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Preventive Health Programs

Preventive Health Programs: Proactively Safeguarding Well-being.
Designed to promote early detection, risk mitigation, and holistic health optimization, Preventive Health Programs leverage evidence-based strategies to empower individuals and communities.
These multi-faceted initiatives target a diverse range of health domains, from chronic disease management to mental wellness, with the aim of enhancing long-term quality of life.
By fostering healthy habits, screenings, and targeted interventions, Preventive Health Programs play a pivitol role in maintaining optimal physical, mental, and social well-being across the lifespan.

Most cited protocols related to «Preventive Health Programs»

1
Targeted Sampling of Injection Drug Users
Cited 34 times
The TS study was the 37th semiannual cross-section of the Urban Health Study (UHS), a study of IDUs in San Francisco. Watters and Biernacki,9 (link) the developers of TS, first implemented the method in the first UHS cross-section in 1986. The procedures and results from this study have been published extensively over the past two decades.29 (link)–31 (link) Briefly, the five steps involved in developing and refining the TS plan are as follows: (1) Collect indicator data from sources including drug treatment admissions data, IDU HIV/AIDS case data from the San Francisco Department of Public Health (SFDPH), data from Citywide HIV testing sites, and narcotics arrest data from the San Francisco police departments. (2) Collect ethnographic data through block-by-block “walk-throughs,” which were conducted at different times of day and night. Ethnographic data collection also included discussions with key informants regarding their observations on the prevalence and type of drug use in various communities. (3) Develop TS plan by estimating the size and demographic characteristics of the IDU population in each area and set recruitment targets. (4) Conduct outreach to recruit IDUs to community field sites in the neighborhoods with the highest concentration of IDUs per secondary data (marked by stars in Fig. 1b). (5) Refine and revise targeted sample after monthly assessments of how well the recruitment targets were met.

Distribution of study recruits by zip code. a RDS. b Targeted sampling.

Eligibility criteria included the following: (1) reported injecting illicit drugs within the past 30 days, (2) had visible sign of injection (“tracks”), (3) were at least 18 years of age at the time of interview, and (4) were able to speak English or Spanish. Participants from previous serial cross-sections did not receive any special recruitment contact, but they were automatically eligible for future cross-sections (6 months apart), even if they had switched to noninjecting methods or had quit using drugs. Participants were assigned a unique ID code, and we checked their identification by asking five questions: sex, birth year, age, race/ethnicity, state of birth, and first two letters of mother's maiden name. This helped to determine which observations were duplicates. For this analysis, we only included active IDUs who reported injecting drugs in the previous 30 days.
After providing informed consent to this anonymous study, participants were interviewed in person by a trained interviewer in a private space using a structured questionnaire on a computer-assisted programmed interview (CAPI) using QDS software (QDS; NOVA Research Company, Bethesda, MD). They were paid $15 for contributing to the study. Questions covered demographic information, injecting and sexual risk behaviors, and utilization of health care, drug treatment, and HIV prevention programs. The questions pertained to the 6-month period preceding the interview date. Blood specimens were drawn following the interview to assess HIV status using enzyme immunoassay and Western blot assay, following standard laboratory methods. Participants were asked to return for HIV serology results in 2 weeks. They were offered HIV counseling, provided with referrals to medical and social services, and paid $15. Study protocols were approved by the University of California, San Francisco (UCSF) Committee on Human Research.
Kral A.H., Malekinejad M., Vaudrey J., Martinez A.N., Lorvick J., McFarland W, & Raymond H.F. (2010). Comparing Respondent-Driven Sampling and Targeted Sampling Methods of Recruiting Injection Drug Users in San Francisco. Journal of Urban Health : Bulletin of the New York Academy of Medicine, 87(5), 839-850.
Publication 2010
Acquired Immunodeficiency Syndrome BLOOD Cardiac Arrest Childbirth Eligibility Determination Enzyme Immunoassay Ethnicity Hispanic or Latino Homo sapiens Idoxuridine Illicit Drugs Interviewers Narcotics Patient Acceptance of Health Care Pharmaceutical Preparations Preventive Health Programs Stars, Celestial Western Blot
2
Systematic Review of Nonfatal Suicide Epidemiology
Cited 33 times
The CDC also maintains data on the estimated rate of nonfatal self-injury based on a national surveillance system of injuries treated in US hospital emergency departments (the National Electronic Injury Surveillance System) (37 ). We reviewed these data to estimate the rate of nonfatal self-injury in the United States. Although these data provide valuable information about the scope of this problem, they have three notable limitations: They lack precision in that they do not distinguish between suicidal and nonsuicidal self-injury; they do not provide data on characteristics or risk or protective factors; and they fail to capture self-injury not treated in US hospital emergency departments. In order to address these limitations, we also obtained data on the prevalence and characteristics of nonfatal suicidal behavior in the United States and other countries via a systematic electronic search of the recent peer-reviewed literature (1997–2007). We searched the US National Library of Medicine's PubMed electronic database using the title and abstract search terms “suicide,” “suicidal behavior,” and “suicide attempt” and requiring the term “epidemiology” or “prevalence.” This search yielded 1,052 abstracts, which we reviewed individually. We used these articles to inform the review if the authors reported the prevalence of suicide (n = 28) or suicidal behavior (n = 65) within some well-defined population, reported on risk/protective factors or prevention programs (n = 132), or provided a review of studies on one or more of the aforementioned topics (n = 102). Excluded were studies with small sample sizes (<100; n = 73), studies for which the full article was not available in English (n = 108), studies of narrowly defined subpopulations (e.g., specific clinical samples) or irrelevant topics (e.g., cellular suicide) (n = 493), and studies that did not provide a specific measure of one of the suicidal behaviors outlined above (n = 51). When we identified multiple articles reporting on the same data source (e.g., the CDC Youth Risk Behavior Survey), we used only the primary or summary report to avoid redundancy.
Nock M.K., Borges G., Bromet E.J., Cha C.B., Kessler R.C, & Lee S. (2008). Suicide and Suicidal Behavior. Epidemiologic reviews, 30(1), 133-154.
Publication 2008
cDNA Library Cells Emergencies Injuries Population Group Preventive Health Programs Suicide Attempt Youth
3
Longitudinal Cohort Study of Adolescent Substance Use
Cited 22 times
This study focuses on two cohorts of youth who were in 6thand 7th grade (age 11–12) in 2008 and were followed until
2015 (age 17). Participants were part of an AOD use prevention program, CHOICE,
conducted in 16 middle schools in the greater Los Angeles area (46 (link)). Schools were initially selected to participate
across three districts to obtain a diverse sample and to have similar AM use
rates at baseline. A total of 14,979 students across all 16 schools received
parental consent forms; 92% of parents returned this form (n =
13,785). Approximately 71% of parents gave permission for their child to
participate (n = 9,828) and 94% of consented students completed
the first survey (n = 8,932). The study has a Certificate of
Confidentiality; all procedures were approved by the institution’s
review board. Youth completed waves 1 through 5 in middle school during PE class
(wave 1: fall 2008, wave 2: spring 2009, wave 3: fall 2009, wave 4: spring 2010,
and wave 5: spring 2011), and follow up rates ranged from 74% to
90%, excluding new youth that could have come in at a subsequent wave.
Procedures are reported more extensively elsewhere (46 (link)). As youth graduated from middle school to high
school between waves 5 and 6, they transitioned from 16 middle schools to over
200 high schools nationally and internationally. The cohort was re-contacted and
re-consented to complete four annual web-based surveys; we utilize the first two
waves in the current study as this is what is available at this time. Wave 6
occurred between May 2013 and April 2014 when participants were in
9th–12th grades. Of the 4,366 youth who were
eligible for the wave 6 survey (i.e., in 6th–7thgrade at wave 1, could be located, were re-consented), 2,653 (61%) of
those completed the survey. Retention from wave 6 to wave 7 was 80%.
Drop out was not significantly associated with demographics or risk behaviors,
such as drinking and marijuana use. The trajectory sample of 6,509 youth
includes original 6th and 7th graders from wave 1, and
youth that completed a survey at any other wave from waves 2–7;
77% of youth completed 4 or more survey waves. See Table 1 for descriptive statistics and Table 2 for sample information at each
wave.
D’Amico E.J., Tucker J.S., Miles J.N., Ewing B.A., Shih R.A, & Pedersen E.R. (2016). Alcohol and Marijuana Use Trajectories in a Diverse Longitudinal Sample of Adolescents: Examining Use Patterns from Age 11 to 17. Addiction (Abingdon, England), 111(10), 1825-1835.
Publication 2016
Child Marijuana Use Parent Preventive Health Programs Retention (Psychology) Student Substance Use Youth
4
Validating NIfETy Neighborhood Assessments
Cited 19 times
In addition to the random sample of census block faces, a second sampling frame was used that corresponded to the residences of an existing sample of youth. Separate and distinct from the census-driven sample described above, the BPP sample was used to validate the NIfETy instrument and method. Archival individual-level data were obtained from the Second Generation Baltimore Prevention Program (BPP) at the Johns Hopkins University Bloomberg School of Public Health Prevention Intervention Research Center (PIRC). The sample in this longitudinal epidemiological study is comprised of 678 high-risk Baltimore City youths (and their caregivers) who have been assessed annually from the fall of their entry into first grade, in 1993, to the present. Each comprehensive annual youth assessment includes multi-item modules to assess constructs such as VAOD exposure, familial management, deviant peer exposure, manifestations of anxiety and depression, injury, behavioral changes, and neighborhood/community disadvantage. These measures will be used in subsidiary analyses to compare NIfETy ratings with youth-rated neighborhood environment and community-level exposure to VAOD. Each year the caregivers are also assessed on constructs such as household structure, neighborhood/community disadvantage, and parenting practices. A subset of these constructs was used in conjunction with the NIfETy to identify specific factors within communities that are associated with increased community VAOD exposure, as reported by the youths. See Furr-Holden et al. (2004) (link) for a more detailed description of the BPP sample and instruments for this longitudinal study.
The BPP investigators provided the unit block information for the addresses of their study participants but not actual addresses. For example, if a BPP participant lived at 1614 N. Wolfe Street, the unit block information (i.e., 1600 N. Wolfe Street) was provided with an encrypted unique identifier for the participant. The NIfETy rating team was then sent to assess the entire 1600 block of N. Wolfe Street. The raters were blind to block face sampling frame; i.e., they were unaware whether they were rating a randomly sampled block face or a block face containing the residence of a BPP project participant.
Furr-Holden C.D., Smart M.J., Pokorni J.L., Ialongo N.S., Leaf P.J., Holder H.D, & Anthony J.C. (2008). The NIfETy Method for Environmental Assessment of Neighborhood-level Indicators of Violence, Alcohol, and Other Drug Exposure. Prevention science : the official journal of the Society for Prevention Research, 9(4), 245-255.
Publication 2008
Anxiety Cardiac Arrest Face Households Injuries Preventive Health Programs Reading Frames Secondary Prevention Visually Impaired Persons Youth
5
Behavioral Therapy for Incontinence in Weight Loss
Cited 17 times
At randomization, all participants were given a self-help behavioral-treatment booklet with instructions for improving bladder control.17 The booklet provided basic information about incontinence, how to locate pelvic-floor muscles and how to perform daily exercises with them, how to use pelvic-floor muscles to avoid stress incontinence, and how to control urinary urgency, as well as instructions on completing voiding diaries. Incontinence was not discussed further in either the control group or the weight-loss group.
Women assigned to the control group were scheduled to participate in four education sessions at months 1, 2, 3, and 4. During these 1-hour group sessions, which included 10 to 15 women, general information was presented about weight loss, physical activity, and healthful eating habits, according to a structured protocol.
The weight-loss program was designed to produce an average loss of 7 to 9% of initial body weight within the first 6 months of the program and was modeled after that used in the following two large clinical trials: Look AHEAD (Action for Health in Diabetes),18 (link),19 (link) a lifestyle intervention trial intended to achieve and maintain weight loss in patients with diabetes, and the Diabetes Prevention Program.20 (link) The participants in the weight-loss program met weekly for 6 months in groups of 10 to 15 for 1-hour sessions that were led by experts in nutrition, exercise, and behavior change and were based on a structured protocol. The participants were given a standard reduced-calorie diet (1200 to 1500 kcal per day), with a goal of providing no more than 30% of the calories from fat. To improve adherence, the participants were provided with sample meal plans and were given vouchers for a meal-replacement product (Slim-Fast) to be used for two meals a day during months 1 to 4 and for one meal a day thereafter.
The participants were encouraged to gradually increase physical activity (brisk walking or activities of similar intensity) until they were active for at least 200 minutes each week. Behavioral skills, including self-monitoring, stimulus control, and problem-solving, were emphasized.
Subak L.L., Wing R., West D.S., Franklin F., Vittinghoff E., Creasman J.M., Richter H.E., Myers D., Burgio K.L., Gorin A.A., Macer J., Kusek J.W, & Grady D. (2009). Weight Loss to Treat Urinary Incontinence in Overweight and Obese Women. The New England journal of medicine, 360(5), 481-490.
Publication 2009
Behavior Therapy Body Weight Diabetes Mellitus Diet Infantile Neuroaxonal Dystrophy Muscle Tissue Patients Pelvic Diaphragm Preventive Health Programs Urinary Bladder Urinary Stress Incontinence Urine Weight Reduction Programs Woman

Most recents protocols related to «Preventive Health Programs»

1
Home-based Virtual Pulmonary Rehabilitation Protocol

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Publication 2023
Ankle Behavior Therapy Conclude Resin Diabetes Mellitus Disease Progression FITT Infection Injuries Leg Long Terminal Repeat Lower Extremity Lung Transplantation One-Step dentin bonding system Oxygen Saturation Preventive Health Programs Pulse Rate Rate, Heart Safety Self Confidence Signs, Vital Wrist
2
Motivations to Evaluate eHealth Services for Older Adults
Motivations to participate in the evaluation of three different eHealth services were inventoried. The first service, Stranded (see Fig. 1), is a web-based, gamified eHealth service for (pre-)frail older adults. Stranded [27 (link)] consists of two parts: a falls prevention programme based on the OTAGO Programme [28 ], and cognitive minigames. The falls prevention programme consists of physical exercise videos that older adults can perform at home. These exercises focus on improving muscle strength, balance, and flexibility. The minigames are different kinds of puzzle games. The duration of the study evaluating Stranded was four weeks. The second eHealth service, Council of Coaches (COUCH) [29 ] (see Fig. 2), is a web-based service designed for adults with Diabetes Mellitus Type 2 or Chronic Pain, and older adults who are dealing with age-related impairments. The goal of COUCH is to encourage a healthy lifestyle via conversations with virtual coaches. Within COUCH six different coaches are available: a physical activity coach, a nutrition coach, a social coach, a cognitive coach, a chronic pain coach (only available for users with chronic pain), and a diabetes coach (only available for users with diabetes). During the summative evaluation of COUCH, participants could use the eHealth service for four weeks. The last eHealth service, the selfBACK app [30 (link)–32 (link)] (see Fig. 3), is a mobile self-management application for adults with neck and/or low back pain. The selfBACK app provides users with a weekly tailored plan to self-manage this pain. The weekly plain focusses on three aspects: Physical activity (i.e., daily step data), physical exercises to strengthen the muscles and increase flexibility, and educational messages to motivate users and to give them advice. This study with the selfBACK app lasted for six weeks.

Screenshot of eHealth service Stranded

Screenshot of eHealth service Council of Coaches. (Names of the virtual coaches f.l.t.r.: Carlos (peer), Olivia (physical activity coach), Emma (social coach), Katarzyna (diabetes coach), Helen (cognitive coach), Coda (helpdesk robot), François (nutrition coach))

Screenshot of eHealth service selfBACK app (showing weekly self-management plan)

Hurmuz M.Z., Jansen-Kosterink S.M, & van Velsen L. (2023). How to Prevent the Drop-Out: Understanding Why Adults Participate in Summative eHealth Evaluations. Journal of Healthcare Informatics Research, 7(1), 125-140.
Publication 2023
Adult Aged Cavitary Optic Disc Anomalies Chronic Pain Cognition Diabetes Mellitus Diabetes Mellitus, Non-Insulin-Dependent Frail Older Adults Low Back Pain Motivation Muscle Strength Muscle Tissue Neck NG-Nitroarginine Methyl Ester Pain Preventive Health Programs Self-Management Telehealth
3
Tai Chi for Older Adults with Cognitive Impairment
Older adults were recruited from three public dementia prevention centers in rural areas of South Korea. These centers were selected based on similarities in population sizes and screening procedures used in dementia prevention programs. The inclusion criteria were (1) community-residing adults aged 75 years or older, (2) registered at the public dementia prevention centers for dementia screening by health professionals with the diagnosis of either MCI or dementia, (3) Korean version of the Montreal Cognitive Assessment (MoCA-K) score of 22 or lower, (4) had not participated in any formal regular exercise program during the previous 6 months, and (5) agreed to participate in the Tai Chi program twice a week for 12 weeks. Those with musculoskeletal disorders, other neurological/psychiatric diseases other than dementia, or chronic conditions that would prevent them from participating in regular exercise were excluded. The recruitment period was from July 2018 to March 2019. According to Julious, it is recommended that a minimum of 12 subjects per group be considered for pilot studies in terms of feasibility and precision [27 (link)]. Considering the rule and the possible dropout rates of the pilot intervention study, we recruited participants with MCI (n = 25) or dementia (n = 25) to form the intervention groups (Fig. 1).

Flow Diagram. Based on CONSORT 2010 statement: extension to randomized pilot and feasibility trials [28 ]

Oh H., Song R, & Kim S.J. (2023). Effects of 12-week Tai Chi program on physical function, depression, and quality of life among cognitively impaired older adults: a feasibility study. BMC Geriatrics, 23, 118.
Publication 2023
Adult Chronic Condition Dementia Diagnosis Koreans Musculoskeletal Diseases Presenile Dementia Preventive Health Programs Screening
4
Randomized Pain Prevention Programs
Randomization was planned by minimization upon inclusion of patients in the study and programmed using ENNOV clinical data management software (ENNOV; Paris, France). Patients were randomly assigned 1:1 to a pain prevention program using MEOPA or VR. Treatment allocation was stratified by center, age, sex, and hemopathy. In case of intolerance in the VR arm, a change to MEOPA was permitted.
Le Du K., Septans A.L., Maloisel F., Vanquaethem H., Schmitt A., Le Goff M., Clavert A., Zinger M., Bourgeois H., Dupuis O., Denis F, & Bouchard S. (2023). A New Option for Pain Prevention Using a Therapeutic Virtual Reality Solution for Bone Marrow Biopsy (REVEH Trial): Open-Label, Randomized, Multicenter, Phase 3 Study. Journal of Medical Internet Research, 25, e38619.
Publication 2023
Meopa Pain Patients Preventive Health Programs
5
Participatory Evaluation of Obesity Prevention Clubs
In this cross-sectional study, a participatory approach was used to evaluate the activities of OBCs within CB health organizations. Participatory research (PR) is an approach that prioritizes co-constructing research through involvement and collaboration between researchers, organizational representatives, and community members in all phases of the research process (16 ). PR values the engagement of those who are beneficiaries, users, and stakeholders of the research in the research process rather than including them only as subjects of the research (17 (link)). Community-friendly and participatory approaches to evaluation are highly recommended and applied in evaluating community activities (18 (link), 19 (link)) and are considered a form of “citizen science”, focusing on the use of public participation to collect and share data with scientists and empower citizens to identify their own needs and concerns within a community (20 , 21 (link)).
To set up the evaluation team, we contacted different stakeholders related to obesity-prevention clubs. The inclusion criteria for participants of the evaluation team were having experience and active involvement in obesity prevention clubs for at least 4–5 years, as well as being able and showing interest to participate. The municipality's leaders and community members were contacted through phone calls. The final evaluation team included community citizens, i.e., volunteers in the program, as well as health managers at district and city levels.
It was also assured that we share the same language through different phases of evaluation, including defining the aims and main questions, the data collection methodology, and how to involve stakeholders in different phases of evaluation (Figure 1). Several meetings were held to reach a consensus on the evaluation process and to establish our team's contact with the district-level manager in the health department of the Tehran municipality (FR). The main aims of the evaluation team were set jointly, which included the following: (1) to describe a timeline to identify the activities and programs of obesity prevention clubs (history and its evolution); (2) to identify the strengths and challenges of the activities and programs of the obesity prevention clubs; and (3) to present suggestions to improve the activities and programs of obesity prevention clubs. The evaluation team performed data collection from November 2019 to September 2021, using five methods (Figure 2), as follows:
Edalati S., Omidvar N., Takian A., Rasam F., Ghodsi D, & Majdzadeh R. (2023). Participatory evaluation of municipal obesity prevention clubs in Tehran city: Strengths, challenges, and future direction. Frontiers in Public Health, 11, 1055210.
Publication 2023
ARID1A protein, human Biological Evolution Obesity Preventive Health Programs Process Assessment, Health Care TimeLine Voluntary Workers

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More about "Preventive Health Programs"

Preventive health initiatives, health promotion programs, disease prevention strategies, wellness interventions, risk reduction programs, holistic health optimization, early detection screenings, targeted health management, community-based health interventions, lifestyle modification programs, chronic disease mitigation, mental wellbeing optimization, evidence-based health practices, proactive health safeguarding, life-long quality of life enhancement.
Preventive Health Programs leverage Stata 13, SAS 9.4, SPSS version 19.0, Vmax Auto Box, WesternBright ECL, SPSS 25.0 software for Windows 10, MedGem, Seca 213 Portable Stadiometer, FACSCalibur flow cytometer, and NVivo 9 to design and evaluate their strategies.
These multi-faceted programs aim to empower individuals and communities by fostering healthy habits, conducting targeted screenings, and implementing personalized interventions across a diverse range of health domains, from chronic disease management to mental wellbeing.
By proactively safeguarding physical, mental, and social well-being, Preventive Health Programs play a pivitol role in enhancing long-term quality of life.