| Literature DB >> 35405971 |
Patrizia Gnagnarella1,2, Yvelise Ferro3, Taira Monge1,4, Ersilia Troiano1,5, Tiziana Montalcini6, Arturo Pujia3, Elisa Mazza1,3.
Abstract
The COVID-19 pandemic has brought about various restrictions around the world, and its impact on healthcare has been enormous: RDNs have had to shift from in-person interactions with clients to telenutrition consultations, encountering obstacles. We designed the first survey to investigate the changes in RDN practices related to telenutrition provision after the onset of the pandemic through an online survey in Italy. Four hundred and thirty-six responses were analyzed. Before the pandemic, only 16% of Italian RDNs provided telenutrition; this percentage increased significantly up to 63% (p < 0.001). Among patients, the lack of interest in accessing telenutrition (30.9%) and the Internet (16.7%) were the most frequently reported barriers. Among RDNs, one of the main obstacles was their inability to conduct nutritional evaluation or monitoring activities (24.4%). Our survey indicated that increased adoption of telenutrition can be a valid, safe alternative to face-to-face visits. Telenutrition was mainly used by young RDNs (20-39 years) with fewer years of professional experience (0-20 years) and master's degrees. Remote nutrition can enable RDNs to maintain normal workloads and provide patients with uninterrupted access to nutritional healthcare. It is important that RDNs using telemedicine resources possess the ability to provide high-quality, efficient, and secure services using evidence-based guidance.Entities:
Keywords: COVID-19 pandemic; dietitians; nutrition assessment; telehealth; telenutrition
Mesh:
Year: 2022 PMID: 35405971 PMCID: PMC9002661 DOI: 10.3390/nu14071359
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Figure 1Flowchart of the study.
Description of the participants’ demographic and professional characteristics (n = 436).
| Characteristics |
| % |
|---|---|---|
| Age groups (years) | ||
| 20–39 | 228 | 52.3 |
| 40–59 | 167 | 38.3 |
| 60–75 | 41 | 9.4 |
| Geographical provenance | ||
| Northern Italy | 249 | 57.1 |
| Central Italy | 110 | 25.2 |
| Southern Italy | 77 | 17.7 |
| Highest degree earned | ||
| Bachelor’s Degree | 233 | 53.4 |
| Master’s Degree | 116 | 26.6 |
| 1st level University Master’s Degree | 69 | 15.8 |
| 2nd level University Master’s Degree | 11 | 2.5 |
| Academic Doctorate Degree | 7 | 1.6 |
| Member of ASAND ° | ||
| Yes | 276 | 63.3 |
| No | 160 | 36.7 |
| Current work ϭ | ||
| NHS employed | 146 | 33.5 |
| Private healthcare facility employee | 27 | 6.2 |
| Freelance | 243 | 55.7 |
| Employed by two institutes/centers # | 12 | 2.8 |
| University professor | 2 | 0.5 |
| Other | 6 | 1.3 |
| Experience as dietitian (years) | ||
| 0–10 | 185 | 42.4 |
| 11–20 | 123 | 28.2 |
| 21–30 | 75 | 17.2 |
| 31–40 | 41 | 9.4 |
| 41–50 | 12 | 2.8 |
| Focus area in which most time is spent | ||
| Artificial nutrition | 16 | 3.7 |
| Diabetes care | 50 | 11.5 |
| Disordered eating | 51 | 11.7 |
| Food and nutrition consultant | 44 | 10.1 |
| Food manager in collective catering companies | 17 | 3.9 |
| Gastroenterological support | 18 | 4.1 |
| Gerontological nutrition | 10 | 2.3 |
| Health prevention and nutrition education | 9 | 2,1 |
| Oncology | 20 | 4.6 |
| Other § | 13 | 3.0 |
| Kidney disease nutrition | 14 | 3.2 |
| Sports nutrition | 17 | 3.9 |
| Weight management | 137 | 31.4 |
| Women and pediatric nutrition | 20 | 4.6 |
| Age range of studying populations * | ||
| Older adults (age 65+) | 187 | 42.9 |
| Adults (ages 22–64) | 382 | 87.6 |
| Pregnant/postpartum women | 122 | 28 |
| Teenagers and young adults (ages 13–21) | 182 | 41.7 |
| Children (ages 6–12) | 105 | 24.1 |
| Young children (ages 1–5) | 44 | 10.1 |
| Infants | 17 | 3.9 |
° ASAND = Technical Scientific Association of Food, Nutrition and Dietetics. ϭ NHS = National Health System; # Employed by two institutes/centers = dietician who works simultaneously for the NHS or private healthcare facility and for themselves; Other = PhD students or job contract. § Other: bariatrics; cardiovascular; neurology; hereditary metabolic diseases; autoimmune diseases; university research; clinical studies. * Participants were able to select all options that applied.
Figure 2Practice area in which most time is spent by responders (n = 436).
Figure 3Setting where at least 20% of the time is spent (n = 436).
Participants’ professional experiences providing telenutrition prior to and during the COVID-19 pandemic.
| Prior to COVID-19 Pandemic | Mean ± SD | |
|---|---|---|
| Hours per week providing face-to-face nutrition care ( | 22.3 ± 12 | |
| Years of experience providing nutrition care via telehealth ( | 4.7 ± 5 | |
| During the COVID-19 pandemic |
| % |
| Targets of patients via telenutrition | ||
| Individuals | 216 | 78.5 |
| Groups | 12 | 4.4 |
| Both individuals and groups | 47 | 17.1 |
| Current modalities used to provide telenutrition | ||
| Telephone (audio only) | 47 | 17.1 |
| Audiovisual | 129 | 46.9 |
| Both telephone and audiovisual | 89 | 32.4 |
| Other § | 10 | 3.6 |
| Audiovisual options used to provide telenutrition | ||
| Audiovisual capability built into the electronic health record | 7 | 2.5 |
| Google Meet | 65 | 23.6 |
| Lifesize | 6 | 2.2 |
| Teams/Cisco WebEx Meetings/WebEx Teams | 23 | 8.4 |
| Zoom | 5 | 1.8 |
| Zoom/Google/Teams/Skype | 77 | 28.0 |
| 23 | 8.4 | |
| WhatsApp, Skype | 12 | 4.4 |
| Healthcare specialized platforms | 14 | 5.1 |
| Other # | 43 | 15.6 |
| Types of nutrition assessment and/or monitoring and evaluation conducted via telehealth * | ||
| Self-reported body measurements | 173 | 62.9 |
| Food and nutrition assessment | 233 | 84.7 |
| Evaluation of knowledge/beliefs/attitudes | 184 | 66.9 |
| Nutritional history | 227 | 82.5 |
| Behaviors | 34 | 12.4 |
| Assessment/monitoring tools | 30 | 10.9 |
| Physical activity and function | 171 | 62.2 |
| Biochemical data | 11 | 4.0 |
| Types of nutrition interventions provided via telehealth * | ||
| Coordination of nutrition care | 30 | 10.9 |
| Nutrition counseling | 220 | 80.0 |
| Nutrition education | 215 | 78.2 |
| Nutrition prescription | 109 | 39.6 |
| Nutrition supplementation | 39 | 14.2 |
| Enteral and parenteral nutrition | 27 | 9.8 |
| Groups of population-based nutrition action | 44 | 16.0 |
| No intervention | 10 | 3.6 |
| Critical issues encountered in patients during telenutrition * | ||
| Unhealthy eating habits | 10 | 3.6 |
| Eating disorders | 37 | 13.5 |
| Obstacles to care access | 5 | 1.8 |
| Emotional eating | 2 | 0.7 |
| Emotional frailty, fear, anxiety, stress, depression | 38 | 13.8 |
| Weight gain | 91 | 33.1 |
| Malnutrition | 5 | 1.8 |
| Redaction of economic possibilities | 8 | 2.9 |
| Poor compliance | 17 | 6.2 |
| Sedentary lifestyle | 44 | 16.0 |
| None | 16 | 5.8 |
≠ RDNs (n = 19) reported zero hours per week providing face-to-face nutrition care because they were already doing telenutrition. § Other: telephone and email; # Other: healthcare-specialized platforms. * Participants (n = 275) were able to select all options that applied.
Figure 4Participants providing telehealth prior to and during the COVID-19 pandemic.
Barriers and benefits encountered by RDNs providing telenutrition during the COVID-19 pandemic.
| Barriers to Providing Telenutrition * |
| % |
|---|---|---|
| Not being able to conduct or evaluate some typical assessment or monitoring/evaluation activities | 67 | 24.4 |
| Not being able to deliver some routine nutrition interventions | 24 | 8.7 |
| Not having equipment to deliver telenutrition at home | 11 | 4.0 |
| Not having remote access to the electronic health record at home | 16 | 5.8 |
| Clients not having a telephone (landline or mobile phone) | 11 | 4.0 |
| Clients not having access to the Internet | 46 | 16.7 |
| Clients not interested in receiving telenutrition | 85 | 30.9 |
| Payer(s) do not include RDNs in their provider networks | 12 | 4.4 |
| Payer(s) do not include nutrition services in their telehealth policies | 21 | 7.6 |
| Lack of employer support | 12 | 4.4 |
| Difficulty of establishing relationships/therapeutic alliance via telehealth | 66 | 24.0 |
| Discomfort with delivering nutrition care via telehealth | 24 | 8.7 |
| None | 67 | 24.4 |
| Benefits experienced by delivering telenutrition * | ||
| Improved patient access | 122 | 44.4 |
| Scheduling flexibility | 150 | 54.5 |
| Reduced transportation costs for patients/clients | 117 | 42.5 |
| Promoting compliance with social distancing measures recommended due to COVID-19 pandemic | 177 | 64.4 |
| None | 5 | 1.8 |
* Participants (n = 275) were able to select all options that applied.
Description of the demographic and professional characteristics of the RDNs providing telehealth during the COVID-19 pandemic.
| Age Groups | ||||
| 20–39 yrs ( | 40–59 yrs ( | 60–75 yrs ( | ||
| Providing telenutrition (%) | 70 | 56 | 56 | 0.007 |
| Geographical provenance | ||||
| Northern Italy ( | Central Italy ( | Southern Italy ( | ||
| Providing telenutrition (%) | 65 | 58 | 64 | 0.56 |
| Degree earned | ||||
| Bachelor’s Degree/1st Level University Master’s Degree ( | Master’s Degree ( | 2nd Level University Master’s Degree/Academic Doctorate Degree ( | ||
| Providing telenutrition (%) | 59 | 72 | 72 | 0.019 |
| Experience as RDN | ||||
| 0–20 yrs ( | 21–40 yrs ( | 41–50 yrs ( | ||
| Providing telenutrition (%) | 66 | 59 | 25 | 0.005 |