of health coaching interventions. The involvement of the target group and the setting seems to be a promising strategy.

Social Support for Changing Multiple Behaviors: Factors Associated With Seeking Support and the Impact of Offered Support

Introduction. Social support is important for behavior change, and it may be particularly important for the complexities of changing multiple risk behaviors (MRB). Research is needed to determine if participants in an MRB intervention can be encouraged to activate their social network to aid their change efforts. Methods. Healthy Directions 2, a cluster-randomized controlled trial of an intervention conducted in two urban health centers, targeted five behaviors (physical activity, fruit and vegetable intake, red meat consumption, multivitamin use, and smoking). The self-guided intervention emphasized changing MRB simultaneously, focused on self-monitoring and action planning, and encouraged participants to seek support from social network members. An MRB score was calculated for each participant, with one point being assigned for each behavioral recommendation that was not met. Analyses were conducted to identify demographic and social contextual factors (e.g., interpersonal, neighborhood, and organizational resources) associated with seeking support and to determine if type and frequency of offered support were associated with changes in MRB score. Results. Half (49.6%) of participants identified a support person. Interpersonal resources were the only contextual factor that predicted engagement of a support person. Compared to individuals who did not seek support, those who identified one support person had 61% greater reduction in MRB score, and participants identifying multiple support persons had 100% greater reduction. Conclusion. Engagement of one’s social network leads to significantly greater change across multiple risk behaviors. Future research should explore strategies to address support need for individuals with limited interpersonal resources.

Feasibility and acceptability of "healthy directions" a lifestyle intervention for adults with lung cancer

OBJECTIVE

The aims of this feasibility study of an adapted lifestyle intervention for adults with lung cancer were to (1) determine rates of enrollment, attrition, and completion of 5 nurse-patient contacts; (2) examine demographic characteristics of those more likely to enroll into the program; (3) determine acceptability of the intervention; and (4) identify patient preferences for the format of supplemental educational intervention materials.

METHODS

This study used a single-arm, pretest and posttest design. Feasibility was defined as ≥20% enrollment and a completion rate of 70% for 5 nurse-patient contact sessions. Acceptability was defined as 80% of patients recommending the program to others. Data was collected through electronic data bases and phone interviews. Descriptive statistics, Fisher's exact test and Wilcoxon rank sum test were used for analyses.

RESULTS

Of 147 eligible patients, 42 (28.6%) enrolled and of these, 32 (76.2%) started the intervention and 27 (N = 27/32; 84.4%; 95% CI, 67.2%-94.7%) completed the intervention. Patients who were younger were more likely to enroll in the study (P = .04) whereas there were no significant differences by gender (P = .35). Twenty-three of the 24 (95.8%) participants' contacted posttest recommended the intervention for others. Nearly equal numbers of participants chose the website (n = 16, 50%) vs print (n = 14, 44%).

CONCLUSION

The intervention was feasible and acceptable in patients with lung cancer. Recruitment rates were higher and completion rates were similar as compared to previous home-based lifestyle interventions for patients with other types of cancer. Strategies to enhance recruitment of older adults are important for future research.

Chronic Disease Diagnosis as a Teachable Moment for Health Behavior Changes Among Middle-Aged and Older Adults

OBJECTIVE

To examine the impact of a new chronic disease diagnosis on substance use (i.e., smoking and drinking), utilization of preventive medical procedures, and physical activity among middle-aged and older adults.

METHOD

Individual-level data came from 1996 to 2010 waves of the U.S. Health and Retirement Study. Disease diagnosis was ascertained from self-reports of physician-diagnosed diseases. A case-control difference-in-differences approach estimated in logistic regression was applied to test study hypotheses.

RESULTS

After a diagnosis of chronic disease, participants decreased substance use and increased utilization of preventive medical procedures. Physical activity declined after a diagnosis of lung disease, cancer, and stroke.

DISCUSSION

Chronic disease diagnosis may be an important teachable moment that can motivate individuals to adopt multiple risk-reducing health behaviors. Future research needs to elucidate the mechanisms through which disease diagnosis affects behaviors and test the modifying effect of time since diagnosis on intervention effectiveness.

Study protocol for Young & Strong: a cluster randomized design to increase attention to unique issues faced by young women with newly diagnosed breast cancer

Background

Each year, approximately 11% of women diagnosed with breast cancer in the United States are 45 years of age or younger. These women have concerns specific to or accentuated by their age, including fertility-related concerns, and have higher rates of psychosocial distress than women diagnosed at older ages. Current guidelines recommend that fertility risks be considered early in all treatment plans; however, the extant research indicates that attention to fertility by the healthcare team is limited. Importantly, attention to fertility may be a proxy for whether or not other important issues warranting attention in younger women with breast cancer are addressed, including genetic risks, psychosocial distress, sexual functioning, and body image concerns. The Young & Strong study tests the efficacy of an intervention designed for young women recently diagnosed with breast cancer and their oncologists with the intention to: 1) increase attention to fertility as an important surrogate for other issues facing young women, 2) educate and support young women and their providers, and 3) reduce psychosocial distress among young women with breast cancer.

Methods/Design

The study employs a cluster randomized design including 14 academic institutions and 40 community sites across the U.S. assigned to either the study intervention arm or contact-time comparison intervention arm. Academic institutions enroll up to 15 patients per site while community sites enroll up to 10 patients. Patient eligibility requirements include: an initial diagnosis of stage I-III invasive breast cancer within three months prior, without a known recurrence or metastatic breast cancer; 18–45 years of age at diagnosis; ability to read and write in English. The primary outcome is oncologists’ attention to fertility concerns as determined by medical record review. Secondary outcomes include differences in patient satisfaction with care and psychosocial distress between the two study arms.

Discussion

Study findings will provide valuable insight into how to increase attention to fertility and other issues specific to young women with breast cancer and how to improve doctor-patient communication around these issues, which may promote better quality of care for this population.

Trial registration

NCT01647607. Registered July 19, 2012.