A Qualitative Evaluation of a Plate-Method Dietary Self-Monitoring Tool in a Sample of Adults Over 50.

Background: Self-monitoring is an important behavioral change technique to help users initiate and maintain dietary changes. Diet self-monitoring tools often involve the itemization of foods and recording of serving sizes. However, this traditional method of tracking does not conform to food guides using plate-based approach to nutrition education, such as the 2019 Canada's Food Guide (CFG). Objective: To explore the acceptability, facilitators and barriers of using a plate-based dietary self-monitoring tool based on the 2019 CFG (Plate Tool) compared with a traditional Food Journal (Food Journal). Methods: The 2 dietary self-monitoring tools were compared using a crossover study design over 2 wk. Adults over 50 (n = 47) from Montreal, Canada, were randomly assigned to use one tool over 3 d during 1 wk, then used the other tool the next week. Semistructured interviews (n = 45) were conducted after completing the second tool. A qualitative description of the interviews was conducted through an inductive determination of themes. Results: Facilitators to using the Plate Tool were its simplicity, quick completion time compared with the Food Journal and easiness to use, increased awareness of dietary habits and accountability, with participants expressing that it could help users make informed dietary changes aligning with the CFG. However, barriers to using the Plate Tool were its lack of precision, the participants' difficulty categorizing foods into the CFG categories and recording intake of foods not present on the CFG. Conclusions: The Plate Tool is an acceptable dietary self-monitoring tool for healthy adults over 50. Self-monitoring tools based on the plate method should take the barriers described in this study into account. Future studies should compare dietary self-monitoring methods to assess adherence and effectiveness at eliciting dietary behavior change.

Use of electronic health data to identify patients with moderate-to-severe osteoarthritis of the hip and/or knee and inadequate response to pain medications.

BACKGROUND: No algorithms exist to identify important osteoarthritis (OA) patient subgroups (i.e., moderate-to-severe disease, inadequate response to pain treatments) in electronic healthcare data, possibly due to the complexity in defining these characteristics as well as the lack of relevant measures in these data sources. We developed and validated algorithms intended for use with claims and/or electronic medical records (EMR) to identify these patient subgroups. METHODS: We obtained claims, EMR, and chart data from two integrated delivery networks. Chart data were used to identify the presence or absence of the three relevant OA-related characteristics (OA of the hip and/or knee, moderate-to-severe disease, inadequate/intolerable response to at least two pain-related medications); the resulting classification served as the benchmark for algorithm validation. We developed two sets of case-identification algorithms: one based on a literature review and clinical input (predefined algorithms), and another using machine learning (ML) methods (logistic regression, classification and regression tree, random forest). Patient classifications based on these algorithms were compared and validated against the chart data. RESULTS: We sampled and analyzed 571 adult patients, of whom 519 had OA of hip and/or knee, 489 had moderate-to-severe OA, and 431 had inadequate response to at least two pain medications. Individual predefined algorithms had high positive predictive values (all PPVs ≥ 0.83) for identifying each of these OA characteristics, but low negative predictive values (all NPVs between 0.16-0.54) and sometimes low sensitivity; their sensitivity and specificity for identifying patients with all three characteristics was 0.95 and 0.26, respectively (NPV 0.65, PPV 0.78, accuracy 0.77). ML-derived algorithms performed better in identifying this patient subgroup (range: sensitivity 0.77-0.86, specificity 0.66-0.75, PPV 0.88-0.92, NPV 0.47-0.62, accuracy 0.75-0.83). CONCLUSIONS: Predefined algorithms adequately identified OA characteristics of interest, but more sophisticated ML-based methods better differentiated between levels of disease severity and identified patients with inadequate response to analgesics. The ML methods performed well, yielding high PPV, NPV, sensitivity, specificity, and accuracy using either claims or EMR data. Use of these algorithms may expand the ability of real-world data to address questions of interest in this underserved patient population.

Barriers and facilitators to diet, physical activity and lifestyle behavior intervention adherence: a qualitative systematic review of the literature.

BACKGROUND: Consuming a balanced diet and regular activity have health benefits. However, many adults have a difficult time adhering to diet and activity recommendations, especially in lifestyle interventions. Adherence to recommendations could be improved if common facilitators and barriers are accounted for in intervention design. The aim of this systematic review was to understand perceived barriers and facilitators to lifestyle (diet and/or activity) intervention guidelines. METHODS: This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Studies included relied on qualitative methods to explore the barriers and facilitators healthy adults ([Formula: see text] 18 years) experienced in lifestyle interventions. Google Scholar, Cochrane Reviews, Medline, PubMed, and Web of Science were searched from January 2005 to October 2021. Main themes from each paper were thematically analyzed and reported as a barrier or facilitator to adherence at the individual, environment or intervention level using inductively derived themes. Study quality was assessed using the Critical Appraisal Skills Programme. RESULTS: Thirty-five papers were included. Of these, 46% were conducted in North America and the majority had more female participants (86% in mixed-sex studies, 26% females only). Similar themes emerged across all three levels as facilitators and barriers. At the individual level, attitudes, concern for health and physical changes. At the environmental level, social support, social accountability, changeable and unchangeable aspects of the community. Finally, delivery and design and content at the intervention level. An additional facilitator at the intervention level included fostering self-regulation through Behavior Change Taxonomies (BCT). CONCLUSIONS: Lifestyle interventions that foster self-regulatory skills, opportunities for social engagement and personalization of goals may improve behaviour adherence. This can be achieved through inclusion of BCT, tapering off of intervention supports, identification of meaningful goals and anticipated barriers with participants.

Evaluation of Increasing Dairy Intake on Bone Density in Postpubertal Youth: A Randomized Controlled Trial Using Motivational Interviewing.

BACKGROUND: Adequate nutrition is important for bone health, especially for bone mineral accretion. OBJECTIVES: The primary objective tested whether increasing dairy intake using the motivational interviewing technique (MInt) improves lumbar spine (LS) bone mineral density (BMD) after 2 y in postpubertal adolescents with habitual dairy intake of <2 dairy servings/d. METHODS: Participants (aged 14-18.9 y) were randomly allocated to: group 1 (control), group 2 (target of 3 dairy servings/d), or group 3 (target of ≥4 dairy servings/d) for 12 mo, with groups 2 and 3 using MInt, with an additional 12-mo nonintervention follow-up. The primary outcome was LS BMD, and secondary outcomes were: whole body, total hip (TH), and 33% distal radius BMD using DXA, bone geometry using peripheral quantitative computed tomography, and bone biomarkers. RESULTS: Ninety-four adolescents (16.6 ± 1.5 y) were recruited. Seventy-six (80.9%) completed the 12-mo assessments. From baseline to 12 mo, dairy intake in female groups 2 and 3 increased by 107% and 208%, respectively; and by 48% and 153% in males of groups 2 and 3, respectively. In females, group 3 had greater increases in TH BMD (4.3% to 7.5%) compared with control (3.7% to 4.9%, P = 0.04) and group 2 (0.0% to 1.7%, P = 0.04) at 12 and 24 mo. No effects due to dairy intake were observed for DXA outcomes in males for radial and tibial volumetric BMD in both sexes. None of the bone biomarkers were different among the dairy groups in females or males. CONCLUSIONS: MInt effectively increased dairy intake with benefits to bone health only in female adolescents with previously low calcium intake who consumed ≥4 dairy servings/d for 12 mo. Larger studies are required to explain the lack of intervention effect in males.

Evaluation of Increasing Dairy Intake on Bone Density in Postpubertal Youth: A Randomized Controlled Trial Using Motivational Interviewing.

BACKGROUND: Adequate nutrition is important for bone health, especially for bone mineral accretion. OBJECTIVES: The primary objective tested whether increasing dairy intake using the motivational interviewing technique (MInt) improves lumbar spine (LS) bone mineral density (BMD) after 2 y in postpubertal adolescents with habitual dairy intake of <2 dairy servings/d. METHODS: Participants (aged 14-18.9 y) were randomly allocated to: group 1 (control), group 2 (target of 3 dairy servings/d), or group 3 (target of ≥4 dairy servings/d) for 12 mo, with groups 2 and 3 using MInt, with an additional 12-mo nonintervention follow-up. The primary outcome was LS BMD, and secondary outcomes were: whole body, total hip (TH), and 33% distal radius BMD using DXA, bone geometry using peripheral quantitative computed tomography, and bone biomarkers. RESULTS: Ninety-four adolescents (16.6 ± 1.5 y) were recruited. Seventy-six (80.9%) completed the 12-mo assessments. From baseline to 12 mo, dairy intake in female groups 2 and 3 increased by 107% and 208%, respectively; and by 48% and 153% in males of groups 2 and 3, respectively. In females, group 3 had greater increases in TH BMD (4.3% to 7.5%) compared with control (3.7% to 4.9%, P = 0.04) and group 2 (0.0% to 1.7%, P = 0.04) at 12 and 24 mo. No effects due to dairy intake were observed for DXA outcomes in males for radial and tibial volumetric BMD in both sexes. None of the bone biomarkers were different among the dairy groups in females or males. CONCLUSIONS: MInt effectively increased dairy intake with benefits to bone health only in female adolescents with previously low calcium intake who consumed ≥4 dairy servings/d for 12 mo. Larger studies are required to explain the lack of intervention effect in males.

Acceptability of a structured diet and exercise weight loss intervention in breast cancer survivors living with an overweight condition or obesity: A qualitative analysis.

BACKGROUND: Weight loss increases survivorship following breast cancer diagnosis. However, most breast cancer survivors (BCS) do not meet diet and exercise recommendations. AIM: The purpose of this study was to explore the barriers and facilitators of BCS who had lymphedema and who participated in a 22-week weight loss lifestyle intervention. METHODS AND RESULTS: Participants completed semi-structured interviews about barriers and facilitators to intervention adherence. Interviews were transcribed verbatim and a thematic analysis was conducted. Participants (n = 17) were 62 ± 8.0 years of age with a mean body mass index of 34.0 ± 7.1 kg/m2 . Four themes emerged: (1) facilitators of intervention adherence, (2) barriers of intervention adherence, (3) continuation of healthy habits post intervention, and (4) recommendations for intervention improvements. Facilitators of intervention adherence were education, social support, routine, motivation, goal-setting, meal-provisioning, self-awareness, and supervised exercise. Barriers to intervention adherence were personal life, health, meal dissatisfaction, seasonality, unchallenging exercises, and exercising alone. All women planned to continue the acquired healthy habits post intervention. Recommendations to improve the study included addressing the exercise regime, meal-provisioning, and dietary intake monitoring methods. CONCLUSION: Future strategies to engage BCS in weight loss interventions should promote group exercise, offer individualized meal-provisioning and exercise regimes, provide transition tools, and allow participants to choose their self-monitoring method.