Table 1.
General study characteristics. Studies are listed alphabetically
| Author / Year | Study Name (if identified) | City (or State/ Province/ Region), Country | Study Aim/s | Study Design | Clinical field | Type of data collected |
|---|---|---|---|---|---|---|
| Amin et al. 2023 [38] | Substudy of PREVENT-ADPKD | Sydney, Wollongong, New Lambton Heights, Gosford, Perth, Australia |
To determine the experiences of participants in a long-term trial Identify factors influencing reasons to enrol, remain, and adhere to trial procedures Develop preliminary recommendations for improving future clinical trials |
Randomized control trial | Kidney Disease | Factors hypothesized to influence participant recruitment and retention (ranked the utility and difficulty of individual components), overall global satisfaction score, Qualitative: Semi structured Interview (explored expectations and motivations before enrolling, adequacy of informed consent, overall experience, perceived adherence, interactions with study staff and recommendations for future trial design |
| Cheraghi et al. 2021 [39] | Tehran Lipid and Glucose Study (TLGS) [59] |
Tehran, Iran |
Clarify factors associated with non-participation in the TGLS cohort Identify sub-groups who are likely to refuse participation and improve retention strategies for these groups |
Longitudinal cohort study | Diabetes and non-communicable diseases (NCDs) | Protocol [59] and this paper include data on prevalence of NCDs, risk factors for NCDs, intervention data for intervention undertaken by specific target groups of cohort including schoolchildren, women, high-risk groups. Interventions focused on lifestyle modifications; diet, smoking and physical activity |
| Crichton et al. 2012 [57] | - | Adelaide, Australia |
Evaluate the recruitment process, retention of participants and challenges faced in a dairy intervention trial Provide strategies to combat the difficulties of running long-term dietary intervention trials |
Randomised controlled dietary intervention | Obesity | Height, weight, blood pressure, health and dietary questionnaires, anthropometry, and blood samples taken at each visit (cardiometabolic and biochemical assessment), arterial compliance, cognitive assessment and mental health assessment |
| Goldberg et al. 2006 [42] | GAZ and ELectricité (GAZEL) Cohort Study | Saint- Maurice, France | Determine the socioeconomic, lifestyle, and health factors associated with response to annual mail questionnaires | Longitudinal cohort study | - | Questionnaires on health status, lifestyle, socio-economic and occupational factors |
| Gourash et al. 2022 [48] | The Longitudinal Assessment of Bariatric Surgery (LABS) | New York, Greenville, Fargo, Portland, Pittsburgh, Seattle, The United States of America |
Determine short-term and long-term safety of bariatric surgery Evaluate psychosocial, quality of life, health economics of obesity, co-morbidities and bariatric surgery |
Prospective cohort study | Obesity | Blood draw, urine sample, physical measures: anthropometrics, blood pressure, corridor walk, activity monitor and diary, sociodemographic, psychologic, behavioural data |
| Griffith Fillipo et al. 2022 [49] | - | Throughout the United States of America | Determine the optimal incentive strategy for study retention | Remote and sequential multiple assignment randomized trial | Psychology | Demographics, Major Depressive episode Screener, Patient Health Questionnaire-9 (PHQ9), The Social Life and Family Life Scales of the Sheehan Disability Scale, 7-item Generalized Anxiety Scale (GAD-7) the NIAAA Alcohol Screening Test, IMPACT assessment of main and psychosis, exit survey |
| Green et al. 2018 [40] | Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study [60] | Cambridge, United Kingdom | Determine the factors that affect response in epidemiological studies | Contemporary cross-sectional population-based cohort study | Epidemiology and Aging | The included study and its accompanying protocol paper [60] collect interview data related to recruitment and inclusion criteria, core cognitive neuroscience (MRI, MEG, cognitive testing), blood pressure, salivary sample and 3 fMRI |
| Hamberger et al. 2000 [50] | - | Wisconsin, United States of America | Identify reasons for participant dropout from a spouse abuse abatement program | Cohort study | Psychology | Race, education, age, marital status, employment status, alcohol abuse, referral status, police violence contact, drug activity, acting out, history of child abuse, witnessing violence, violence duration, violence level report |
| Irvine et al. 2017 [41] | - | Dundee, United Kingdom | Assess feasibility of trial for reduction of alcohol consumption in obese men | Community-based Intervention | Obesity | Alcohol consumption measures and body mass index |
| Janus et al. 1997 [51] | - | Toronto, Canada | Determine factors influencing family participation in a longitudinal study | Longitudinal birth cohort study | Cystic fibrosis, Congenital heart disease | Severity of chronic illness, diary completed by parents, developmental level, child temperament, family environment, Mother–Child relationship |
| Kannisto et al. 2017 [44] | Mobile.Net | Turku, Finland | Determine the dropout predictors from a mHealth-based trial and evaluate the effects of tailored short message service (SMS) text message constructed to encourage patient adherence | mHealth-Based Randomized Controlled Trial | Psychology | Participant’s quality of life (Q-LES-Q) and satisfaction with the treatment (CSQ-8) |
| Kelfve et al. 2017 [45] | Swedish level-of-living survey (LNU)/ The Swedish panel study of living conditions of the oldest old (SWEOLD) | Stockholm, Sweden | Determine how selective survey participation affects the sample composition, in addition to selective mortality of participants | Longitudinal cohort survey study | Aging | Both LNU and SWEOLD primarily use face-to-face interviews to gather data. The questionnaires used cover a broad range of topics, such as living conditions, family situation, health, health behaviours, and financial resources |
| Lee et al. 2009 [61] | The European Male Ageing Study (EMAS) | European cities: Florence (Italy), Leuven (Belgium), Lodz (Poland), Malmo ¨ (Sweden), Manchester (United Kingdom), Santiago de Compostela (Spain), Szeged (Hungary) and Tartu (Estonia) | Examine aspects of aging in men | Prospective cohort study | Aging | Questionnaire: assess quality of life, depressive symptoms, Adverse Life Events Scale, Physical Activity Scale, International Prostate Symptom Score, previous surgical procedures, sexual function questionnaire. Screening: Physical and cognitive performance, Anthropometry, Calcaneal ultrasound, Food diary, blood samples |
| Limmroth et al. 2023 [47] | PROmyBETAappGame | Multiple Locations, Germanya | Investigate medication-taking behaviour in patients with multiple sclerosis receiving interferon β-1b for 1 year and to provide additional information on patient reported outcomes. To test the feasibility of gamification (using cognitive training tool PEAK) to incentivise patients to remain committee to the study | Prospective and retrospective, noninterventional observational cohort study | Multiple sclerosis | Demographic data: age gender, injection-related data: date/time of injection, injection speed and injection depth (collected from the app or manually recorded), self-reported measures: health-related quality of life, EuroQol-5-Dimension 5-Level questionnaire, Treatment Satisfaction Questionnaire of Medication, questionnaire on satisfaction with the BETAPLUS, BETACONNECT and the app via a service questionnaire |
| Markanday et al. 2013 [58] | Geelong Osteoporosis Study | Geelong, Australia | Investigate sex-differences in non-participation at baseline of the Geelong Osteoporosis Study (GOS) | Prospective cohort study | Osteoporosis | Reasons for not participating |
| Méjean et al. 2014 [43] | NutriNet-Santé Study | Paris, France | Evaluate relationships between participation motives and sociodemographic, health, and lifestyle characteristics of participants in cohort designed to identify nutritional risk or protective factors for chronic diseases | Web-based, Prospective cohort study | Nutrition | Questionnaires assessing dietary intake, physical activity, anthropometrics, lifestyle, and socioeconomic conditions along with health status |
| Oleske et al. 2007 [52] | - | 3 Midwestern statesb, United States of America | Determine influence of demographics, health, and job factors in continued participation of employed persons in a longitudinal intervention study for work-related low-back disorders | Randomized clinical trial | Work-related low-back disorders | Self-reported measures: Back pain frequency and how bothered participants were by pain, back pain disability, physical health, mental health, neurogenic symptoms, psychological job strain / Measures: height, weight, body fat percentage, waist and hip circumference, body mass index |
| Olmos-Ochoa et al. 2019 [53] | - | Los Angeles, United States of America | Identify barriers to study participation and retention, in two modes of intervention for serious mental illness | Cohort study | Psychology | Barriers to physical activity and healthy eating |
| Pogue et al. 2022 [54] | - | North and Central Texas, United States of America | To investigate the impact of the COVID-19 pandemic on mental health | Longitudinal study | Psychology | Depression (PHQ-8), posttraumatic stress symptoms (Posttraumatic Diagnostic Scale-5), anxiety (GAD-7), resilience (10-item Connor-Davidson Resilience Scale), coping strategies (brief COPE), physical activity (International Physical Activity Questionnaire), personality (10-item Personality Inventory), COVID stigma, vaccine hesitancy, COVID-19 impact (COVID Impact Scale), COVID fear (COVID Fear Scale), workplace demographics |
| Rose et al. 1976 [36] | Normative Aging Study of the Veterans Administration | Boston, United States of America | Determine the non-pathological aspects of aging | Longitudinal health cohort | Aging | Age, social class, geographic stability and health |
| Schilling et al. 2023 [37] | Data4Life Consortium | Pensieve Health (Mumbai), Hande Hospital (Panvel, Navi, Mumbai), ACUMDX Laboratory and Research Center (Ghatkopar, Mumbai, Kota, Jodhpur in Rajasthan) and Sun Diagnostics (Ghatkopar, Mumbai), India | Investigate (via digital recruitment and data collection methods) the long-term effects of COVID-19 in India | Observational, longitudinal study | Infectious disease | Demographics, participant feedback, medical and COVID-19 history, physical measurements, social connections, isolation risks, depression (PHQ-9), anxiety (GAD-7), activity levels (IPAQ-SF), asleep patterns (PSQI), alcohol, tobacco, dietary habits |
| Snow et al. 2007 [55] | The Lung Health Study (LHS) | Minneapolis, United States of America and Winnipeg, Canada | Examine the impact of smoking cessation coupled with the use of an inhaled bronchodilator on chronic obstructive pulmonary disease | Randomized, controlled clinical trial | Chronic obstructive pulmonary disease | Demographic variables, alcohol intake, body mass index (BMI), smoking-related variables, past and present illness, lung function, and social support variables |
| Ullmanet al. 1998 [56] | Newcomb [62] | Los Angeles, United States of America | Develop models that differentiate eager, reluctant, and nonresponding participants using participants’ demographics, personality, and drug use characteristics | Longitudinal cohort study | Psychosocial health and Substance use | The included paper and its accompanying protocol [62] collect data on use of monetised incentives for longitudinal recruitment, participant demographics, drug and alcohol intake, personality and attitudinal traits, including support of science/medicine and social conformity |
| vanWees et al. 2019 [46] | Mathematical models incorporating Psychological determinants: control of Chlamydia Transmission (iMPaCT) | Amsterdam, Hollands Noorden, Kennemerland, and Twente, the Netherlands | Identify predictors of non-response and loss to follow-up in longitudinal sexual health study | Longitudinal cohort study | Chlamydia Transmission, Sexually transmitted infections (STI) | Data on sexual behaviour, psychological determinants and chlamydia infections. Participants were tested for chlamydia using nucleic acid amplification tests at enrolment at the STI clinic and through a self-sampling kit sent to a laboratory at six-month follow-up |
aClinicalTrials.gov NCT03808142 lists multiple locations in Germany, however locations with principal investigators are not listed
bMidwestern states are not detailed